Optimize metrics import and split off metrics import functions (untested)
This commit is contained in:
@@ -30,10 +30,31 @@ CREATE TABLE IF NOT EXISTS products (
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INDEX idx_brand (brand)
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);
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-- Temporary tables for batch metrics processing
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CREATE TABLE IF NOT EXISTS temp_sales_metrics (
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product_id BIGINT NOT NULL,
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daily_sales_avg DECIMAL(10,3),
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weekly_sales_avg DECIMAL(10,3),
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monthly_sales_avg DECIMAL(10,3),
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total_revenue DECIMAL(10,3),
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avg_margin_percent DECIMAL(10,3),
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first_sale_date DATE,
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last_sale_date DATE,
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PRIMARY KEY (product_id)
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);
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CREATE TABLE IF NOT EXISTS temp_purchase_metrics (
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product_id BIGINT NOT NULL,
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avg_lead_time_days INT,
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last_purchase_date DATE,
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last_received_date DATE,
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PRIMARY KEY (product_id)
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);
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-- New table for product metrics
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CREATE TABLE IF NOT EXISTS product_metrics (
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product_id BIGINT NOT NULL,
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last_calculated_at TIMESTAMP NOT NULL,
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last_calculated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
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-- Sales velocity metrics
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daily_sales_avg DECIMAL(10,3),
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weekly_sales_avg DECIMAL(10,3),
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@@ -57,6 +78,10 @@ CREATE TABLE IF NOT EXISTS product_metrics (
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FOREIGN KEY (product_id) REFERENCES products(product_id) ON DELETE CASCADE
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);
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-- Optimized indexes for metrics calculations
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CREATE INDEX idx_orders_metrics ON orders (product_id, date, canceled, quantity, price);
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CREATE INDEX idx_purchase_orders_metrics ON purchase_orders (product_id, date, status, ordered, received);
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-- New table for time-based aggregates
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CREATE TABLE IF NOT EXISTS product_time_aggregates (
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product_id BIGINT NOT NULL,
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359
inventory-server/scripts/calculate-metrics.js
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359
inventory-server/scripts/calculate-metrics.js
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@@ -0,0 +1,359 @@
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const mysql = require('mysql2/promise');
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const path = require('path');
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require('dotenv').config({ path: path.resolve(__dirname, '..', '.env') });
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// Helper function to output progress
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function outputProgress(data) {
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console.log(JSON.stringify(data));
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}
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// Helper function to log errors
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function logError(error, context) {
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console.error(JSON.stringify({
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status: 'error',
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error: error.message || error,
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context
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}));
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}
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// Database configuration
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const dbConfig = {
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host: process.env.DB_HOST,
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user: process.env.DB_USER,
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password: process.env.DB_PASSWORD,
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database: process.env.DB_NAME,
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waitForConnections: true,
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connectionLimit: 10,
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queueLimit: 0
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};
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async function calculateMetrics() {
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let pool;
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try {
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pool = mysql.createPool(dbConfig);
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const connection = await pool.getConnection();
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try {
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// Create temporary tables for metrics calculations
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outputProgress({
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status: 'running',
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operation: 'Creating temporary tables',
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percentage: '0'
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});
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await connection.query(`
