Add metrics historical backfill scripts, fix up all new metrics calc queries and add combined script to run
This commit is contained in:
558
inventory-server/old/calculate-metrics.js
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558
inventory-server/old/calculate-metrics.js
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@@ -0,0 +1,558 @@
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const path = require('path');
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// Change working directory to script directory
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process.chdir(path.dirname(__filename));
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require('dotenv').config({ path: path.resolve(__dirname, '..', '.env') });
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// Configuration flags for controlling which metrics to calculate
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// Set to 1 to skip the corresponding calculation, 0 to run it
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const SKIP_PRODUCT_METRICS = 0;
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const SKIP_TIME_AGGREGATES = 0;
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const SKIP_FINANCIAL_METRICS = 0;
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const SKIP_VENDOR_METRICS = 0;
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const SKIP_CATEGORY_METRICS = 0;
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const SKIP_BRAND_METRICS = 0;
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const SKIP_SALES_FORECASTS = 0;
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// Add error handler for uncaught exceptions
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process.on('uncaughtException', (error) => {
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console.error('Uncaught Exception:', error);
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process.exit(1);
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});
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// Add error handler for unhandled promise rejections
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process.on('unhandledRejection', (reason, promise) => {
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console.error('Unhandled Rejection at:', promise, 'reason:', reason);
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process.exit(1);
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});
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const progress = require('./metrics/utils/progress');
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console.log('Progress module loaded:', {
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modulePath: require.resolve('./metrics/utils/progress'),
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exports: Object.keys(progress),
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currentDir: process.cwd(),
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scriptDir: __dirname
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});
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// Store progress functions in global scope to ensure availability
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global.formatElapsedTime = progress.formatElapsedTime;
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global.estimateRemaining = progress.estimateRemaining;
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global.calculateRate = progress.calculateRate;
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global.outputProgress = progress.outputProgress;
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global.clearProgress = progress.clearProgress;
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global.getProgress = progress.getProgress;
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global.logError = progress.logError;
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// List of temporary tables used in the calculation process
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const TEMP_TABLES = [
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'temp_revenue_ranks',
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'temp_sales_metrics',
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'temp_purchase_metrics',
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'temp_product_metrics',
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'temp_vendor_metrics',
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'temp_category_metrics',
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'temp_brand_metrics',
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'temp_forecast_dates',
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'temp_daily_sales',
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'temp_product_stats',
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'temp_category_sales',
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'temp_category_stats',
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'temp_beginning_inventory',
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'temp_monthly_inventory'
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];
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// Add cleanup function for temporary tables
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async function cleanupTemporaryTables(connection) {
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try {
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// Drop each temporary table if it exists
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for (const table of TEMP_TABLES) {
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await connection.query(`DROP TABLE IF EXISTS ${table}`);
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}
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} catch (err) {
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console.error('Error cleaning up temporary tables:', err);
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}
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}
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const { getConnection, closePool } = require('./metrics/utils/db');
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const calculateProductMetrics = require('./metrics/product-metrics');
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const calculateTimeAggregates = require('./metrics/time-aggregates');
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const calculateFinancialMetrics = require('./metrics/financial-metrics');
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const calculateVendorMetrics = require('./metrics/vendor-metrics');
