24 Commits

Author SHA1 Message Date
f2a5c06005 Fixes for re-running reset scripts 2025-02-13 10:25:04 -05:00
fb9f959fe5 Update schemas and reset scripts 2025-02-12 16:14:25 -05:00
169407a729 Fix o3 issues on time-aggregates script 2025-02-12 15:01:04 -05:00
302172c537 Add refresh button to settings page status tables, fix duration on active scripts 2025-02-12 14:30:05 -05:00
4fdaab9e87 Fix o3 issues on product-metrics script 2025-02-11 23:36:14 -05:00
4dcc1f9e90 Fix frontend reset script and visual tweaks 2025-02-11 22:15:13 -05:00
67d57c8872 Update frontend to launch relevant scripts and show script history + output 2025-02-11 21:52:42 -05:00
d7bf79dec9 Fix o3 issues on calculate-metrics script 2025-02-11 15:46:43 -05:00
d90e9b51dc Add combined scripts 2025-02-11 15:02:58 -05:00
98e2e4073a Exclude calculate history table from resets 2025-02-11 14:31:01 -05:00
23c2085f1c Remove duplicate table creates 2025-02-11 14:12:12 -05:00
2a6a0d0a87 Fixed calculations for frontend (likely still wrong but they display) + related regressions to calculate script 2025-02-05 00:02:06 -05:00
ebffb8f912 Enhance calculate scripts to deal with times and counts + fix regressions 2025-02-03 22:21:39 -05:00
5676e9094d Add calculate time tracking 2025-02-02 21:22:46 -05:00
b926aba9ff Add calculate history tracking 2025-02-02 20:41:23 -05:00
e62c6ac8ee Fix issues with change tracking 2025-02-02 20:24:23 -05:00
18f4970059 Set up change tracking in core tables 2025-02-02 19:12:39 -05:00
12cab7473a Fix calculate script regressions 2025-02-02 09:27:06 -05:00
06b0f1251e Fix import script regressions 2025-02-02 01:40:05 -05:00
8a43da502a Fix (probably) discrepancies and errors in import/calculate scripts 2025-02-02 00:01:46 -05:00
bd5bcdd548 Fix calculate errors 2025-02-01 23:38:13 -05:00
0a51328da2 Add a bunch of untested calculations enhancements based on import script changes 2025-02-01 14:46:17 -05:00
b2d7744cc5 Merge branch 'Improve-data-import' 2025-02-01 14:09:34 -05:00
8124fc9add Update gitignore 2025-02-01 14:09:25 -05:00
30 changed files with 5153 additions and 8215 deletions

1
.gitignore vendored
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@@ -26,6 +26,7 @@ dist-ssr
dashboard/build/** dashboard/build/**
dashboard-server/frontend/build/** dashboard-server/frontend/build/**
**/build/** **/build/**
.fuse_hidden**
._* ._*
# Build directories # Build directories

185
docs/calculate-issues.md Normal file
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@@ -0,0 +1,185 @@
1. **Missing Updates for Reorder Point and Safety Stock** [RESOLVED - product-metrics.js]
- **Problem:** In the **product_metrics** table (used by the inventory health view), the fields **reorder_point** and **safety_stock** are never updated in the product metrics calculations. Although a helper function (`calculateReorderQuantities`) exists and computes these values, the update query in the `calculateProductMetrics` function does not assign any values to these columns.
- **Effect:** The inventory health view relies on these fields (using COALESCE to default them to 0), which means that stock might never be classified as "Reorder" or "Healthy" based on the proper reorder point or safety stock calculations.
- **Example:** Even if a product's base metrics would require a reorder (for example, if its days of inventory are low), the view always shows a value of 0 for reorder_point and safety_stock.
- **Fix:** Update the product metrics query (or add a subsequent update) so that **pm.reorder_point** and **pm.safety_stock** are calculated (for instance, by integrating the logic from `calculateReorderQuantities`) and stored in the table.
2. **Overwritten Module Exports When Combining Scripts** [RESOLVED - calculate-metrics.js]
- **Problem:** The code provided shows two distinct exports. The main metrics calculation module exports `calculateMetrics` (along with cancel and getProgress helpers), but later in the same concatenated file the module exports are overwritten.
- **Effect:** If these two code sections end up in a single module file, the export for the main calculation will be lost. This would break any code that calls the overall metrics calculation.
- **Example:** An external caller expecting to run `calculateMetrics` would instead receive the `calculateProductMetrics` function.
- **Fix:** Make sure each script resides in its own module file. Verify that the module boundaries and exports are not accidentally merged or overwritten when deployed.
3. **Potential Formula Issue in EOQ Calculation (Reorder Qty)** [RESOLVED - product-metrics.js]
- **Problem:** The helper function `calculateReorderQuantities` uses an EOQ formula with a holding cost expressed as a percentage (0.25) rather than a perunit cost.
- **Effect:** If the intent was to use the traditional EOQ formula (which expects a holding cost per unit rather than a percentage), this could lead to an incorrect reorder quantity.
- **Example:** For a given annual demand and fixed order cost, the computed reorder quantity might be higher or lower than expected.
- **Fix:** Double-check the EOQ formula. If the intention is to compute based on a percentage, then document that clearly; otherwise, adjust the formula to use the proper holding cost value.
4. **Potential Overlap or Redundancy in GMROI Calculation** [RESOLVED - time-aggregates.js]
- **Problem:** In the time aggregates function, GMROI is calculated in two steps. The initial INSERT query computes GMROI as
`CASE WHEN s.inventory_value > 0 THEN (s.total_revenue - s.total_cost) / s.inventory_value ELSE 0 END`
and then a subsequent UPDATE query recalculates it as an annualized value using gross profit and active days.
- **Effect:** Overwriting a computed value may be intentional to refine the metric, but if not coordinated it can cause confusion or unexpected output in the `product_time_aggregates` table.
- **Example:** A product's GMROI might first appear as a simple ratio but then be updated to a scaled value based on the number of active days, which could lead to inconsistent reporting if not documented.
- **Fix:** Consolidated the GMROI calculation into a single step in the initial INSERT query, properly handling annualization and NULL values.
5. **Handling of Products Without Orders or Purchase Data** [RESOLVED - time-aggregates.js]
- **Problem:** In the INSERT query of the time aggregates function, the UNION covers two cases: one for products with order data (from `monthly_sales`) and one for products that have entries in `monthly_stock` but no matching order data.
- **Effect:** If a product has neither orders nor purchase orders, it won't get an entry in `product_time_aggregates`. Depending on business rules, this might be acceptable or might mean missing data.
- **Example:** A product that's new or rarely ordered might not appear in the time aggregates view, potentially affecting downstream calculations.
- **Fix:** Added an `all_products` CTE and modified the JOIN structure to ensure every product gets an entry with appropriate default values, even if it has no orders or purchase orders.
6. **Redundant Recalculation of Vendor Metrics**
- **Problem:** Similar concepts from prior scripts where cumulative metrics (like **total_revenue** and **total_cost**) are calculated in multiple query steps without necessary validation or optimization. In the vendor metrics script, calculations for total revenue and margin are performed within a `WITH` clause, which is then used in other parts of the process, making it more complex than needed.
- **Effect:** There's unnecessary duplication in querying the same data multiple times across subqueries. It could result in decreased performance and may even lead to excess computation if the subqueries are not optimized or correctly indexed.
- **Example:** Vendor sales and vendor purchase orders (PO) metrics are calculated in separate `WITH` clauses, leading to repeated calculations.
- **Fix:** Synthesize the required metrics into fewer queries or reuse the results within the `WITH` clause itself. Avoid redundant calculations of **revenue** and **cost** unless truly necessary.
7. **Handling Products Without Orders or Purchase Orders**
- **Problem:** In your `calculateVendorMetrics` script, the initial insert for vendor sales doesn't fully address the products that might not have matching orders or purchase orders. If a vendor has products without any sales within the last 12 months, the results may not be fully accurate unless handled explicitly.
- **Effect:** If no orders exist for a product associated with a particular vendor, that product will not contribute to the vendor's metrics, potentially omitting important data when calculating **total_orders** or **total_revenue**.
- **Example:** The scripted statistics fill gaps, but products with no recent purchase or sales orders might not be counted accurately.
- **Fix:** Include logic to handle scenarios where these products still need to be part of the vendor calculation. Use a `LEFT JOIN` wherever possible to account for cases without sales or purchase orders.
8. **Redundant `ON DUPLICATE KEY UPDATE`**
- **Problem:** Multiple queries in the `calculateVendorMetrics` script use `ON DUPLICATE KEY UPDATE` clauses to handle repeated metrics updates. This is useful for ensuring the most up-to-date calculations but can cause inconsistencies if multiple calculations happen for the same product or vendor simultaneously.
- **Effect:** This approach can lead to an inaccurate update of brand-specific data when insertion and update overlap. Each time you add a new batch, an existing entry could be overwritten if not handled correctly.
- **Example:** Vendor country, category, or sales-related metrics could unintentionally update during processing.
- **Fix:** Match on current status more robustly in case of existing rows to avoid unnecessary updates. Ensure that the key used for `ON DUPLICATE KEY` aligns with any foreign key relationships that might indicate an already processed entry.
9. **SQL Query Performance with Multiple Nested `WITH` Clauses**
- **Problem:** Heavily nested queries (especially **WITH** clauses) may lead to slow performance depending on the size of the dataset.
- **Effect:** Computational burden could be high when the database is large, e.g., querying **purchase orders**, **vendor sales**, and **product info** simultaneously. Even with proper indexes, the deployment might struggle in production environments.
- **Example:** Multiple `WITH` clauses in the vendor and brand metrics calculation scripts might work fine in small datasets but degrade performance in production.
- **Fix:** Combine some subqueries and reduce the layer of computations needed for calculating final metrics. Test performance on a production-sized dataset to see how nested queries are handled.
10. **Missing Updates for Reorder Metrics (Vendor/Brand)**
- **Previously Identified Issue:** Inconsistent updates for **reorder_point** and **safety_stock** across earlier scripts.
- **Current Impact on This Script:** The vendor and brand metrics do not have explicit updates for reorder point or safety stock, which are essential for inventory evaluation.
- **Effect:** The correct thresholds and reorder logic for vendor product inventory aren't fully accounted for in these scripts.
- **Fix:** Integrate relevant logic to update **reorder_point** or **safety_stock** within the vendor and brand metrics calculations. Ensure that it's consistently computed and stored.
11. **Data Integrity and Consistency**
**w**hen tracking sales growth or performance
- **Problem:** Brand metrics include a sales growth clause where negative results can sometimes be skewed severely if period data varies considerably.
- **Effect:** If period boundaries are incorrect or records are missing, this can create drastic growth rate calculations.
- **Example:** If the "previous" period has no sales but "current" has a substantial increase, the growth rate will show as **100%**.
- **Fix:** Implement checks that ensure both periods are valid and that the system calculates growth accurately, avoiding growth rates based solely on potential outliers. Replace consistent gaps with a no-growth rate or a meaningful zero.
12. **Exclusion of Vendors With No Sales**
The vendor metrics query is driven by the `vendor_sales` CTE, which aggregates data only for vendors that have orders in the past 12 months.
- **Impact:** Vendors that have purchase activity (or simply exist in vendor_details) but no recent sales won't show up in vendor_metrics. This could cause the frontend to miss metrics for vendors that might still be important.
- **Fix:** Consider adding a UNION or changing the driving set so that all vendors (for example, from vendor_details) are included—even if they have zero sales.
13. **Identical Formulas for On-Time Delivery and Order Fill Rates**
Both metrics are calculated as `(received_orders / total_orders) * 100`.
- **Impact:** If the business expects these to be distinct (for example, one might factor in on-time receipt versus mere receipt), then showing identical values on the frontend could be misleading.
- **Fix:** Verify and adjust the formulas if on-time delivery and order fill rates should be computed differently.
14. **Handling Nulls and Defaults in Aggregations**
The query uses COALESCE in most places, but be sure that every aggregated value (like average lead time) correctly defaults when no data is present.
- **Impact:** Incorrect defaults might cause odd or missing numbers on the production interface.
- **Fix:** Double-check that all numeric aggregates reliably default to 0 where needed.
15. **Inconsistent Stock Filtering Conditions**
In the main brand metrics query the CTE filters products with the condition
`p.stock_quantity <= 5000 AND p.stock_quantity >= 0`
whereas in the brand time-based metrics query the condition is only `p.stock_quantity <= 5000`.
- **Impact:** This discrepancy may lead to inconsistent numbers (for example, if any products have negative stock, which might be due to data issues) between overall brand metrics and time-based metrics on the frontend.
- **Fix:** Standardize the filtering criteria so that both queries treat out-of-range stock values in the same way.
16. **Growth Rate Calculation Periods**
The growth rate is computed by comparing revenue from the last 3 months ("current") against a period from 1512 months ago ("previous").
- **Impact:** This narrow window may not reflect typical year-over-year performance and could lead to volatile or unexpected growth percentages on the frontend.
- **Fix:** Revisit the business logic for growth—if a longer or different comparison period is preferred, adjust the date intervals accordingly.
17. **Potential NULLs in Aggregated Time-Based Metrics**
In the brand time-based metrics query, aggregate expressions such as `SUM(o.quantity * o.price)` aren't wrapped with COALESCE.
- **Impact:** If there are no orders for a given brand/month, these sums might return NULL rather than 0, which could propagate into the frontend display.
- **Fix:** Wrap such aggregates in COALESCE (e.g. `COALESCE(SUM(o.quantity * o.price), 0)`) to ensure a default numeric value.
18. **Grouping by Category Status in Base Metrics Insert**
- **Problem:** The INSERT for base category metrics groups by both `c.cat_id` and `c.status` even though the table's primary key is just `category_id`.
- **Effect:** If a category's status changes over time, the grouping may produce unexpected updates (or even multiple groups before the duplicate key update kicks in), possibly causing the wrong status or aggregated figures to be stored.
- **Example:** A category that toggles between "active" and "inactive" might have its metrics calculated differently on different runs.
- **Fix:** Ensure that the grouping keys match the primary key (or that the status update logic is exactly as intended) so that a single row per category is maintained.
19. **Potential Null Handling in Margin Calculations**
- **Problem:** In the query for category time metrics, the calculation of average margin uses expressions such as `SUM(o.quantity * (o.price - GREATEST(p.cost_price, 0)))` without using `COALESCE` on `p.cost_price`.
- **Effect:** If any product's `cost_price` is `NULL`, then `GREATEST(p.cost_price, 0)` returns `NULL` and the resulting sum (and thus the margin) could become `NULL` rather than defaulting to 0. This might lead to missing or misleading margin figures on the frontend.
- **Example:** A product with a missing cost price would make the entire margin expression evaluate to `NULL` even when sales exist.
- **Fix:** Replace `GREATEST(p.cost_price, 0)` with `GREATEST(COALESCE(p.cost_price, 0), 0)` (or simply use `COALESCE(p.cost_price, 0)`) to ensure that missing values are handled.
20. **Data Coverage in Growth Rate Calculation**
- **Problem:** The growth rate update depends on multiple CTEs (current period, previous period, and trend analysis) that require a minimum amount of data (for instance, `HAVING COUNT(*) >= 6` in the trend_stats CTE).
- **Effect:** Categories with insufficient historical data will fall into the "ELSE" branch (or may even be skipped if no revenue is present), which might result in a growth rate of 0.0 or an unexpected value.
- **Example:** A newly created category that has only two months of data won't have trend analysis, so its growth rate will be calculated solely by the simple difference, which might not reflect true performance.
- **Fix:** Confirm that this fallback behavior is acceptable for production; if not, adjust the logic so that every category receives a consistent growth rate even with sparse data.
21. **Omission of Forecasts for ZeroSales Categories**
- **Observation:** The categorysales metrics query uses a `HAVING AVG(cs.daily_quantity) > 0` clause.
- **Effect:** Categories without any average daily sales will not receive a forecast record in `category_sales_metrics`. If the frontend expects a row (even with zeros) for every category, this will lead to missing data.
- **Fix:** Verify that it's acceptable for categories with no sales to have no forecast entry. If not, adjust the query so that a default forecast (with zeros) is inserted.
22. **Randomness in Category-Level Forecast Revenue Calculation**
- **Problem:** In the category-level forecasts query, the forecast revenue is multiplied by a factor of `(0.95 + (RAND() * 0.1))`.
- **Effect:** This introduces randomness into the forecast figures so that repeated runs could yield slightly different values. If deterministic forecasts are expected on the production frontend, this could lead to inconsistent displays.
- **Example:** The same category might show a 5% higher forecast on one run and 3% on another because of the random multiplier.
- **Fix:** Confirm that this randomness is intentional for your forecasting model; if forecasts are meant to be reproducible, remove or replace the `RAND()` factor with a fixed multiplier.
23. **Multi-Statement Cleanup of Temporary Tables**
- **Problem:** The cleanup query drops multiple temporary tables in one call (separated by semicolons).
- **Effect:** If your Node.js MySQL driver isn't configured to allow multi-statement execution, this query may fail, leaving temporary tables behind. Leftover temporary tables might eventually cause conflicts or resource issues.
- **Example:** Running the cleanup query could produce an error like "multi-statement queries not enabled," preventing proper cleanup.
- **Fix:** Either configure your database connection to allow multi-statements or issue separate queries for each temporary table drop to ensure that the cleanup runs successfully.
24. **Handling Products with No Sales Data**
- **Problem:** In the product-level forecast calculation, the CTE `daily_stats` includes a `HAVING AVG(ds.daily_quantity) > 0` clause.
- **Effect:** Products that have no sales (or a zero average daily quantity) will be excluded from the forecasts. This means the frontend won't show forecasts for nonselling products, which might be acceptable but could also be a completeness issue.
- **Example:** A product that has never sold will not appear in the `sales_forecasts` table.
- **Fix:** Confirm that it is intended for forecasts to be generated only for products with some sales activity. If forecasts are required for all products, adjust the query to insert default forecast records for products with zero sales.
25. **Complexity of the Forecast Formula Involving the Seasonality Factor**
- **Issue:**
The sales forecast calculations incorporate an adjustment factor using `COALESCE(sf.seasonality_factor, 0)` to modify forecast units and revenue. This means that if the seasonality data is missing (or not populated), the factor defaults to 0.
- **Potential Problem:**
A default value of 0 will drastically alter the forecast calculations—often leading to a forecast of 0 or an overly dampened forecast—when in reality the intended behavior might be to use a neutral multiplier (typically 1.0). This could result in forecasts that are not reflective of the actual seasonal impact, thereby skewing the figures that reach the frontend.
- **Fix:**
Review your data source for seasonality (the `sales_seasonality` table) and ensure it's consistently populated. Alternatively, if missing seasonality data is possible, consider using a more neutral default (such as 1.0) in your COALESCE. This change would prevent the forecast formulas from over-simplifying (or even nullifying) the forecast output due to missing seasonality factors.
26. **Group By with Seasonality Factor Variability**
- **Observation:** In the forecast insertion query, the GROUP BY clause includes `sf.seasonality_factor` along with other fields.
- **Effect:** If the seasonality factor differs (or is `NULL` versus a value) for different forecast dates, this might result in multiple rows for the same product and forecast date. However, the `ON DUPLICATE KEY UPDATE` clause will merge them—but only if the primary key (pid, forecast_date) is truly unique.
- **Fix:** Verify that the grouping produces exactly one row per product per forecast date. If there's potential for multiple rows due to seasonality variability, consider applying a COALESCE or an aggregation on the seasonality factor so that it does not affect grouping.
27. **Memory Management for Temporary Tables** [RESOLVED - calculate-metrics.js]
- **Problem:** In metrics calculations, temporary tables aren't always properly cleaned up if the process fails between creation and the DROP statement.
- **Effect:** If a process fails after creating temporary tables but before dropping them, these tables remain in memory until the connection is closed. In a production environment with multiple calculation runs, this could lead to memory leaks or table name conflicts.
- **Example:** The `temp_revenue_ranks` table creation in ABC classification could remain if the process fails before reaching the DROP statement.
- **Fix:** Implement proper cleanup in a finally block or use transaction management that ensures temporary tables are always cleaned up, even in failure scenarios.

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@@ -1,150 +1,154 @@
-- Configuration tables schema -- Configuration tables schema
-- Stock threshold configurations -- Stock threshold configurations
CREATE TABLE IF NOT EXISTS stock_thresholds ( CREATE TABLE stock_thresholds (
id INT NOT NULL, id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors vendor VARCHAR(100), -- NULL means applies to all vendors
critical_days INT NOT NULL DEFAULT 7, critical_days INTEGER NOT NULL DEFAULT 7,
reorder_days INT NOT NULL DEFAULT 14, reorder_days INTEGER NOT NULL DEFAULT 14,
overstock_days INT NOT NULL DEFAULT 90, overstock_days INTEGER NOT NULL DEFAULT 90,
low_stock_threshold INT NOT NULL DEFAULT 5, low_stock_threshold INTEGER NOT NULL DEFAULT 5,
min_reorder_quantity INT NOT NULL DEFAULT 1, min_reorder_quantity INTEGER NOT NULL DEFAULT 1,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id), PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE KEY unique_category_vendor (category_id, vendor), UNIQUE (category_id, vendor)
INDEX idx_st_metrics (category_id, vendor)
); );
CREATE INDEX idx_st_metrics ON stock_thresholds(category_id, vendor);
-- Lead time threshold configurations -- Lead time threshold configurations
CREATE TABLE IF NOT EXISTS lead_time_thresholds ( CREATE TABLE lead_time_thresholds (
id INT NOT NULL, id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors vendor VARCHAR(100), -- NULL means applies to all vendors
target_days INT NOT NULL DEFAULT 14, target_days INTEGER NOT NULL DEFAULT 14,
warning_days INT NOT NULL DEFAULT 21, warning_days INTEGER NOT NULL DEFAULT 21,
critical_days INT NOT NULL DEFAULT 30, critical_days INTEGER NOT NULL DEFAULT 30,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id), PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE KEY unique_category_vendor (category_id, vendor) UNIQUE (category_id, vendor)
); );
-- Sales velocity window configurations -- Sales velocity window configurations
CREATE TABLE IF NOT EXISTS sales_velocity_config ( CREATE TABLE sales_velocity_config (
id INT NOT NULL, id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors vendor VARCHAR(100), -- NULL means applies to all vendors
daily_window_days INT NOT NULL DEFAULT 30, daily_window_days INTEGER NOT NULL DEFAULT 30,
weekly_window_days INT NOT NULL DEFAULT 7, weekly_window_days INTEGER NOT NULL DEFAULT 7,
monthly_window_days INT NOT NULL DEFAULT 90, monthly_window_days INTEGER NOT NULL DEFAULT 90,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id), PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE KEY unique_category_vendor (category_id, vendor), UNIQUE (category_id, vendor)
INDEX idx_sv_metrics (category_id, vendor)
); );
CREATE INDEX idx_sv_metrics ON sales_velocity_config(category_id, vendor);
-- ABC Classification configurations -- ABC Classification configurations
CREATE TABLE IF NOT EXISTS abc_classification_config ( CREATE TABLE abc_classification_config (
id INT NOT NULL PRIMARY KEY, id INTEGER NOT NULL PRIMARY KEY,
a_threshold DECIMAL(5,2) NOT NULL DEFAULT 20.0, a_threshold DECIMAL(5,2) NOT NULL DEFAULT 20.0,
b_threshold DECIMAL(5,2) NOT NULL DEFAULT 50.0, b_threshold DECIMAL(5,2) NOT NULL DEFAULT 50.0,
classification_period_days INT NOT NULL DEFAULT 90, classification_period_days INTEGER NOT NULL DEFAULT 90,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
); );
-- Safety stock configurations -- Safety stock configurations
CREATE TABLE IF NOT EXISTS safety_stock_config ( CREATE TABLE safety_stock_config (
id INT NOT NULL, id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors vendor VARCHAR(100), -- NULL means applies to all vendors
coverage_days INT NOT NULL DEFAULT 14, coverage_days INTEGER NOT NULL DEFAULT 14,
service_level DECIMAL(5,2) NOT NULL DEFAULT 95.0, service_level DECIMAL(5,2) NOT NULL DEFAULT 95.0,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id), PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE KEY unique_category_vendor (category_id, vendor), UNIQUE (category_id, vendor)
INDEX idx_ss_metrics (category_id, vendor)
); );
CREATE INDEX idx_ss_metrics ON safety_stock_config(category_id, vendor);
-- Turnover rate configurations -- Turnover rate configurations
CREATE TABLE IF NOT EXISTS turnover_config ( CREATE TABLE turnover_config (
id INT NOT NULL, id INTEGER NOT NULL,
category_id BIGINT, -- NULL means default/global threshold category_id BIGINT, -- NULL means default/global threshold
vendor VARCHAR(100), -- NULL means applies to all vendors vendor VARCHAR(100), -- NULL means applies to all vendors
calculation_period_days INT NOT NULL DEFAULT 30, calculation_period_days INTEGER NOT NULL DEFAULT 30,
target_rate DECIMAL(10,2) NOT NULL DEFAULT 1.0, target_rate DECIMAL(10,2) NOT NULL DEFAULT 1.0,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id), PRIMARY KEY (id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE,
UNIQUE KEY unique_category_vendor (category_id, vendor) UNIQUE (category_id, vendor)
); );
-- Create table for sales seasonality factors -- Create table for sales seasonality factors
CREATE TABLE IF NOT EXISTS sales_seasonality ( CREATE TABLE sales_seasonality (
month INT NOT NULL, month INTEGER NOT NULL,
seasonality_factor DECIMAL(5,3) DEFAULT 0, seasonality_factor DECIMAL(5,3) DEFAULT 0,
last_updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (month), PRIMARY KEY (month),
CHECK (month BETWEEN 1 AND 12), CONSTRAINT month_range CHECK (month BETWEEN 1 AND 12),
CHECK (seasonality_factor BETWEEN -1.0 AND 1.0) CONSTRAINT seasonality_range CHECK (seasonality_factor BETWEEN -1.0 AND 1.0)
); );
-- Insert default global thresholds if not exists -- Insert default global thresholds
INSERT INTO stock_thresholds (id, category_id, vendor, critical_days, reorder_days, overstock_days) INSERT INTO stock_thresholds (id, category_id, vendor, critical_days, reorder_days, overstock_days)
VALUES (1, NULL, NULL, 7, 14, 90) VALUES (1, NULL, NULL, 7, 14, 90)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
critical_days = VALUES(critical_days), critical_days = EXCLUDED.critical_days,
reorder_days = VALUES(reorder_days), reorder_days = EXCLUDED.reorder_days,
overstock_days = VALUES(overstock_days); overstock_days = EXCLUDED.overstock_days;
INSERT INTO lead_time_thresholds (id, category_id, vendor, target_days, warning_days, critical_days) INSERT INTO lead_time_thresholds (id, category_id, vendor, target_days, warning_days, critical_days)
VALUES (1, NULL, NULL, 14, 21, 30) VALUES (1, NULL, NULL, 14, 21, 30)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
target_days = VALUES(target_days), target_days = EXCLUDED.target_days,
warning_days = VALUES(warning_days), warning_days = EXCLUDED.warning_days,
critical_days = VALUES(critical_days); critical_days = EXCLUDED.critical_days;
INSERT INTO sales_velocity_config (id, category_id, vendor, daily_window_days, weekly_window_days, monthly_window_days) INSERT INTO sales_velocity_config (id, category_id, vendor, daily_window_days, weekly_window_days, monthly_window_days)
VALUES (1, NULL, NULL, 30, 7, 90) VALUES (1, NULL, NULL, 30, 7, 90)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
daily_window_days = VALUES(daily_window_days), daily_window_days = EXCLUDED.daily_window_days,
weekly_window_days = VALUES(weekly_window_days), weekly_window_days = EXCLUDED.weekly_window_days,
monthly_window_days = VALUES(monthly_window_days); monthly_window_days = EXCLUDED.monthly_window_days;
INSERT INTO abc_classification_config (id, a_threshold, b_threshold, classification_period_days) INSERT INTO abc_classification_config (id, a_threshold, b_threshold, classification_period_days)
VALUES (1, 20.0, 50.0, 90) VALUES (1, 20.0, 50.0, 90)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
a_threshold = VALUES(a_threshold), a_threshold = EXCLUDED.a_threshold,
b_threshold = VALUES(b_threshold), b_threshold = EXCLUDED.b_threshold,
classification_period_days = VALUES(classification_period_days); classification_period_days = EXCLUDED.classification_period_days;
INSERT INTO safety_stock_config (id, category_id, vendor, coverage_days, service_level) INSERT INTO safety_stock_config (id, category_id, vendor, coverage_days, service_level)
VALUES (1, NULL, NULL, 14, 95.0) VALUES (1, NULL, NULL, 14, 95.0)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
coverage_days = VALUES(coverage_days), coverage_days = EXCLUDED.coverage_days,
service_level = VALUES(service_level); service_level = EXCLUDED.service_level;
INSERT INTO turnover_config (id, category_id, vendor, calculation_period_days, target_rate) INSERT INTO turnover_config (id, category_id, vendor, calculation_period_days, target_rate)
VALUES (1, NULL, NULL, 30, 1.0) VALUES (1, NULL, NULL, 30, 1.0)
ON DUPLICATE KEY UPDATE ON CONFLICT (id) DO UPDATE SET
calculation_period_days = VALUES(calculation_period_days), calculation_period_days = EXCLUDED.calculation_period_days,
target_rate = VALUES(target_rate); target_rate = EXCLUDED.target_rate;
-- Insert default seasonality factors (neutral) -- Insert default seasonality factors (neutral)
INSERT INTO sales_seasonality (month, seasonality_factor) INSERT INTO sales_seasonality (month, seasonality_factor)
VALUES VALUES
(1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0),
(7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0) (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0)
ON DUPLICATE KEY UPDATE last_updated = CURRENT_TIMESTAMP; ON CONFLICT (month) DO UPDATE SET
last_updated = CURRENT_TIMESTAMP;
-- View to show thresholds with category names -- View to show thresholds with category names
CREATE OR REPLACE VIEW stock_thresholds_view AS CREATE OR REPLACE VIEW stock_thresholds_view AS
@@ -153,9 +157,9 @@ SELECT
c.name as category_name, c.name as category_name,
CASE CASE
WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 'Global Default' WHEN st.category_id IS NULL AND st.vendor IS NULL THEN 'Global Default'
WHEN st.category_id IS NULL THEN CONCAT('Vendor: ', st.vendor) WHEN st.category_id IS NULL THEN 'Vendor: ' || st.vendor
WHEN st.vendor IS NULL THEN CONCAT('Category: ', c.name) WHEN st.vendor IS NULL THEN 'Category: ' || c.name
ELSE CONCAT('Category: ', c.name, ' / Vendor: ', st.vendor) ELSE 'Category: ' || c.name || ' / Vendor: ' || st.vendor
END as threshold_scope END as threshold_scope
FROM FROM
stock_thresholds st stock_thresholds st
@@ -171,26 +175,51 @@ ORDER BY
c.name, c.name,
st.vendor; st.vendor;
-- History and status tables
CREATE TABLE IF NOT EXISTS calculate_history (
id BIGSERIAL PRIMARY KEY,
start_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
end_time TIMESTAMP NULL,
duration_seconds INTEGER,
duration_minutes DECIMAL(10,2) GENERATED ALWAYS AS (duration_seconds::decimal / 60.0) STORED,
total_products INTEGER DEFAULT 0,
total_orders INTEGER DEFAULT 0,
total_purchase_orders INTEGER DEFAULT 0,
processed_products INTEGER DEFAULT 0,
processed_orders INTEGER DEFAULT 0,
processed_purchase_orders INTEGER DEFAULT 0,
status calculation_status DEFAULT 'running',
error_message TEXT,
additional_info JSONB
);
CREATE TABLE IF NOT EXISTS calculate_status (
module_name module_name PRIMARY KEY,
last_calculation_timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
);
CREATE TABLE IF NOT EXISTS sync_status ( CREATE TABLE IF NOT EXISTS sync_status (
table_name VARCHAR(50) PRIMARY KEY, table_name VARCHAR(50) PRIMARY KEY,
last_sync_timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_sync_timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
last_sync_id BIGINT, last_sync_id BIGINT
INDEX idx_last_sync (last_sync_timestamp)
); );
CREATE TABLE IF NOT EXISTS import_history ( CREATE TABLE IF NOT EXISTS import_history (
id BIGINT AUTO_INCREMENT PRIMARY KEY, id BIGSERIAL PRIMARY KEY,
table_name VARCHAR(50) NOT NULL, table_name VARCHAR(50) NOT NULL,
start_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, start_time TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
end_time TIMESTAMP NULL, end_time TIMESTAMP NULL,
duration_seconds INT, duration_seconds INTEGER,
duration_minutes DECIMAL(10,2) GENERATED ALWAYS AS (duration_seconds / 60.0) STORED, duration_minutes DECIMAL(10,2) GENERATED ALWAYS AS (duration_seconds::decimal / 60.0) STORED,
records_added INT DEFAULT 0, records_added INTEGER DEFAULT 0,
records_updated INT DEFAULT 0, records_updated INTEGER DEFAULT 0,
is_incremental BOOLEAN DEFAULT FALSE, is_incremental BOOLEAN DEFAULT FALSE,
status ENUM('running', 'completed', 'failed', 'cancelled') DEFAULT 'running', status calculation_status DEFAULT 'running',
error_message TEXT, error_message TEXT,
additional_info JSON, additional_info JSONB
INDEX idx_table_time (table_name, start_time),
INDEX idx_status (status)
); );
-- Create all indexes after tables are fully created
CREATE INDEX IF NOT EXISTS idx_last_calc ON calculate_status(last_calculation_timestamp);
CREATE INDEX IF NOT EXISTS idx_last_sync ON sync_status(last_sync_timestamp);
CREATE INDEX IF NOT EXISTS idx_table_time ON import_history(table_name, start_time);