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CREATE TABLE IF NOT EXISTS temp_sales_metrics (
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product_id INT PRIMARY KEY,
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total_quantity_sold INT DEFAULT 0,
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total_revenue DECIMAL(10,2) DEFAULT 0.00,
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average_price DECIMAL(10,2) DEFAULT 0.00,
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last_sale_date DATE,
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sales_rank INT
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);
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CREATE TABLE IF NOT EXISTS temp_purchase_metrics (
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product_id INT PRIMARY KEY,
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total_quantity_purchased INT DEFAULT 0,
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total_cost DECIMAL(10,2) DEFAULT 0.00,
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average_cost DECIMAL(10,2) DEFAULT 0.00,
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last_purchase_date DATE,
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purchase_rank INT
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);
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TRUNCATE TABLE temp_sales_metrics;
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TRUNCATE TABLE temp_purchase_metrics;
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`);
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// Calculate sales metrics
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outputProgress({
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status: 'running',
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operation: 'Calculating sales metrics',
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percentage: '20'
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});
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await connection.query(`
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INSERT INTO temp_sales_metrics (
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product_id,
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total_quantity_sold,
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total_revenue,
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average_price,
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last_sale_date
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)
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SELECT
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product_id,
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SUM(quantity) as total_quantity_sold,
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SUM((price - COALESCE(discount, 0)) * quantity) as total_revenue,
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AVG(price - COALESCE(discount, 0)) as average_price,
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MAX(date) as last_sale_date
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FROM orders
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WHERE canceled = 0
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GROUP BY product_id;
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UPDATE temp_sales_metrics
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SET sales_rank = (
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SELECT rank
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FROM (
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SELECT
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product_id,
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RANK() OVER (ORDER BY total_revenue DESC) as rank
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FROM temp_sales_metrics
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) rankings
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WHERE rankings.product_id = temp_sales_metrics.product_id
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);
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`);
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// Calculate purchase metrics
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outputProgress({
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status: 'running',
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operation: 'Calculating purchase metrics',
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percentage: '40'
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});
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await connection.query(`
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INSERT INTO temp_purchase_metrics (
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product_id,
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total_quantity_purchased,
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total_cost,
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average_cost,
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last_purchase_date
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)
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SELECT
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product_id,
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SUM(received) as total_quantity_purchased,
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SUM(cost_price * received) as total_cost,
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AVG(cost_price) as average_cost,
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MAX(received_date) as last_purchase_date
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FROM purchase_orders
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WHERE status = 'closed' AND received > 0
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GROUP BY product_id;
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UPDATE temp_purchase_metrics
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SET purchase_rank = (
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SELECT rank
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FROM (
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SELECT
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product_id,
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RANK() OVER (ORDER BY total_cost DESC) as rank
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FROM temp_purchase_metrics
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) rankings
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WHERE rankings.product_id = temp_purchase_metrics.product_id
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);
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`);