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const calculateCategoryMetrics = require('./metrics/category-metrics');
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const calculateBrandMetrics = require('./metrics/brand-metrics');
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const calculateSalesForecasts = require('./metrics/sales-forecasts');
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// Add cancel handler
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let isCancelled = false;
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function cancelCalculation() {
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isCancelled = true;
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console.log('Calculation has been cancelled by user');
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// Force-terminate any query that's been running for more than 5 seconds
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try {
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const connection = getConnection();
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connection.then(async (conn) => {
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try {
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// Identify and terminate long-running queries from our application
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await conn.query(`
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SELECT pg_cancel_backend(pid)
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FROM pg_stat_activity
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WHERE query_start < now() - interval '5 seconds'
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AND application_name LIKE '%node%'
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AND query NOT LIKE '%pg_cancel_backend%'
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`);
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// Clean up any temporary tables
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await cleanupTemporaryTables(conn);
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// Release connection
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conn.release();
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} catch (err) {
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console.error('Error during force cancellation:', err);
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conn.release();
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}
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}).catch(err => {
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console.error('Could not get connection for cancellation:', err);
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});
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} catch (err) {
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console.error('Failed to terminate running queries:', err);
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}
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return {
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success: true,
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message: 'Calculation has been cancelled'
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};
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}
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// Handle SIGTERM signal for cancellation
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process.on('SIGTERM', cancelCalculation);
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// Update the main calculation function to use the new modular structure
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async function calculateMetrics() {
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let connection;
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const startTime = Date.now();
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let processedProducts = 0;
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let processedOrders = 0;
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let processedPurchaseOrders = 0;
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let totalProducts = 0;
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let totalOrders = 0;
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let totalPurchaseOrders = 0;
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let calculateHistoryId;
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// Set a maximum execution time (30 minutes)
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const MAX_EXECUTION_TIME = 30 * 60 * 1000;
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const timeout = setTimeout(() => {
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console.error(`Calculation timed out after ${MAX_EXECUTION_TIME/1000} seconds, forcing termination`);
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// Call cancel and force exit
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cancelCalculation();
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process.exit(1);
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}, MAX_EXECUTION_TIME);
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try {
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// Clean up any previously running calculations
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connection = await getConnection();
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await connection.query(`
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UPDATE calculate_history
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SET
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status = 'cancelled',
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end_time = NOW(),
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duration_seconds = EXTRACT(EPOCH FROM (NOW() - start_time))::INTEGER,
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error_message = 'Previous calculation was not completed properly'
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WHERE status = 'running'
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`);
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// Get counts from all relevant tables
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const [productCountResult, orderCountResult, poCountResult] = await Promise.all([
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connection.query('SELECT COUNT(*) as total FROM products'),
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connection.query('SELECT COUNT(*) as total FROM orders'),
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connection.query('SELECT COUNT(*) as total FROM purchase_orders')
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]);