View File

@@ -1,8 +1,8 @@
-- Disable foreign key checks -- Disable foreign key checks
SET FOREIGN_KEY_CHECKS = 0; SET session_replication_role = 'replica';
-- Temporary tables for batch metrics processing -- Temporary tables for batch metrics processing
CREATE TABLE IF NOT EXISTS temp_sales_metrics ( CREATE TABLE temp_sales_metrics (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
daily_sales_avg DECIMAL(10,3), daily_sales_avg DECIMAL(10,3),
weekly_sales_avg DECIMAL(10,3), weekly_sales_avg DECIMAL(10,3),
@@ -14,9 +14,9 @@ CREATE TABLE IF NOT EXISTS temp_sales_metrics (
PRIMARY KEY (pid) PRIMARY KEY (pid)
); );
CREATE TABLE IF NOT EXISTS temp_purchase_metrics ( CREATE TABLE temp_purchase_metrics (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
avg_lead_time_days INT, avg_lead_time_days INTEGER,
last_purchase_date DATE, last_purchase_date DATE,
first_received_date DATE, first_received_date DATE,
last_received_date DATE, last_received_date DATE,
@@ -24,7 +24,7 @@ CREATE TABLE IF NOT EXISTS temp_purchase_metrics (
); );
-- New table for product metrics -- New table for product metrics
CREATE TABLE IF NOT EXISTS product_metrics ( CREATE TABLE product_metrics (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-- Sales velocity metrics -- Sales velocity metrics
@@ -32,16 +32,16 @@ CREATE TABLE IF NOT EXISTS product_metrics (
weekly_sales_avg DECIMAL(10,3), weekly_sales_avg DECIMAL(10,3),
monthly_sales_avg DECIMAL(10,3), monthly_sales_avg DECIMAL(10,3),
avg_quantity_per_order DECIMAL(10,3), avg_quantity_per_order DECIMAL(10,3),
number_of_orders INT, number_of_orders INTEGER,
first_sale_date DATE, first_sale_date DATE,
last_sale_date DATE, last_sale_date DATE,
-- Stock metrics -- Stock metrics
days_of_inventory INT, days_of_inventory INTEGER,
weeks_of_inventory INT, weeks_of_inventory INTEGER,
reorder_point INT, reorder_point INTEGER,
safety_stock INT, safety_stock INTEGER,
reorder_qty INT DEFAULT 0, reorder_qty INTEGER DEFAULT 0,
overstocked_amt INT DEFAULT 0, overstocked_amt INTEGER DEFAULT 0,
-- Financial metrics -- Financial metrics
avg_margin_percent DECIMAL(10,3), avg_margin_percent DECIMAL(10,3),
total_revenue DECIMAL(10,3), total_revenue DECIMAL(10,3),
@@ -50,7 +50,7 @@ CREATE TABLE IF NOT EXISTS product_metrics (
gross_profit DECIMAL(10,3), gross_profit DECIMAL(10,3),
gmroi DECIMAL(10,3), gmroi DECIMAL(10,3),
-- Purchase metrics -- Purchase metrics
avg_lead_time_days INT, avg_lead_time_days INTEGER,
last_purchase_date DATE, last_purchase_date DATE,
first_received_date DATE, first_received_date DATE,
last_received_date DATE, last_received_date DATE,
@@ -60,97 +60,99 @@ CREATE TABLE IF NOT EXISTS product_metrics (
-- Turnover metrics -- Turnover metrics
turnover_rate DECIMAL(12,3), turnover_rate DECIMAL(12,3),
-- Lead time metrics -- Lead time metrics
current_lead_time INT, current_lead_time INTEGER,
target_lead_time INT, target_lead_time INTEGER,
lead_time_status VARCHAR(20), lead_time_status VARCHAR(20),
-- Forecast metrics -- Forecast metrics
forecast_accuracy DECIMAL(5,2) DEFAULT NULL, forecast_accuracy DECIMAL(5,2) DEFAULT NULL,
forecast_bias DECIMAL(5,2) DEFAULT NULL, forecast_bias DECIMAL(5,2) DEFAULT NULL,
last_forecast_date DATE DEFAULT NULL, last_forecast_date DATE DEFAULT NULL,
PRIMARY KEY (pid), PRIMARY KEY (pid),
FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE, FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE
INDEX idx_metrics_revenue (total_revenue),
INDEX idx_metrics_stock_status (stock_status),
INDEX idx_metrics_lead_time (lead_time_status),
INDEX idx_metrics_turnover (turnover_rate),
INDEX idx_metrics_last_calculated (last_calculated_at),
INDEX idx_metrics_abc (abc_class),
INDEX idx_metrics_sales (daily_sales_avg, weekly_sales_avg, monthly_sales_avg),
INDEX idx_metrics_forecast (forecast_accuracy, forecast_bias)
); );
CREATE INDEX idx_metrics_revenue ON product_metrics(total_revenue);
CREATE INDEX idx_metrics_stock_status ON product_metrics(stock_status);
CREATE INDEX idx_metrics_lead_time ON product_metrics(lead_time_status);
CREATE INDEX idx_metrics_turnover ON product_metrics(turnover_rate);
CREATE INDEX idx_metrics_last_calculated ON product_metrics(last_calculated_at);
CREATE INDEX idx_metrics_abc ON product_metrics(abc_class);
CREATE INDEX idx_metrics_sales ON product_metrics(daily_sales_avg, weekly_sales_avg, monthly_sales_avg);
CREATE INDEX idx_metrics_forecast ON product_metrics(forecast_accuracy, forecast_bias);
-- New table for time-based aggregates -- New table for time-based aggregates
CREATE TABLE IF NOT EXISTS product_time_aggregates ( CREATE TABLE product_time_aggregates (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
year INT NOT NULL, year INTEGER NOT NULL,
month INT NOT NULL, month INTEGER NOT NULL,
-- Sales metrics -- Sales metrics
total_quantity_sold INT DEFAULT 0, total_quantity_sold INTEGER DEFAULT 0,
total_revenue DECIMAL(10,3) DEFAULT 0, total_revenue DECIMAL(10,3) DEFAULT 0,
total_cost DECIMAL(10,3) DEFAULT 0, total_cost DECIMAL(10,3) DEFAULT 0,
order_count INT DEFAULT 0, order_count INTEGER DEFAULT 0,
-- Stock changes -- Stock changes
stock_received INT DEFAULT 0, stock_received INTEGER DEFAULT 0,
stock_ordered INT DEFAULT 0, stock_ordered INTEGER DEFAULT 0,
-- Calculated fields -- Calculated fields
avg_price DECIMAL(10,3), avg_price DECIMAL(10,3),
profit_margin DECIMAL(10,3), profit_margin DECIMAL(10,3),
inventory_value DECIMAL(10,3), inventory_value DECIMAL(10,3),
gmroi DECIMAL(10,3), gmroi DECIMAL(10,3),
PRIMARY KEY (pid, year, month), PRIMARY KEY (pid, year, month),
FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE, FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE
INDEX idx_date (year, month)
); );
-- Create vendor details table CREATE INDEX idx_date ON product_time_aggregates(year, month);
CREATE TABLE IF NOT EXISTS vendor_details (
vendor VARCHAR(100) NOT NULL, -- Create vendor_details table
CREATE TABLE vendor_details (
vendor VARCHAR(100) PRIMARY KEY,
contact_name VARCHAR(100), contact_name VARCHAR(100),
email VARCHAR(100), email VARCHAR(255),
phone VARCHAR(20), phone VARCHAR(50),
status VARCHAR(20) DEFAULT 'active', status VARCHAR(20) DEFAULT 'active',
notes TEXT, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (vendor),
INDEX idx_vendor_status (status)
); );
CREATE INDEX idx_vendor_details_status ON vendor_details(status);
-- New table for vendor metrics -- New table for vendor metrics
CREATE TABLE IF NOT EXISTS vendor_metrics ( CREATE TABLE vendor_metrics (
vendor VARCHAR(100) NOT NULL, vendor VARCHAR(100) NOT NULL,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-- Performance metrics -- Performance metrics
avg_lead_time_days DECIMAL(10,3), avg_lead_time_days DECIMAL(10,3),
on_time_delivery_rate DECIMAL(5,2), on_time_delivery_rate DECIMAL(5,2),
order_fill_rate DECIMAL(5,2), order_fill_rate DECIMAL(5,2),
total_orders INT DEFAULT 0, total_orders INTEGER DEFAULT 0,
total_late_orders INT DEFAULT 0, total_late_orders INTEGER DEFAULT 0,
total_purchase_value DECIMAL(10,3) DEFAULT 0, total_purchase_value DECIMAL(10,3) DEFAULT 0,
avg_order_value DECIMAL(10,3), avg_order_value DECIMAL(10,3),
-- Product metrics -- Product metrics
active_products INT DEFAULT 0, active_products INTEGER DEFAULT 0,
total_products INT DEFAULT 0, total_products INTEGER DEFAULT 0,
-- Financial metrics -- Financial metrics
total_revenue DECIMAL(10,3) DEFAULT 0, total_revenue DECIMAL(10,3) DEFAULT 0,
avg_margin_percent DECIMAL(5,2), avg_margin_percent DECIMAL(5,2),
-- Status -- Status
status VARCHAR(20) DEFAULT 'active', status VARCHAR(20) DEFAULT 'active',
PRIMARY KEY (vendor), PRIMARY KEY (vendor),
FOREIGN KEY (vendor) REFERENCES vendor_details(vendor) ON DELETE CASCADE, FOREIGN KEY (vendor) REFERENCES vendor_details(vendor) ON DELETE CASCADE
INDEX idx_vendor_performance (on_time_delivery_rate),
INDEX idx_vendor_status (status),
INDEX idx_metrics_last_calculated (last_calculated_at),
INDEX idx_vendor_metrics_orders (total_orders, total_late_orders)
); );
CREATE INDEX idx_vendor_performance ON vendor_metrics(on_time_delivery_rate);
CREATE INDEX idx_vendor_status ON vendor_metrics(status);
CREATE INDEX idx_vendor_metrics_last_calculated ON vendor_metrics(last_calculated_at);
CREATE INDEX idx_vendor_metrics_orders ON vendor_metrics(total_orders, total_late_orders);
-- New table for category metrics -- New table for category metrics
CREATE TABLE IF NOT EXISTS category_metrics ( CREATE TABLE category_metrics (
category_id BIGINT NOT NULL, category_id BIGINT NOT NULL,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-- Product metrics -- Product metrics
product_count INT DEFAULT 0, product_count INTEGER DEFAULT 0,
active_products INT DEFAULT 0, active_products INTEGER DEFAULT 0,
-- Financial metrics -- Financial metrics
total_value DECIMAL(15,3) DEFAULT 0, total_value DECIMAL(15,3) DEFAULT 0,
avg_margin DECIMAL(5,2), avg_margin DECIMAL(5,2),
@@ -159,272 +161,215 @@ CREATE TABLE IF NOT EXISTS category_metrics (
-- Status -- Status
status VARCHAR(20) DEFAULT 'active', status VARCHAR(20) DEFAULT 'active',
PRIMARY KEY (category_id), PRIMARY KEY (category_id),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE
INDEX idx_category_status (status),
INDEX idx_category_growth (growth_rate),
INDEX idx_metrics_last_calculated (last_calculated_at),
INDEX idx_category_metrics_products (product_count, active_products)
); );
CREATE INDEX idx_category_status ON category_metrics(status);
CREATE INDEX idx_category_growth ON category_metrics(growth_rate);
CREATE INDEX idx_metrics_last_calculated_cat ON category_metrics(last_calculated_at);
CREATE INDEX idx_category_metrics_products ON category_metrics(product_count, active_products);
-- New table for vendor time-based metrics -- New table for vendor time-based metrics
CREATE TABLE IF NOT EXISTS vendor_time_metrics ( CREATE TABLE vendor_time_metrics (
vendor VARCHAR(100) NOT NULL, vendor VARCHAR(100) NOT NULL,
year INT NOT NULL, year INTEGER NOT NULL,
month INT NOT NULL, month INTEGER NOT NULL,
-- Order metrics -- Order metrics
total_orders INT DEFAULT 0, total_orders INTEGER DEFAULT 0,
late_orders INT DEFAULT 0, late_orders INTEGER DEFAULT 0,
avg_lead_time_days DECIMAL(10,3), avg_lead_time_days DECIMAL(10,3),
-- Financial metrics -- Financial metrics
total_purchase_value DECIMAL(10,3) DEFAULT 0, total_purchase_value DECIMAL(10,3) DEFAULT 0,
total_revenue DECIMAL(10,3) DEFAULT 0, total_revenue DECIMAL(10,3) DEFAULT 0,
avg_margin_percent DECIMAL(5,2), avg_margin_percent DECIMAL(5,2),
PRIMARY KEY (vendor, year, month), PRIMARY KEY (vendor, year, month),
FOREIGN KEY (vendor) REFERENCES vendor_details(vendor) ON DELETE CASCADE, FOREIGN KEY (vendor) REFERENCES vendor_details(vendor) ON DELETE CASCADE
INDEX idx_vendor_date (year, month)
); );
CREATE INDEX idx_vendor_date ON vendor_time_metrics(year, month);
-- New table for category time-based metrics -- New table for category time-based metrics
CREATE TABLE IF NOT EXISTS category_time_metrics ( CREATE TABLE category_time_metrics (
category_id BIGINT NOT NULL, category_id BIGINT NOT NULL,
year INT NOT NULL, year INTEGER NOT NULL,
month INT NOT NULL, month INTEGER NOT NULL,
-- Product metrics -- Product metrics
product_count INT DEFAULT 0, product_count INTEGER DEFAULT 0,
active_products INT DEFAULT 0, active_products INTEGER DEFAULT 0,
-- Financial metrics -- Financial metrics
total_value DECIMAL(15,3) DEFAULT 0, total_value DECIMAL(15,3) DEFAULT 0,
total_revenue DECIMAL(15,3) DEFAULT 0, total_revenue DECIMAL(15,3) DEFAULT 0,
avg_margin DECIMAL(5,2), avg_margin DECIMAL(5,2),
turnover_rate DECIMAL(12,3), turnover_rate DECIMAL(12,3),
PRIMARY KEY (category_id, year, month), PRIMARY KEY (category_id, year, month),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE
INDEX idx_category_date (year, month)
); );
CREATE INDEX idx_category_date ON category_time_metrics(year, month);
-- New table for category-based sales metrics -- New table for category-based sales metrics
CREATE TABLE IF NOT EXISTS category_sales_metrics ( CREATE TABLE category_sales_metrics (
category_id BIGINT NOT NULL, category_id BIGINT NOT NULL,
brand VARCHAR(100) NOT NULL, brand VARCHAR(100) NOT NULL,
period_start DATE NOT NULL, period_start DATE NOT NULL,
period_end DATE NOT NULL, period_end DATE NOT NULL,
avg_daily_sales DECIMAL(10,3) DEFAULT 0, avg_daily_sales DECIMAL(10,3) DEFAULT 0,
total_sold INT DEFAULT 0, total_sold INTEGER DEFAULT 0,
num_products INT DEFAULT 0, num_products INTEGER DEFAULT 0,
avg_price DECIMAL(10,3) DEFAULT 0, avg_price DECIMAL(10,3) DEFAULT 0,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (category_id, brand, period_start, period_end), PRIMARY KEY (category_id, brand, period_start, period_end),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE
INDEX idx_category_brand (category_id, brand),
INDEX idx_period (period_start, period_end)
); );
CREATE INDEX idx_category_brand ON category_sales_metrics(category_id, brand);
CREATE INDEX idx_period ON category_sales_metrics(period_start, period_end);
-- New table for brand metrics -- New table for brand metrics
CREATE TABLE IF NOT EXISTS brand_metrics ( CREATE TABLE brand_metrics (
brand VARCHAR(100) NOT NULL, brand VARCHAR(100) NOT NULL,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-- Product metrics -- Product metrics
product_count INT DEFAULT 0, product_count INTEGER DEFAULT 0,
active_products INT DEFAULT 0, active_products INTEGER DEFAULT 0,
-- Stock metrics -- Stock metrics
total_stock_units INT DEFAULT 0, total_stock_units INTEGER DEFAULT 0,
total_stock_cost DECIMAL(15,2) DEFAULT 0, total_stock_cost DECIMAL(15,2) DEFAULT 0,
total_stock_retail DECIMAL(15,2) DEFAULT 0, total_stock_retail DECIMAL(15,2) DEFAULT 0,
-- Sales metrics -- Sales metrics
total_revenue DECIMAL(15,2) DEFAULT 0, total_revenue DECIMAL(15,2) DEFAULT 0,
avg_margin DECIMAL(5,2) DEFAULT 0, avg_margin DECIMAL(5,2) DEFAULT 0,
growth_rate DECIMAL(5,2) DEFAULT 0, growth_rate DECIMAL(5,2) DEFAULT 0,
PRIMARY KEY (brand), PRIMARY KEY (brand)
INDEX idx_brand_metrics_last_calculated (last_calculated_at),
INDEX idx_brand_metrics_revenue (total_revenue),
INDEX idx_brand_metrics_growth (growth_rate)
); );
CREATE INDEX idx_brand_metrics_last_calculated ON brand_metrics(last_calculated_at);
CREATE INDEX idx_brand_metrics_revenue ON brand_metrics(total_revenue);
CREATE INDEX idx_brand_metrics_growth ON brand_metrics(growth_rate);
-- New table for brand time-based metrics -- New table for brand time-based metrics
CREATE TABLE IF NOT EXISTS brand_time_metrics ( CREATE TABLE brand_time_metrics (
brand VARCHAR(100) NOT NULL, brand VARCHAR(100) NOT NULL,
year INT NOT NULL, year INTEGER NOT NULL,
month INT NOT NULL, month INTEGER NOT NULL,
-- Product metrics -- Product metrics
product_count INT DEFAULT 0, product_count INTEGER DEFAULT 0,
active_products INT DEFAULT 0, active_products INTEGER DEFAULT 0,
-- Stock metrics -- Stock metrics
total_stock_units INT DEFAULT 0, total_stock_units INTEGER DEFAULT 0,
total_stock_cost DECIMAL(15,2) DEFAULT 0, total_stock_cost DECIMAL(15,2) DEFAULT 0,
total_stock_retail DECIMAL(15,2) DEFAULT 0, total_stock_retail DECIMAL(15,2) DEFAULT 0,
-- Sales metrics -- Sales metrics
total_revenue DECIMAL(15,2) DEFAULT 0, total_revenue DECIMAL(15,2) DEFAULT 0,
avg_margin DECIMAL(5,2) DEFAULT 0, avg_margin DECIMAL(5,2) DEFAULT 0,
PRIMARY KEY (brand, year, month), growth_rate DECIMAL(5,2) DEFAULT 0,
INDEX idx_brand_date (year, month) PRIMARY KEY (brand, year, month)
); );
CREATE INDEX idx_brand_time_date ON brand_time_metrics(year, month);
-- New table for sales forecasts -- New table for sales forecasts
CREATE TABLE IF NOT EXISTS sales_forecasts ( CREATE TABLE sales_forecasts (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
forecast_date DATE NOT NULL, forecast_date DATE NOT NULL,
forecast_units DECIMAL(10,2) DEFAULT 0, forecast_quantity INTEGER,
forecast_revenue DECIMAL(10,2) DEFAULT 0, confidence_level DECIMAL(5,2),
confidence_level DECIMAL(5,2) DEFAULT 0, created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (pid, forecast_date), PRIMARY KEY (pid, forecast_date),
FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE, FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE
INDEX idx_forecast_date (forecast_date),
INDEX idx_forecast_last_calculated (last_calculated_at)
); );
CREATE INDEX idx_forecast_date ON sales_forecasts(forecast_date);
-- New table for category forecasts -- New table for category forecasts
CREATE TABLE IF NOT EXISTS category_forecasts ( CREATE TABLE category_forecasts (
category_id BIGINT NOT NULL, category_id BIGINT NOT NULL,
forecast_date DATE NOT NULL, forecast_date DATE NOT NULL,
forecast_units DECIMAL(10,2) DEFAULT 0, forecast_revenue DECIMAL(15,2),
forecast_revenue DECIMAL(10,2) DEFAULT 0, forecast_units INTEGER,
confidence_level DECIMAL(5,2) DEFAULT 0, confidence_level DECIMAL(5,2),
last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (category_id, forecast_date), PRIMARY KEY (category_id, forecast_date),
FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (category_id) REFERENCES categories(cat_id) ON DELETE CASCADE
INDEX idx_category_forecast_date (forecast_date),
INDEX idx_category_forecast_last_calculated (last_calculated_at)
); );
-- Create view for inventory health CREATE INDEX idx_cat_forecast_date ON category_forecasts(forecast_date);
-- Create views for common calculations
CREATE OR REPLACE VIEW inventory_health AS CREATE OR REPLACE VIEW inventory_health AS
WITH product_thresholds AS ( WITH stock_levels AS (
SELECT SELECT
p.pid, p.pid,
COALESCE( p.title,
-- Try category+vendor specific p.SKU,
(SELECT critical_days FROM stock_thresholds st p.stock_quantity,
JOIN product_categories pc ON st.category_id = pc.cat_id p.preorder_count,
WHERE pc.pid = p.pid pm.daily_sales_avg,
AND st.vendor = p.vendor LIMIT 1), pm.weekly_sales_avg,
-- Try category specific pm.monthly_sales_avg,
(SELECT critical_days FROM stock_thresholds st pm.reorder_point,
JOIN product_categories pc ON st.category_id = pc.cat_id pm.safety_stock,
WHERE pc.pid = p.pid pm.days_of_inventory,
AND st.vendor IS NULL LIMIT 1), pm.weeks_of_inventory,
-- Try vendor specific pm.stock_status,
(SELECT critical_days FROM stock_thresholds st pm.abc_class,
WHERE st.category_id IS NULL pm.turnover_rate,
AND st.vendor = p.vendor LIMIT 1), pm.avg_lead_time_days,
-- Fall back to default pm.current_lead_time,
(SELECT critical_days FROM stock_thresholds st pm.target_lead_time,
WHERE st.category_id IS NULL pm.lead_time_status,
AND st.vendor IS NULL LIMIT 1), p.cost_price,
7 p.price,
) as critical_days, pm.inventory_value,
COALESCE( pm.gmroi
-- Try category+vendor specific
(SELECT reorder_days FROM stock_thresholds st
JOIN product_categories pc ON st.category_id = pc.cat_id
WHERE pc.pid = p.pid
AND st.vendor = p.vendor LIMIT 1),
-- Try category specific
(SELECT reorder_days FROM stock_thresholds st
JOIN product_categories pc ON st.category_id = pc.cat_id
WHERE pc.pid = p.pid
AND st.vendor IS NULL LIMIT 1),
-- Try vendor specific
(SELECT reorder_days FROM stock_thresholds st
WHERE st.category_id IS NULL
AND st.vendor = p.vendor LIMIT 1),
-- Fall back to default
(SELECT reorder_days FROM stock_thresholds st
WHERE st.category_id IS NULL
AND st.vendor IS NULL LIMIT 1),
14
) as reorder_days,
COALESCE(
-- Try category+vendor specific
(SELECT overstock_days FROM stock_thresholds st
JOIN product_categories pc ON st.category_id = pc.cat_id
WHERE pc.pid = p.pid
AND st.vendor = p.vendor LIMIT 1),
-- Try category specific
(SELECT overstock_days FROM stock_thresholds st
JOIN product_categories pc ON st.category_id = pc.cat_id
WHERE pc.pid = p.pid
AND st.vendor IS NULL LIMIT 1),
-- Try vendor specific
(SELECT overstock_days FROM stock_thresholds st
WHERE st.category_id IS NULL
AND st.vendor = p.vendor LIMIT 1),
-- Fall back to default
(SELECT overstock_days FROM stock_thresholds st
WHERE st.category_id IS NULL
AND st.vendor IS NULL LIMIT 1),
90
) as overstock_days
FROM products p FROM products p
LEFT JOIN product_metrics pm ON p.pid = pm.pid
WHERE p.managing_stock = true AND p.visible = true
) )
SELECT SELECT
p.pid, *,
p.SKU,
p.title,
p.stock_quantity,
COALESCE(pm.daily_sales_avg, 0) as daily_sales_avg,
COALESCE(pm.days_of_inventory, 0) as days_of_inventory,
COALESCE(pm.reorder_point, 0) as reorder_point,
COALESCE(pm.safety_stock, 0) as safety_stock,
CASE CASE
WHEN pm.daily_sales_avg = 0 THEN 'New' WHEN stock_quantity <= safety_stock THEN 'Critical'
WHEN p.stock_quantity <= CEIL(pm.daily_sales_avg * pt.critical_days) THEN 'Critical' WHEN stock_quantity <= reorder_point THEN 'Low'
WHEN p.stock_quantity <= CEIL(pm.daily_sales_avg * pt.reorder_days) THEN 'Reorder' WHEN stock_quantity > (reorder_point * 3) THEN 'Excess'
WHEN p.stock_quantity > (pm.daily_sales_avg * pt.overstock_days) THEN 'Overstocked'
ELSE 'Healthy' ELSE 'Healthy'
END as stock_status END as inventory_status,
FROM CASE
products p WHEN lead_time_status = 'delayed' AND stock_status = 'low' THEN 'High'
LEFT JOIN WHEN lead_time_status = 'delayed' OR stock_status = 'low' THEN 'Medium'
product_metrics pm ON p.pid = pm.pid ELSE 'Low'
LEFT JOIN END as risk_level
product_thresholds pt ON p.pid = pt.pid FROM stock_levels;
WHERE
p.managing_stock = true;
-- Create view for category performance trends -- Create view for category performance trends
CREATE OR REPLACE VIEW category_performance_trends AS CREATE OR REPLACE VIEW category_performance_trends AS
WITH monthly_trends AS (
SELECT
c.cat_id,
c.name as category_name,
ctm.year,
ctm.month,
ctm.product_count,
ctm.active_products,
ctm.total_value,
ctm.total_revenue,
ctm.avg_margin,
ctm.turnover_rate,
LAG(ctm.total_revenue) OVER (PARTITION BY c.cat_id ORDER BY ctm.year, ctm.month) as prev_month_revenue,
LAG(ctm.turnover_rate) OVER (PARTITION BY c.cat_id ORDER BY ctm.year, ctm.month) as prev_month_turnover
FROM categories c
JOIN category_time_metrics ctm ON c.cat_id = ctm.category_id
)
SELECT SELECT
c.cat_id as category_id, *,
c.name,
c.description,
p.name as parent_name,
c.status,
cm.product_count,
cm.active_products,
cm.total_value,
cm.avg_margin,
cm.turnover_rate,
cm.growth_rate,
CASE CASE
WHEN cm.growth_rate >= 20 THEN 'High Growth' WHEN prev_month_revenue IS NULL THEN 0
WHEN cm.growth_rate >= 5 THEN 'Growing' ELSE ((total_revenue - prev_month_revenue) / prev_month_revenue) * 100
WHEN cm.growth_rate >= -5 THEN 'Stable' END as revenue_growth_percent,
ELSE 'Declining' CASE
END as performance_rating WHEN prev_month_turnover IS NULL THEN 0
FROM ELSE ((turnover_rate - prev_month_turnover) / prev_month_turnover) * 100
categories c END as turnover_growth_percent
LEFT JOIN FROM monthly_trends;
categories p ON c.parent_id = p.cat_id
LEFT JOIN
category_metrics cm ON c.cat_id = cm.category_id;
-- Re-enable foreign key checks SET session_replication_role = 'origin';
SET FOREIGN_KEY_CHECKS = 1;
-- Create table for sales seasonality factors
CREATE TABLE IF NOT EXISTS sales_seasonality (
month INT NOT NULL,
seasonality_factor DECIMAL(5,3) DEFAULT 0,
last_updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (month),
CHECK (month BETWEEN 1 AND 12),
CHECK (seasonality_factor BETWEEN -1.0 AND 1.0)
);
-- Insert default seasonality factors (neutral)
INSERT INTO sales_seasonality (month, seasonality_factor)
VALUES
(1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0),
(7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0)
ON DUPLICATE KEY UPDATE last_updated = CURRENT_TIMESTAMP;