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// Update product metrics
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outputProgress({
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status: 'running',
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operation: 'Updating product metrics',
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percentage: '60'
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});
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await connection.query(`
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INSERT INTO product_metrics (
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product_id,
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total_quantity_sold,
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total_revenue,
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average_price,
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total_quantity_purchased,
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total_cost,
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average_cost,
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profit_margin,
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turnover_rate,
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last_sale_date,
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last_purchase_date,
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sales_rank,
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purchase_rank,
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last_calculated_at
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)
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SELECT
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p.product_id,
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COALESCE(s.total_quantity_sold, 0),
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COALESCE(s.total_revenue, 0.00),
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COALESCE(s.average_price, 0.00),
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COALESCE(po.total_quantity_purchased, 0),
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COALESCE(po.total_cost, 0.00),
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COALESCE(po.average_cost, 0.00),
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CASE
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WHEN COALESCE(s.total_revenue, 0) = 0 THEN 0
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ELSE ((s.total_revenue - po.total_cost) / s.total_revenue) * 100
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END as profit_margin,
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CASE
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WHEN COALESCE(po.total_quantity_purchased, 0) = 0 THEN 0
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ELSE (s.total_quantity_sold / po.total_quantity_purchased) * 100
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END as turnover_rate,
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s.last_sale_date,
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po.last_purchase_date,
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s.sales_rank,
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po.purchase_rank,
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NOW()
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FROM products p
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LEFT JOIN temp_sales_metrics s ON p.product_id = s.product_id
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LEFT JOIN temp_purchase_metrics po ON p.product_id = po.product_id
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ON DUPLICATE KEY UPDATE
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total_quantity_sold = VALUES(total_quantity_sold),
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total_revenue = VALUES(total_revenue),
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average_price = VALUES(average_price),
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total_quantity_purchased = VALUES(total_quantity_purchased),
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total_cost = VALUES(total_cost),
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average_cost = VALUES(average_cost),
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profit_margin = VALUES(profit_margin),
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turnover_rate = VALUES(turnover_rate),
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last_sale_date = VALUES(last_sale_date),
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last_purchase_date = VALUES(last_purchase_date),
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sales_rank = VALUES(sales_rank),
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purchase_rank = VALUES(purchase_rank),
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last_calculated_at = VALUES(last_calculated_at);
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`);
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// Calculate ABC classification
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outputProgress({
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status: 'running',
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operation: 'Calculating ABC classification',
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percentage: '80'
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});
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await connection.query(`
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WITH revenue_percentiles AS (
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SELECT
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product_id,
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total_revenue,
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PERCENT_RANK() OVER (ORDER BY total_revenue DESC) as revenue_percentile
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FROM product_metrics
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WHERE total_revenue > 0
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)
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UPDATE product_metrics pm
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JOIN revenue_percentiles rp ON pm.product_id = rp.product_id
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SET pm.abc_class =
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CASE
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WHEN rp.revenue_percentile < 0.2 THEN 'A'
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WHEN rp.revenue_percentile < 0.5 THEN 'B'
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ELSE 'C'
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END;
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`);