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totalProducts = parseInt(productCountResult.rows[0].total);
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totalOrders = parseInt(orderCountResult.rows[0].total);
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totalPurchaseOrders = parseInt(poCountResult.rows[0].total);
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// Create history record for this calculation
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const historyResult = await connection.query(`
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INSERT INTO calculate_history (
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start_time,
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status,
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total_products,
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total_orders,
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total_purchase_orders,
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additional_info
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) VALUES (
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NOW(),
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'running',
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$1,
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$2,
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$3,
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jsonb_build_object(
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'skip_product_metrics', ($4::int > 0),
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'skip_time_aggregates', ($5::int > 0),
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'skip_financial_metrics', ($6::int > 0),
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'skip_vendor_metrics', ($7::int > 0),
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'skip_category_metrics', ($8::int > 0),
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'skip_brand_metrics', ($9::int > 0),
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'skip_sales_forecasts', ($10::int > 0)
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)
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) RETURNING id
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`, [
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totalProducts,
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totalOrders,
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totalPurchaseOrders,
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SKIP_PRODUCT_METRICS,
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SKIP_TIME_AGGREGATES,
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SKIP_FINANCIAL_METRICS,
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SKIP_VENDOR_METRICS,
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SKIP_CATEGORY_METRICS,
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SKIP_BRAND_METRICS,
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SKIP_SALES_FORECASTS
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]);
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calculateHistoryId = historyResult.rows[0].id;
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// Add debug logging for the progress functions
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console.log('Debug - Progress functions:', {
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formatElapsedTime: typeof global.formatElapsedTime,
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estimateRemaining: typeof global.estimateRemaining,
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calculateRate: typeof global.calculateRate,
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startTime: startTime
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});
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try {
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const elapsed = global.formatElapsedTime(startTime);
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console.log('Debug - formatElapsedTime test successful:', elapsed);
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} catch (err) {
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console.error('Debug - Error testing formatElapsedTime:', err);
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throw err;
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}
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// Release the connection before getting a new one
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connection.release();
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isCancelled = false;
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connection = await getConnection();
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try {
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global.outputProgress({
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status: 'running',
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operation: 'Starting metrics calculation',
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current: 0,
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total: 100,
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elapsed: '0s',
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remaining: 'Calculating...',
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rate: 0,
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percentage: '0',
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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// Update progress periodically
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const updateProgress = async (products = null, orders = null, purchaseOrders = null) => {
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// Ensure all values are valid numbers or default to previous value
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if (products !== null) processedProducts = Number(products) || processedProducts || 0;
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if (orders !== null) processedOrders = Number(orders) || processedOrders || 0;
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if (purchaseOrders !== null) processedPurchaseOrders = Number(purchaseOrders) || processedPurchaseOrders || 0;
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// Ensure we never send NaN to the database
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const safeProducts = Number(processedProducts) || 0;
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const safeOrders = Number(processedOrders) || 0;
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const safePurchaseOrders = Number(processedPurchaseOrders) || 0;
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await connection.query(`