View File

@@ -1,6 +1,5 @@
-- Enable strict error reporting -- Enable strict error reporting
SET sql_mode = 'STRICT_ALL_TABLES,ERROR_FOR_DIVISION_BY_ZERO,NO_ZERO_DATE,NO_ZERO_IN_DATE,NO_ENGINE_SUBSTITUTION'; SET session_replication_role = 'replica'; -- Disable foreign key checks temporarily
SET FOREIGN_KEY_CHECKS = 0;
-- Create tables -- Create tables
CREATE TABLE products ( CREATE TABLE products (
@@ -8,11 +7,11 @@ CREATE TABLE products (
title VARCHAR(255) NOT NULL, title VARCHAR(255) NOT NULL,
description TEXT, description TEXT,
SKU VARCHAR(50) NOT NULL, SKU VARCHAR(50) NOT NULL,
created_at TIMESTAMP NULL, created_at TIMESTAMP,
first_received TIMESTAMP NULL, first_received TIMESTAMP,
stock_quantity INT DEFAULT 0, stock_quantity INTEGER DEFAULT 0,
preorder_count INT DEFAULT 0, preorder_count INTEGER DEFAULT 0,
notions_inv_count INT DEFAULT 0, notions_inv_count INTEGER DEFAULT 0,
price DECIMAL(10, 3) NOT NULL, price DECIMAL(10, 3) NOT NULL,
regular_price DECIMAL(10, 3) NOT NULL, regular_price DECIMAL(10, 3) NOT NULL,
cost_price DECIMAL(10, 3), cost_price DECIMAL(10, 3),
@@ -37,57 +36,52 @@ CREATE TABLE products (
artist VARCHAR(100), artist VARCHAR(100),
options TEXT, options TEXT,
tags TEXT, tags TEXT,
moq INT DEFAULT 1, moq INTEGER DEFAULT 1,
uom INT DEFAULT 1, uom INTEGER DEFAULT 1,
rating DECIMAL(10,2) DEFAULT 0.00, rating DECIMAL(10,2) DEFAULT 0.00,
reviews INT UNSIGNED DEFAULT 0, reviews INTEGER DEFAULT 0,
weight DECIMAL(10,3), weight DECIMAL(10,3),
length DECIMAL(10,3), length DECIMAL(10,3),
width DECIMAL(10,3), width DECIMAL(10,3),
height DECIMAL(10,3), height DECIMAL(10,3),
country_of_origin VARCHAR(5), country_of_origin VARCHAR(5),
location VARCHAR(50), location VARCHAR(50),
total_sold INT UNSIGNED DEFAULT 0, total_sold INTEGER DEFAULT 0,
baskets INT UNSIGNED DEFAULT 0, baskets INTEGER DEFAULT 0,
notifies INT UNSIGNED DEFAULT 0, notifies INTEGER DEFAULT 0,
date_last_sold DATE, date_last_sold DATE,
PRIMARY KEY (pid), updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
INDEX idx_sku (SKU), PRIMARY KEY (pid)
INDEX idx_vendor (vendor), );
INDEX idx_brand (brand),
INDEX idx_location (location), -- Create indexes for products table
INDEX idx_total_sold (total_sold), CREATE INDEX idx_products_sku ON products(SKU);
INDEX idx_date_last_sold (date_last_sold) CREATE INDEX idx_products_vendor ON products(vendor);
) ENGINE=InnoDB; CREATE INDEX idx_products_brand ON products(brand);
CREATE INDEX idx_products_location ON products(location);
CREATE INDEX idx_products_total_sold ON products(total_sold);
CREATE INDEX idx_products_date_last_sold ON products(date_last_sold);
CREATE INDEX idx_products_updated ON products(updated);
-- Create categories table with hierarchy support -- Create categories table with hierarchy support
CREATE TABLE categories ( CREATE TABLE categories (
cat_id BIGINT PRIMARY KEY, cat_id BIGINT PRIMARY KEY,
name VARCHAR(100) NOT NULL, name VARCHAR(100) NOT NULL,
type SMALLINT NOT NULL COMMENT '10=section, 11=category, 12=subcategory, 13=subsubcategory, 1=company, 2=line, 3=subline, 40=artist', type SMALLINT NOT NULL,
parent_id BIGINT, parent_id BIGINT,
description TEXT, description TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
status VARCHAR(20) DEFAULT 'active', status VARCHAR(20) DEFAULT 'active',
FOREIGN KEY (parent_id) REFERENCES categories(cat_id), FOREIGN KEY (parent_id) REFERENCES categories(cat_id)
INDEX idx_parent (parent_id), );
INDEX idx_type (type),
INDEX idx_status (status),
INDEX idx_name_type (name, type)
) ENGINE=InnoDB;
-- Create vendor_details table COMMENT ON COLUMN categories.type IS '10=section, 11=category, 12=subcategory, 13=subsubcategory, 1=company, 2=line, 3=subline, 40=artist';
CREATE TABLE vendor_details (
vendor VARCHAR(100) PRIMARY KEY, CREATE INDEX idx_categories_parent ON categories(parent_id);
contact_name VARCHAR(100), CREATE INDEX idx_categories_type ON categories(type);
email VARCHAR(255), CREATE INDEX idx_categories_status ON categories(status);
phone VARCHAR(50), CREATE INDEX idx_categories_name_type ON categories(name, type);
status VARCHAR(20) DEFAULT 'active',
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
INDEX idx_status (status)
) ENGINE=InnoDB;
-- Create product_categories junction table -- Create product_categories junction table
CREATE TABLE product_categories ( CREATE TABLE product_categories (
@@ -95,74 +89,86 @@ CREATE TABLE product_categories (
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
PRIMARY KEY (pid, cat_id), PRIMARY KEY (pid, cat_id),
FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE, FOREIGN KEY (pid) REFERENCES products(pid) ON DELETE CASCADE,
FOREIGN KEY (cat_id) REFERENCES categories(cat_id) ON DELETE CASCADE, FOREIGN KEY (cat_id) REFERENCES categories(cat_id) ON DELETE CASCADE
INDEX idx_category (cat_id), );
INDEX idx_product (pid)
) ENGINE=InnoDB; CREATE INDEX idx_product_categories_category ON product_categories(cat_id);
CREATE INDEX idx_product_categories_product ON product_categories(pid);
-- Create orders table with its indexes -- Create orders table with its indexes
CREATE TABLE IF NOT EXISTS orders ( CREATE TABLE orders (
id BIGINT NOT NULL AUTO_INCREMENT, id BIGSERIAL PRIMARY KEY,
order_number VARCHAR(50) NOT NULL, order_number VARCHAR(50) NOT NULL,
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
SKU VARCHAR(50) NOT NULL, SKU VARCHAR(50) NOT NULL,
date DATE NOT NULL, date DATE NOT NULL,
price DECIMAL(10,3) NOT NULL, price DECIMAL(10,3) NOT NULL,
quantity INT NOT NULL, quantity INTEGER NOT NULL,
discount DECIMAL(10,3) DEFAULT 0.000, discount DECIMAL(10,3) DEFAULT 0.000,
tax DECIMAL(10,3) DEFAULT 0.000, tax DECIMAL(10,3) DEFAULT 0.000,
tax_included TINYINT(1) DEFAULT 0, tax_included BOOLEAN DEFAULT false,
shipping DECIMAL(10,3) DEFAULT 0.000, shipping DECIMAL(10,3) DEFAULT 0.000,
costeach DECIMAL(10,3) DEFAULT 0.000, costeach DECIMAL(10,3) DEFAULT 0.000,
customer VARCHAR(50) NOT NULL, customer VARCHAR(50) NOT NULL,
customer_name VARCHAR(100), customer_name VARCHAR(100),
status VARCHAR(20) DEFAULT 'pending', status VARCHAR(20) DEFAULT 'pending',
canceled TINYINT(1) DEFAULT 0, canceled BOOLEAN DEFAULT false,
PRIMARY KEY (id), updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
UNIQUE KEY unique_order_line (order_number, pid), UNIQUE (order_number, pid)
KEY order_number (order_number), );
KEY pid (pid),
KEY customer (customer), CREATE INDEX idx_orders_number ON orders(order_number);
KEY date (date), CREATE INDEX idx_orders_pid ON orders(pid);
KEY status (status), CREATE INDEX idx_orders_customer ON orders(customer);
INDEX idx_orders_metrics (pid, date, canceled) CREATE INDEX idx_orders_date ON orders(date);
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4; CREATE INDEX idx_orders_status ON orders(status);
CREATE INDEX idx_orders_metrics ON orders(pid, date, canceled);
CREATE INDEX idx_orders_updated ON orders(updated);
-- Create purchase_orders table with its indexes -- Create purchase_orders table with its indexes
CREATE TABLE purchase_orders ( CREATE TABLE purchase_orders (
id BIGINT AUTO_INCREMENT PRIMARY KEY, id BIGSERIAL PRIMARY KEY,
po_id VARCHAR(50) NOT NULL, po_id VARCHAR(50) NOT NULL,
vendor VARCHAR(100) NOT NULL, vendor VARCHAR(100) NOT NULL,
date DATE NOT NULL, date DATE NOT NULL,
expected_date DATE, expected_date DATE,
pid BIGINT NOT NULL, pid BIGINT NOT NULL,
sku VARCHAR(50) NOT NULL, sku VARCHAR(50) NOT NULL,
name VARCHAR(100) NOT NULL COMMENT 'Product name from products.description', name VARCHAR(100) NOT NULL,
cost_price DECIMAL(10, 3) NOT NULL, cost_price DECIMAL(10, 3) NOT NULL,
po_cost_price DECIMAL(10, 3) NOT NULL COMMENT 'Original cost from PO, before receiving adjustments', po_cost_price DECIMAL(10, 3) NOT NULL,
status TINYINT UNSIGNED DEFAULT 1 COMMENT '0=canceled,1=created,10=electronically_ready_send,11=ordered,12=preordered,13=electronically_sent,15=receiving_started,50=done', status SMALLINT DEFAULT 1,
receiving_status TINYINT UNSIGNED DEFAULT 1 COMMENT '0=canceled,1=created,30=partial_received,40=full_received,50=paid', receiving_status SMALLINT DEFAULT 1,
notes TEXT, notes TEXT,
long_note TEXT, long_note TEXT,
ordered INT NOT NULL, ordered INTEGER NOT NULL,
received INT DEFAULT 0, received INTEGER DEFAULT 0,
received_date DATE COMMENT 'Date of first receiving', received_date DATE,
last_received_date DATE COMMENT 'Date of most recent receiving', last_received_date DATE,
received_by INT, received_by VARCHAR(100),
receiving_history JSON COMMENT 'Array of receiving records with qty, date, cost, receiving_id, and alt_po flag', receiving_history JSONB,
updated TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (pid) REFERENCES products(pid), FOREIGN KEY (pid) REFERENCES products(pid),
INDEX idx_po_id (po_id), UNIQUE (po_id, pid)
INDEX idx_vendor (vendor), );
INDEX idx_status (status),
INDEX idx_receiving_status (receiving_status),
INDEX idx_purchase_orders_metrics (pid, date, status, ordered, received),
INDEX idx_po_metrics (pid, date, receiving_status, received_date),
INDEX idx_po_product_date (pid, date),
INDEX idx_po_product_status (pid, status),
UNIQUE KEY unique_po_product (po_id, pid)
) ENGINE=InnoDB;
SET FOREIGN_KEY_CHECKS = 1; COMMENT ON COLUMN purchase_orders.name IS 'Product name from products.description';
COMMENT ON COLUMN purchase_orders.po_cost_price IS 'Original cost from PO, before receiving adjustments';
COMMENT ON COLUMN purchase_orders.status IS '0=canceled,1=created,10=electronically_ready_send,11=ordered,12=preordered,13=electronically_sent,15=receiving_started,50=done';
COMMENT ON COLUMN purchase_orders.receiving_status IS '0=canceled,1=created,30=partial_received,40=full_received,50=paid';
COMMENT ON COLUMN purchase_orders.receiving_history IS 'Array of receiving records with qty, date, cost, receiving_id, and alt_po flag';
CREATE INDEX idx_po_id ON purchase_orders(po_id);
CREATE INDEX idx_po_vendor ON purchase_orders(vendor);
CREATE INDEX idx_po_status ON purchase_orders(status);
CREATE INDEX idx_po_receiving_status ON purchase_orders(receiving_status);
CREATE INDEX idx_po_metrics ON purchase_orders(pid, date, status, ordered, received);
CREATE INDEX idx_po_metrics_receiving ON purchase_orders(pid, date, receiving_status, received_date);
CREATE INDEX idx_po_product_date ON purchase_orders(pid, date);
CREATE INDEX idx_po_product_status ON purchase_orders(pid, status);
CREATE INDEX idx_po_updated ON purchase_orders(updated);
SET session_replication_role = 'origin'; -- Re-enable foreign key checks
-- Create views for common calculations -- Create views for common calculations
-- product_sales_trends view moved to metrics-schema.sql -- product_sales_trends view moved to metrics-schema.sql

File diff suppressed because it is too large Load Diff

View File

@@ -9,12 +9,14 @@
"version": "1.0.0", "version": "1.0.0",
"license": "ISC", "license": "ISC",
"dependencies": { "dependencies": {
"bcrypt": "^5.1.1",
"cors": "^2.8.5", "cors": "^2.8.5",
"csv-parse": "^5.6.0", "csv-parse": "^5.6.0",
"dotenv": "^16.4.7", "dotenv": "^16.4.7",
"express": "^4.18.2", "express": "^4.18.2",
"multer": "^1.4.5-lts.1", "multer": "^1.4.5-lts.1",
"mysql2": "^3.12.0", "mysql2": "^3.12.0",
"pg": "^8.13.2",
"pm2": "^5.3.0", "pm2": "^5.3.0",
"ssh2": "^1.16.0", "ssh2": "^1.16.0",
"uuid": "^9.0.1" "uuid": "^9.0.1"
@@ -23,6 +25,74 @@
"nodemon": "^3.0.2" "nodemon": "^3.0.2"
} }
}, },
"node_modules/@mapbox/node-pre-gyp": {
"version": "1.0.11",
"resolved": "https://registry.npmjs.org/@mapbox/node-pre-gyp/-/node-pre-gyp-1.0.11.tgz",
"integrity": "sha512-Yhlar6v9WQgUp/He7BdgzOz8lqMQ8sU+jkCq7Wx8Myc5YFJLbEe7lgui/V7G1qB1DJykHSGwreceSaD60Y0PUQ==",
"license": "BSD-3-Clause",
"dependencies": {
"detect-libc": "^2.0.0",
"https-proxy-agent": "^5.0.0",
"make-dir": "^3.1.0",
"node-fetch": "^2.6.7",
"nopt": "^5.0.0",
"npmlog": "^5.0.1",
"rimraf": "^3.0.2",
"semver": "^7.3.5",
"tar": "^6.1.11"
},
"bin": {
"node-pre-gyp": "bin/node-pre-gyp"
}
},
"node_modules/@mapbox/node-pre-gyp/node_modules/agent-base": {
"version": "6.0.2",
"resolved": "https://registry.npmjs.org/agent-base/-/agent-base-6.0.2.tgz",
"integrity": "sha512-RZNwNclF7+MS/8bDg70amg32dyeZGZxiDuQmZxKLAlQjr3jGyLx+4Kkk58UO7D2QdgFIQCovuSuZESne6RG6XQ==",
"license": "MIT",
"dependencies": {
"debug": "4"
},
"engines": {
"node": ">= 6.0.0"
}
},
"node_modules/@mapbox/node-pre-gyp/node_modules/debug": {
"version": "4.4.0",
"resolved": "https://registry.npmjs.org/debug/-/debug-4.4.0.tgz",
"integrity": "sha512-6WTZ/IxCY/T6BALoZHaE4ctp9xm+Z5kY/pzYaCHRFeyVhojxlrm+46y68HA6hr0TcwEssoxNiDEUJQjfPZ/RYA==",
"license": "MIT",
"dependencies": {
"ms": "^2.1.3"
},
"engines": {
"node": ">=6.0"
},
"peerDependenciesMeta": {
"supports-color": {
"optional": true
}
}
},
"node_modules/@mapbox/node-pre-gyp/node_modules/https-proxy-agent": {
"version": "5.0.1",
"resolved": "https://registry.npmjs.org/https-proxy-agent/-/https-proxy-agent-5.0.1.tgz",
"integrity": "sha512-dFcAjpTQFgoLMzC2VwU+C/CbS7uRL0lWmxDITmqm7C+7F0Odmj6s9l6alZc6AELXhrnggM2CeWSXHGOdX2YtwA==",
"license": "MIT",
"dependencies": {
"agent-base": "6",
"debug": "4"
},
"engines": {
"node": ">= 6"
}
},
"node_modules/@mapbox/node-pre-gyp/node_modules/ms": {
"version": "2.1.3",
"resolved": "https://registry.npmjs.org/ms/-/ms-2.1.3.tgz",
"integrity": "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==",
"license": "MIT"
},
"node_modules/@pm2/agent": { "node_modules/@pm2/agent": {
"version": "2.0.4", "version": "2.0.4",
"resolved": "https://registry.npmjs.org/@pm2/agent/-/agent-2.0.4.tgz", "resolved": "https://registry.npmjs.org/@pm2/agent/-/agent-2.0.4.tgz",
@@ -276,6 +346,12 @@
"integrity": "sha512-C5Mc6rdnsaJDjO3UpGW/CQTHtCKaYlScZTly4JIu97Jxo/odCiH0ITnDXSJPTOrEKk/ycSZ0AOgTmkDtkOsvIA==", "integrity": "sha512-C5Mc6rdnsaJDjO3UpGW/CQTHtCKaYlScZTly4JIu97Jxo/odCiH0ITnDXSJPTOrEKk/ycSZ0AOgTmkDtkOsvIA==",
"license": "MIT" "license": "MIT"
}, },
"node_modules/abbrev": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/abbrev/-/abbrev-1.1.1.tgz",
"integrity": "sha512-nne9/IiQ/hzIhY6pdDnbBtz7DjPTKrY00P/zvPSm5pOFkl6xuGrGnXn/VtTNNfNtAfZ9/1RtehkszU9qcTii0Q==",
"license": "ISC"
},
"node_modules/accepts": { "node_modules/accepts": {
"version": "1.3.8", "version": "1.3.8",
"resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.8.tgz", "resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.8.tgz",
@@ -322,6 +398,15 @@
"node": ">=6" "node": ">=6"
} }
}, },
"node_modules/ansi-regex": {
"version": "5.0.1",
"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
"integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==",
"license": "MIT",
"engines": {
"node": ">=8"
}
},
"node_modules/ansi-styles": { "node_modules/ansi-styles": {
"version": "4.3.0", "version": "4.3.0",
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@@ -356,6 +441,40 @@
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"node_modules/ws": { "node_modules/ws": {
"version": "7.5.10", "version": "7.5.10",
"resolved": "https://registry.npmjs.org/ws/-/ws-7.5.10.tgz", "resolved": "https://registry.npmjs.org/ws/-/ws-7.5.10.tgz",

View File

@@ -18,12 +18,14 @@
"author": "", "author": "",
"license": "ISC", "license": "ISC",
"dependencies": { "dependencies": {
"bcrypt": "^5.1.1",
"cors": "^2.8.5", "cors": "^2.8.5",
"csv-parse": "^5.6.0", "csv-parse": "^5.6.0",
"dotenv": "^16.4.7", "dotenv": "^16.4.7",
"express": "^4.18.2", "express": "^4.18.2",
"multer": "^1.4.5-lts.1", "multer": "^1.4.5-lts.1",
"mysql2": "^3.12.0", "mysql2": "^3.12.0",
"pg": "^8.13.2",
"pm2": "^5.3.0", "pm2": "^5.3.0",
"ssh2": "^1.16.0", "ssh2": "^1.16.0",
"uuid": "^9.0.1" "uuid": "^9.0.1"

View File

@@ -0,0 +1,79 @@
const { Client } = require('pg');
const bcrypt = require('bcrypt');
const path = require('path');
const readline = require('readline');
require('dotenv').config({ path: path.resolve(__dirname, '../.env') });
const SALT_ROUNDS = 10;
const dbConfig = {
host: process.env.DB_HOST,
user: process.env.DB_USER,
password: process.env.DB_PASSWORD,
database: process.env.DB_NAME,
port: process.env.DB_PORT || 5432
};
function prompt(question) {
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout
});
return new Promise(resolve => {
rl.question(question, answer => {
rl.close();
resolve(answer);
});
});
}
async function addUser() {
try {
const username = await prompt('Enter username: ');
if (!username.trim()) {
console.error('Error: Username cannot be empty');
process.exit(1);
}
const password = await prompt('Enter password: ');
if (!password.trim()) {
console.error('Error: Password cannot be empty');
process.exit(1);
}
const client = new Client(dbConfig);
await client.connect();
// Check if user exists
const checkUser = await client.query(
'SELECT username FROM users WHERE username = $1',
[username]
);
if (checkUser.rows.length > 0) {
console.error('Error: Username already exists');
process.exit(1);
}
// Hash password
const hashedPassword = await bcrypt.hash(password, SALT_ROUNDS);
// Insert new user
await client.query(
'INSERT INTO users (username, password) VALUES ($1, $2)',
[username, hashedPassword]
);
console.log(`User '${username}' created successfully`);
await client.end();
} catch (error) {
console.error('Error creating user:', error.message);
process.exit(1);
}
}
// Run if called directly
if (require.main === module) {
addUser();
}