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// Calculate time-based aggregates
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outputProgress({
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status: 'running',
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operation: 'Calculating time aggregates',
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percentage: '90'
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});
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await connection.query(`
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TRUNCATE TABLE product_time_aggregates;
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-- Daily aggregates
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INSERT INTO product_time_aggregates (product_id, period_type, period_start, quantity_sold, revenue)
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SELECT
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product_id,
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'daily' as period_type,
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DATE(date) as period_start,
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SUM(quantity) as quantity_sold,
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SUM((price - COALESCE(discount, 0)) * quantity) as revenue
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FROM orders
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WHERE canceled = 0
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GROUP BY product_id, DATE(date);
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-- Weekly aggregates
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INSERT INTO product_time_aggregates (product_id, period_type, period_start, quantity_sold, revenue)
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SELECT
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product_id,
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'weekly' as period_type,
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DATE(DATE_SUB(date, INTERVAL WEEKDAY(date) DAY)) as period_start,
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SUM(quantity) as quantity_sold,
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SUM((price - COALESCE(discount, 0)) * quantity) as revenue
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FROM orders
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WHERE canceled = 0
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GROUP BY product_id, DATE(DATE_SUB(date, INTERVAL WEEKDAY(date) DAY));
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-- Monthly aggregates
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INSERT INTO product_time_aggregates (product_id, period_type, period_start, quantity_sold, revenue)
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SELECT
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product_id,
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'monthly' as period_type,
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DATE(DATE_SUB(date, INTERVAL DAY(date)-1 DAY)) as period_start,
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SUM(quantity) as quantity_sold,
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SUM((price - COALESCE(discount, 0)) * quantity) as revenue
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FROM orders
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WHERE canceled = 0
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GROUP BY product_id, DATE(DATE_SUB(date, INTERVAL DAY(date)-1 DAY));
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`);
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// Calculate vendor metrics
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outputProgress({
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status: 'running',
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operation: 'Calculating vendor metrics',
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percentage: '95'
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});
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await connection.query(`
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INSERT INTO vendor_metrics (
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vendor,
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total_orders,
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total_items_ordered,
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total_items_received,
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total_spend,
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average_order_value,
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fulfillment_rate,
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average_delivery_days,
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last_order_date,
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last_delivery_date
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)
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SELECT
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vendor,
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COUNT(DISTINCT po_id) as total_orders,
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SUM(ordered) as total_items_ordered,
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SUM(received) as total_items_received,
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SUM(cost_price * received) as total_spend,
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AVG(cost_price * ordered) as average_order_value,
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(SUM(received) / NULLIF(SUM(ordered), 0)) * 100 as fulfillment_rate,
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AVG(DATEDIFF(received_date, date)) as average_delivery_days,
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MAX(date) as last_order_date,
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MAX(received_date) as last_delivery_date
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FROM purchase_orders
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WHERE status = 'closed'
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GROUP BY vendor
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ON DUPLICATE KEY UPDATE
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total_orders = VALUES(total_orders),
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total_items_ordered = VALUES(total_items_ordered),
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total_items_received = VALUES(total_items_received),
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total_spend = VALUES(total_spend),
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average_order_value = VALUES(average_order_value),