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UPDATE calculate_history
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SET
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processed_products = $1,
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processed_orders = $2,
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processed_purchase_orders = $3
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WHERE id = $4
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`, [safeProducts, safeOrders, safePurchaseOrders, calculateHistoryId]);
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};
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// Helper function to ensure valid progress numbers
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const ensureValidProgress = (current, total) => ({
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current: Number(current) || 0,
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total: Number(total) || 1, // Default to 1 to avoid division by zero
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percentage: (((Number(current) || 0) / (Number(total) || 1)) * 100).toFixed(1)
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});
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// Initial progress
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const initialProgress = ensureValidProgress(0, totalProducts);
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global.outputProgress({
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status: 'running',
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operation: 'Starting metrics calculation',
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current: initialProgress.current,
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total: initialProgress.total,
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elapsed: '0s',
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remaining: 'Calculating...',
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rate: 0,
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percentage: initialProgress.percentage,
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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if (!SKIP_PRODUCT_METRICS) {
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const result = await calculateProductMetrics(startTime, totalProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Product metrics calculation failed');
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}
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} else {
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console.log('Skipping product metrics calculation...');
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processedProducts = Math.floor(totalProducts * 0.6);
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await updateProgress(processedProducts);
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global.outputProgress({
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status: 'running',
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operation: 'Skipping product metrics calculation',
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current: processedProducts,
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total: totalProducts,
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elapsed: global.formatElapsedTime(startTime),
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remaining: global.estimateRemaining(startTime, processedProducts, totalProducts),
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rate: global.calculateRate(startTime, processedProducts),
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percentage: '60',
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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}
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// Calculate time-based aggregates
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if (!SKIP_TIME_AGGREGATES) {
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const result = await calculateTimeAggregates(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Time aggregates calculation failed');
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}
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} else {
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console.log('Skipping time aggregates calculation');
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}
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// Calculate financial metrics
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if (!SKIP_FINANCIAL_METRICS) {
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const result = await calculateFinancialMetrics(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Financial metrics calculation failed');
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}
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} else {
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console.log('Skipping financial metrics calculation');
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}
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// Calculate vendor metrics
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if (!SKIP_VENDOR_METRICS) {
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const result = await calculateVendorMetrics(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Vendor metrics calculation failed');
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}
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} else {
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console.log('Skipping vendor metrics calculation');
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}
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// Calculate category metrics
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if (!SKIP_CATEGORY_METRICS) {
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const result = await calculateCategoryMetrics(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Category metrics calculation failed');
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}
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} else {
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console.log('Skipping category metrics calculation');
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}
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// Calculate brand metrics
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if (!SKIP_BRAND_METRICS) {
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const result = await calculateBrandMetrics(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Brand metrics calculation failed');
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}