View File

@@ -7,13 +7,13 @@ require('dotenv').config({ path: path.resolve(__dirname, '..', '.env') });
// Configuration flags for controlling which metrics to calculate // Configuration flags for controlling which metrics to calculate
// Set to 1 to skip the corresponding calculation, 0 to run it // Set to 1 to skip the corresponding calculation, 0 to run it
const SKIP_PRODUCT_METRICS = 1; // Skip all product metrics const SKIP_PRODUCT_METRICS = 0;
const SKIP_TIME_AGGREGATES = 1; // Skip time aggregates const SKIP_TIME_AGGREGATES = 0;
const SKIP_FINANCIAL_METRICS = 1; // Skip financial metrics const SKIP_FINANCIAL_METRICS = 0;
const SKIP_VENDOR_METRICS = 1; // Skip vendor metrics const SKIP_VENDOR_METRICS = 0;
const SKIP_CATEGORY_METRICS = 1; // Skip category metrics const SKIP_CATEGORY_METRICS = 0;
const SKIP_BRAND_METRICS = 1; // Skip brand metrics const SKIP_BRAND_METRICS = 0;
const SKIP_SALES_FORECASTS = 1; // Skip sales forecasts const SKIP_SALES_FORECASTS = 0;
// Add error handler for uncaught exceptions // Add error handler for uncaught exceptions
process.on('uncaughtException', (error) => { process.on('uncaughtException', (error) => {
@@ -44,6 +44,34 @@ global.clearProgress = progress.clearProgress;
global.getProgress = progress.getProgress; global.getProgress = progress.getProgress;
global.logError = progress.logError; global.logError = progress.logError;
// List of temporary tables used in the calculation process
const TEMP_TABLES = [
'temp_revenue_ranks',
'temp_sales_metrics',
'temp_purchase_metrics',
'temp_product_metrics',
'temp_vendor_metrics',
'temp_category_metrics',
'temp_brand_metrics',
'temp_forecast_dates',
'temp_daily_sales',
'temp_product_stats',
'temp_category_sales',
'temp_category_stats'
];
// Add cleanup function for temporary tables
async function cleanupTemporaryTables(connection) {
try {
for (const table of TEMP_TABLES) {
await connection.query(`DROP TEMPORARY TABLE IF EXISTS ${table}`);
}
} catch (error) {
logError(error, 'Error cleaning up temporary tables');
throw error; // Re-throw to be handled by the caller
}
}
const { getConnection, closePool } = require('./metrics/utils/db'); const { getConnection, closePool } = require('./metrics/utils/db');
const calculateProductMetrics = require('./metrics/product-metrics'); const calculateProductMetrics = require('./metrics/product-metrics');
const calculateTimeAggregates = require('./metrics/time-aggregates'); const calculateTimeAggregates = require('./metrics/time-aggregates');
@@ -83,10 +111,78 @@ process.on('SIGTERM', cancelCalculation);
async function calculateMetrics() { async function calculateMetrics() {
let connection; let connection;
const startTime = Date.now(); const startTime = Date.now();
let processedCount = 0; let processedProducts = 0;
let processedOrders = 0;
let processedPurchaseOrders = 0;
let totalProducts = 0; let totalProducts = 0;
let totalOrders = 0;
let totalPurchaseOrders = 0;
let calculateHistoryId;
try { try {
// Clean up any previously running calculations
connection = await getConnection();
await connection.query(`
UPDATE calculate_history
SET
status = 'cancelled',
end_time = NOW(),
duration_seconds = TIMESTAMPDIFF(SECOND, start_time, NOW()),
error_message = 'Previous calculation was not completed properly'
WHERE status = 'running'
`);
// Get counts from all relevant tables
const [[productCount], [orderCount], [poCount]] = await Promise.all([
connection.query('SELECT COUNT(*) as total FROM products'),
connection.query('SELECT COUNT(*) as total FROM orders'),
connection.query('SELECT COUNT(*) as total FROM purchase_orders')
]);
totalProducts = productCount.total;
totalOrders = orderCount.total;
totalPurchaseOrders = poCount.total;
// Create history record for this calculation
const [historyResult] = await connection.query(`
INSERT INTO calculate_history (
start_time,
status,
total_products,
total_orders,
total_purchase_orders,
additional_info
) VALUES (
NOW(),
'running',
?,
?,
?,
JSON_OBJECT(
'skip_product_metrics', ?,
'skip_time_aggregates', ?,
'skip_financial_metrics', ?,
'skip_vendor_metrics', ?,
'skip_category_metrics', ?,
'skip_brand_metrics', ?,
'skip_sales_forecasts', ?
)
)
`, [
totalProducts,
totalOrders,
totalPurchaseOrders,
SKIP_PRODUCT_METRICS,
SKIP_TIME_AGGREGATES,
SKIP_FINANCIAL_METRICS,
SKIP_VENDOR_METRICS,
SKIP_CATEGORY_METRICS,
SKIP_BRAND_METRICS,
SKIP_SALES_FORECASTS
]);
calculateHistoryId = historyResult.insertId;
connection.release();
// Add debug logging for the progress functions // Add debug logging for the progress functions
console.log('Debug - Progress functions:', { console.log('Debug - Progress functions:', {
formatElapsedTime: typeof global.formatElapsedTime, formatElapsedTime: typeof global.formatElapsedTime,
@@ -115,72 +211,150 @@ async function calculateMetrics() {
elapsed: '0s', elapsed: '0s',
remaining: 'Calculating...', remaining: 'Calculating...',
rate: 0, rate: 0,
percentage: '0' percentage: '0',
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Get total number of products // Update progress periodically
const [countResult] = await connection.query('SELECT COUNT(*) as total FROM products') const updateProgress = async (products = null, orders = null, purchaseOrders = null) => {
.catch(err => { // Ensure all values are valid numbers or default to previous value
global.logError(err, 'Failed to count products'); if (products !== null) processedProducts = Number(products) || processedProducts || 0;
throw err; if (orders !== null) processedOrders = Number(orders) || processedOrders || 0;
}); if (purchaseOrders !== null) processedPurchaseOrders = Number(purchaseOrders) || processedPurchaseOrders || 0;
totalProducts = countResult[0].total;
// Ensure we never send NaN to the database
const safeProducts = Number(processedProducts) || 0;
const safeOrders = Number(processedOrders) || 0;
const safePurchaseOrders = Number(processedPurchaseOrders) || 0;
await connection.query(`
UPDATE calculate_history
SET
processed_products = ?,
processed_orders = ?,
processed_purchase_orders = ?
WHERE id = ?
`, [safeProducts, safeOrders, safePurchaseOrders, calculateHistoryId]);
};
// Helper function to ensure valid progress numbers
const ensureValidProgress = (current, total) => ({
current: Number(current) || 0,
total: Number(total) || 1, // Default to 1 to avoid division by zero
percentage: (((Number(current) || 0) / (Number(total) || 1)) * 100).toFixed(1)
});
// Initial progress
const initialProgress = ensureValidProgress(0, totalProducts);
global.outputProgress({
status: 'running',
operation: 'Starting metrics calculation',
current: initialProgress.current,
total: initialProgress.total,
elapsed: '0s',
remaining: 'Calculating...',
rate: 0,
percentage: initialProgress.percentage,
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
if (!SKIP_PRODUCT_METRICS) { if (!SKIP_PRODUCT_METRICS) {
processedCount = await calculateProductMetrics(startTime, totalProducts); const result = await calculateProductMetrics(startTime, totalProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Product metrics calculation failed');
}
} else { } else {
console.log('Skipping product metrics calculation...'); console.log('Skipping product metrics calculation...');
processedCount = Math.floor(totalProducts * 0.6); processedProducts = Math.floor(totalProducts * 0.6);
await updateProgress(processedProducts);
global.outputProgress({ global.outputProgress({
status: 'running', status: 'running',
operation: 'Skipping product metrics calculation', operation: 'Skipping product metrics calculation',
current: processedCount, current: processedProducts,
total: totalProducts, total: totalProducts,
elapsed: global.formatElapsedTime(startTime), elapsed: global.formatElapsedTime(startTime),
remaining: global.estimateRemaining(startTime, processedCount, totalProducts), remaining: global.estimateRemaining(startTime, processedProducts, totalProducts),
rate: global.calculateRate(startTime, processedCount), rate: global.calculateRate(startTime, processedProducts),
percentage: '60' percentage: '60',
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
} }
// Calculate time-based aggregates // Calculate time-based aggregates
if (!SKIP_TIME_AGGREGATES) { if (!SKIP_TIME_AGGREGATES) {
processedCount = await calculateTimeAggregates(startTime, totalProducts, processedCount); const result = await calculateTimeAggregates(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Time aggregates calculation failed');
}
} else { } else {
console.log('Skipping time aggregates calculation'); console.log('Skipping time aggregates calculation');
} }
// Calculate financial metrics // Calculate financial metrics
if (!SKIP_FINANCIAL_METRICS) { if (!SKIP_FINANCIAL_METRICS) {
processedCount = await calculateFinancialMetrics(startTime, totalProducts, processedCount); const result = await calculateFinancialMetrics(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Financial metrics calculation failed');
}
} else { } else {
console.log('Skipping financial metrics calculation'); console.log('Skipping financial metrics calculation');
} }
// Calculate vendor metrics // Calculate vendor metrics
if (!SKIP_VENDOR_METRICS) { if (!SKIP_VENDOR_METRICS) {
processedCount = await calculateVendorMetrics(startTime, totalProducts, processedCount); const result = await calculateVendorMetrics(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Vendor metrics calculation failed');
}
} else { } else {
console.log('Skipping vendor metrics calculation'); console.log('Skipping vendor metrics calculation');
} }
// Calculate category metrics // Calculate category metrics
if (!SKIP_CATEGORY_METRICS) { if (!SKIP_CATEGORY_METRICS) {
processedCount = await calculateCategoryMetrics(startTime, totalProducts, processedCount); const result = await calculateCategoryMetrics(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Category metrics calculation failed');
}
} else { } else {
console.log('Skipping category metrics calculation'); console.log('Skipping category metrics calculation');
} }
// Calculate brand metrics // Calculate brand metrics
if (!SKIP_BRAND_METRICS) { if (!SKIP_BRAND_METRICS) {
processedCount = await calculateBrandMetrics(startTime, totalProducts, processedCount); const result = await calculateBrandMetrics(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Brand metrics calculation failed');
}
} else { } else {
console.log('Skipping brand metrics calculation'); console.log('Skipping brand metrics calculation');
} }
// Calculate sales forecasts // Calculate sales forecasts
if (!SKIP_SALES_FORECASTS) { if (!SKIP_SALES_FORECASTS) {
processedCount = await calculateSalesForecasts(startTime, totalProducts, processedCount); const result = await calculateSalesForecasts(startTime, totalProducts, processedProducts);
await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
if (!result.success) {
throw new Error('Sales forecasts calculation failed');
}
} else { } else {
console.log('Skipping sales forecasts calculation'); console.log('Skipping sales forecasts calculation');
} }
@@ -189,15 +363,25 @@ async function calculateMetrics() {
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting ABC classification', operation: 'Starting ABC classification',
current: processedCount, current: processedProducts || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedProducts || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedProducts || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedProducts || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedProducts || 0,
processedOrders: processedOrders || 0,
processedPurchaseOrders: 0,
success: false
};
const [abcConfig] = await connection.query('SELECT a_threshold, b_threshold FROM abc_classification_config WHERE id = 1'); const [abcConfig] = await connection.query('SELECT a_threshold, b_threshold FROM abc_classification_config WHERE id = 1');
const abcThresholds = abcConfig[0] || { a_threshold: 20, b_threshold: 50 }; const abcThresholds = abcConfig[0] || { a_threshold: 20, b_threshold: 50 };
@@ -218,15 +402,25 @@ async function calculateMetrics() {
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Creating revenue rankings', operation: 'Creating revenue rankings',
current: processedCount, current: processedProducts || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedProducts || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedProducts || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedProducts || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedProducts || 0,
processedOrders: processedOrders || 0,
processedPurchaseOrders: 0,
success: false
};
await connection.query(` await connection.query(`
INSERT INTO temp_revenue_ranks INSERT INTO temp_revenue_ranks
@@ -247,26 +441,44 @@ async function calculateMetrics() {
// Get total count for percentage calculation // Get total count for percentage calculation
const [rankingCount] = await connection.query('SELECT MAX(rank_num) as total_count FROM temp_revenue_ranks'); const [rankingCount] = await connection.query('SELECT MAX(rank_num) as total_count FROM temp_revenue_ranks');
const totalCount = rankingCount[0].total_count || 1; const totalCount = rankingCount[0].total_count || 1;
const max_rank = totalCount; // Store max_rank for use in classification
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Updating ABC classifications', operation: 'Updating ABC classifications',
current: processedCount, current: processedProducts || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedProducts || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedProducts || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedProducts || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedProducts || 0,
processedOrders: processedOrders || 0,
processedPurchaseOrders: 0,
success: false
};
// Process updates in batches // ABC classification progress tracking
let abcProcessedCount = 0; let abcProcessedCount = 0;
const batchSize = 5000; const batchSize = 5000;
let lastProgressUpdate = Date.now();
const progressUpdateInterval = 1000; // Update every second
while (true) { while (true) {
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: Number(processedProducts) || 0,
processedOrders: Number(processedOrders) || 0,
processedPurchaseOrders: 0,
success: false
};
// First get a batch of PIDs that need updating // First get a batch of PIDs that need updating
const [pids] = await connection.query(` const [pids] = await connection.query(`
@@ -282,8 +494,8 @@ async function calculateMetrics() {
ELSE 'C' ELSE 'C'
END END
LIMIT ? LIMIT ?
`, [totalCount, abcThresholds.a_threshold, `, [max_rank, abcThresholds.a_threshold,
totalCount, abcThresholds.b_threshold, max_rank, abcThresholds.b_threshold,
batchSize]); batchSize]);
if (pids.length === 0) { if (pids.length === 0) {
@@ -303,23 +515,42 @@ async function calculateMetrics() {
END, END,
pm.last_calculated_at = NOW() pm.last_calculated_at = NOW()
WHERE pm.pid IN (?) WHERE pm.pid IN (?)
`, [totalCount, abcThresholds.a_threshold, `, [max_rank, abcThresholds.a_threshold,
totalCount, abcThresholds.b_threshold, max_rank, abcThresholds.b_threshold,
pids.map(row => row.pid)]); pids.map(row => row.pid)]);
abcProcessedCount += result.affectedRows; abcProcessedCount += result.affectedRows;
processedCount = Math.floor(totalProducts * (0.99 + (abcProcessedCount / totalCount) * 0.01));
outputProgress({ // Calculate progress ensuring valid numbers
status: 'running', const currentProgress = Math.floor(totalProducts * (0.99 + (abcProcessedCount / (totalCount || 1)) * 0.01));
operation: 'ABC classification progress', processedProducts = Number(currentProgress) || processedProducts || 0;
current: processedCount,
total: totalProducts, // Only update progress at most once per second
elapsed: formatElapsedTime(startTime), const now = Date.now();
remaining: estimateRemaining(startTime, processedCount, totalProducts), if (now - lastProgressUpdate >= progressUpdateInterval) {
rate: calculateRate(startTime, processedCount), const progress = ensureValidProgress(processedProducts, totalProducts);
percentage: ((processedCount / totalProducts) * 100).toFixed(1)
}); outputProgress({
status: 'running',
operation: 'ABC classification progress',
current: progress.current,
total: progress.total,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, progress.current, progress.total),
rate: calculateRate(startTime, progress.current),
percentage: progress.percentage,
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
lastProgressUpdate = now;
}
// Update database progress
await updateProgress(processedProducts, processedOrders, processedPurchaseOrders);
// Small delay between batches to allow other transactions // Small delay between batches to allow other transactions
await new Promise(resolve => setTimeout(resolve, 100)); await new Promise(resolve => setTimeout(resolve, 100));
@@ -328,61 +559,145 @@ async function calculateMetrics() {
// Clean up // Clean up
await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_revenue_ranks'); await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_revenue_ranks');
const endTime = Date.now();
const totalElapsedSeconds = Math.round((endTime - startTime) / 1000);
// Update calculate_status for ABC classification
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('abc_classification', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
// Final progress update with guaranteed valid numbers
const finalProgress = ensureValidProgress(totalProducts, totalProducts);
// Final success message // Final success message
outputProgress({ outputProgress({
status: 'complete', status: 'complete',
operation: 'Metrics calculation complete', operation: 'Metrics calculation complete',
current: totalProducts, current: finalProgress.current,
total: totalProducts, total: finalProgress.total,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: '0s', remaining: '0s',
rate: calculateRate(startTime, totalProducts), rate: calculateRate(startTime, finalProgress.current),
percentage: '100' percentage: '100',
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: totalElapsedSeconds
}
}); });
// Ensure all values are valid numbers before final update
const finalStats = {
processedProducts: Number(processedProducts) || 0,
processedOrders: Number(processedOrders) || 0,
processedPurchaseOrders: Number(processedPurchaseOrders) || 0
};
// Update history with completion
await connection.query(`
UPDATE calculate_history
SET
end_time = NOW(),
duration_seconds = ?,
processed_products = ?,
processed_orders = ?,
processed_purchase_orders = ?,
status = 'completed'
WHERE id = ?
`, [totalElapsedSeconds,
finalStats.processedProducts,
finalStats.processedOrders,
finalStats.processedPurchaseOrders,
calculateHistoryId]);
// Clear progress file on successful completion // Clear progress file on successful completion
global.clearProgress(); global.clearProgress();
} catch (error) { } catch (error) {
const endTime = Date.now();
const totalElapsedSeconds = Math.round((endTime - startTime) / 1000);
// Update history with error
await connection.query(`
UPDATE calculate_history
SET
end_time = NOW(),
duration_seconds = ?,
processed_products = ?,
processed_orders = ?,
processed_purchase_orders = ?,
status = ?,
error_message = ?
WHERE id = ?
`, [
totalElapsedSeconds,
processedProducts || 0, // Ensure we have a valid number
processedOrders || 0, // Ensure we have a valid number
processedPurchaseOrders || 0, // Ensure we have a valid number
isCancelled ? 'cancelled' : 'failed',
error.message,
calculateHistoryId
]);
if (isCancelled) { if (isCancelled) {
global.outputProgress({ global.outputProgress({
status: 'cancelled', status: 'cancelled',
operation: 'Calculation cancelled', operation: 'Calculation cancelled',
current: processedCount, current: processedProducts,
total: totalProducts || 0, total: totalProducts || 0,
elapsed: global.formatElapsedTime(startTime), elapsed: global.formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: global.calculateRate(startTime, processedCount), rate: global.calculateRate(startTime, processedProducts),
percentage: ((processedCount / (totalProducts || 1)) * 100).toFixed(1) percentage: ((processedProducts / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
} else { } else {
global.outputProgress({ global.outputProgress({
status: 'error', status: 'error',
operation: 'Error: ' + error.message, operation: 'Error: ' + error.message,
current: processedCount, current: processedProducts,
total: totalProducts || 0, total: totalProducts || 0,
elapsed: global.formatElapsedTime(startTime), elapsed: global.formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: global.calculateRate(startTime, processedCount), rate: global.calculateRate(startTime, processedProducts),
percentage: ((processedCount / (totalProducts || 1)) * 100).toFixed(1) percentage: ((processedProducts / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
} }
throw error; throw error;
} finally { } finally {
if (connection) { if (connection) {
connection.release(); // Ensure temporary tables are cleaned up
await cleanupTemporaryTables(connection);
connection.release();
} }
// Close the connection pool when we're done
await closePool();
} }
} finally { } catch (error) {
// Close the connection pool when we're done success = false;
await closePool(); logError(error, 'Error in metrics calculation');
throw error;
} }
} }
// Export both functions and progress checker // Export as a module with all necessary functions
module.exports = calculateMetrics; module.exports = {
module.exports.cancelCalculation = cancelCalculation; calculateMetrics,
module.exports.getProgress = global.getProgress; cancelCalculation,
getProgress: global.getProgress
};
// Run directly if called from command line // Run directly if called from command line
if (require.main === module) { if (require.main === module) {

View File

@@ -0,0 +1,115 @@
const path = require('path');
const { spawn } = require('child_process');
function outputProgress(data) {
if (!data.status) {
data = {
status: 'running',
...data
};
}
console.log(JSON.stringify(data));
}
function runScript(scriptPath) {
return new Promise((resolve, reject) => {
const child = spawn('node', [scriptPath], {
stdio: ['inherit', 'pipe', 'pipe'],
env: {
...process.env,
PGHOST: process.env.DB_HOST,
PGUSER: process.env.DB_USER,
PGPASSWORD: process.env.DB_PASSWORD,
PGDATABASE: process.env.DB_NAME,
PGPORT: process.env.DB_PORT || '5432'
}
});
let output = '';
child.stdout.on('data', (data) => {
const lines = data.toString().split('\n');
lines.filter(line => line.trim()).forEach(line => {
try {
console.log(line); // Pass through the JSON output
output += line + '\n';
} catch (e) {
console.log(line); // If not JSON, just log it directly
}
});
});
child.stderr.on('data', (data) => {
console.error(data.toString());
});
child.on('close', (code) => {
if (code !== 0) {
reject(new Error(`Script ${scriptPath} exited with code ${code}`));
} else {
resolve(output);
}
});
child.on('error', (err) => {
reject(err);
});
});
}
async function fullReset() {
try {
// Step 1: Reset Database
outputProgress({
operation: 'Starting full reset',
message: 'Step 1/3: Resetting database...'
});
await runScript(path.join(__dirname, 'reset-db.js'));
outputProgress({
status: 'complete',
operation: 'Database reset step complete',
message: 'Database reset finished, moving to import...'
});
// Step 2: Import from Production
outputProgress({
operation: 'Starting import',
message: 'Step 2/3: Importing from production...'
});
await runScript(path.join(__dirname, 'import-from-prod.js'));
outputProgress({
status: 'complete',
operation: 'Import step complete',
message: 'Import finished, moving to metrics calculation...'
});
// Step 3: Calculate Metrics
outputProgress({
operation: 'Starting metrics calculation',
message: 'Step 3/3: Calculating metrics...'
});
await runScript(path.join(__dirname, 'calculate-metrics.js'));
// Final completion message
outputProgress({
status: 'complete',
operation: 'Full reset complete',
message: 'Successfully completed all steps: database reset, import, and metrics calculation'
});
} catch (error) {
outputProgress({
status: 'error',
operation: 'Full reset failed',
error: error.message,
stack: error.stack
});
process.exit(1);
}
}
// Run if called directly
if (require.main === module) {
fullReset();
}
module.exports = fullReset;

View File

@@ -0,0 +1,100 @@
const path = require('path');
const { spawn } = require('child_process');
function outputProgress(data) {
if (!data.status) {
data = {
status: 'running',
...data
};
}
console.log(JSON.stringify(data));
}
function runScript(scriptPath) {
return new Promise((resolve, reject) => {
const child = spawn('node', [scriptPath], {
stdio: ['inherit', 'pipe', 'pipe']
});
let output = '';
child.stdout.on('data', (data) => {
const lines = data.toString().split('\n');
lines.filter(line => line.trim()).forEach(line => {
try {
console.log(line); // Pass through the JSON output
output += line + '\n';
} catch (e) {
console.log(line); // If not JSON, just log it directly
}
});
});
child.stderr.on('data', (data) => {
console.error(data.toString());
});
child.on('close', (code) => {
if (code !== 0) {
reject(new Error(`Script ${scriptPath} exited with code ${code}`));
} else {
resolve(output);
}
});
child.on('error', (err) => {
reject(err);
});
});
}
async function fullUpdate() {
try {
// Step 1: Import from Production
outputProgress({
operation: 'Starting full update',
message: 'Step 1/2: Importing from production...'
});
await runScript(path.join(__dirname, 'import-from-prod.js'));
outputProgress({
status: 'complete',
operation: 'Import step complete',
message: 'Import finished, moving to metrics calculation...'
});
// Step 2: Calculate Metrics
outputProgress({
operation: 'Starting metrics calculation',
message: 'Step 2/2: Calculating metrics...'
});
await runScript(path.join(__dirname, 'calculate-metrics.js'));
outputProgress({
status: 'complete',
operation: 'Metrics step complete',
message: 'Metrics calculation finished'
});
// Final completion message
outputProgress({
status: 'complete',
operation: 'Full update complete',
message: 'Successfully completed all steps: import and metrics calculation'
});
} catch (error) {
outputProgress({
status: 'error',
operation: 'Full update failed',
error: error.message,
stack: error.stack
});
process.exit(1);
}
}
// Run if called directly
if (require.main === module) {
fullUpdate();
}
module.exports = fullUpdate;

View File

@@ -28,9 +28,18 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
let cumulativeProcessedOrders = 0; let cumulativeProcessedOrders = 0;
try { try {
// Insert temporary table creation queries // Clean up any existing temp tables first
await localConnection.query(` await localConnection.query(`
CREATE TABLE IF NOT EXISTS temp_order_items ( DROP TEMPORARY TABLE IF EXISTS temp_order_items;
DROP TEMPORARY TABLE IF EXISTS temp_order_meta;
DROP TEMPORARY TABLE IF EXISTS temp_order_discounts;
DROP TEMPORARY TABLE IF EXISTS temp_order_taxes;
DROP TEMPORARY TABLE IF EXISTS temp_order_costs;
`);
// Create all temp tables with correct schema
await localConnection.query(`
CREATE TEMPORARY TABLE temp_order_items (
order_id INT UNSIGNED NOT NULL, order_id INT UNSIGNED NOT NULL,
pid INT UNSIGNED NOT NULL, pid INT UNSIGNED NOT NULL,
SKU VARCHAR(50) NOT NULL, SKU VARCHAR(50) NOT NULL,
@@ -40,35 +49,41 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
PRIMARY KEY (order_id, pid) PRIMARY KEY (order_id, pid)
) ENGINE=InnoDB DEFAULT CHARSET=utf8; ) ENGINE=InnoDB DEFAULT CHARSET=utf8;
`); `);
await localConnection.query(` await localConnection.query(`
CREATE TABLE IF NOT EXISTS temp_order_meta ( CREATE TEMPORARY TABLE temp_order_meta (
order_id INT UNSIGNED NOT NULL, order_id INT UNSIGNED NOT NULL,
date DATE NOT NULL, date DATE NOT NULL,
customer VARCHAR(100) NOT NULL, customer VARCHAR(100) NOT NULL,
customer_name VARCHAR(150) NOT NULL, customer_name VARCHAR(150) NOT NULL,
status INT, status INT,
canceled TINYINT(1), canceled TINYINT(1),
summary_discount DECIMAL(10,2) DEFAULT 0.00,
summary_subtotal DECIMAL(10,2) DEFAULT 0.00,
PRIMARY KEY (order_id) PRIMARY KEY (order_id)
) ENGINE=InnoDB DEFAULT CHARSET=utf8; ) ENGINE=InnoDB DEFAULT CHARSET=utf8;
`); `);
await localConnection.query(` await localConnection.query(`
CREATE TABLE IF NOT EXISTS temp_order_discounts ( CREATE TEMPORARY TABLE temp_order_discounts (
order_id INT UNSIGNED NOT NULL, order_id INT UNSIGNED NOT NULL,
pid INT UNSIGNED NOT NULL, pid INT UNSIGNED NOT NULL,
discount DECIMAL(10,2) NOT NULL, discount DECIMAL(10,2) NOT NULL,
PRIMARY KEY (order_id, pid) PRIMARY KEY (order_id, pid)
) ENGINE=InnoDB DEFAULT CHARSET=utf8; ) ENGINE=InnoDB DEFAULT CHARSET=utf8;
`); `);
await localConnection.query(` await localConnection.query(`
CREATE TABLE IF NOT EXISTS temp_order_taxes ( CREATE TEMPORARY TABLE temp_order_taxes (
order_id INT UNSIGNED NOT NULL, order_id INT UNSIGNED NOT NULL,
pid INT UNSIGNED NOT NULL, pid INT UNSIGNED NOT NULL,
tax DECIMAL(10,2) NOT NULL, tax DECIMAL(10,2) NOT NULL,
PRIMARY KEY (order_id, pid) PRIMARY KEY (order_id, pid)
) ENGINE=InnoDB DEFAULT CHARSET=utf8; ) ENGINE=InnoDB DEFAULT CHARSET=utf8;
`); `);
await localConnection.query(` await localConnection.query(`
CREATE TABLE IF NOT EXISTS temp_order_costs ( CREATE TEMPORARY TABLE temp_order_costs (
order_id INT UNSIGNED NOT NULL, order_id INT UNSIGNED NOT NULL,
pid INT UNSIGNED NOT NULL, pid INT UNSIGNED NOT NULL,
costeach DECIMAL(10,3) DEFAULT 0.000, costeach DECIMAL(10,3) DEFAULT 0.000,
@@ -81,6 +96,7 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
SELECT COLUMN_NAME SELECT COLUMN_NAME
FROM INFORMATION_SCHEMA.COLUMNS FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = 'orders' WHERE TABLE_NAME = 'orders'
AND COLUMN_NAME != 'updated' -- Exclude the updated column
ORDER BY ORDINAL_POSITION ORDER BY ORDINAL_POSITION
`); `);
const columnNames = columns.map(col => col.COLUMN_NAME); const columnNames = columns.map(col => col.COLUMN_NAME);
@@ -212,7 +228,9 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
o.order_cid as customer, o.order_cid as customer,
CONCAT(COALESCE(u.firstname, ''), ' ', COALESCE(u.lastname, '')) as customer_name, CONCAT(COALESCE(u.firstname, ''), ' ', COALESCE(u.lastname, '')) as customer_name,
o.order_status as status, o.order_status as status,
CASE WHEN o.date_cancelled != '0000-00-00 00:00:00' THEN 1 ELSE 0 END as canceled CASE WHEN o.date_cancelled != '0000-00-00 00:00:00' THEN 1 ELSE 0 END as canceled,
o.summary_discount,
o.summary_subtotal
FROM _order o FROM _order o
LEFT JOIN users u ON o.order_cid = u.cid LEFT JOIN users u ON o.order_cid = u.cid
WHERE o.order_id IN (?) WHERE o.order_id IN (?)
@@ -226,19 +244,37 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
console.log('Found duplicates:', duplicates); console.log('Found duplicates:', duplicates);
} }
const placeholders = orders.map(() => "(?, ?, ?, ?, ?, ?)").join(","); const placeholders = orders.map(() => "(?, ?, ?, ?, ?, ?, ?, ?)").join(",");
const values = orders.flatMap(order => [ const values = orders.flatMap(order => [
order.order_id, order.date, order.customer, order.customer_name, order.status, order.canceled order.order_id,
order.date,
order.customer,
order.customer_name,
order.status,
order.canceled,
order.summary_discount,
order.summary_subtotal
]); ]);
await localConnection.query(` await localConnection.query(`
INSERT INTO temp_order_meta VALUES ${placeholders} INSERT INTO temp_order_meta (
order_id,
date,
customer,
customer_name,
status,
canceled,
summary_discount,
summary_subtotal
) VALUES ${placeholders}
ON DUPLICATE KEY UPDATE ON DUPLICATE KEY UPDATE
date = VALUES(date), date = VALUES(date),
customer = VALUES(customer), customer = VALUES(customer),
customer_name = VALUES(customer_name), customer_name = VALUES(customer_name),
status = VALUES(status), status = VALUES(status),
canceled = VALUES(canceled) canceled = VALUES(canceled),
summary_discount = VALUES(summary_discount),
summary_subtotal = VALUES(summary_subtotal)
`, values); `, values);
processedCount = i + orders.length; processedCount = i + orders.length;
@@ -317,14 +353,25 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
for (let i = 0; i < orderIds.length; i += 5000) { for (let i = 0; i < orderIds.length; i += 5000) {
const batchIds = orderIds.slice(i, i + 5000); const batchIds = orderIds.slice(i, i + 5000);
const [costs] = await prodConnection.query(` const [costs] = await prodConnection.query(`
SELECT orderid as order_id, pid, costeach SELECT
FROM order_costs oc.orderid as order_id,
WHERE orderid IN (?) oc.pid,
COALESCE(
oc.costeach,
(SELECT pi.costeach
FROM product_inventory pi
WHERE pi.pid = oc.pid
AND pi.daterec <= o.date_placed
ORDER BY pi.daterec DESC LIMIT 1)
) as costeach
FROM order_costs oc
JOIN _order o ON oc.orderid = o.order_id
WHERE oc.orderid IN (?)
`, [batchIds]); `, [batchIds]);
if (costs.length > 0) { if (costs.length > 0) {
const placeholders = costs.map(() => '(?, ?, ?)').join(","); const placeholders = costs.map(() => '(?, ?, ?)').join(",");
const values = costs.flatMap(c => [c.order_id, c.pid, c.costeach]); const values = costs.flatMap(c => [c.order_id, c.pid, c.costeach || 0]);
await localConnection.query(` await localConnection.query(`
INSERT INTO temp_order_costs (order_id, pid, costeach) INSERT INTO temp_order_costs (order_id, pid, costeach)
VALUES ${placeholders} VALUES ${placeholders}
@@ -355,7 +402,13 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
om.date, om.date,
oi.price, oi.price,
oi.quantity, oi.quantity,
oi.base_discount + COALESCE(od.discount, 0) as discount, oi.base_discount + COALESCE(od.discount, 0) +
CASE
WHEN om.summary_discount > 0 THEN
ROUND((om.summary_discount * (oi.price * oi.quantity)) /
NULLIF(om.summary_subtotal, 0), 2)
ELSE 0
END as discount,
COALESCE(ot.tax, 0) as tax, COALESCE(ot.tax, 0) as tax,
0 as tax_included, 0 as tax_included,
0 as shipping, 0 as shipping,
@@ -455,7 +508,13 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
om.date, om.date,
oi.price, oi.price,
oi.quantity, oi.quantity,
oi.base_discount + COALESCE(od.discount, 0) as discount, oi.base_discount + COALESCE(od.discount, 0) +
CASE
WHEN o.summary_discount > 0 THEN
ROUND((o.summary_discount * (oi.price * oi.quantity)) /
NULLIF(o.summary_subtotal, 0), 2)
ELSE 0
END as discount,
COALESCE(ot.tax, 0) as tax, COALESCE(ot.tax, 0) as tax,
0 as tax_included, 0 as tax_included,
0 as shipping, 0 as shipping,
@@ -466,6 +525,7 @@ async function importOrders(prodConnection, localConnection, incrementalUpdate =
COALESCE(tc.costeach, 0) as costeach COALESCE(tc.costeach, 0) as costeach
FROM temp_order_items oi FROM temp_order_items oi
JOIN temp_order_meta om ON oi.order_id = om.order_id JOIN temp_order_meta om ON oi.order_id = om.order_id
LEFT JOIN _order o ON oi.order_id = o.order_id
LEFT JOIN temp_order_discounts od ON oi.order_id = od.order_id AND oi.pid = od.pid LEFT JOIN temp_order_discounts od ON oi.order_id = od.order_id AND oi.pid = od.pid
LEFT JOIN temp_order_taxes ot ON oi.order_id = ot.order_id AND oi.pid = ot.pid LEFT JOIN temp_order_taxes ot ON oi.order_id = ot.order_id AND oi.pid = ot.pid
LEFT JOIN temp_order_costs tc ON oi.order_id = tc.order_id AND oi.pid = tc.pid LEFT JOIN temp_order_costs tc ON oi.order_id = tc.order_id AND oi.pid = tc.pid