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fulfillment_rate = VALUES(fulfillment_rate),
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average_delivery_days = VALUES(average_delivery_days),
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last_order_date = VALUES(last_order_date),
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last_delivery_date = VALUES(last_delivery_date);
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`);
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outputProgress({
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status: 'complete',
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operation: 'Metrics calculation completed',
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percentage: '100'
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});
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} catch (error) {
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logError(error, 'Error calculating metrics');
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throw error;
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} finally {
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connection.release();
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}
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} catch (error) {
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logError(error, 'Fatal error during metrics calculation');
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throw error;
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} finally {
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if (pool) {
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await pool.end();
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}
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}
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}
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// Export the function if being required as a module
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if (typeof module !== 'undefined' && module.exports) {
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module.exports = calculateMetrics;
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}
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// Run directly if called from command line
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if (require.main === module) {
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calculateMetrics().catch(error => {
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console.error('Error:', error);
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process.exit(1);
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});
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}
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@@ -401,38 +401,75 @@ async function calculateVendorMetrics(connection) {
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}
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}
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// Helper function to update product metrics
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async function updateProductMetrics(connection, productId, startTime, current, total) {
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// Helper function to calculate metrics in batches
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async function calculateMetricsInBatch(connection) {
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try {
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// Calculate sales velocity metrics
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const velocityMetrics = await calculateSalesVelocity(connection, productId);
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// Calculate stock metrics
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const stockMetrics = await calculateStockMetrics(connection, productId, velocityMetrics.daily_sales_avg);
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// Calculate financial metrics
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const financialMetrics = await calculateFinancialMetrics(connection, productId);
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// Calculate purchase metrics
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const purchaseMetrics = await calculatePurchaseMetrics(connection, productId);
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// Update metrics in database
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// Clear temporary tables
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await connection.query('TRUNCATE TABLE temp_sales_metrics');
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await connection.query('TRUNCATE TABLE temp_purchase_metrics');
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// Calculate sales metrics for all products in one go
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await connection.query(`
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INSERT INTO temp_sales_metrics
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SELECT
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o.product_id,
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COUNT(*) / NULLIF(DATEDIFF(MAX(o.date), MIN(o.date)), 0) as daily_sales_avg,
|
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SUM(o.quantity) / NULLIF(DATEDIFF(MAX(o.date), MIN(o.date)), 0) * 7 as weekly_sales_avg,
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SUM(o.quantity) / NULLIF(DATEDIFF(MAX(o.date), MIN(o.date)), 0) * 30 as monthly_sales_avg,
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SUM(o.price * o.quantity) as total_revenue,
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AVG((o.price - p.cost_price) / o.price * 100) as avg_margin_percent,
|
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MIN(o.date) as first_sale_date,
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MAX(o.date) as last_sale_date
|
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FROM orders o
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JOIN products p ON o.product_id = p.product_id
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WHERE o.canceled = false
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GROUP BY o.product_id
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`);
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// Calculate purchase metrics for all products in one go
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await connection.query(`
|
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INSERT INTO temp_purchase_metrics
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SELECT
|
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product_id,
|
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AVG(DATEDIFF(received_date, date)) as avg_lead_time_days,