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} else {
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console.log('Skipping brand metrics calculation');
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}
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// Calculate sales forecasts
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if (!SKIP_SALES_FORECASTS) {
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const result = await calculateSalesForecasts(startTime, totalProducts, processedProducts);
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await updateProgress(result.processedProducts, result.processedOrders, result.processedPurchaseOrders);
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if (!result.success) {
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throw new Error('Sales forecasts calculation failed');
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}
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} else {
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console.log('Skipping sales forecasts calculation');
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}
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// Final progress update with guaranteed valid numbers
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const finalProgress = ensureValidProgress(totalProducts, totalProducts);
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// Final success message
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outputProgress({
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status: 'complete',
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operation: 'Metrics calculation complete',
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current: finalProgress.current,
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total: finalProgress.total,
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elapsed: global.formatElapsedTime(startTime),
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remaining: '0s',
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rate: global.calculateRate(startTime, finalProgress.current),
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percentage: '100',
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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// Ensure all values are valid numbers before final update
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const finalStats = {
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processedProducts: Number(processedProducts) || 0,
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processedOrders: Number(processedOrders) || 0,
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processedPurchaseOrders: Number(processedPurchaseOrders) || 0
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};
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// Update history with completion
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await connection.query(`
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UPDATE calculate_history
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SET
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end_time = NOW(),
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duration_seconds = $1,
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processed_products = $2,
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processed_orders = $3,
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processed_purchase_orders = $4,
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status = 'completed'
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WHERE id = $5
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`, [Math.round((Date.now() - startTime) / 1000),
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finalStats.processedProducts,
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finalStats.processedOrders,
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finalStats.processedPurchaseOrders,
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calculateHistoryId]);
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// Clear progress file on successful completion
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global.clearProgress();
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return {
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success: true,
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message: 'Calculation completed successfully',
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duration: Math.round((Date.now() - startTime) / 1000)
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};
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} catch (error) {
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const endTime = Date.now();
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const totalElapsedSeconds = Math.round((endTime - startTime) / 1000);
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// Update history with error
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await connection.query(`
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UPDATE calculate_history
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SET
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end_time = NOW(),
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duration_seconds = $1,
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processed_products = $2,
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processed_orders = $3,
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processed_purchase_orders = $4,
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status = $5,
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error_message = $6
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WHERE id = $7
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`, [
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totalElapsedSeconds,
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processedProducts || 0, // Ensure we have a valid number
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processedOrders || 0, // Ensure we have a valid number
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processedPurchaseOrders || 0, // Ensure we have a valid number
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isCancelled ? 'cancelled' : 'failed',
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error.message,
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calculateHistoryId
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]);
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if (isCancelled) {
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global.outputProgress({
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status: 'cancelled',