File diff suppressed because it is too large Load Diff

View File

@@ -33,16 +33,15 @@ async function importPurchaseOrders(prodConnection, localConnection, incremental
status: "running", status: "running",
}); });
// Get column names for the insert // Get column names first
const [columns] = await localConnection.query(` const [columns] = await localConnection.query(`
SELECT COLUMN_NAME SELECT COLUMN_NAME
FROM INFORMATION_SCHEMA.COLUMNS FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = 'purchase_orders' WHERE TABLE_NAME = 'purchase_orders'
AND COLUMN_NAME != 'updated' -- Exclude the updated column
ORDER BY ORDINAL_POSITION ORDER BY ORDINAL_POSITION
`); `);
const columnNames = columns const columnNames = columns.map(col => col.COLUMN_NAME);
.map((col) => col.COLUMN_NAME)
.filter((name) => name !== "id");
// Build incremental conditions // Build incremental conditions
const incrementalWhereClause = incrementalUpdate const incrementalWhereClause = incrementalUpdate
@@ -321,41 +320,47 @@ async function importPurchaseOrders(prodConnection, localConnection, incremental
let lastFulfillmentReceiving = null; let lastFulfillmentReceiving = null;
for (const receiving of allReceivings) { for (const receiving of allReceivings) {
const qtyToApply = Math.min(remainingToFulfill, receiving.qty_each); // Convert quantities to base units using supplier data
if (qtyToApply > 0) { const baseQtyReceived = receiving.qty_each * (
// If this is the first receiving being applied, use its cost receiving.type === 'original' ? 1 :
if (actualCost === null) { Math.max(1, product.supplier_qty_per_unit || 1)
actualCost = receiving.cost_each; );
firstFulfillmentReceiving = receiving; const qtyToApply = Math.min(remainingToFulfill, baseQtyReceived);
if (qtyToApply > 0) {
// If this is the first receiving being applied, use its cost
if (actualCost === null && receiving.cost_each > 0) {
actualCost = receiving.cost_each;
firstFulfillmentReceiving = receiving;
}
lastFulfillmentReceiving = receiving;
fulfillmentTracking.push({
receiving_id: receiving.receiving_id,
qty_applied: qtyToApply,
qty_total: baseQtyReceived,
cost: receiving.cost_each || actualCost || product.cost_each,
date: receiving.received_date,
received_by: receiving.received_by,
received_by_name: receiving.received_by_name || 'Unknown',
type: receiving.type,
remaining_qty: baseQtyReceived - qtyToApply
});
remainingToFulfill -= qtyToApply;
} else {
// Track excess receivings
fulfillmentTracking.push({
receiving_id: receiving.receiving_id,
qty_applied: 0,
qty_total: baseQtyReceived,
cost: receiving.cost_each || actualCost || product.cost_each,
date: receiving.received_date,
received_by: receiving.received_by,
received_by_name: receiving.received_by_name || 'Unknown',
type: receiving.type,
is_excess: true
});
} }
lastFulfillmentReceiving = receiving; totalReceived += baseQtyReceived;
fulfillmentTracking.push({
receiving_id: receiving.receiving_id,
qty_applied: qtyToApply,
qty_total: receiving.qty_each,
cost: receiving.cost_each,
date: receiving.received_date,
received_by: receiving.received_by,
received_by_name: receiving.received_by_name || 'Unknown',
type: receiving.type,
remaining_qty: receiving.qty_each - qtyToApply
});
remainingToFulfill -= qtyToApply;
} else {
// Track excess receivings
fulfillmentTracking.push({
receiving_id: receiving.receiving_id,
qty_applied: 0,
qty_total: receiving.qty_each,
cost: receiving.cost_each,
date: receiving.received_date,
received_by: receiving.received_by,
received_by_name: receiving.received_by_name || 'Unknown',
type: receiving.type,
is_excess: true
});
}
totalReceived += receiving.qty_each;
} }
const receiving_status = !totalReceived ? 1 : // created const receiving_status = !totalReceived ? 1 : // created

View File

@@ -1,82 +0,0 @@
// Split into inserts and updates
const insertsAndUpdates = batch.reduce((acc, po) => {
const key = `${po.po_id}-${po.pid}`;
if (existingPOMap.has(key)) {
const existing = existingPOMap.get(key);
// Check if any values are different
const hasChanges = columnNames.some(col => {
const newVal = po[col] ?? null;
const oldVal = existing[col] ?? null;
// Special handling for numbers to avoid type coercion issues
if (typeof newVal === 'number' && typeof oldVal === 'number') {
return Math.abs(newVal - oldVal) > 0.00001; // Allow for tiny floating point differences
}
// Special handling for receiving_history JSON
if (col === 'receiving_history') {
return JSON.stringify(newVal) !== JSON.stringify(oldVal);
}
return newVal !== oldVal;
});
if (hasChanges) {
console.log(`PO line changed: ${key}`, {
po_id: po.po_id,
pid: po.pid,
changes: columnNames.filter(col => {
const newVal = po[col] ?? null;
const oldVal = existing[col] ?? null;
if (typeof newVal === 'number' && typeof oldVal === 'number') {
return Math.abs(newVal - oldVal) > 0.00001;
}
if (col === 'receiving_history') {
return JSON.stringify(newVal) !== JSON.stringify(oldVal);
}
return newVal !== oldVal;
})
});
acc.updates.push({
po_id: po.po_id,
pid: po.pid,
values: columnNames.map(col => po[col] ?? null)
});
}
} else {
console.log(`New PO line: ${key}`);
acc.inserts.push({
po_id: po.po_id,
pid: po.pid,
values: columnNames.map(col => po[col] ?? null)
});
}
return acc;
}, { inserts: [], updates: [] });
// Handle inserts
if (insertsAndUpdates.inserts.length > 0) {
const insertPlaceholders = Array(insertsAndUpdates.inserts.length).fill(placeholderGroup).join(",");
const insertResult = await localConnection.query(`
INSERT INTO purchase_orders (${columnNames.join(",")})
VALUES ${insertPlaceholders}
`, insertsAndUpdates.inserts.map(i => i.values).flat());
recordsAdded += insertResult[0].affectedRows;
}
// Handle updates
if (insertsAndUpdates.updates.length > 0) {
const updatePlaceholders = Array(insertsAndUpdates.updates.length).fill(placeholderGroup).join(",");
const updateResult = await localConnection.query(`
INSERT INTO purchase_orders (${columnNames.join(",")})
VALUES ${updatePlaceholders}
ON DUPLICATE KEY UPDATE
${columnNames
.filter(col => col !== "po_id" && col !== "pid")
.map(col => `${col} = VALUES(${col})`)
.join(",")};
`, insertsAndUpdates.updates.map(u => u.values).flat());
// Each update affects 2 rows in affectedRows, so we divide by 2 to get actual count
recordsUpdated += insertsAndUpdates.updates.length;
}

View File

@@ -1,8 +1,11 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateBrandMetrics(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateBrandMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +16,29 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders: 0,
processedPurchaseOrders: 0,
success
};
} }
// Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
`);
processedOrders = orderCount[0].count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting brand metrics calculation', operation: 'Starting brand metrics calculation',
@@ -26,7 +47,12 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Calculate brand metrics with optimized queries // Calculate brand metrics with optimized queries
@@ -45,10 +71,21 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
WITH filtered_products AS ( WITH filtered_products AS (
SELECT SELECT
p.*, p.*,
CASE WHEN p.stock_quantity <= 5000 THEN p.pid END as valid_pid,
CASE WHEN p.visible = true AND p.stock_quantity <= 5000 THEN p.pid END as active_pid,
CASE CASE
WHEN p.stock_quantity IS NULL OR p.stock_quantity < 0 OR p.stock_quantity > 5000 THEN 0 WHEN p.stock_quantity <= 5000 AND p.stock_quantity >= 0
THEN p.pid
END as valid_pid,
CASE
WHEN p.visible = true
AND p.stock_quantity <= 5000
AND p.stock_quantity >= 0
THEN p.pid
END as active_pid,
CASE
WHEN p.stock_quantity IS NULL
OR p.stock_quantity < 0
OR p.stock_quantity > 5000
THEN 0
ELSE p.stock_quantity ELSE p.stock_quantity
END as valid_stock END as valid_stock
FROM products p FROM products p
@@ -57,10 +94,13 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
sales_periods AS ( sales_periods AS (
SELECT SELECT
p.brand, p.brand,
SUM(o.quantity * o.price) as period_revenue, SUM(o.quantity * (o.price - COALESCE(o.discount, 0))) as period_revenue,
SUM(o.quantity * (o.price - COALESCE(o.discount, 0) - p.cost_price)) as period_margin,
COUNT(DISTINCT DATE(o.date)) as period_days,
CASE CASE
WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) THEN 'current' WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) THEN 'current'
WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH) AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) THEN 'previous' WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH)
AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) THEN 'previous'
END as period_type END as period_type
FROM filtered_products p FROM filtered_products p
JOIN orders o ON p.pid = o.pid JOIN orders o ON p.pid = o.pid
@@ -76,10 +116,20 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
SUM(p.valid_stock) as total_stock_units, SUM(p.valid_stock) as total_stock_units,
SUM(p.valid_stock * p.cost_price) as total_stock_cost, SUM(p.valid_stock * p.cost_price) as total_stock_cost,
SUM(p.valid_stock * p.price) as total_stock_retail, SUM(p.valid_stock * p.price) as total_stock_retail,
COALESCE(SUM(o.quantity * o.price), 0) as total_revenue, COALESCE(SUM(o.quantity * (o.price - COALESCE(o.discount, 0))), 0) as total_revenue,
CASE CASE
WHEN SUM(o.quantity * o.price) > 0 THEN WHEN SUM(o.quantity * o.price) > 0
(SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity) THEN GREATEST(
-100.0,
LEAST(
100.0,
(
SUM(o.quantity * o.price) - -- Use gross revenue (before discounts)
SUM(o.quantity * COALESCE(p.cost_price, 0)) -- Total costs
) * 100.0 /
NULLIF(SUM(o.quantity * o.price), 0) -- Divide by gross revenue
)
)
ELSE 0 ELSE 0
END as avg_margin END as avg_margin
FROM filtered_products p FROM filtered_products p
@@ -97,16 +147,18 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
bd.avg_margin, bd.avg_margin,
CASE CASE
WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0 WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0
AND MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) > 0 THEN 100.0 AND MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) > 0
WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0 THEN 0.0 THEN 100.0
ELSE LEAST( WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0
GREATEST( THEN 0.0
ELSE GREATEST(
-100.0,
LEAST(
((MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) - ((MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) -
MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END)) / MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END)) /
NULLIF(MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END), 0)) * 100.0, NULLIF(ABS(MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END)), 0)) * 100.0,
-100.0 999.99
), )
999.99
) )
END as growth_rate END as growth_rate
FROM brand_data bd FROM brand_data bd
@@ -134,10 +186,20 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Calculate brand time-based metrics with optimized query // Calculate brand time-based metrics with optimized query
await connection.query(` await connection.query(`
@@ -177,8 +239,18 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
SUM(p.valid_stock * p.price) as total_stock_retail, SUM(p.valid_stock * p.price) as total_stock_retail,
SUM(o.quantity * o.price) as total_revenue, SUM(o.quantity * o.price) as total_revenue,
CASE CASE
WHEN SUM(o.quantity * o.price) > 0 THEN WHEN SUM(o.quantity * o.price) > 0
(SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity) THEN GREATEST(
-100.0,
LEAST(
100.0,
(
SUM(o.quantity * o.price) - -- Use gross revenue (before discounts)
SUM(o.quantity * COALESCE(p.cost_price, 0)) -- Total costs
) * 100.0 /
NULLIF(SUM(o.quantity * o.price), 0) -- Divide by gross revenue
)
)
ELSE 0 ELSE 0
END as avg_margin END as avg_margin
FROM filtered_products p FROM filtered_products p
@@ -207,11 +279,33 @@ async function calculateBrandMetrics(startTime, totalProducts, processedCount, i
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; // If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('brand_metrics', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating brand metrics'); logError(error, 'Error calculating brand metrics');
throw error; throw error;
} finally { } finally {

View File

@@ -1,8 +1,11 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateCategoryMetrics(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateCategoryMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +16,29 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders: 0,
processedPurchaseOrders: 0,
success
};
} }
// Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
`);
processedOrders = orderCount[0].count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting category metrics calculation', operation: 'Starting category metrics calculation',
@@ -26,7 +47,12 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// First, calculate base category metrics // First, calculate base category metrics
@@ -67,10 +93,20 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Then update with margin and turnover data // Then update with margin and turnover data
await connection.query(` await connection.query(`
@@ -80,19 +116,35 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
SUM(o.quantity * o.price) as total_sales, SUM(o.quantity * o.price) as total_sales,
SUM(o.quantity * (o.price - p.cost_price)) as total_margin, SUM(o.quantity * (o.price - p.cost_price)) as total_margin,
SUM(o.quantity) as units_sold, SUM(o.quantity) as units_sold,
AVG(GREATEST(p.stock_quantity, 0)) as avg_stock AVG(GREATEST(p.stock_quantity, 0)) as avg_stock,
COUNT(DISTINCT DATE(o.date)) as active_days
FROM product_categories pc FROM product_categories pc
JOIN products p ON pc.pid = p.pid JOIN products p ON pc.pid = p.pid
JOIN orders o ON p.pid = o.pid JOIN orders o ON p.pid = o.pid
LEFT JOIN turnover_config tc ON
(tc.category_id = pc.cat_id AND tc.vendor = p.vendor) OR
(tc.category_id = pc.cat_id AND tc.vendor IS NULL) OR
(tc.category_id IS NULL AND tc.vendor = p.vendor) OR
(tc.category_id IS NULL AND tc.vendor IS NULL)
WHERE o.canceled = false WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL COALESCE(tc.calculation_period_days, 30) DAY)
GROUP BY pc.cat_id GROUP BY pc.cat_id
) )
UPDATE category_metrics cm UPDATE category_metrics cm
JOIN category_sales cs ON cm.category_id = cs.cat_id JOIN category_sales cs ON cm.category_id = cs.cat_id
LEFT JOIN turnover_config tc ON
(tc.category_id = cm.category_id AND tc.vendor IS NULL) OR
(tc.category_id IS NULL AND tc.vendor IS NULL)
SET SET
cm.avg_margin = COALESCE(cs.total_margin * 100.0 / NULLIF(cs.total_sales, 0), 0), cm.avg_margin = COALESCE(cs.total_margin * 100.0 / NULLIF(cs.total_sales, 0), 0),
cm.turnover_rate = LEAST(COALESCE(cs.units_sold / NULLIF(cs.avg_stock, 0), 0), 999.99), cm.turnover_rate = CASE
WHEN cs.avg_stock > 0 AND cs.active_days > 0
THEN LEAST(
(cs.units_sold / cs.avg_stock) * (365.0 / cs.active_days),
999.99
)
ELSE 0
END,
cm.last_calculated_at = NOW() cm.last_calculated_at = NOW()
`); `);
@@ -105,20 +157,34 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Finally update growth rates // Finally update growth rates
await connection.query(` await connection.query(`
WITH current_period AS ( WITH current_period AS (
SELECT SELECT
pc.cat_id, pc.cat_id,
SUM(o.quantity * o.price) as revenue SUM(o.quantity * (o.price - COALESCE(o.discount, 0)) /
(1 + COALESCE(ss.seasonality_factor, 0))) as revenue,
SUM(o.quantity * (o.price - COALESCE(o.discount, 0) - p.cost_price)) as gross_profit,
COUNT(DISTINCT DATE(o.date)) as days
FROM product_categories pc FROM product_categories pc
JOIN products p ON pc.pid = p.pid JOIN products p ON pc.pid = p.pid
JOIN orders o ON p.pid = o.pid JOIN orders o ON p.pid = o.pid
LEFT JOIN sales_seasonality ss ON MONTH(o.date) = ss.month
WHERE o.canceled = false WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH)
GROUP BY pc.cat_id GROUP BY pc.cat_id
@@ -126,30 +192,106 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
previous_period AS ( previous_period AS (
SELECT SELECT
pc.cat_id, pc.cat_id,
SUM(o.quantity * o.price) as revenue SUM(o.quantity * (o.price - COALESCE(o.discount, 0)) /
(1 + COALESCE(ss.seasonality_factor, 0))) as revenue,
COUNT(DISTINCT DATE(o.date)) as days
FROM product_categories pc
JOIN products p ON pc.pid = p.pid
JOIN orders o ON p.pid = o.pid
LEFT JOIN sales_seasonality ss ON MONTH(o.date) = ss.month
WHERE o.canceled = false
AND o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH)
AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
GROUP BY pc.cat_id
),
trend_data AS (
SELECT
pc.cat_id,
MONTH(o.date) as month,
SUM(o.quantity * (o.price - COALESCE(o.discount, 0)) /
(1 + COALESCE(ss.seasonality_factor, 0))) as revenue,
COUNT(DISTINCT DATE(o.date)) as days_in_month
FROM product_categories pc
JOIN products p ON pc.pid = p.pid
JOIN orders o ON p.pid = o.pid
LEFT JOIN sales_seasonality ss ON MONTH(o.date) = ss.month
WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH)
GROUP BY pc.cat_id, MONTH(o.date)
),
trend_stats AS (
SELECT
cat_id,
COUNT(*) as n,
AVG(month) as avg_x,
AVG(revenue / NULLIF(days_in_month, 0)) as avg_y,
SUM(month * (revenue / NULLIF(days_in_month, 0))) as sum_xy,
SUM(month * month) as sum_xx
FROM trend_data
GROUP BY cat_id
HAVING COUNT(*) >= 6
),
trend_analysis AS (
SELECT
cat_id,
((n * sum_xy) - (avg_x * n * avg_y)) /
NULLIF((n * sum_xx) - (n * avg_x * avg_x), 0) as trend_slope,
avg_y as avg_daily_revenue
FROM trend_stats
),
margin_calc AS (
SELECT
pc.cat_id,
CASE
WHEN SUM(o.quantity * o.price) > 0 THEN
GREATEST(
-100.0,
LEAST(
100.0,
(
SUM(o.quantity * o.price) - -- Use gross revenue (before discounts)
SUM(o.quantity * COALESCE(p.cost_price, 0)) -- Total costs
) * 100.0 /
NULLIF(SUM(o.quantity * o.price), 0) -- Divide by gross revenue
)
)
ELSE NULL
END as avg_margin
FROM product_categories pc FROM product_categories pc
JOIN products p ON pc.pid = p.pid JOIN products p ON pc.pid = p.pid
JOIN orders o ON p.pid = o.pid JOIN orders o ON p.pid = o.pid
WHERE o.canceled = false WHERE o.canceled = false
AND o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH) AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH)
AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
GROUP BY pc.cat_id GROUP BY pc.cat_id
) )
UPDATE category_metrics cm UPDATE category_metrics cm
LEFT JOIN current_period cp ON cm.category_id = cp.cat_id LEFT JOIN current_period cp ON cm.category_id = cp.cat_id
LEFT JOIN previous_period pp ON cm.category_id = pp.cat_id LEFT JOIN previous_period pp ON cm.category_id = pp.cat_id
LEFT JOIN trend_analysis ta ON cm.category_id = ta.cat_id
LEFT JOIN margin_calc mc ON cm.category_id = mc.cat_id
SET SET
cm.growth_rate = CASE cm.growth_rate = CASE
WHEN pp.revenue = 0 AND COALESCE(cp.revenue, 0) > 0 THEN 100.0 WHEN pp.revenue = 0 AND COALESCE(cp.revenue, 0) > 0 THEN 100.0
WHEN pp.revenue = 0 THEN 0.0 WHEN pp.revenue = 0 OR cp.revenue IS NULL THEN 0.0
ELSE LEAST( WHEN ta.trend_slope IS NOT NULL THEN
GREATEST( GREATEST(
((COALESCE(cp.revenue, 0) - pp.revenue) / pp.revenue) * 100.0, -100.0,
-100.0 LEAST(
), (ta.trend_slope / NULLIF(ta.avg_daily_revenue, 0)) * 365 * 100,
999.99 999.99
) )
)
ELSE
GREATEST(
-100.0,
LEAST(
((COALESCE(cp.revenue, 0) - pp.revenue) /
NULLIF(ABS(pp.revenue), 0)) * 100.0,
999.99
)
)
END, END,
cm.avg_margin = COALESCE(mc.avg_margin, cm.avg_margin),
cm.last_calculated_at = NOW() cm.last_calculated_at = NOW()
WHERE cp.cat_id IS NOT NULL OR pp.cat_id IS NOT NULL WHERE cp.cat_id IS NOT NULL OR pp.cat_id IS NOT NULL
`); `);
@@ -163,10 +305,20 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Calculate time-based metrics // Calculate time-based metrics
await connection.query(` await connection.query(`
@@ -189,13 +341,23 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
COUNT(DISTINCT CASE WHEN p.visible = true THEN p.pid END) as active_products, COUNT(DISTINCT CASE WHEN p.visible = true THEN p.pid END) as active_products,
SUM(p.stock_quantity * p.cost_price) as total_value, SUM(p.stock_quantity * p.cost_price) as total_value,
SUM(o.quantity * o.price) as total_revenue, SUM(o.quantity * o.price) as total_revenue,
CASE
WHEN SUM(o.quantity * o.price) > 0 THEN
LEAST(
GREATEST(
SUM(o.quantity * (o.price - GREATEST(p.cost_price, 0))) * 100.0 /
SUM(o.quantity * o.price),
-100
),
100
)
ELSE 0
END as avg_margin,
COALESCE( COALESCE(
SUM(o.quantity * (o.price - p.cost_price)) * 100.0 / LEAST(
NULLIF(SUM(o.quantity * o.price), 0), SUM(o.quantity) / NULLIF(AVG(GREATEST(p.stock_quantity, 0)), 0),
0 999.99
) as avg_margin, ),
COALESCE(
SUM(o.quantity) / NULLIF(AVG(GREATEST(p.stock_quantity, 0)), 0),
0 0
) as turnover_rate ) as turnover_rate
FROM product_categories pc FROM product_categories pc
@@ -216,17 +378,138 @@ async function calculateCategoryMetrics(startTime, totalProducts, processedCount
processedCount = Math.floor(totalProducts * 0.99); processedCount = Math.floor(totalProducts * 0.99);
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Time-based metrics calculated', operation: 'Time-based metrics calculated, updating category-sales metrics',
current: processedCount, current: processedCount,
total: totalProducts, total: totalProducts,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Calculate category-sales metrics
await connection.query(`
INSERT INTO category_sales_metrics (
category_id,
brand,
period_start,
period_end,
avg_daily_sales,
total_sold,
num_products,
avg_price,
last_calculated_at
)
WITH date_ranges AS (
SELECT
DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) as period_start,
CURRENT_DATE as period_end
UNION ALL
SELECT
DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY),
DATE_SUB(CURRENT_DATE, INTERVAL 31 DAY)
UNION ALL
SELECT
DATE_SUB(CURRENT_DATE, INTERVAL 180 DAY),
DATE_SUB(CURRENT_DATE, INTERVAL 91 DAY)
UNION ALL
SELECT
DATE_SUB(CURRENT_DATE, INTERVAL 365 DAY),
DATE_SUB(CURRENT_DATE, INTERVAL 181 DAY)
),
sales_data AS (
SELECT
pc.cat_id,
COALESCE(p.brand, 'Unknown') as brand,
dr.period_start,
dr.period_end,
COUNT(DISTINCT p.pid) as num_products,
SUM(o.quantity) as total_sold,
SUM(o.quantity * o.price) as total_revenue,
COUNT(DISTINCT DATE(o.date)) as num_days
FROM products p
JOIN product_categories pc ON p.pid = pc.pid
JOIN orders o ON p.pid = o.pid
CROSS JOIN date_ranges dr
WHERE o.canceled = false
AND o.date BETWEEN dr.period_start AND dr.period_end
GROUP BY pc.cat_id, p.brand, dr.period_start, dr.period_end
)
SELECT
cat_id as category_id,
brand,
period_start,
period_end,
CASE
WHEN num_days > 0
THEN total_sold / num_days
ELSE 0
END as avg_daily_sales,
total_sold,
num_products,
CASE
WHEN total_sold > 0
THEN total_revenue / total_sold
ELSE 0
END as avg_price,
NOW() as last_calculated_at
FROM sales_data
ON DUPLICATE KEY UPDATE
avg_daily_sales = VALUES(avg_daily_sales),
total_sold = VALUES(total_sold),
num_products = VALUES(num_products),
avg_price = VALUES(avg_price),
last_calculated_at = VALUES(last_calculated_at)
`);
processedCount = Math.floor(totalProducts * 1.0);
outputProgress({
status: 'running',
operation: 'Category-sales metrics calculated',
current: processedCount,
total: totalProducts,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
// If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('category_metrics', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating category metrics'); logError(error, 'Error calculating category metrics');
throw error; throw error;
} finally { } finally {