|
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MAX(date) as last_purchase_date,
|
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MAX(received_date) as last_received_date
|
||||
FROM purchase_orders
|
||||
WHERE status = 'closed'
|
||||
GROUP BY product_id
|
||||
`);
|
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|
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// Update product_metrics table with all metrics at once
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await connection.query(`
|
||||
INSERT INTO product_metrics (
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||||
product_id,
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daily_sales_avg,
|
||||
weekly_sales_avg,
|
||||
monthly_sales_avg,
|
||||
days_of_inventory,
|
||||
weeks_of_inventory,
|
||||
safety_stock,
|
||||
reorder_point,
|
||||
total_revenue,
|
||||
avg_margin_percent,
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||||
avg_lead_time_days,
|
||||
last_purchase_date,
|
||||
last_received_date
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
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product_id, daily_sales_avg, weekly_sales_avg, monthly_sales_avg,
|
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days_of_inventory, weeks_of_inventory, safety_stock, reorder_point,
|
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avg_margin_percent, total_revenue, avg_lead_time_days,
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||||
last_purchase_date, last_received_date
|
||||
)
|
||||
SELECT
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||||
p.product_id,
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||||
COALESCE(s.daily_sales_avg, 0),
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||||
COALESCE(s.weekly_sales_avg, 0),
|
||||
COALESCE(s.monthly_sales_avg, 0),
|
||||
CASE
|
||||
WHEN s.daily_sales_avg > 0 THEN FLOOR(p.stock_quantity / s.daily_sales_avg)
|
||||
ELSE 999
|
||||
END as days_of_inventory,
|
||||
CASE
|
||||
WHEN s.daily_sales_avg > 0 THEN FLOOR(p.stock_quantity / s.daily_sales_avg / 7)
|
||||
ELSE 999
|
||||
END as weeks_of_inventory,
|
||||
CEIL(COALESCE(s.daily_sales_avg, 0) * 14) as safety_stock,
|
||||
CEIL(COALESCE(s.daily_sales_avg, 0) * 21) as reorder_point,
|
||||
COALESCE(s.avg_margin_percent, 0),
|
||||
COALESCE(s.total_revenue, 0),
|
||||
COALESCE(pm.avg_lead_time_days, 0),
|
||||
pm.last_purchase_date,
|
||||
pm.last_received_date
|
||||
FROM products p
|
||||
LEFT JOIN temp_sales_metrics s ON p.product_id = s.product_id
|
||||
LEFT JOIN temp_purchase_metrics pm ON p.product_id = pm.product_id
|
||||
ON DUPLICATE KEY UPDATE
|
||||
daily_sales_avg = VALUES(daily_sales_avg),
|
||||
weekly_sales_avg = VALUES(weekly_sales_avg),
|
||||
@@ -441,34 +478,37 @@ async function updateProductMetrics(connection, productId, startTime, current, t
|
||||
weeks_of_inventory = VALUES(weeks_of_inventory),
|
||||
safety_stock = VALUES(safety_stock),
|
||||
reorder_point = VALUES(reorder_point),
|
||||
total_revenue = VALUES(total_revenue),
|
||||
avg_margin_percent = VALUES(avg_margin_percent),
|
||||
total_revenue = VALUES(total_revenue),
|
||||
avg_lead_time_days = VALUES(avg_lead_time_days),
|
||||
last_purchase_date = VALUES(last_purchase_date),
|
||||
last_received_date = VALUES(last_received_date)
|
||||
`, [
|
||||
productId,
|
||||
velocityMetrics.daily_sales_avg,
|
||||
velocityMetrics.weekly_sales_avg,
|
||||
velocityMetrics.monthly_sales_avg,
|
||||
stockMetrics?.days_of_inventory || 0,
|
||||
stockMetrics?.weeks_of_inventory || 0,
|
||||
stockMetrics?.safety_stock || 0,
|
||||
stockMetrics?.reorder_point || 0,
|
||||
financialMetrics.total_revenue,
|
||||
financialMetrics.avg_margin_percent,
|
||||
purchaseMetrics.avg_lead_time_days,
|
||||
purchaseMetrics.last_purchase_date,
|
||||
purchaseMetrics.last_received_date
|
||||
]);
|
||||
last_received_date = VALUES(last_received_date),
|
||||
last_calculated_at = CURRENT_TIMESTAMP
|
||||
`);
|
||||
|
||||
// Calculate ABC classification in one go
|
||||
await connection.query(`
|
||||
WITH revenue_ranks AS (
|
||||
SELECT
|
||||
product_id,
|
||||
total_revenue,
|
||||
total_revenue / SUM(total_revenue) OVER () * 100 as revenue_percent,
|
||||
ROW_NUMBER() OVER (ORDER BY total_revenue DESC) as rank
|
||||
FROM product_metrics
|
||||
WHERE total_revenue > 0
|
||||
)
|
||||
UPDATE product_metrics pm
|
||||
JOIN revenue_ranks r ON pm.product_id = r.product_id
|
||||
SET abc_class =
|
||||
CASE
|
||||
WHEN r.revenue_percent >= 20 THEN 'A'
|
||||
WHEN r.revenue_percent >= 5 THEN 'B'
|
||||
ELSE 'C'
|
||||
END
|
||||
`);
|
||||
|
||||
// Output progress every 5 products or every second
|
||||
if (current % 5 === 0 || Date.now() - startTime > 1000) {
|
||||
updateProgress(current, total, 'Calculating product metrics', startTime);
|
||||
startTime = Date.now();
|
||||
}
|
||||
} catch (error) {
|
||||
logError(error, `Error updating metrics for product ${productId}`);
|
||||
logError(error, 'Error in batch metrics calculation');
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
@@ -1051,43 +1091,8 @@ async function main() {
|
||||
|
||||
const connection = await pool.getConnection();
|
||||
try {
|
||||
// Calculate product metrics
|
||||
const [products] = await connection.query('SELECT DISTINCT product_id FROM products');
|
||||
const totalProducts = products.length;
|
||||
let processedProducts = 0;
|
||||
const metricsStartTime = Date.now();
|
||||
|
||||
outputProgress({
|
||||
operation: 'Starting product metrics calculation',
|
||||
message: `Calculating metrics for ${totalProducts} products...`,
|
||||
current: 0,
|
||||
total: totalProducts,
|
||||
percentage: '0'
|
||||
});
|
||||
|
||||
for (const product of products) {
|
||||
try {
|
||||
// Update progress every 5 products or 1 second
|
||||
if (processedProducts % 5 === 0 || (Date.now() - lastUpdate) > 1000) {
|
||||
updateProgress(processedProducts, totalProducts, 'Calculating product metrics', metricsStartTime);
|
||||
lastUpdate = Date.now();
|
||||
}
|
||||
|
||||
await updateProductMetrics(connection, product.product_id, metricsStartTime, processedProducts, totalProducts);
|
||||
processedProducts++;
|
||||
} catch (error) {
|
||||
logError(error, `Error calculating metrics for product ${product.product_id}`);
|
||||
// Continue with next product instead of failing completely
|
||||
}
|
||||
}
|
||||
|
||||
outputProgress({
|
||||
operation: 'Product metrics calculation completed',
|
||||
current: processedProducts,
|
||||
total: totalProducts,
|
||||
duration: formatDuration((Date.now() - metricsStartTime) / 1000),
|
||||
percentage: '100'
|
||||
});
|
||||
// Calculate metrics in batches
|
||||
await calculateMetricsInBatch(connection);
|
||||
|
||||