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operation: 'Calculation cancelled',
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current: processedProducts,
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total: totalProducts || 0,
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elapsed: global.formatElapsedTime(startTime),
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remaining: null,
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rate: global.calculateRate(startTime, processedProducts),
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percentage: ((processedProducts / (totalProducts || 1)) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
|
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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} else {
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global.outputProgress({
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||||
status: 'error',
|
||||
operation: 'Error: ' + error.message,
|
||||
current: processedProducts,
|
||||
total: totalProducts || 0,
|
||||
elapsed: global.formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
rate: global.calculateRate(startTime, processedProducts),
|
||||
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;
|
||||
} finally {
|
||||
// Clear the timeout to prevent forced termination
|
||||
clearTimeout(timeout);
|
||||
|
||||
// Always clean up and release connection
|
||||
if (connection) {
|
||||
try {
|
||||
await cleanupTemporaryTables(connection);
|
||||
connection.release();
|
||||
} catch (err) {
|
||||
console.error('Error in final cleanup:', err);
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error in metrics calculation', error);
|
||||
|
||||
try {
|
||||
if (connection) {
|
||||
await connection.query(`
|
||||
UPDATE calculate_history
|
||||
SET
|
||||
status = 'failed',
|
||||
end_time = NOW(),
|
||||
duration_seconds = EXTRACT(EPOCH FROM (NOW() - start_time))::INTEGER,
|
||||
error_message = $1
|
||||
WHERE id = $2
|
||||
`, [error.message.substring(0, 500), calculateHistoryId]);
|
||||
}
|
||||
} catch (updateError) {
|
||||
console.error('Error updating calculation history:', updateError);
|
||||
}
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
// Export as a module with all necessary functions
|
||||
module.exports = {
|
||||
calculateMetrics,
|
||||
cancelCalculation,
|
||||
getProgress: global.getProgress
|
||||
};
|
||||
|
||||
// Run directly if called from command line
|
||||
if (require.main === module) {
|
||||
calculateMetrics().catch(error => {
|
||||
if (!error.message.includes('Operation cancelled')) {
|
||||
console.error('Error:', error);
|
||||
}
|
||||
process.exit(1);
|
||||
});
|
||||
}
|
||||
321
inventory-server/old/metrics/brand-metrics.js
Normal file
321
inventory-server/old/metrics/brand-metrics.js
Normal file
@@ -0,0 +1,321 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateBrandMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Brand metrics calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
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 = parseInt(orderCount.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting brand metrics calculation',
|
||||
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 brand metrics with optimized queries
|
||||
await connection.query(`
|
||||
INSERT INTO brand_metrics (
|
||||
brand,
|
||||
product_count,
|
||||
active_products,
|
||||
total_stock_units,
|
||||
total_stock_cost,
|
||||
total_stock_retail,
|
||||
total_revenue,
|
||||
avg_margin,
|
||||
growth_rate
|
||||
)
|
||||
WITH filtered_products AS (
|
||||
SELECT
|
||||
p.*,
|
||||
CASE
|
||||
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
|
||||
END as valid_stock
|
||||
FROM products p
|
||||
WHERE p.brand IS NOT NULL
|
||||
),
|
||||
sales_periods AS (
|
||||
SELECT
|
||||
p.brand,
|
||||
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
|
||||
WHEN o.date >= CURRENT_DATE - INTERVAL '3 months' THEN 'current'
|
||||
WHEN o.date BETWEEN CURRENT_DATE - INTERVAL '15 months'
|
||||
AND CURRENT_DATE - INTERVAL '12 months' THEN 'previous'
|
||||
END as period_type
|
||||
FROM filtered_products p
|
||||
JOIN orders o ON p.pid = o.pid
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '15 months'
|
||||
GROUP BY p.brand, period_type
|
||||
),
|
||||
brand_data AS (
|
||||
SELECT
|
||||
p.brand,
|
||||
COUNT(DISTINCT p.valid_pid) as product_count,
|
||||
COUNT(DISTINCT p.active_pid) as active_products,
|
||||
SUM(p.valid_stock) as total_stock_units,
|
||||
SUM(p.valid_stock * p.cost_price) as total_stock_cost,
|
||||
SUM(p.valid_stock * p.price) as total_stock_retail,
|
||||
COALESCE(SUM(o.quantity * (o.price - COALESCE(o.discount, 0))), 0) as total_revenue,
|
||||
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 0
|
||||
END as avg_margin
|
||||
FROM filtered_products p
|
||||
LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
|
||||
GROUP BY p.brand
|
||||
)
|
||||
SELECT
|
||||
bd.brand,
|
||||
bd.product_count,
|
||||
bd.active_products,
|
||||
bd.total_stock_units,
|
||||
bd.total_stock_cost,
|
||||
bd.total_stock_retail,
|
||||
bd.total_revenue,
|
||||
bd.avg_margin,
|
||||
CASE
|
||||
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
|
||||
WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0
|
||||
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 = 'previous' THEN sp.period_revenue END)) /
|
||||
NULLIF(ABS(MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END)), 0)) * 100.0,
|
||||
999.99
|
||||
)
|
||||
)
|
||||
END as growth_rate
|
||||
FROM brand_data bd
|
||||
LEFT JOIN sales_periods sp ON bd.brand = sp.brand
|
||||
GROUP BY bd.brand, bd.product_count, bd.active_products, bd.total_stock_units,
|
||||
bd.total_stock_cost, bd.total_stock_retail, bd.total_revenue, bd.avg_margin
|
||||
ON CONFLICT (brand) DO UPDATE
|
||||
SET
|
||||
product_count = EXCLUDED.product_count,
|
||||
active_products = EXCLUDED.active_products,
|
||||
total_stock_units = EXCLUDED.total_stock_units,
|
||||
total_stock_cost = EXCLUDED.total_stock_cost,
|
||||
total_stock_retail = EXCLUDED.total_stock_retail,
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
avg_margin = EXCLUDED.avg_margin,
|
||||
growth_rate = EXCLUDED.growth_rate,
|
||||
last_calculated_at = CURRENT_TIMESTAMP
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.97);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Brand metrics calculated, starting time-based metrics',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Calculate brand time-based metrics with optimized query
|
||||
await connection.query(`
|
||||
INSERT INTO brand_time_metrics (
|
||||
brand,
|
||||
year,
|
||||
month,
|
||||
product_count,
|
||||