View File

@@ -1,8 +1,11 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateFinancialMetrics(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateFinancialMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +16,30 @@ async function calculateFinancialMetrics(startTime, totalProducts, processedCoun
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders: 0,
processedPurchaseOrders: 0,
success
};
} }
// Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
AND DATE(o.date) >= DATE_SUB(CURDATE(), INTERVAL 12 MONTH)
`);
processedOrders = orderCount[0].count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting financial metrics calculation', operation: 'Starting financial metrics calculation',
@@ -26,7 +48,12 @@ async function calculateFinancialMetrics(startTime, totalProducts, processedCoun
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Calculate financial metrics with optimized query // Calculate financial metrics with optimized query
@@ -59,7 +86,8 @@ async function calculateFinancialMetrics(startTime, totalProducts, processedCoun
WHEN COALESCE(pf.inventory_value, 0) > 0 AND pf.active_days > 0 THEN WHEN COALESCE(pf.inventory_value, 0) > 0 AND pf.active_days > 0 THEN
(COALESCE(pf.gross_profit, 0) * (365.0 / pf.active_days)) / COALESCE(pf.inventory_value, 0) (COALESCE(pf.gross_profit, 0) * (365.0 / pf.active_days)) / COALESCE(pf.inventory_value, 0)
ELSE 0 ELSE 0
END END,
pm.last_calculated_at = CURRENT_TIMESTAMP
`); `);
processedCount = Math.floor(totalProducts * 0.65); processedCount = Math.floor(totalProducts * 0.65);
@@ -71,10 +99,20 @@ async function calculateFinancialMetrics(startTime, totalProducts, processedCoun
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Update time-based aggregates with optimized query // Update time-based aggregates with optimized query
await connection.query(` await connection.query(`
@@ -115,11 +153,33 @@ async function calculateFinancialMetrics(startTime, totalProducts, processedCoun
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; // If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('financial_metrics', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating financial metrics'); logError(error, 'Error calculating financial metrics');
throw error; throw error;
} finally { } finally {

View File

@@ -11,11 +11,21 @@ function sanitizeValue(value) {
async function calculateProductMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) { async function calculateProductMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
const BATCH_SIZE = 5000;
try { try {
// Skip flags are inherited from the parent scope // Skip flags are inherited from the parent scope
const SKIP_PRODUCT_BASE_METRICS = 0; const SKIP_PRODUCT_BASE_METRICS = 0;
const SKIP_PRODUCT_TIME_AGGREGATES = 0; const SKIP_PRODUCT_TIME_AGGREGATES = 0;
// Get total product count if not provided
if (!totalProducts) {
const [productCount] = await connection.query('SELECT COUNT(*) as count FROM products');
totalProducts = productCount[0].count;
}
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
status: 'cancelled', status: 'cancelled',
@@ -25,11 +35,37 @@ async function calculateProductMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} }
// First ensure all products have a metrics record
await connection.query(`
INSERT IGNORE INTO product_metrics (pid, last_calculated_at)
SELECT pid, NOW()
FROM products
`);
// Get threshold settings once
const [thresholds] = await connection.query(`
SELECT critical_days, reorder_days, overstock_days, low_stock_threshold
FROM stock_thresholds
WHERE category_id IS NULL AND vendor IS NULL
LIMIT 1
`);
const defaultThresholds = thresholds[0];
// Calculate base product metrics // Calculate base product metrics
if (!SKIP_PRODUCT_BASE_METRICS) { if (!SKIP_PRODUCT_BASE_METRICS) {
outputProgress({ outputProgress({
@@ -40,89 +76,237 @@ async function calculateProductMetrics(startTime, totalProducts, processedCount
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Calculate base metrics // Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
`);
processedOrders = orderCount[0].count;
// Clear temporary tables
await connection.query('TRUNCATE TABLE temp_sales_metrics');
await connection.query('TRUNCATE TABLE temp_purchase_metrics');
// Populate temp_sales_metrics with base stats and sales averages
await connection.query(` await connection.query(`
UPDATE product_metrics pm INSERT INTO temp_sales_metrics
JOIN ( SELECT
SELECT p.pid,
p.pid, COALESCE(SUM(o.quantity) / NULLIF(COUNT(DISTINCT DATE(o.date)), 0), 0) as daily_sales_avg,
p.cost_price * p.stock_quantity as inventory_value, COALESCE(SUM(o.quantity) / NULLIF(CEIL(COUNT(DISTINCT DATE(o.date)) / 7), 0), 0) as weekly_sales_avg,
SUM(o.quantity) as total_quantity, COALESCE(SUM(o.quantity) / NULLIF(CEIL(COUNT(DISTINCT DATE(o.date)) / 30), 0), 0) as monthly_sales_avg,
COUNT(DISTINCT o.order_number) as number_of_orders, COALESCE(SUM(o.quantity * o.price), 0) as total_revenue,
SUM(o.quantity * o.price) as total_revenue, CASE
SUM(o.quantity * p.cost_price) as cost_of_goods_sold, WHEN SUM(o.quantity * o.price) > 0
AVG(o.price) as avg_price, THEN ((SUM(o.quantity * o.price) - SUM(o.quantity * p.cost_price)) / SUM(o.quantity * o.price)) * 100
STDDEV(o.price) as price_std,
MIN(o.date) as first_sale_date,
MAX(o.date) as last_sale_date,
COUNT(DISTINCT DATE(o.date)) as active_days
FROM products p
LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
GROUP BY p.pid
) stats ON pm.pid = stats.pid
SET
pm.inventory_value = COALESCE(stats.inventory_value, 0),
pm.avg_quantity_per_order = COALESCE(stats.total_quantity / NULLIF(stats.number_of_orders, 0), 0),
pm.number_of_orders = COALESCE(stats.number_of_orders, 0),
pm.total_revenue = COALESCE(stats.total_revenue, 0),
pm.cost_of_goods_sold = COALESCE(stats.cost_of_goods_sold, 0),
pm.gross_profit = COALESCE(stats.total_revenue - stats.cost_of_goods_sold, 0),
pm.avg_margin_percent = CASE
WHEN COALESCE(stats.total_revenue, 0) > 0
THEN ((stats.total_revenue - stats.cost_of_goods_sold) / stats.total_revenue) * 100
ELSE 0 ELSE 0
END, END as avg_margin_percent,
pm.first_sale_date = stats.first_sale_date, MIN(o.date) as first_sale_date,
pm.last_sale_date = stats.last_sale_date, MAX(o.date) as last_sale_date
pm.gmroi = CASE FROM products p
WHEN COALESCE(stats.inventory_value, 0) > 0 LEFT JOIN orders o ON p.pid = o.pid
THEN (stats.total_revenue - stats.cost_of_goods_sold) / stats.inventory_value AND o.canceled = false
ELSE 0 AND o.date >= DATE_SUB(CURDATE(), INTERVAL 90 DAY)
END, GROUP BY p.pid
pm.last_calculated_at = NOW()
`); `);
processedCount = Math.floor(totalProducts * 0.4); // Populate temp_purchase_metrics
outputProgress({ await connection.query(`
status: 'running', INSERT INTO temp_purchase_metrics
operation: 'Base product metrics calculated', SELECT
current: processedCount, p.pid,
total: totalProducts, AVG(DATEDIFF(po.received_date, po.date)) as avg_lead_time_days,
elapsed: formatElapsedTime(startTime), MAX(po.date) as last_purchase_date,
remaining: estimateRemaining(startTime, processedCount, totalProducts), MIN(po.received_date) as first_received_date,
rate: calculateRate(startTime, processedCount), MAX(po.received_date) as last_received_date
percentage: ((processedCount / totalProducts) * 100).toFixed(1) FROM products p
}); LEFT JOIN purchase_orders po ON p.pid = po.pid
} else { AND po.received_date IS NOT NULL
processedCount = Math.floor(totalProducts * 0.4); AND po.date >= DATE_SUB(CURDATE(), INTERVAL 365 DAY)
outputProgress({ GROUP BY p.pid
status: 'running', `);
operation: 'Skipping base product metrics calculation',
current: processedCount,
total: totalProducts,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1)
});
}
if (isCancelled) return processedCount; // Process updates in batches
let lastPid = 0;
while (true) {
if (isCancelled) break;
const [batch] = await connection.query(
'SELECT pid FROM products WHERE pid > ? ORDER BY pid LIMIT ?',
[lastPid, BATCH_SIZE]
);
if (batch.length === 0) break;
await connection.query(`
UPDATE product_metrics pm
JOIN products p ON pm.pid = p.pid
LEFT JOIN temp_sales_metrics sm ON pm.pid = sm.pid
LEFT JOIN temp_purchase_metrics lm ON pm.pid = lm.pid
SET
pm.inventory_value = p.stock_quantity * NULLIF(p.cost_price, 0),
pm.daily_sales_avg = COALESCE(sm.daily_sales_avg, 0),
pm.weekly_sales_avg = COALESCE(sm.weekly_sales_avg, 0),
pm.monthly_sales_avg = COALESCE(sm.monthly_sales_avg, 0),
pm.total_revenue = COALESCE(sm.total_revenue, 0),
pm.avg_margin_percent = COALESCE(sm.avg_margin_percent, 0),
pm.first_sale_date = sm.first_sale_date,
pm.last_sale_date = sm.last_sale_date,
pm.avg_lead_time_days = COALESCE(lm.avg_lead_time_days, 30),
pm.days_of_inventory = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0
THEN FLOOR(p.stock_quantity / NULLIF(sm.daily_sales_avg, 0))
ELSE NULL
END,
pm.weeks_of_inventory = CASE
WHEN COALESCE(sm.weekly_sales_avg, 0) > 0
THEN FLOOR(p.stock_quantity / NULLIF(sm.weekly_sales_avg, 0))
ELSE NULL
END,
pm.stock_status = CASE
WHEN p.stock_quantity <= 0 THEN 'Out of Stock'
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 AND p.stock_quantity <= ? THEN 'Low Stock'
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 THEN 'In Stock'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ? THEN 'Critical'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ? THEN 'Reorder'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ? THEN 'Overstocked'
ELSE 'Healthy'
END,
pm.safety_stock = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 THEN
CEIL(sm.daily_sales_avg * SQRT(COALESCE(lm.avg_lead_time_days, 30)) * 1.96)
ELSE ?
END,
pm.reorder_point = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 THEN
CEIL(sm.daily_sales_avg * COALESCE(lm.avg_lead_time_days, 30)) +
CEIL(sm.daily_sales_avg * SQRT(COALESCE(lm.avg_lead_time_days, 30)) * 1.96)
ELSE ?
END,
pm.reorder_qty = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 AND NULLIF(p.cost_price, 0) IS NOT NULL THEN
GREATEST(
CEIL(SQRT((2 * (sm.daily_sales_avg * 365) * 25) / (NULLIF(p.cost_price, 0) * 0.25))),
?
)
ELSE ?
END,
pm.overstocked_amt = CASE
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ?
THEN GREATEST(0, p.stock_quantity - CEIL(sm.daily_sales_avg * ?))
ELSE 0
END,
pm.last_calculated_at = NOW()
WHERE p.pid IN (${batch.map(() => '?').join(',')})
`,
[
defaultThresholds.low_stock_threshold,
defaultThresholds.critical_days,
defaultThresholds.reorder_days,
defaultThresholds.overstock_days,
defaultThresholds.low_stock_threshold,
defaultThresholds.low_stock_threshold,
defaultThresholds.low_stock_threshold,
defaultThresholds.low_stock_threshold,
defaultThresholds.overstock_days,
defaultThresholds.overstock_days,
...batch.map(row => row.pid)
]
);
lastPid = batch[batch.length - 1].pid;
processedCount += batch.length;
outputProgress({
status: 'running',
operation: 'Processing base metrics batch',
current: processedCount,
total: totalProducts,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
}
// Calculate forecast accuracy and bias in batches
lastPid = 0;
while (true) {
if (isCancelled) break;
const [batch] = await connection.query(
'SELECT pid FROM products WHERE pid > ? ORDER BY pid LIMIT ?',
[lastPid, BATCH_SIZE]
);
if (batch.length === 0) break;
await connection.query(`
UPDATE product_metrics pm
JOIN (
SELECT
sf.pid,
AVG(CASE
WHEN o.quantity > 0
THEN ABS(sf.forecast_units - o.quantity) / o.quantity * 100
ELSE 100
END) as avg_forecast_error,
AVG(CASE
WHEN o.quantity > 0
THEN (sf.forecast_units - o.quantity) / o.quantity * 100
ELSE 0
END) as avg_forecast_bias,
MAX(sf.forecast_date) as last_forecast_date
FROM sales_forecasts sf
JOIN orders o ON sf.pid = o.pid
AND DATE(o.date) = sf.forecast_date
WHERE o.canceled = false
AND sf.forecast_date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
AND sf.pid IN (?)
GROUP BY sf.pid
) fa ON pm.pid = fa.pid
SET
pm.forecast_accuracy = GREATEST(0, 100 - LEAST(fa.avg_forecast_error, 100)),
pm.forecast_bias = GREATEST(-100, LEAST(fa.avg_forecast_bias, 100)),
pm.last_forecast_date = fa.last_forecast_date,
pm.last_calculated_at = NOW()
WHERE pm.pid IN (?)
`, [batch.map(row => row.pid), batch.map(row => row.pid)]);
lastPid = batch[batch.length - 1].pid;
}
}
// Calculate product time aggregates // Calculate product time aggregates
if (!SKIP_PRODUCT_TIME_AGGREGATES) { if (!SKIP_PRODUCT_TIME_AGGREGATES) {
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting product time aggregates calculation', operation: 'Starting product time aggregates calculation',
current: processedCount, current: processedCount || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedCount || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Calculate time-based aggregates // Calculate time-based aggregates
@@ -179,29 +363,206 @@ async function calculateProductMetrics(startTime, totalProducts, processedCount
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Product time aggregates calculated', operation: 'Product time aggregates calculated',
current: processedCount, current: processedCount || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedCount || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
} else { } else {
processedCount = Math.floor(totalProducts * 0.6); processedCount = Math.floor(totalProducts * 0.6);
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Skipping product time aggregates calculation', operation: 'Skipping product time aggregates calculation',
current: processedCount, current: processedCount || 0,
total: totalProducts, total: totalProducts || 0,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount || 0),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: (((processedCount || 0) / (totalProducts || 1)) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
} }
return processedCount; // Calculate ABC classification
outputProgress({
status: 'running',
operation: 'Starting ABC classification',
current: processedCount,
total: totalProducts,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0, // This module doesn't process POs
success
};
const [abcConfig] = await connection.query('SELECT a_threshold, b_threshold FROM abc_classification_config WHERE id = 1');
const abcThresholds = abcConfig[0] || { a_threshold: 20, b_threshold: 50 };
// First, create and populate the rankings table with an index
await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_revenue_ranks');
await connection.query(`
CREATE TEMPORARY TABLE temp_revenue_ranks (
pid BIGINT NOT NULL,
total_revenue DECIMAL(10,3),
rank_num INT,
dense_rank_num INT,
percentile DECIMAL(5,2),
total_count INT,
PRIMARY KEY (pid),
INDEX (rank_num),
INDEX (dense_rank_num),
INDEX (percentile)
) ENGINE=MEMORY
`);
// Calculate rankings with proper tie handling
await connection.query(`
INSERT INTO temp_revenue_ranks
WITH revenue_data AS (
SELECT
pid,
total_revenue,
COUNT(*) OVER () as total_count,
PERCENT_RANK() OVER (ORDER BY total_revenue DESC) * 100 as percentile,
RANK() OVER (ORDER BY total_revenue DESC) as rank_num,
DENSE_RANK() OVER (ORDER BY total_revenue DESC) as dense_rank_num
FROM product_metrics
WHERE total_revenue > 0
)
SELECT
pid,
total_revenue,
rank_num,
dense_rank_num,
percentile,
total_count
FROM revenue_data
`);
// Get total count for percentage calculation
const [rankingCount] = await connection.query('SELECT MAX(rank_num) as total_count FROM temp_revenue_ranks');
const totalCount = rankingCount[0].total_count || 1;
const max_rank = totalCount;
// Process updates in batches
let abcProcessedCount = 0;
const batchSize = 5000;
while (true) {
if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0, // This module doesn't process POs
success
};
// Get a batch of PIDs that need updating
const [pids] = await connection.query(`
SELECT pm.pid
FROM product_metrics pm
LEFT JOIN temp_revenue_ranks tr ON pm.pid = tr.pid
WHERE pm.abc_class IS NULL
OR pm.abc_class !=
CASE
WHEN tr.pid IS NULL THEN 'C'
WHEN tr.percentile <= ? THEN 'A'
WHEN tr.percentile <= ? THEN 'B'
ELSE 'C'
END
LIMIT ?
`, [abcThresholds.a_threshold, abcThresholds.b_threshold, batchSize]);
if (pids.length === 0) break;
await connection.query(`
UPDATE product_metrics pm
LEFT JOIN temp_revenue_ranks tr ON pm.pid = tr.pid
SET pm.abc_class =
CASE
WHEN tr.pid IS NULL THEN 'C'
WHEN tr.percentile <= ? THEN 'A'
WHEN tr.percentile <= ? THEN 'B'
ELSE 'C'
END,
pm.last_calculated_at = NOW()
WHERE pm.pid IN (?)
`, [abcThresholds.a_threshold, abcThresholds.b_threshold, pids.map(row => row.pid)]);
// Now update turnover rate with proper handling of zero inventory periods
await connection.query(`
UPDATE product_metrics pm
JOIN (
SELECT
o.pid,
SUM(o.quantity) as total_sold,
COUNT(DISTINCT DATE(o.date)) as active_days,
AVG(CASE
WHEN p.stock_quantity > 0 THEN p.stock_quantity
ELSE NULL
END) as avg_nonzero_stock
FROM orders o
JOIN products p ON o.pid = p.pid
WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
AND o.pid IN (?)
GROUP BY o.pid
) sales ON pm.pid = sales.pid
SET
pm.turnover_rate = CASE
WHEN sales.avg_nonzero_stock > 0 AND sales.active_days > 0
THEN LEAST(
(sales.total_sold / sales.avg_nonzero_stock) * (365.0 / sales.active_days),
999.99
)
ELSE 0
END,
pm.last_calculated_at = NOW()
WHERE pm.pid IN (?)
`, [pids.map(row => row.pid), pids.map(row => row.pid)]);
}
// If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('product_metrics', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount || 0,
processedOrders: processedOrders || 0,
processedPurchaseOrders: 0, // This module doesn't process POs
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating product metrics'); logError(error, 'Error calculating product metrics');
throw error; throw error;
} finally { } finally {
@@ -257,9 +618,9 @@ function calculateReorderQuantities(stock, stock_status, daily_sales_avg, avg_le
if (daily_sales_avg > 0) { if (daily_sales_avg > 0) {
const annual_demand = daily_sales_avg * 365; const annual_demand = daily_sales_avg * 365;
const order_cost = 25; // Fixed cost per order const order_cost = 25; // Fixed cost per order
const holding_cost_percent = 0.25; // 25% annual holding cost const holding_cost = config.cost_price * 0.25; // 25% of unit cost as annual holding cost
reorder_qty = Math.ceil(Math.sqrt((2 * annual_demand * order_cost) / holding_cost_percent)); reorder_qty = Math.ceil(Math.sqrt((2 * annual_demand * order_cost) / holding_cost));
} else { } else {
// If no sales data, use a basic calculation // If no sales data, use a basic calculation
reorder_qty = Math.max(safety_stock, config.low_stock_threshold); reorder_qty = Math.max(safety_stock, config.low_stock_threshold);

View File

@@ -1,8 +1,11 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateSalesForecasts(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateSalesForecasts(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +16,30 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders: 0,
processedPurchaseOrders: 0,
success
};
} }
// Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
`);
processedOrders = orderCount[0].count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting sales forecasts calculation', operation: 'Starting sales forecasts calculation',
@@ -26,7 +48,12 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// First, create a temporary table for forecast dates // First, create a temporary table for forecast dates
@@ -65,10 +92,20 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Create temporary table for daily sales stats // Create temporary table for daily sales stats
await connection.query(` await connection.query(`
@@ -94,10 +131,20 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Create temporary table for product stats // Create temporary table for product stats
await connection.query(` await connection.query(`
@@ -119,10 +166,20 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Calculate product-level forecasts // Calculate product-level forecasts
await connection.query(` await connection.query(`
@@ -134,37 +191,76 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
confidence_level, confidence_level,
last_calculated_at last_calculated_at
) )
WITH daily_stats AS (
SELECT
ds.pid,
AVG(ds.daily_quantity) as avg_daily_qty,
STDDEV(ds.daily_quantity) as std_daily_qty,
COUNT(DISTINCT ds.day_count) as data_points,
SUM(ds.day_count) as total_days,
AVG(ds.daily_revenue) as avg_daily_revenue,
STDDEV(ds.daily_revenue) as std_daily_revenue,
MIN(ds.daily_quantity) as min_daily_qty,
MAX(ds.daily_quantity) as max_daily_qty,
-- Calculate variance without using LAG
COALESCE(
STDDEV(ds.daily_quantity) / NULLIF(AVG(ds.daily_quantity), 0),
0
) as daily_variance_ratio
FROM temp_daily_sales ds
GROUP BY ds.pid
HAVING AVG(ds.daily_quantity) > 0
)
SELECT SELECT
ds.pid, ds.pid,
fd.forecast_date, fd.forecast_date,
GREATEST(0, GREATEST(0,
AVG(ds.daily_quantity) * ROUND(
(1 + COALESCE(sf.seasonality_factor, 0)) ds.avg_daily_qty *
(1 + COALESCE(sf.seasonality_factor, 0)) *
CASE
WHEN ds.std_daily_qty / NULLIF(ds.avg_daily_qty, 0) > 1.5 THEN 0.85
WHEN ds.std_daily_qty / NULLIF(ds.avg_daily_qty, 0) > 1.0 THEN 0.9
WHEN ds.std_daily_qty / NULLIF(ds.avg_daily_qty, 0) > 0.5 THEN 0.95
ELSE 1.0
END,
2
)
) as forecast_units, ) as forecast_units,
GREATEST(0, GREATEST(0,
COALESCE( ROUND(
CASE COALESCE(
WHEN SUM(ds.day_count) >= 4 THEN AVG(ds.daily_revenue) CASE
ELSE ps.overall_avg_revenue WHEN ds.data_points >= 4 THEN ds.avg_daily_revenue
END * ELSE ps.overall_avg_revenue
(1 + COALESCE(sf.seasonality_factor, 0)) * END *
(0.95 + (RAND() * 0.1)), (1 + COALESCE(sf.seasonality_factor, 0)) *
0 CASE
WHEN ds.std_daily_revenue / NULLIF(ds.avg_daily_revenue, 0) > 1.5 THEN 0.85
WHEN ds.std_daily_revenue / NULLIF(ds.avg_daily_revenue, 0) > 1.0 THEN 0.9
WHEN ds.std_daily_revenue / NULLIF(ds.avg_daily_revenue, 0) > 0.5 THEN 0.95
ELSE 1.0
END,
0
),
2
) )
) as forecast_revenue, ) as forecast_revenue,
CASE CASE
WHEN ps.total_days >= 60 THEN 90 WHEN ds.total_days >= 60 AND ds.daily_variance_ratio < 0.5 THEN 90
WHEN ps.total_days >= 30 THEN 80 WHEN ds.total_days >= 60 THEN 85
WHEN ps.total_days >= 14 THEN 70 WHEN ds.total_days >= 30 AND ds.daily_variance_ratio < 0.5 THEN 80
WHEN ds.total_days >= 30 THEN 75
WHEN ds.total_days >= 14 AND ds.daily_variance_ratio < 0.5 THEN 70
WHEN ds.total_days >= 14 THEN 65
ELSE 60 ELSE 60
END as confidence_level, END as confidence_level,
NOW() as last_calculated_at NOW() as last_calculated_at
FROM temp_daily_sales ds FROM daily_stats ds
JOIN temp_product_stats ps ON ds.pid = ps.pid JOIN temp_product_stats ps ON ds.pid = ps.pid
CROSS JOIN temp_forecast_dates fd CROSS JOIN temp_forecast_dates fd
LEFT JOIN sales_seasonality sf ON fd.month = sf.month LEFT JOIN sales_seasonality sf ON fd.month = sf.month
GROUP BY ds.pid, fd.forecast_date, ps.overall_avg_revenue, ps.total_days, sf.seasonality_factor GROUP BY ds.pid, fd.forecast_date, ps.overall_avg_revenue, sf.seasonality_factor
HAVING AVG(ds.daily_quantity) > 0
ON DUPLICATE KEY UPDATE ON DUPLICATE KEY UPDATE
forecast_units = VALUES(forecast_units), forecast_units = VALUES(forecast_units),
forecast_revenue = VALUES(forecast_revenue), forecast_revenue = VALUES(forecast_revenue),
@@ -181,10 +277,20 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Create temporary table for category stats // Create temporary table for category stats
await connection.query(` await connection.query(`
@@ -221,10 +327,20 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Calculate category-level forecasts // Calculate category-level forecasts
await connection.query(` await connection.query(`
@@ -292,11 +408,33 @@ async function calculateSalesForecasts(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; // If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('sales_forecasts', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating sales forecasts'); logError(error, 'Error calculating sales forecasts');
throw error; throw error;
} finally { } finally {