// Calculate vendor metrics
|
||||
await calculateVendorMetrics(connection);
|
||||
|
||||
170
inventory-server/scripts/reset-metrics.js
Normal file
170
inventory-server/scripts/reset-metrics.js
Normal file
@@ -0,0 +1,170 @@
|
||||
const mysql = require('mysql2/promise');
|
||||
const path = require('path');
|
||||
const dotenv = require('dotenv');
|
||||
const fs = require('fs');
|
||||
|
||||
dotenv.config({ path: path.join(__dirname, '../.env') });
|
||||
|
||||
const dbConfig = {
|
||||
host: process.env.DB_HOST,
|
||||
user: process.env.DB_USER,
|
||||
password: process.env.DB_PASSWORD,
|
||||
database: process.env.DB_NAME,
|
||||
multipleStatements: true,
|
||||
waitForConnections: true,
|
||||
connectionLimit: 10,
|
||||
queueLimit: 0,
|
||||
namedPlaceholders: true
|
||||
};
|
||||
|
||||
// Set up logging
|
||||
const LOG_DIR = path.join(__dirname, '../logs');
|
||||
const ERROR_LOG = path.join(LOG_DIR, 'import-errors.log');
|
||||
const IMPORT_LOG = path.join(LOG_DIR, 'import.log');
|
||||
|
||||
// Ensure log directory exists
|
||||
if (!fs.existsSync(LOG_DIR)) {
|
||||
fs.mkdirSync(LOG_DIR, { recursive: true });
|
||||
}
|
||||
|
||||
// Helper function to log errors
|
||||
function logError(error, context = '') {
|
||||
const timestamp = new Date().toISOString();
|
||||
const errorMessage = `[${timestamp}] ${context}\nError: ${error.message}\nStack: ${error.stack}\n\n`;
|
||||
fs.appendFileSync(ERROR_LOG, errorMessage);
|
||||
console.error(`\n${context}\nError: ${error.message}`);
|
||||
}
|
||||
|
||||
// Helper function to log progress
|
||||
function outputProgress(data) {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logMessage = `[${timestamp}] ${JSON.stringify(data)}\n`;
|
||||
fs.appendFileSync(IMPORT_LOG, logMessage);
|
||||
console.log(JSON.stringify(data));
|
||||
}
|
||||
|
||||
async function resetMetrics() {
|
||||
let pool;
|
||||
try {
|
||||
pool = mysql.createPool(dbConfig);
|
||||
const connection = await pool.getConnection();
|
||||
|
||||
try {
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting metrics reset',
|
||||
message: 'Creating/resetting metrics tables...',
|
||||
percentage: '0'
|
||||
});
|
||||
|
||||
// Create tables if they don't exist and then truncate them
|
||||
await connection.query(`
|
||||
CREATE TABLE IF NOT EXISTS temp_sales_metrics (
|
||||
product_id INT PRIMARY KEY,
|
||||
total_quantity_sold INT DEFAULT 0,
|
||||
total_revenue DECIMAL(10,2) DEFAULT 0.00,
|
||||
average_price DECIMAL(10,2) DEFAULT 0.00,
|
||||
last_sale_date DATE,
|
||||
sales_rank INT
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS temp_purchase_metrics (
|
||||
product_id INT PRIMARY KEY,
|
||||
total_quantity_purchased INT DEFAULT 0,
|
||||
total_cost DECIMAL(10,2) DEFAULT 0.00,
|
||||
average_cost DECIMAL(10,2) DEFAULT 0.00,
|
||||
last_purchase_date DATE,
|
||||
purchase_rank INT
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS product_metrics (
|
||||
product_id INT PRIMARY KEY,
|
||||
total_quantity_sold INT DEFAULT 0,
|
||||
total_revenue DECIMAL(10,2) DEFAULT 0.00,
|
||||
average_price DECIMAL(10,2) DEFAULT 0.00,
|
||||
total_quantity_purchased INT DEFAULT 0,
|
||||
total_cost DECIMAL(10,2) DEFAULT 0.00,
|
||||
average_cost DECIMAL(10,2) DEFAULT 0.00,
|
||||
profit_margin DECIMAL(5,2) DEFAULT 0.00,
|
||||
turnover_rate DECIMAL(5,2) DEFAULT 0.00,
|
||||
abc_class CHAR(1),
|
||||
last_calculated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
last_sale_date DATE,
|
||||
last_purchase_date DATE,
|
||||
sales_rank INT,
|
||||
purchase_rank INT
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS product_time_aggregates (
|
||||
product_id INT,
|
||||
period_type ENUM('daily', 'weekly', 'monthly', 'quarterly', 'yearly'),
|
||||
period_start DATE,
|
||||
quantity_sold INT DEFAULT 0,
|
||||
revenue DECIMAL(10,2) DEFAULT 0.00,
|
||||
quantity_purchased INT DEFAULT 0,
|
||||
purchase_cost DECIMAL(10,2) DEFAULT 0.00,
|
||||
PRIMARY KEY (product_id, period_type, period_start)
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS vendor_metrics (
|
||||
vendor VARCHAR(255) PRIMARY KEY,
|
||||
total_orders INT DEFAULT 0,
|
||||
total_items_ordered INT DEFAULT 0,
|
||||
total_items_received INT DEFAULT 0,
|
||||
total_spend DECIMAL(10,2) DEFAULT 0.00,
|
||||
average_order_value DECIMAL(10,2) DEFAULT 0.00,
|
||||
fulfillment_rate DECIMAL(5,2) DEFAULT 0.00,
|
||||
average_delivery_days DECIMAL(5,1),
|
||||
last_order_date DATE,
|
||||
last_delivery_date DATE
|
||||
);
|
||||
|
||||
TRUNCATE TABLE temp_sales_metrics;
|
||||
TRUNCATE TABLE temp_purchase_metrics;
|
||||
TRUNCATE TABLE product_metrics;
|
||||
TRUNCATE TABLE product_time_aggregates;
|
||||
TRUNCATE TABLE vendor_metrics;
|
||||
`);
|
||||
|
||||
outputProgress({
|
||||
status: 'complete',
|
||||
operation: 'Metrics reset completed',
|
||||
message: 'All metrics tables have been created/cleared',
|
||||
percentage: '100'
|
||||
});
|
||||
|
||||
} catch (error) {
|
||||
logError(error, 'Error resetting metrics tables');
|
||||
outputProgress({
|
||||
status: 'error',
|
||||
error: error.message,
|
||||
operation: 'Failed to reset metrics'
|
||||
});
|
||||
throw error;
|
||||
} finally {
|
||||
connection.release();
|
||||
}
|
||||
} catch (error) {
|
||||
logError(error, 'Fatal error during metrics reset');
|
||||
outputProgress({
|
||||
status: 'error',
|
||||
error: error.message,
|
||||
operation: 'Failed to reset metrics'
|
||||
});
|
||||
throw error;
|
||||
} finally {
|
||||
if (pool) {
|
||||
await pool.end();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Run if called directly
|
||||
if (require.main === module) {
|
||||
resetMetrics().catch(error => {
|
||||
logError(error, 'Unhandled error in main process');
|
||||
process.exit(1);
|
||||
});
|
||||
}
|
||||
|
||||
module.exports = resetMetrics;
|
||||
@@ -17,6 +17,7 @@ let importProgress = null;
|
||||
const updateClients = new Set();
|
||||
const importClients = new Set();
|
||||
const resetClients = new Set();
|
||||
const resetMetricsClients = new Set();
|
||||
|
||||
// Helper to send progress to specific clients
|
||||
function sendProgressToClients(clients, progress) {
|
||||
@@ -107,6 +108,28 @@ router.get('/reset/progress', (req, 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);
|
||||
});
|
||||
});
|
||||
|
||||
// Debug endpoint to verify route registration
|
||||
router.get('/test', (req, res) => {
|
||||
console.log('CSV test endpoint hit');
|
||||
@@ -434,4 +457,104 @@ router.post('/reset', async (req, res) => {
|
||||
}
|
||||
});
|
||||
|
||||
// Add reset-metrics endpoint
|
||||
router.post('/reset-metrics', async (req, res) => {
|
||||
if (activeImport) {
|
||||
res.status(400).json({ error: 'Operation already in progress' });
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
