Optimize metrics import and split off metrics import functions (untested)
This commit is contained in:
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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