View File

@@ -1,8 +1,11 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateTimeAggregates(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateTimeAggregates(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +16,29 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders: 0,
processedPurchaseOrders: 0,
success
};
} }
// Get order count that will be processed
const [orderCount] = await connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
`);
processedOrders = orderCount[0].count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting time aggregates calculation', operation: 'Starting time aggregates calculation',
@@ -26,7 +47,12 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// Initial insert of time-based aggregates // Initial insert of time-based aggregates
@@ -42,9 +68,11 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
stock_received, stock_received,
stock_ordered, stock_ordered,
avg_price, avg_price,
profit_margin profit_margin,
inventory_value,
gmroi
) )
WITH sales_data AS ( WITH monthly_sales AS (
SELECT SELECT
o.pid, o.pid,
YEAR(o.date) as year, YEAR(o.date) as year,
@@ -55,17 +83,19 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
COUNT(DISTINCT o.order_number) as order_count, COUNT(DISTINCT o.order_number) as order_count,
AVG(o.price - COALESCE(o.discount, 0)) as avg_price, AVG(o.price - COALESCE(o.discount, 0)) as avg_price,
CASE CASE
WHEN SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) = 0 THEN 0 WHEN SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) > 0
ELSE ((SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) - THEN ((SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) - SUM(COALESCE(p.cost_price, 0) * o.quantity))
SUM(COALESCE(p.cost_price, 0) * o.quantity)) / / SUM((o.price - COALESCE(o.discount, 0)) * o.quantity)) * 100
SUM((o.price - COALESCE(o.discount, 0)) * o.quantity)) * 100 ELSE 0
END as profit_margin END as profit_margin,
p.cost_price * p.stock_quantity as inventory_value,
COUNT(DISTINCT DATE(o.date)) as active_days
FROM orders o FROM orders o
JOIN products p ON o.pid = p.pid JOIN products p ON o.pid = p.pid
WHERE o.canceled = 0 WHERE o.canceled = false
GROUP BY o.pid, YEAR(o.date), MONTH(o.date) GROUP BY o.pid, YEAR(o.date), MONTH(o.date)
), ),
purchase_data AS ( monthly_stock AS (
SELECT SELECT
pid, pid,
YEAR(date) as year, YEAR(date) as year,
@@ -73,45 +103,100 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
SUM(received) as stock_received, SUM(received) as stock_received,
SUM(ordered) as stock_ordered SUM(ordered) as stock_ordered
FROM purchase_orders FROM purchase_orders
WHERE status = 50
GROUP BY pid, YEAR(date), MONTH(date) GROUP BY pid, YEAR(date), MONTH(date)
),
base_products AS (
SELECT
p.pid,
p.cost_price * p.stock_quantity as inventory_value
FROM products p
) )
SELECT SELECT
s.pid, COALESCE(s.pid, ms.pid) as pid,
s.year, COALESCE(s.year, ms.year) as year,
s.month, COALESCE(s.month, ms.month) as month,
s.total_quantity_sold, COALESCE(s.total_quantity_sold, 0) as total_quantity_sold,
s.total_revenue, COALESCE(s.total_revenue, 0) as total_revenue,
s.total_cost, COALESCE(s.total_cost, 0) as total_cost,
s.order_count, COALESCE(s.order_count, 0) as order_count,
COALESCE(p.stock_received, 0) as stock_received, COALESCE(ms.stock_received, 0) as stock_received,
COALESCE(p.stock_ordered, 0) as stock_ordered, COALESCE(ms.stock_ordered, 0) as stock_ordered,
s.avg_price, COALESCE(s.avg_price, 0) as avg_price,
s.profit_margin COALESCE(s.profit_margin, 0) as profit_margin,
FROM sales_data s COALESCE(s.inventory_value, bp.inventory_value, 0) as inventory_value,
LEFT JOIN purchase_data p CASE
ON s.pid = p.pid WHEN COALESCE(s.inventory_value, bp.inventory_value, 0) > 0
AND s.year = p.year AND COALESCE(s.active_days, 0) > 0
AND s.month = p.month THEN (COALESCE(s.total_revenue - s.total_cost, 0) * (365.0 / s.active_days))
/ COALESCE(s.inventory_value, bp.inventory_value)
ELSE 0
END as gmroi
FROM (
SELECT * FROM monthly_sales s
UNION ALL
SELECT
ms.pid,
ms.year,
ms.month,
0 as total_quantity_sold,
0 as total_revenue,
0 as total_cost,
0 as order_count,
NULL as avg_price,
0 as profit_margin,
NULL as inventory_value,
0 as active_days
FROM monthly_stock ms
WHERE NOT EXISTS (
SELECT 1 FROM monthly_sales s2
WHERE s2.pid = ms.pid
AND s2.year = ms.year
AND s2.month = ms.month
)
) s
LEFT JOIN monthly_stock ms
ON s.pid = ms.pid
AND s.year = ms.year
AND s.month = ms.month
JOIN base_products bp ON COALESCE(s.pid, ms.pid) = bp.pid
UNION UNION
SELECT SELECT
p.pid, ms.pid,
p.year, ms.year,
p.month, ms.month,
0 as total_quantity_sold, 0 as total_quantity_sold,
0 as total_revenue, 0 as total_revenue,
0 as total_cost, 0 as total_cost,
0 as order_count, 0 as order_count,
p.stock_received, ms.stock_received,
p.stock_ordered, ms.stock_ordered,
0 as avg_price, 0 as avg_price,
0 as profit_margin 0 as profit_margin,
FROM purchase_data p bp.inventory_value,
LEFT JOIN sales_data s 0 as gmroi
ON p.pid = s.pid FROM monthly_stock ms
AND p.year = s.year JOIN base_products bp ON ms.pid = bp.pid
AND p.month = s.month WHERE NOT EXISTS (
WHERE s.pid IS NULL SELECT 1 FROM (
SELECT * FROM monthly_sales
UNION ALL
SELECT
ms2.pid,
ms2.year,
ms2.month,
0, 0, 0, 0, NULL, 0, NULL, 0
FROM monthly_stock ms2
WHERE NOT EXISTS (
SELECT 1 FROM monthly_sales s2
WHERE s2.pid = ms2.pid
AND s2.year = ms2.year
AND s2.month = ms2.month
)
) s
WHERE s.pid = ms.pid
AND s.year = ms.year
AND s.month = ms.month
)
ON DUPLICATE KEY UPDATE ON DUPLICATE KEY UPDATE
total_quantity_sold = VALUES(total_quantity_sold), total_quantity_sold = VALUES(total_quantity_sold),
total_revenue = VALUES(total_revenue), total_revenue = VALUES(total_revenue),
@@ -120,7 +205,9 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
stock_received = VALUES(stock_received), stock_received = VALUES(stock_received),
stock_ordered = VALUES(stock_ordered), stock_ordered = VALUES(stock_ordered),
avg_price = VALUES(avg_price), avg_price = VALUES(avg_price),
profit_margin = VALUES(profit_margin) profit_margin = VALUES(profit_margin),
inventory_value = VALUES(inventory_value),
gmroi = VALUES(gmroi)
`); `);
processedCount = Math.floor(totalProducts * 0.60); processedCount = Math.floor(totalProducts * 0.60);
@@ -132,10 +219,20 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
// Update with financial metrics // Update with financial metrics
await connection.query(` await connection.query(`
@@ -147,7 +244,7 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
MONTH(o.date) as month, MONTH(o.date) as month,
p.cost_price * p.stock_quantity as inventory_value, p.cost_price * p.stock_quantity as inventory_value,
SUM(o.quantity * (o.price - p.cost_price)) as gross_profit, SUM(o.quantity * (o.price - p.cost_price)) as gross_profit,
COUNT(DISTINCT DATE(o.date)) as days_in_period COUNT(DISTINCT DATE(o.date)) as active_days
FROM products p FROM products p
LEFT JOIN orders o ON p.pid = o.pid LEFT JOIN orders o ON p.pid = o.pid
WHERE o.canceled = false WHERE o.canceled = false
@@ -156,12 +253,7 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
AND pta.year = fin.year AND pta.year = fin.year
AND pta.month = fin.month AND pta.month = fin.month
SET SET
pta.inventory_value = COALESCE(fin.inventory_value, 0), pta.inventory_value = COALESCE(fin.inventory_value, 0)
pta.gmroi = CASE
WHEN COALESCE(fin.inventory_value, 0) > 0 AND fin.days_in_period > 0 THEN
(COALESCE(fin.gross_profit, 0) * (365.0 / fin.days_in_period)) / COALESCE(fin.inventory_value, 0)
ELSE 0
END
`); `);
processedCount = Math.floor(totalProducts * 0.65); processedCount = Math.floor(totalProducts * 0.65);
@@ -173,11 +265,33 @@ async function calculateTimeAggregates(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; // If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('time_aggregates', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders: 0,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating time aggregates'); logError(error, 'Error calculating time aggregates');
throw error; throw error;
} finally { } finally {

View File

@@ -1,8 +1,12 @@
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress'); const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db'); const { getConnection } = require('./utils/db');
async function calculateVendorMetrics(startTime, totalProducts, processedCount, isCancelled = false) { async function calculateVendorMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
const connection = await getConnection(); const connection = await getConnection();
let success = false;
let processedOrders = 0;
let processedPurchaseOrders = 0;
try { try {
if (isCancelled) { if (isCancelled) {
outputProgress({ outputProgress({
@@ -13,11 +17,37 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: null, remaining: null,
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders,
success
};
} }
// Get counts of records that will be processed
const [[orderCount], [poCount]] = await Promise.all([
connection.query(`
SELECT COUNT(*) as count
FROM orders o
WHERE o.canceled = false
`),
connection.query(`
SELECT COUNT(*) as count
FROM purchase_orders po
WHERE po.status != 0
`)
]);
processedOrders = orderCount.count;
processedPurchaseOrders = poCount.count;
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Starting vendor metrics calculation', operation: 'Starting vendor metrics calculation',
@@ -26,7 +56,12 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
// First ensure all vendors exist in vendor_details // First ensure all vendors exist in vendor_details
@@ -50,10 +85,20 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
if (isCancelled) return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders,
success
};
// Now calculate vendor metrics // Now calculate vendor metrics
await connection.query(` await connection.query(`
@@ -68,6 +113,8 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
avg_order_value, avg_order_value,
active_products, active_products,
total_products, total_products,
total_purchase_value,
avg_margin_percent,
status, status,
last_calculated_at last_calculated_at
) )
@@ -76,7 +123,8 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
p.vendor, p.vendor,
SUM(o.quantity * o.price) as total_revenue, SUM(o.quantity * o.price) as total_revenue,
COUNT(DISTINCT o.id) as total_orders, COUNT(DISTINCT o.id) as total_orders,
COUNT(DISTINCT p.pid) as active_products COUNT(DISTINCT p.pid) as active_products,
SUM(o.quantity * (o.price - p.cost_price)) as total_margin
FROM products p FROM products p
JOIN orders o ON p.pid = o.pid JOIN orders o ON p.pid = o.pid
WHERE o.canceled = false WHERE o.canceled = false
@@ -91,7 +139,8 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
AVG(CASE AVG(CASE
WHEN po.receiving_status = 40 WHEN po.receiving_status = 40
THEN DATEDIFF(po.received_date, po.date) THEN DATEDIFF(po.received_date, po.date)
END) as avg_lead_time_days END) as avg_lead_time_days,
SUM(po.ordered * po.po_cost_price) as total_purchase_value
FROM products p FROM products p
JOIN purchase_orders po ON p.pid = po.pid JOIN purchase_orders po ON p.pid = po.pid
WHERE po.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) WHERE po.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
@@ -127,6 +176,12 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
END as avg_order_value, END as avg_order_value,
COALESCE(vs.active_products, 0) as active_products, COALESCE(vs.active_products, 0) as active_products,
COALESCE(vpr.total_products, 0) as total_products, COALESCE(vpr.total_products, 0) as total_products,
COALESCE(vp.total_purchase_value, 0) as total_purchase_value,
CASE
WHEN vs.total_revenue > 0
THEN (vs.total_margin / vs.total_revenue) * 100
ELSE 0
END as avg_margin_percent,
'active' as status, 'active' as status,
NOW() as last_calculated_at NOW() as last_calculated_at
FROM vendor_sales vs FROM vendor_sales vs
@@ -143,6 +198,8 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
avg_order_value = VALUES(avg_order_value), avg_order_value = VALUES(avg_order_value),
active_products = VALUES(active_products), active_products = VALUES(active_products),
total_products = VALUES(total_products), total_products = VALUES(total_products),
total_purchase_value = VALUES(total_purchase_value),
avg_margin_percent = VALUES(avg_margin_percent),
status = VALUES(status), status = VALUES(status),
last_calculated_at = VALUES(last_calculated_at) last_calculated_at = VALUES(last_calculated_at)
`); `);
@@ -150,17 +207,155 @@ async function calculateVendorMetrics(startTime, totalProducts, processedCount,
processedCount = Math.floor(totalProducts * 0.9); processedCount = Math.floor(totalProducts * 0.9);
outputProgress({ outputProgress({
status: 'running', status: 'running',
operation: 'Vendor metrics calculated', operation: 'Vendor metrics calculated, updating time-based metrics',
current: processedCount, current: processedCount,
total: totalProducts, total: totalProducts,
elapsed: formatElapsedTime(startTime), elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts), remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount), rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1) percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
}); });
return processedCount; if (isCancelled) return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders,
success
};
// Calculate time-based metrics
await connection.query(`
INSERT INTO vendor_time_metrics (
vendor,
year,
month,
total_orders,
late_orders,
avg_lead_time_days,
total_purchase_value,
total_revenue,
avg_margin_percent
)
WITH monthly_orders AS (
SELECT
p.vendor,
YEAR(o.date) as year,
MONTH(o.date) as month,
COUNT(DISTINCT o.id) as total_orders,
SUM(o.quantity * o.price) as total_revenue,
SUM(o.quantity * (o.price - p.cost_price)) as total_margin
FROM products p
JOIN orders o ON p.pid = o.pid
WHERE o.canceled = false
AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
AND p.vendor IS NOT NULL
GROUP BY p.vendor, YEAR(o.date), MONTH(o.date)
),
monthly_po AS (
SELECT
p.vendor,
YEAR(po.date) as year,
MONTH(po.date) as month,
COUNT(DISTINCT po.id) as total_po,
COUNT(DISTINCT CASE
WHEN po.receiving_status = 40 AND po.received_date > po.expected_date
THEN po.id
END) as late_orders,
AVG(CASE
WHEN po.receiving_status = 40
THEN DATEDIFF(po.received_date, po.date)
END) as avg_lead_time_days,
SUM(po.ordered * po.po_cost_price) as total_purchase_value
FROM products p
JOIN purchase_orders po ON p.pid = po.pid
WHERE po.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
AND p.vendor IS NOT NULL
GROUP BY p.vendor, YEAR(po.date), MONTH(po.date)
)
SELECT
mo.vendor,
mo.year,
mo.month,
COALESCE(mp.total_po, 0) as total_orders,
COALESCE(mp.late_orders, 0) as late_orders,
COALESCE(mp.avg_lead_time_days, 0) as avg_lead_time_days,
COALESCE(mp.total_purchase_value, 0) as total_purchase_value,
mo.total_revenue,
CASE
WHEN mo.total_revenue > 0
THEN (mo.total_margin / mo.total_revenue) * 100
ELSE 0
END as avg_margin_percent
FROM monthly_orders mo
LEFT JOIN monthly_po mp ON mo.vendor = mp.vendor
AND mo.year = mp.year
AND mo.month = mp.month
UNION
SELECT
mp.vendor,
mp.year,
mp.month,
mp.total_po as total_orders,
mp.late_orders,
mp.avg_lead_time_days,
mp.total_purchase_value,
0 as total_revenue,
0 as avg_margin_percent
FROM monthly_po mp
LEFT JOIN monthly_orders mo ON mp.vendor = mo.vendor
AND mp.year = mo.year
AND mp.month = mo.month
WHERE mo.vendor IS NULL
ON DUPLICATE KEY UPDATE
total_orders = VALUES(total_orders),
late_orders = VALUES(late_orders),
avg_lead_time_days = VALUES(avg_lead_time_days),
total_purchase_value = VALUES(total_purchase_value),
total_revenue = VALUES(total_revenue),
avg_margin_percent = VALUES(avg_margin_percent)
`);
processedCount = Math.floor(totalProducts * 0.95);
outputProgress({
status: 'running',
operation: 'Time-based vendor metrics calculated',
current: processedCount,
total: totalProducts,
elapsed: formatElapsedTime(startTime),
remaining: estimateRemaining(startTime, processedCount, totalProducts),
rate: calculateRate(startTime, processedCount),
percentage: ((processedCount / totalProducts) * 100).toFixed(1),
timing: {
start_time: new Date(startTime).toISOString(),
end_time: new Date().toISOString(),
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
}
});
// If we get here, everything completed successfully
success = true;
// Update calculate_status
await connection.query(`
INSERT INTO calculate_status (module_name, last_calculation_timestamp)
VALUES ('vendor_metrics', NOW())
ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
`);
return {
processedProducts: processedCount,
processedOrders,
processedPurchaseOrders,
success
};
} catch (error) { } catch (error) {
success = false;
logError(error, 'Error calculating vendor metrics'); logError(error, 'Error calculating vendor metrics');
throw error; throw error;
} finally { } finally {

View File

@@ -1,4 +1,4 @@
const mysql = require('mysql2/promise'); const { Client } = require('pg');
const path = require('path'); const path = require('path');
const dotenv = require('dotenv'); const dotenv = require('dotenv');
const fs = require('fs'); const fs = require('fs');
@@ -10,7 +10,7 @@ const dbConfig = {
user: process.env.DB_USER, user: process.env.DB_USER,
password: process.env.DB_PASSWORD, password: process.env.DB_PASSWORD,
database: process.env.DB_NAME, database: process.env.DB_NAME,
multipleStatements: true port: process.env.DB_PORT || 5432
}; };
// Helper function to output progress in JSON format // Helper function to output progress in JSON format
@@ -120,46 +120,42 @@ async function resetDatabase() {
} }
}); });
const connection = await mysql.createConnection(dbConfig); const client = new Client(dbConfig);
await client.connect();
try { try {
// Check MySQL privileges // Check PostgreSQL version and user
outputProgress({ outputProgress({
operation: 'Checking privileges', operation: 'Checking database',
message: 'Verifying MySQL user privileges...' message: 'Verifying PostgreSQL version and user privileges...'
}); });
const [grants] = await connection.query('SHOW GRANTS'); const versionResult = await client.query('SELECT version()');
const userResult = await client.query('SELECT current_user, current_database()');
outputProgress({ outputProgress({
operation: 'User privileges', operation: 'Database info',
message: { message: {
grants: grants.map(g => Object.values(g)[0]) version: versionResult.rows[0].version,
user: userResult.rows[0].current_user,
database: userResult.rows[0].current_database
} }
}); });
// Enable warnings as errors
await connection.query('SET SESSION sql_notes = 1');
// Log database config (without sensitive info)
outputProgress({
operation: 'Database config',
message: `Using database: ${dbConfig.database} on host: ${dbConfig.host}`
});
// Get list of all tables in the current database // Get list of all tables in the current database
outputProgress({ outputProgress({
operation: 'Getting table list', operation: 'Getting table list',
message: 'Retrieving all table names...' message: 'Retrieving all table names...'
}); });
const [tables] = await connection.query(` const tablesResult = await client.query(`
SELECT GROUP_CONCAT(table_name) as tables SELECT string_agg(tablename, ', ') as tables
FROM information_schema.tables FROM pg_tables
WHERE table_schema = DATABASE() WHERE schemaname = 'public'
AND table_name NOT IN ('users', 'import_history') AND tablename NOT IN ('users', 'calculate_history', 'import_history');
`); `);
if (!tables[0].tables) { if (!tablesResult.rows[0].tables) {
outputProgress({ outputProgress({
operation: 'No tables found', operation: 'No tables found',
message: 'Database is already empty' message: 'Database is already empty'
@@ -170,20 +166,73 @@ async function resetDatabase() {
message: 'Dropping all existing tables...' message: 'Dropping all existing tables...'
}); });
await connection.query('SET FOREIGN_KEY_CHECKS = 0'); // Disable triggers/foreign key checks
const dropQuery = ` await client.query('SET session_replication_role = \'replica\';');
DROP TABLE IF EXISTS
${tables[0].tables // Drop all tables except users
.split(',') const tables = tablesResult.rows[0].tables.split(', ');
.filter(table => table !== 'users') for (const table of tables) {
.map(table => '`' + table + '`') if (!['users'].includes(table)) {
.join(', ')} await client.query(`DROP TABLE IF EXISTS "${table}" CASCADE`);
`; }
await connection.query(dropQuery); }
await connection.query('SET FOREIGN_KEY_CHECKS = 1');
// Only drop types if we're not preserving history tables
const historyTablesExist = await client.query(`
SELECT EXISTS (
SELECT FROM pg_tables
WHERE schemaname = 'public'
AND tablename IN ('calculate_history', 'import_history')
);
`);
if (!historyTablesExist.rows[0].exists) {
await client.query('DROP TYPE IF EXISTS calculation_status CASCADE;');
await client.query('DROP TYPE IF EXISTS module_name CASCADE;');
}
// Re-enable triggers/foreign key checks
await client.query('SET session_replication_role = \'origin\';');
} }
// Read and execute main schema (core tables) // Create enum types if they don't exist
outputProgress({
operation: 'Creating enum types',
message: 'Setting up required enum types...'
});
// Check if types exist before creating
const typesExist = await client.query(`
SELECT EXISTS (
SELECT 1 FROM pg_type
WHERE typname = 'calculation_status'
) as calc_status_exists,
EXISTS (
SELECT 1 FROM pg_type
WHERE typname = 'module_name'
) as module_name_exists;
`);
if (!typesExist.rows[0].calc_status_exists) {
await client.query(`CREATE TYPE calculation_status AS ENUM ('running', 'completed', 'failed', 'cancelled')`);
}
if (!typesExist.rows[0].module_name_exists) {
await client.query(`
CREATE TYPE module_name AS ENUM (
'product_metrics',
'time_aggregates',
'financial_metrics',
'vendor_metrics',
'category_metrics',
'brand_metrics',
'sales_forecasts',
'abc_classification'
)
`);
}
// Read and execute main schema first (core tables)
outputProgress({ outputProgress({
operation: 'Running database setup', operation: 'Running database setup',
message: 'Creating core tables...' message: 'Creating core tables...'
@@ -223,35 +272,24 @@ async function resetDatabase() {
for (let i = 0; i < statements.length; i++) { for (let i = 0; i < statements.length; i++) {
const stmt = statements[i]; const stmt = statements[i];
try { try {
const [result, fields] = await connection.query(stmt); const result = await client.query(stmt);
// Check for warnings
const [warnings] = await connection.query('SHOW WARNINGS');
if (warnings && warnings.length > 0) {
outputProgress({
status: 'warning',
operation: 'SQL Warning',
statement: i + 1,
warnings: warnings
});
}
// Verify if table was created (if this was a CREATE TABLE statement) // Verify if table was created (if this was a CREATE TABLE statement)
if (stmt.trim().toLowerCase().startsWith('create table')) { if (stmt.trim().toLowerCase().startsWith('create table')) {
const tableName = stmt.match(/create\s+table\s+(?:if\s+not\s+exists\s+)?`?(\w+)`?/i)?.[1]; const tableName = stmt.match(/create\s+table\s+(?:if\s+not\s+exists\s+)?["]?(\w+)["]?/i)?.[1];
if (tableName) { if (tableName) {
const [tableExists] = await connection.query(` const tableExists = await client.query(`
SELECT COUNT(*) as count SELECT COUNT(*) as count
FROM information_schema.tables FROM information_schema.tables
WHERE table_schema = DATABASE() WHERE table_schema = 'public'
AND table_name = ? AND table_name = $1
`, [tableName]); `, [tableName]);
outputProgress({ outputProgress({
operation: 'Table Creation Verification', operation: 'Table Creation Verification',
message: { message: {
table: tableName, table: tableName,
exists: tableExists[0].count > 0 exists: tableExists.rows[0].count > 0
} }
}); });
} }
@@ -263,7 +301,7 @@ async function resetDatabase() {
statement: i + 1, statement: i + 1,
total: statements.length, total: statements.length,
preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''), preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''),
affectedRows: result.affectedRows rowCount: result.rowCount
} }
}); });
} catch (sqlError) { } catch (sqlError) {
@@ -271,8 +309,6 @@ async function resetDatabase() {
status: 'error', status: 'error',
operation: 'SQL Error', operation: 'SQL Error',
error: sqlError.message, error: sqlError.message,
sqlState: sqlError.sqlState,
errno: sqlError.errno,
statement: stmt, statement: stmt,
statementNumber: i + 1 statementNumber: i + 1
}); });
@@ -280,66 +316,12 @@ async function resetDatabase() {
} }
} }
// List all tables in the database after schema execution // Verify core tables were created
outputProgress({ const existingTables = (await client.query(`
operation: 'Debug database', SELECT table_name
message: {
currentDatabase: (await connection.query('SELECT DATABASE() as db'))[0][0].db
}
});
const [allTables] = await connection.query(`
SELECT
table_schema,
table_name,
engine,
create_time,
table_rows
FROM information_schema.tables FROM information_schema.tables
WHERE table_schema = DATABASE() WHERE table_schema = 'public'
`); `)).rows.map(t => t.table_name);
if (allTables.length === 0) {
outputProgress({
operation: 'Warning',
message: 'No tables found in database after schema execution'
});
} else {
outputProgress({
operation: 'Tables after schema execution',
message: {
count: allTables.length,
tables: allTables.map(t => ({
schema: t.table_schema,
name: t.table_name,
engine: t.engine,
created: t.create_time,
rows: t.table_rows
}))
}
});
}
// Also check table status
const [tableStatus] = await connection.query('SHOW TABLE STATUS');
outputProgress({
operation: 'Table Status',
message: {
tables: tableStatus.map(t => ({
name: t.Name,
engine: t.Engine,
version: t.Version,
rowFormat: t.Row_format,
rows: t.Rows,
createTime: t.Create_time,
updateTime: t.Update_time
}))
}
});
// Verify core tables were created using SHOW TABLES
const [showTables] = await connection.query('SHOW TABLES');
const existingTables = showTables.map(t => Object.values(t)[0]);
outputProgress({ outputProgress({
operation: 'Core tables verification', operation: 'Core tables verification',
@@ -359,22 +341,12 @@ async function resetDatabase() {
); );
} }
// Verify all core tables use InnoDB
const [engineStatus] = await connection.query('SHOW TABLE STATUS WHERE Name IN (?)', [CORE_TABLES]);
const nonInnoDBTables = engineStatus.filter(t => t.Engine !== 'InnoDB');
if (nonInnoDBTables.length > 0) {
throw new Error(
`Tables using non-InnoDB engine: ${nonInnoDBTables.map(t => t.Name).join(', ')}`
);
}
outputProgress({ outputProgress({
operation: 'Core tables created', operation: 'Core tables created',
message: `Successfully created tables: ${CORE_TABLES.join(', ')}` message: `Successfully created tables: ${CORE_TABLES.join(', ')}`
}); });
// Read and execute config schema // Now read and execute config schema (since core tables exist)
outputProgress({ outputProgress({
operation: 'Running config setup', operation: 'Running config setup',
message: 'Creating configuration tables...' message: 'Creating configuration tables...'
@@ -400,18 +372,7 @@ async function resetDatabase() {
for (let i = 0; i < configStatements.length; i++) { for (let i = 0; i < configStatements.length; i++) {
const stmt = configStatements[i]; const stmt = configStatements[i];
try { try {
const [result, fields] = await connection.query(stmt); const result = await client.query(stmt);
// Check for warnings
const [warnings] = await connection.query('SHOW WARNINGS');
if (warnings && warnings.length > 0) {
outputProgress({
status: 'warning',
operation: 'Config SQL Warning',
statement: i + 1,
warnings: warnings
});
}
outputProgress({ outputProgress({
operation: 'Config SQL Progress', operation: 'Config SQL Progress',
@@ -419,7 +380,7 @@ async function resetDatabase() {
statement: i + 1, statement: i + 1,
total: configStatements.length, total: configStatements.length,
preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''), preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''),
affectedRows: result.affectedRows rowCount: result.rowCount
} }
}); });
} catch (sqlError) { } catch (sqlError) {
@@ -427,8 +388,6 @@ async function resetDatabase() {
status: 'error', status: 'error',
operation: 'Config SQL Error', operation: 'Config SQL Error',
error: sqlError.message, error: sqlError.message,
sqlState: sqlError.sqlState,
errno: sqlError.errno,
statement: stmt, statement: stmt,
statementNumber: i + 1 statementNumber: i + 1
}); });
@@ -436,33 +395,6 @@ async function resetDatabase() {
} }
} }
// Verify config tables were created
const [showConfigTables] = await connection.query('SHOW TABLES');
const existingConfigTables = showConfigTables.map(t => Object.values(t)[0]);
outputProgress({
operation: 'Config tables verification',
message: {
found: existingConfigTables,
expected: CONFIG_TABLES
}
});
const missingConfigTables = CONFIG_TABLES.filter(
t => !existingConfigTables.includes(t)
);
if (missingConfigTables.length > 0) {
throw new Error(
`Failed to create config tables: ${missingConfigTables.join(', ')}`
);
}
outputProgress({
operation: 'Config tables created',
message: `Successfully created tables: ${CONFIG_TABLES.join(', ')}`
});
// Read and execute metrics schema (metrics tables) // Read and execute metrics schema (metrics tables)
outputProgress({ outputProgress({
operation: 'Running metrics setup', operation: 'Running metrics setup',
@@ -489,18 +421,7 @@ async function resetDatabase() {
for (let i = 0; i < metricsStatements.length; i++) { for (let i = 0; i < metricsStatements.length; i++) {
const stmt = metricsStatements[i]; const stmt = metricsStatements[i];
try { try {
const [result, fields] = await connection.query(stmt); const result = await client.query(stmt);
// Check for warnings
const [warnings] = await connection.query('SHOW WARNINGS');
if (warnings && warnings.length > 0) {
outputProgress({
status: 'warning',
operation: 'Metrics SQL Warning',
statement: i + 1,
warnings: warnings
});
}
outputProgress({ outputProgress({
operation: 'Metrics SQL Progress', operation: 'Metrics SQL Progress',
@@ -508,7 +429,7 @@ async function resetDatabase() {
statement: i + 1, statement: i + 1,
total: metricsStatements.length, total: metricsStatements.length,
preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''), preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''),
affectedRows: result.affectedRows rowCount: result.rowCount
} }
}); });
} catch (sqlError) { } catch (sqlError) {
@@ -516,8 +437,6 @@ async function resetDatabase() {
status: 'error', status: 'error',
operation: 'Metrics SQL Error', operation: 'Metrics SQL Error',
error: sqlError.message, error: sqlError.message,
sqlState: sqlError.sqlState,
errno: sqlError.errno,
statement: stmt, statement: stmt,
statementNumber: i + 1 statementNumber: i + 1
}); });
@@ -539,9 +458,19 @@ async function resetDatabase() {
}); });
process.exit(1); process.exit(1);
} finally { } finally {
await connection.end(); await client.end();
} }
} }
// Run the reset // Export if required as a module
resetDatabase(); if (typeof module !== 'undefined' && module.exports) {
module.exports = resetDatabase;
}
// Run if called directly
if (require.main === module) {
resetDatabase().catch(error => {
console.error('Error:', error);
process.exit(1);
});
}