// Set active import to prevent concurrent operations
|
||||
activeImport = {
|
||||
type: 'reset-metrics',
|
||||
status: 'running',
|
||||
operation: 'Starting metrics reset'
|
||||
};
|
||||
|
||||
// Send initial response
|
||||
res.status(200).json({ message: 'Reset metrics started' });
|
||||
|
||||
// Send initial progress through SSE
|
||||
sendProgressToClients(resetMetricsClients, {
|
||||
status: 'running',
|
||||
operation: 'Starting metrics reset'
|
||||
});
|
||||
|
||||
// Run the reset metrics script
|
||||
const resetMetrics = require('../../scripts/reset-metrics');
|
||||
await resetMetrics();
|
||||
|
||||
// Send completion through SSE
|
||||
sendProgressToClients(resetMetricsClients, {
|
||||
status: 'complete',
|
||||
operation: 'Metrics reset completed'
|
||||
});
|
||||
|
||||
activeImport = null;
|
||||
} catch (error) {
|
||||
console.error('Error during metrics reset:', error);
|
||||
|
||||
// Send error through SSE
|
||||
sendProgressToClients(resetMetricsClients, {
|
||||
status: 'error',
|
||||
error: error.message || 'Failed to reset metrics'
|
||||
});
|
||||
|
||||
activeImport = null;
|
||||
res.status(500).json({ error: error.message || 'Failed to reset metrics' });
|
||||
}
|
||||
});
|
||||
|
||||
// Add calculate-metrics endpoint
|
||||
router.post('/calculate-metrics', async (req, res) => {
|
||||
if (activeImport) {
|
||||
res.status(400).json({ error: 'Operation already in progress' });
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
// Set active import to prevent concurrent operations
|
||||
activeImport = {
|
||||
type: 'calculate-metrics',
|
||||
status: 'running',
|
||||
operation: 'Starting metrics calculation'
|
||||
};
|
||||
|
||||
// Send initial response
|
||||
res.status(200).json({ message: 'Metrics calculation started' });
|
||||
|
||||
// Send initial progress through SSE
|
||||
sendProgressToClients(importClients, {
|
||||
status: 'running',
|
||||
operation: 'Starting metrics calculation',
|
||||
percentage: '0'
|
||||
});
|
||||
|
||||
// Run the metrics calculation script
|
||||
const calculateMetrics = require('../../scripts/calculate-metrics');
|
||||
await calculateMetrics();
|
||||
|
||||
// Send completion through SSE
|
||||
sendProgressToClients(importClients, {
|
||||
status: 'complete',
|
||||
operation: 'Metrics calculation completed',
|
||||
percentage: '100'
|
||||
});
|
||||
|
||||
activeImport = null;
|
||||
} catch (error) {
|
||||
console.error('Error during metrics calculation:', error);
|
||||
|
||||
// Send error through SSE
|
||||
sendProgressToClients(importClients, {
|
||||
status: 'error',
|
||||
error: error.message || 'Failed to calculate metrics'
|
||||
});
|
||||
|
||||
activeImport = null;
|
||||
res.status(500).json({ error: error.message || 'Failed to calculate metrics' });
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = router;
|
||||
@@ -1,6 +1,8 @@
|
||||
const express = require('express');
|
||||
const cors = require('cors');
|
||||
const { spawn } = require('child_process');
|
||||
const path = require('path');
|
||||
const fs = require('fs');
|
||||
const express = require('express');
|
||||
const mysql = require('mysql2/promise');
|
||||
const { corsMiddleware, corsErrorHandler } = require('./middleware/cors');
|
||||
const { initPool } = require('./utils/db');
|
||||
@@ -127,6 +129,111 @@ pool.getConnection()
|
||||
process.exit(1);
|
||||
});
|
||||
|
||||
// Initialize client sets for SSE
|
||||
const importClients = new Set();
|
||||
const updateClients = new Set();
|
||||
const resetClients = new Set();
|
||||
const resetMetricsClients = new Set();
|
||||
|
||||
// Helper function to send progress to SSE clients
|
||||
const sendProgressToClients = (clients, data) => {
|
||||
clients.forEach(client => {
|
||||
try {
|
||||
client.write(`data: ${JSON.stringify(data)}\n\n`);
|
||||
} catch (error) {
|
||||
console.error('Error sending SSE update:', error);
|
||||
}
|
||||
});
|
||||
};
|
||||
|
||||
// Setup SSE connection
|
||||
const setupSSE = (req, res) => {
|
||||
const { type } = req.params;
|
||||
|
||||
// Set headers for SSE
|
||||
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 initial message
|
||||
res.write('data: {"status":"connected"}\n\n');
|
||||
|
||||
// Add client to appropriate set
|
||||
const clientSet = type === 'import' ? importClients :
|
||||
type === 'update' ? updateClients :
|
||||
type === 'reset' ? resetClients :
|
||||
type === 'reset-metrics' ? resetMetricsClients :
|
||||
null;
|
||||
|
||||
if (clientSet) {
|
||||
clientSet.add(res);
|
||||
|
||||
// Remove client when connection closes
|
||||
req.on('close', () => {
|
||||
clientSet.delete(res);
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
// Update the status endpoint to include reset-metrics
|
||||
app.get('/csv/status', (req, res) => {
|
||||
res.json({
|
||||
active: !!currentOperation,
|
||||
type: currentOperation?.type || null,
|
||||
progress: currentOperation ? {
|
||||
status: currentOperation.status,
|
||||
operation: currentOperation.operation,
|
||||
current: currentOperation.current,
|
||||
total: currentOperation.total,
|
||||
percentage: currentOperation.percentage
|
||||
} : null
|
||||
});
|
||||
});
|
||||
|
||||
// Update progress endpoint mapping
|
||||
app.get('/csv/:type/progress', (req, res) => {
|
||||
const { type } = req.params;
|
||||
if (!['import', 'update', 'reset', 'reset-metrics'].includes(type)) {
|
||||
res.status(400).json({ error: 'Invalid operation type' });
|
||||
return;
|
||||
}
|
||||
|
||||
setupSSE(req, res);
|
||||
});
|
||||
|
||||
// Update the cancel endpoint to handle reset-metrics
|
||||
app.post('/csv/cancel', (req, res) => {
|
||||
const { operation } = req.query;
|
||||
|
||||
if (!currentOperation) {
|
||||
res.status(400).json({ error: 'No operation in progress' });
|
||||
return;
|
||||
}
|
||||
|
||||
if (operation && operation.toLowerCase() !== currentOperation.type) {
|
||||
res.status(400).json({ error: 'Operation type mismatch' });
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
// Handle cancellation based on operation type
|
||||
if (currentOperation.type === 'reset-metrics') {
|
||||
// Reset metrics doesn't need special cleanup
|
||||
currentOperation = null;
|
||||
res.json({ message: 'Reset metrics cancelled' });
|
||||
} else {
|
||||
// ... existing cancellation logic for other operations ...
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error during cancellation:', error);
|
||||
res.status(500).json({ error: 'Failed to cancel operation' });
|
||||
}
|
||||
});
|
||||
|
||||
const PORT = process.env.PORT || 3000;
|
||||
app.listen(PORT, () => {
|
||||
console.log(`[Server] Running in ${process.env.NODE_ENV || 'development'} mode on port ${PORT}`);
|
||||
|
||||
Reference in New Issue
Block a user