View File

@@ -1,4 +1,4 @@
const mysql = require('mysql2/promise'); const { Client } = require('pg');
const path = require('path'); const path = require('path');
const fs = require('fs'); const fs = require('fs');
require('dotenv').config({ path: path.resolve(__dirname, '../.env') }); require('dotenv').config({ path: path.resolve(__dirname, '../.env') });
@@ -8,7 +8,7 @@ const dbConfig = {
user: process.env.DB_USER, user: process.env.DB_USER,
password: process.env.DB_PASSWORD, password: process.env.DB_PASSWORD,
database: process.env.DB_NAME, database: process.env.DB_NAME,
multipleStatements: true port: process.env.DB_PORT || 5432
}; };
function outputProgress(data) { function outputProgress(data) {
@@ -34,8 +34,8 @@ const METRICS_TABLES = [
'sales_forecasts', 'sales_forecasts',
'temp_purchase_metrics', 'temp_purchase_metrics',
'temp_sales_metrics', 'temp_sales_metrics',
'vendor_metrics', //before vendor_details for foreign key 'vendor_metrics',
'vendor_time_metrics', //before vendor_details for foreign key 'vendor_time_metrics',
'vendor_details' 'vendor_details'
]; ];
@@ -90,31 +90,31 @@ function splitSQLStatements(sql) {
} }
async function resetMetrics() { async function resetMetrics() {
let connection; let client;
try { try {
outputProgress({ outputProgress({
operation: 'Starting metrics reset', operation: 'Starting metrics reset',
message: 'Connecting to database...' message: 'Connecting to database...'
}); });
connection = await mysql.createConnection(dbConfig); client = new Client(dbConfig);
await connection.beginTransaction(); await client.connect();
// First verify current state // First verify current state
const [initialTables] = await connection.query(` const initialTables = await client.query(`
SELECT TABLE_NAME as name SELECT tablename as name
FROM information_schema.tables FROM pg_tables
WHERE TABLE_SCHEMA = DATABASE() WHERE schemaname = 'public'
AND TABLE_NAME IN (?) AND tablename = ANY($1)
`, [METRICS_TABLES]); `, [METRICS_TABLES]);
outputProgress({ outputProgress({
operation: 'Initial state', operation: 'Initial state',
message: `Found ${initialTables.length} existing metrics tables: ${initialTables.map(t => t.name).join(', ')}` message: `Found ${initialTables.rows.length} existing metrics tables: ${initialTables.rows.map(t => t.name).join(', ')}`
}); });
// Disable foreign key checks at the start // Disable foreign key checks at the start
await connection.query('SET FOREIGN_KEY_CHECKS = 0'); await client.query('SET session_replication_role = \'replica\'');
// Drop all metrics tables in reverse order to handle dependencies // Drop all metrics tables in reverse order to handle dependencies
outputProgress({ outputProgress({
@@ -124,17 +124,17 @@ async function resetMetrics() {
for (const table of [...METRICS_TABLES].reverse()) { for (const table of [...METRICS_TABLES].reverse()) {
try { try {
await connection.query(`DROP TABLE IF EXISTS ${table}`); await client.query(`DROP TABLE IF EXISTS "${table}" CASCADE`);
// Verify the table was actually dropped // Verify the table was actually dropped
const [checkDrop] = await connection.query(` const checkDrop = await client.query(`
SELECT COUNT(*) as count SELECT COUNT(*) as count
FROM information_schema.tables FROM pg_tables
WHERE TABLE_SCHEMA = DATABASE() WHERE schemaname = 'public'
AND TABLE_NAME = ? AND tablename = $1
`, [table]); `, [table]);
if (checkDrop[0].count > 0) { if (parseInt(checkDrop.rows[0].count) > 0) {
throw new Error(`Failed to drop table ${table} - table still exists`); throw new Error(`Failed to drop table ${table} - table still exists`);
} }
@@ -153,15 +153,15 @@ async function resetMetrics() {
} }
// Verify all tables were dropped // Verify all tables were dropped
const [afterDrop] = await connection.query(` const afterDrop = await client.query(`
SELECT TABLE_NAME as name SELECT tablename as name
FROM information_schema.tables FROM pg_tables
WHERE TABLE_SCHEMA = DATABASE() WHERE schemaname = 'public'
AND TABLE_NAME IN (?) AND tablename = ANY($1)
`, [METRICS_TABLES]); `, [METRICS_TABLES]);
if (afterDrop.length > 0) { if (afterDrop.rows.length > 0) {
throw new Error(`Failed to drop all tables. Remaining tables: ${afterDrop.map(t => t.name).join(', ')}`); throw new Error(`Failed to drop all tables. Remaining tables: ${afterDrop.rows.map(t => t.name).join(', ')}`);
} }
// Read metrics schema // Read metrics schema
@@ -187,39 +187,26 @@ async function resetMetrics() {
for (let i = 0; i < statements.length; i++) { for (let i = 0; i < statements.length; i++) {
const stmt = statements[i]; const stmt = statements[i];
try { try {
await connection.query(stmt); const result = await client.query(stmt);
// Check for warnings
const [warnings] = await connection.query('SHOW WARNINGS');
if (warnings && warnings.length > 0) {
outputProgress({
status: 'warning',
operation: 'SQL Warning',
message: {
statement: i + 1,
warnings: warnings
}
});
}
// If this is a CREATE TABLE statement, verify the table was created // If this is a CREATE TABLE statement, verify the table was created
if (stmt.trim().toLowerCase().startsWith('create table')) { if (stmt.trim().toLowerCase().startsWith('create table')) {
const tableName = stmt.match(/create\s+table\s+(?:if\s+not\s+exists\s+)?`?(\w+)`?/i)?.[1]; const tableName = stmt.match(/create\s+table\s+(?:if\s+not\s+exists\s+)?["]?(\w+)["]?/i)?.[1];
if (tableName) { if (tableName) {
const [checkCreate] = await connection.query(` const checkCreate = await client.query(`
SELECT TABLE_NAME as name, CREATE_TIME as created SELECT tablename as name
FROM information_schema.tables FROM pg_tables
WHERE TABLE_SCHEMA = DATABASE() WHERE schemaname = 'public'
AND TABLE_NAME = ? AND tablename = $1
`, [tableName]); `, [tableName]);
if (checkCreate.length === 0) { if (checkCreate.rows.length === 0) {
throw new Error(`Failed to create table ${tableName} - table does not exist after CREATE statement`); throw new Error(`Failed to create table ${tableName} - table does not exist after CREATE statement`);
} }
outputProgress({ outputProgress({
operation: 'Table created', operation: 'Table created',
message: `Successfully created table: ${tableName} at ${checkCreate[0].created}` message: `Successfully created table: ${tableName}`
}); });
} }
} }
@@ -229,7 +216,8 @@ async function resetMetrics() {
message: { message: {
statement: i + 1, statement: i + 1,
total: statements.length, total: statements.length,
preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : '') preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''),
rowCount: result.rowCount
} }
}); });
} catch (sqlError) { } catch (sqlError) {
@@ -238,8 +226,6 @@ async function resetMetrics() {
operation: 'SQL Error', operation: 'SQL Error',
message: { message: {
error: sqlError.message, error: sqlError.message,
sqlState: sqlError.sqlState,
errno: sqlError.errno,
statement: stmt, statement: stmt,
statementNumber: i + 1 statementNumber: i + 1
} }
@@ -249,7 +235,7 @@ async function resetMetrics() {
} }
// Re-enable foreign key checks after all tables are created // Re-enable foreign key checks after all tables are created
await connection.query('SET FOREIGN_KEY_CHECKS = 1'); await client.query('SET session_replication_role = \'origin\'');
// Verify metrics tables were created // Verify metrics tables were created
outputProgress({ outputProgress({
@@ -257,37 +243,36 @@ async function resetMetrics() {
message: 'Checking all metrics tables were created...' message: 'Checking all metrics tables were created...'
}); });
const [metricsTablesResult] = await connection.query(` const metricsTablesResult = await client.query(`
SELECT SELECT tablename as name
TABLE_NAME as name, FROM pg_tables
TABLE_ROWS as \`rows\`, WHERE schemaname = 'public'
CREATE_TIME as created AND tablename = ANY($1)
FROM information_schema.tables
WHERE TABLE_SCHEMA = DATABASE()
AND TABLE_NAME IN (?)
`, [METRICS_TABLES]); `, [METRICS_TABLES]);
outputProgress({ outputProgress({
operation: 'Tables found', operation: 'Tables found',
message: `Found ${metricsTablesResult.length} tables: ${metricsTablesResult.map(t => message: `Found ${metricsTablesResult.rows.length} tables: ${metricsTablesResult.rows.map(t => t.name).join(', ')}`
`${t.name} (created: ${t.created})`
).join(', ')}`
}); });
const existingMetricsTables = metricsTablesResult.map(t => t.name); const existingMetricsTables = metricsTablesResult.rows.map(t => t.name);
const missingMetricsTables = METRICS_TABLES.filter(t => !existingMetricsTables.includes(t)); const missingMetricsTables = METRICS_TABLES.filter(t => !existingMetricsTables.includes(t));
if (missingMetricsTables.length > 0) { if (missingMetricsTables.length > 0) {
// Do one final check of the actual tables // Do one final check of the actual tables
const [finalCheck] = await connection.query('SHOW TABLES'); const finalCheck = await client.query(`
SELECT tablename as name
FROM pg_tables
WHERE schemaname = 'public'
`);
outputProgress({ outputProgress({
operation: 'Final table check', operation: 'Final table check',
message: `All database tables: ${finalCheck.map(t => Object.values(t)[0]).join(', ')}` message: `All database tables: ${finalCheck.rows.map(t => t.name).join(', ')}`
}); });
throw new Error(`Failed to create metrics tables: ${missingMetricsTables.join(', ')}`); throw new Error(`Failed to create metrics tables: ${missingMetricsTables.join(', ')}`);
} }
await connection.commit(); await client.query('COMMIT');
outputProgress({ outputProgress({
status: 'complete', status: 'complete',
@@ -302,17 +287,17 @@ async function resetMetrics() {
stack: error.stack stack: error.stack
}); });
if (connection) { if (client) {
await connection.rollback(); await client.query('ROLLBACK');
// Make sure to re-enable foreign key checks even if there's an error // Make sure to re-enable foreign key checks even if there's an error
await connection.query('SET FOREIGN_KEY_CHECKS = 1').catch(() => {}); await client.query('SET session_replication_role = \'origin\'').catch(() => {});
} }
throw error; throw error;
} finally { } finally {
if (connection) { if (client) {
// One final attempt to ensure foreign key checks are enabled // One final attempt to ensure foreign key checks are enabled
await connection.query('SET FOREIGN_KEY_CHECKS = 1').catch(() => {}); await client.query('SET session_replication_role = \'origin\'').catch(() => {});
await connection.end(); await client.end();
} }
} }
} }

View File

@@ -2,6 +2,7 @@ const express = require('express');
const router = express.Router(); const router = express.Router();
const { spawn } = require('child_process'); const { spawn } = require('child_process');
const path = require('path'); const path = require('path');
const db = require('../utils/db');
// Debug middleware MUST be first // Debug middleware MUST be first
router.use((req, res, next) => { router.use((req, res, next) => {
@@ -9,9 +10,11 @@ router.use((req, res, next) => {
next(); next();
}); });
// Store active import process and its progress // Store active processes and their progress
let activeImport = null; let activeImport = null;
let importProgress = null; let importProgress = null;
let activeFullUpdate = null;
let activeFullReset = null;
// SSE clients for progress updates // SSE clients for progress updates
const updateClients = new Set(); const updateClients = new Set();
@@ -19,17 +22,16 @@ const importClients = new Set();
const resetClients = new Set(); const resetClients = new Set();
const resetMetricsClients = new Set(); const resetMetricsClients = new Set();
const calculateMetricsClients = new Set(); const calculateMetricsClients = new Set();
const fullUpdateClients = new Set();
const fullResetClients = new Set();
// Helper to send progress to specific clients // Helper to send progress to specific clients
function sendProgressToClients(clients, progress) { function sendProgressToClients(clients, data) {
const data = typeof progress === 'string' ? { progress } : progress; // If data is a string, send it directly
// If it's an object, convert it to JSON
// Ensure we have a status field const message = typeof data === 'string'
if (!data.status) { ? `data: ${data}\n\n`
data.status = 'running'; : `data: ${JSON.stringify(data)}\n\n`;
}
const message = `data: ${JSON.stringify(data)}\n\n`;
clients.forEach(client => { clients.forEach(client => {
try { try {
@@ -45,115 +47,149 @@ function sendProgressToClients(clients, progress) {
}); });
} }
// Helper to run a script and stream progress
function runScript(scriptPath, type, clients) {
return new Promise((resolve, reject) => {
// Kill any existing process of this type
let activeProcess;
switch (type) {
case 'update':
if (activeFullUpdate) {
try { activeFullUpdate.kill(); } catch (e) { }
}
activeProcess = activeFullUpdate;
break;
case 'reset':
if (activeFullReset) {
try { activeFullReset.kill(); } catch (e) { }
}
activeProcess = activeFullReset;
break;
}
const child = spawn('node', [scriptPath], {
stdio: ['inherit', 'pipe', 'pipe']
});
switch (type) {
case 'update':
activeFullUpdate = child;
break;
case 'reset':
activeFullReset = child;
break;
}
let output = '';
child.stdout.on('data', (data) => {
const text = data.toString();
output += text;
// Split by lines to handle multiple JSON outputs
const lines = text.split('\n');
lines.filter(line => line.trim()).forEach(line => {
try {
// Try to parse as JSON but don't let it affect the display
const jsonData = JSON.parse(line);
// Only end the process if we get a final status
if (jsonData.status === 'complete' || jsonData.status === 'error' || jsonData.status === 'cancelled') {
if (jsonData.status === 'complete' && !jsonData.operation?.includes('complete')) {
// Don't close for intermediate completion messages
sendProgressToClients(clients, line);
return;
}
// Close only on final completion/error/cancellation
switch (type) {
case 'update':
activeFullUpdate = null;
break;
case 'reset':
activeFullReset = null;
break;
}
if (jsonData.status === 'error') {
reject(new Error(jsonData.error || 'Unknown error'));
} else {
resolve({ output });
}
}
} catch (e) {
// Not JSON, just display as is
}
// Always send the raw line
sendProgressToClients(clients, line);
});
});
child.stderr.on('data', (data) => {
const text = data.toString();
console.error(text);
// Send stderr output directly too
sendProgressToClients(clients, text);
});
child.on('close', (code) => {
switch (type) {
case 'update':
activeFullUpdate = null;
break;
case 'reset':
activeFullReset = null;
break;
}
if (code !== 0) {
const error = `Script ${scriptPath} exited with code ${code}`;
sendProgressToClients(clients, error);
reject(new Error(error));
}
// Don't resolve here - let the completion message from the script trigger the resolve
});
child.on('error', (err) => {
switch (type) {
case 'update':
activeFullUpdate = null;
break;
case 'reset':
activeFullReset = null;
break;
}
sendProgressToClients(clients, err.message);
reject(err);
});
});
}
// Progress endpoints // Progress endpoints
router.get('/update/progress', (req, res) => { router.get('/:type/progress', (req, res) => {
res.writeHead(200, { const { type } = req.params;
'Content-Type': 'text/event-stream', if (!['update', 'reset'].includes(type)) {
'Cache-Control': 'no-cache', return res.status(400).json({ error: 'Invalid operation type' });
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Send an initial message to test the connection
res.write('data: {"status":"running","operation":"Initializing connection..."}\n\n');
// Add this client to the update set
updateClients.add(res);
// Remove client when connection closes
req.on('close', () => {
updateClients.delete(res);
});
});
router.get('/import/progress', (req, res) => {
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Send an initial message to test the connection
res.write('data: {"status":"running","operation":"Initializing connection..."}\n\n');
// Add this client to the import set
importClients.add(res);
// Remove client when connection closes
req.on('close', () => {
importClients.delete(res);
});
});
router.get('/reset/progress', (req, res) => {
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Send an initial message to test the connection
res.write('data: {"status":"running","operation":"Initializing connection..."}\n\n');
// Add this client to the reset set
resetClients.add(res);
// Remove client when connection closes
req.on('close', () => {
resetClients.delete(res);
});
});
// Add reset-metrics progress endpoint
router.get('/reset-metrics/progress', (req, res) => {
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Send an initial message to test the connection
res.write('data: {"status":"running","operation":"Initializing connection..."}\n\n');
// Add this client to the reset-metrics set
resetMetricsClients.add(res);
// Remove client when connection closes
req.on('close', () => {
resetMetricsClients.delete(res);
});
});
// Add calculate-metrics progress endpoint
router.get('/calculate-metrics/progress', (req, res) => {
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Send current progress if it exists
if (importProgress) {
res.write(`data: ${JSON.stringify(importProgress)}\n\n`);
} else {
res.write('data: {"status":"running","operation":"Initializing connection..."}\n\n');
} }
// Add this client to the calculate-metrics set res.writeHead(200, {
calculateMetricsClients.add(res); 'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Access-Control-Allow-Origin': req.headers.origin || '*',
'Access-Control-Allow-Credentials': 'true'
});
// Remove client when connection closes // Add this client to the correct set
const clients = type === 'update' ? fullUpdateClients : fullResetClients;
clients.add(res);
// Send initial connection message
sendProgressToClients(new Set([res]), JSON.stringify({
status: 'running',
operation: 'Initializing connection...'
}));
// Handle client disconnect
req.on('close', () => { req.on('close', () => {
calculateMetricsClients.delete(res); clients.delete(res);
}); });
}); });
@@ -174,7 +210,6 @@ router.get('/status', (req, res) => {
// Add calculate-metrics status endpoint // Add calculate-metrics status endpoint
router.get('/calculate-metrics/status', (req, res) => { router.get('/calculate-metrics/status', (req, res) => {
console.log('Calculate metrics status endpoint hit');
const calculateMetrics = require('../../scripts/calculate-metrics'); const calculateMetrics = require('../../scripts/calculate-metrics');
const progress = calculateMetrics.getProgress(); const progress = calculateMetrics.getProgress();
@@ -371,49 +406,35 @@ router.post('/import', async (req, res) => {
// Route to cancel active process // Route to cancel active process
router.post('/cancel', (req, res) => { router.post('/cancel', (req, res) => {
if (!activeImport) { let killed = false;
return res.status(404).json({ error: 'No active process to cancel' });
// Get the operation type from the request
const { type } = req.query;
const clients = type === 'update' ? fullUpdateClients : fullResetClients;
const activeProcess = type === 'update' ? activeFullUpdate : activeFullReset;
if (activeProcess) {
try {
activeProcess.kill('SIGTERM');
if (type === 'update') {
activeFullUpdate = null;
} else {
activeFullReset = null;
}
killed = true;
sendProgressToClients(clients, JSON.stringify({
status: 'cancelled',
operation: 'Operation cancelled'
}));
} catch (err) {
console.error(`Error killing ${type} process:`, err);
}
} }
try { if (killed) {
// If it's the prod import module, call its cancel function
if (typeof activeImport.cancelImport === 'function') {
activeImport.cancelImport();
} else {
// Otherwise it's a child process
activeImport.kill('SIGTERM');
}
// Get the operation type from the request
const { operation } = req.query;
// Send cancel message only to the appropriate client set
const cancelMessage = {
status: 'cancelled',
operation: 'Operation cancelled'
};
switch (operation) {
case 'update':
sendProgressToClients(updateClients, cancelMessage);
break;
case 'import':
sendProgressToClients(importClients, cancelMessage);
break;
case 'reset':
sendProgressToClients(resetClients, cancelMessage);
break;
case 'calculate-metrics':
sendProgressToClients(calculateMetricsClients, cancelMessage);
break;
}
res.json({ success: true }); res.json({ success: true });
} catch (error) { } else {
// Even if there's an error, try to clean up res.status(404).json({ error: 'No active process to cancel' });
activeImport = null;
importProgress = null;
res.status(500).json({ error: 'Failed to cancel process' });
} }
}); });
@@ -552,20 +573,6 @@ router.post('/reset-metrics', async (req, res) => {
} }
}); });
// Add calculate-metrics status endpoint
router.get('/calculate-metrics/status', (req, res) => {
const calculateMetrics = require('../../scripts/calculate-metrics');
const progress = calculateMetrics.getProgress();
// Only consider it active if both the process is running and we have progress
const isActive = !!activeImport && !!progress;
res.json({
active: isActive,
progress: isActive ? progress : null
});
});
// Add calculate-metrics endpoint // Add calculate-metrics endpoint
router.post('/calculate-metrics', async (req, res) => { router.post('/calculate-metrics', async (req, res) => {
if (activeImport) { if (activeImport) {
@@ -711,4 +718,96 @@ router.post('/import-from-prod', async (req, res) => {
} }
}); });
// POST /csv/full-update - Run full update script
router.post('/full-update', async (req, res) => {
try {
const scriptPath = path.join(__dirname, '../../scripts/full-update.js');
runScript(scriptPath, 'update', fullUpdateClients)
.catch(error => {
console.error('Update failed:', error);
});
res.status(202).json({ message: 'Update started' });
} catch (error) {
res.status(500).json({ error: error.message });
}
});
// POST /csv/full-reset - Run full reset script
router.post('/full-reset', async (req, res) => {
try {
const scriptPath = path.join(__dirname, '../../scripts/full-reset.js');
runScript(scriptPath, 'reset', fullResetClients)
.catch(error => {
console.error('Reset failed:', error);
});
res.status(202).json({ message: 'Reset started' });
} catch (error) {
res.status(500).json({ error: error.message });
}
});
// GET /history/import - Get recent import history
router.get('/history/import', async (req, res) => {
try {
const pool = req.app.locals.pool;
const [rows] = await pool.query(`
SELECT * FROM import_history
ORDER BY start_time DESC
LIMIT 20
`);
res.json(rows || []);
} catch (error) {
console.error('Error fetching import history:', error);
res.status(500).json({ error: error.message });
}
});
// GET /history/calculate - Get recent calculation history
router.get('/history/calculate', async (req, res) => {
try {
const pool = req.app.locals.pool;
const [rows] = await pool.query(`
SELECT * FROM calculate_history
ORDER BY start_time DESC
LIMIT 20
`);
res.json(rows || []);
} catch (error) {
console.error('Error fetching calculate history:', error);
res.status(500).json({ error: error.message });
}
});
// GET /status/modules - Get module calculation status
router.get('/status/modules', async (req, res) => {
try {
const pool = req.app.locals.pool;
const [rows] = await pool.query(`
SELECT module_name, last_calculation_timestamp
FROM calculate_status
ORDER BY module_name
`);
res.json(rows || []);
} catch (error) {
console.error('Error fetching module status:', error);
res.status(500).json({ error: error.message });
}
});
// GET /status/tables - Get table sync status
router.get('/status/tables', async (req, res) => {
try {
const pool = req.app.locals.pool;
const [rows] = await pool.query(`
SELECT table_name, last_sync_timestamp
FROM sync_status
ORDER BY table_name
`);
res.json(rows || []);
} catch (error) {
console.error('Error fetching table status:', error);
res.status(500).json({ error: error.message });
}
});
module.exports = router; module.exports = router;

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View File

@@ -133,6 +133,10 @@ export function PerformanceMetrics() {
} }
}; };
function getCategoryName(_cat_id: number): import("react").ReactNode {
throw new Error('Function not implemented.');
}
return ( return (
<div className="max-w-[700px] space-y-4"> <div className="max-w-[700px] space-y-4">
{/* Lead Time Thresholds Card */} {/* Lead Time Thresholds Card */}
@@ -205,11 +209,11 @@ export function PerformanceMetrics() {
<Table> <Table>
<TableHeader> <TableHeader>
<TableRow> <TableRow>
<TableHead>Category</TableHead> <TableCell>Category</TableCell>
<TableHead>Vendor</TableHead> <TableCell>Vendor</TableCell>
<TableHead className="text-right">A Threshold</TableHead> <TableCell className="text-right">A Threshold</TableCell>
<TableHead className="text-right">B Threshold</TableHead> <TableCell className="text-right">B Threshold</TableCell>
<TableHead className="text-right">Period Days</TableHead> <TableCell className="text-right">Period Days</TableCell>
</TableRow> </TableRow>
</TableHeader> </TableHeader>
<TableBody> <TableBody>
@@ -242,10 +246,10 @@ export function PerformanceMetrics() {
<Table> <Table>
<TableHeader> <TableHeader>
<TableRow> <TableRow>
<TableHead>Category</TableHead> <TableCell>Category</TableCell>
<TableHead>Vendor</TableHead> <TableCell>Vendor</TableCell>
<TableHead className="text-right">Period Days</TableHead> <TableCell className="text-right">Period Days</TableCell>
<TableHead className="text-right">Target Rate</TableHead> <TableCell className="text-right">Target Rate</TableCell>
</TableRow> </TableRow>
</TableHeader> </TableHeader>
<TableBody> <TableBody>

View File

@@ -5,7 +5,6 @@ import { Input } from "@/components/ui/input";
import { Label } from "@/components/ui/label"; import { Label } from "@/components/ui/label";
import { toast } from "sonner"; import { toast } from "sonner";
import config from '../../config'; import config from '../../config';
import { Table, TableBody, TableCell, TableHeader, TableRow } from "@/components/ui/table";
interface StockThreshold { interface StockThreshold {
id: number; id: number;
@@ -244,54 +243,6 @@ export function StockManagement() {
</div> </div>
</CardContent> </CardContent>
</Card> </Card>
<Table>
<TableHeader>
<TableRow>
<TableHead>Category</TableHead>
<TableHead>Vendor</TableHead>
<TableHead className="text-right">Critical Days</TableHead>
<TableHead className="text-right">Reorder Days</TableHead>
<TableHead className="text-right">Overstock Days</TableHead>
<TableHead className="text-right">Low Stock</TableHead>
<TableHead className="text-right">Min Reorder</TableHead>
</TableRow>
</TableHeader>
<TableBody>
{stockThresholds.map((threshold) => (
<TableRow key={`${threshold.cat_id}-${threshold.vendor}`}>
<TableCell>{threshold.cat_id ? getCategoryName(threshold.cat_id) : 'Global'}</TableCell>
<TableCell>{threshold.vendor || 'All Vendors'}</TableCell>
<TableCell className="text-right">{threshold.critical_days}</TableCell>
<TableCell className="text-right">{threshold.reorder_days}</TableCell>
<TableCell className="text-right">{threshold.overstock_days}</TableCell>
<TableCell className="text-right">{threshold.low_stock_threshold}</TableCell>
<TableCell className="text-right">{threshold.min_reorder_quantity}</TableCell>
</TableRow>
))}
</TableBody>
</Table>
<Table>
<TableHeader>
<TableRow>
<TableHead>Category</TableHead>
<TableHead>Vendor</TableHead>
<TableHead className="text-right">Coverage Days</TableHead>
<TableHead className="text-right">Service Level</TableHead>
</TableRow>
</TableHeader>
<TableBody>
{safetyStockConfigs.map((config) => (
<TableRow key={`${config.cat_id}-${config.vendor}`}>
<TableCell>{config.cat_id ? getCategoryName(config.cat_id) : 'Global'}</TableCell>
<TableCell>{config.vendor || 'All Vendors'}</TableCell>
<TableCell className="text-right">{config.coverage_days}</TableCell>
<TableCell className="text-right">{config.service_level}%</TableCell>
</TableRow>
))}
</TableBody>
</Table>
</div> </div>
); );
} }

View File

@@ -1,7 +1,7 @@
#!/bin/zsh #!/bin/zsh
#Clear previous mount in case its still there #Clear previous mount in case its still there
umount ~/Dev/inventory/inventory-server umount /Users/matt/Library/Mobile Documents/com~apple~CloudDocs/Dev/inventory/inventory-server
#Mount #Mount
sshfs matt@dashboard.kent.pw:/var/www/html/inventory -p 22122 ~/Dev/inventory/inventory-server/ sshfs matt@dashboard.kent.pw:/var/www/html/inventory -p 22122 /Users/matt/Library/Mobile Documents/com~apple~CloudDocs/Dev/inventory/inventory-server/