active_products,
|
||||
total_stock_units,
|
||||
total_stock_cost,
|
||||
total_stock_retail,
|
||||
total_revenue,
|
||||
avg_margin
|
||||
)
|
||||
WITH filtered_products AS (
|
||||
SELECT
|
||||
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
|
||||
WHEN p.stock_quantity IS NULL OR p.stock_quantity < 0 OR p.stock_quantity > 5000 THEN 0
|
||||
ELSE p.stock_quantity
|
||||
END as valid_stock
|
||||
FROM products p
|
||||
WHERE p.brand IS NOT NULL
|
||||
),
|
||||
monthly_metrics AS (
|
||||
SELECT
|
||||
p.brand,
|
||||
EXTRACT(YEAR FROM o.date::timestamp with time zone) as year,
|
||||
EXTRACT(MONTH FROM o.date::timestamp with time zone) as month,
|
||||
COUNT(DISTINCT p.valid_pid) as product_count,
|
||||
COUNT(DISTINCT p.active_pid) as active_products,
|
||||
SUM(p.valid_stock) as total_stock_units,
|
||||
SUM(p.valid_stock * p.cost_price) as total_stock_cost,
|
||||
SUM(p.valid_stock * p.price) as total_stock_retail,
|
||||
SUM(o.quantity * o.price) as total_revenue,
|
||||
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 0
|
||||
END as avg_margin
|
||||
FROM filtered_products p
|
||||
LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
|
||||
WHERE o.date >= CURRENT_DATE - INTERVAL '12 months'
|
||||
GROUP BY p.brand, EXTRACT(YEAR FROM o.date::timestamp with time zone), EXTRACT(MONTH FROM o.date::timestamp with time zone)
|
||||
)
|
||||
SELECT *
|
||||
FROM monthly_metrics
|
||||
ON CONFLICT (brand, year, month) DO UPDATE
|
||||
SET
|
||||
product_count = EXCLUDED.product_count,
|
||||
active_products = EXCLUDED.active_products,
|
||||
total_stock_units = EXCLUDED.total_stock_units,
|
||||
total_stock_cost = EXCLUDED.total_stock_cost,
|
||||
total_stock_retail = EXCLUDED.total_stock_retail,
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
avg_margin = EXCLUDED.avg_margin
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.99);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Brand time-based 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 ('brand_metrics', NOW())
|
||||
ON CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating brand metrics');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateBrandMetrics;
|
||||
554
inventory-server/old/metrics/category-metrics.js
Normal file
554
inventory-server/old/metrics/category-metrics.js
Normal file
@@ -0,0 +1,554 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateCategoryMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Category metrics calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
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 = parseInt(orderCount.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting category metrics calculation',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// First, calculate base category metrics
|
||||
await connection.query(`
|
||||
INSERT INTO category_metrics (
|
||||
category_id,
|
||||
product_count,
|
||||
active_products,
|
||||
total_value,
|
||||
status,
|
||||
last_calculated_at
|
||||
)
|
||||
SELECT
|
||||
c.cat_id,
|
||||
COUNT(DISTINCT p.pid) as product_count,
|
||||
COUNT(DISTINCT CASE WHEN p.visible = true THEN p.pid END) as active_products,
|
||||
COALESCE(SUM(p.stock_quantity * p.cost_price), 0) as total_value,
|
||||
c.status,
|
||||
NOW() as last_calculated_at
|
||||
FROM categories c
|
||||
LEFT JOIN product_categories pc ON c.cat_id = pc.cat_id
|
||||
LEFT JOIN products p ON pc.pid = p.pid
|
||||
GROUP BY c.cat_id, c.status
|
||||
ON CONFLICT (category_id) DO UPDATE
|
||||
SET
|
||||
product_count = EXCLUDED.product_count,
|
||||
active_products = EXCLUDED.active_products,
|
||||
total_value = EXCLUDED.total_value,
|
||||
status = EXCLUDED.status,
|
||||
last_calculated_at = EXCLUDED.last_calculated_at
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.90);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Base category metrics calculated, updating with margin data',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Then update with margin and turnover data
|
||||
await connection.query(`
|
||||
WITH category_sales AS (
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
SUM(o.quantity * o.price) as total_sales,
|
||||
SUM(o.quantity * (o.price - p.cost_price)) as total_margin,
|
||||
SUM(o.quantity) as units_sold,
|
||||
AVG(GREATEST(p.stock_quantity, 0)) as avg_stock,
|
||||
COUNT(DISTINCT DATE(o.date)) as active_days
|
||||
FROM product_categories pc
|
||||
JOIN products p ON pc.pid = p.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
|
||||
AND o.date >= CURRENT_DATE - (COALESCE(tc.calculation_period_days, 30) || ' days')::INTERVAL
|
||||
GROUP BY pc.cat_id
|
||||
)
|
||||
UPDATE category_metrics
|
||||
SET
|
||||
avg_margin = COALESCE(cs.total_margin * 100.0 / NULLIF(cs.total_sales, 0), 0),
|
||||
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,
|
||||
last_calculated_at = NOW()
|
||||
FROM category_sales cs
|
||||
WHERE category_id = cs.cat_id
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.95);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Margin data updated, calculating growth rates',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Finally update growth rates
|
||||
await connection.query(`
|
||||
WITH current_period AS (
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
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
|
||||
JOIN products p ON pc.pid = p.pid
|
||||
JOIN orders o ON p.pid = o.pid
|
||||
LEFT JOIN sales_seasonality ss ON EXTRACT(MONTH FROM o.date) = ss.month
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '3 months'
|
||||
GROUP BY pc.cat_id
|
||||
),
|
||||
previous_period AS (
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
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 EXTRACT(MONTH FROM o.date) = ss.month
|
||||
WHERE o.canceled = false
|
||||
AND o.date BETWEEN CURRENT_DATE - INTERVAL '15 months'
|
||||
AND CURRENT_DATE - INTERVAL '12 months'
|
||||
GROUP BY pc.cat_id
|
||||
),
|
||||
trend_data AS (
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
EXTRACT(MONTH FROM 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 EXTRACT(MONTH FROM o.date) = ss.month
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '15 months'
|
||||
GROUP BY pc.cat_id, EXTRACT(MONTH FROM 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
|
||||
JOIN products p ON pc.pid = p.pid
|
||||
JOIN orders o ON p.pid = o.pid
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '3 months'
|
||||
GROUP BY pc.cat_id
|
||||
),
|
||||
combined_metrics AS (
|
||||
SELECT
|
||||
COALESCE(cp.cat_id, pp.cat_id) as category_id,
|
||||
CASE
|
||||
WHEN pp.revenue = 0 AND COALESCE(cp.revenue, 0) > 0 THEN 100.0
|
||||
WHEN pp.revenue = 0 OR cp.revenue IS NULL THEN 0.0
|
||||
WHEN ta.trend_slope IS NOT NULL THEN
|
||||
GREATEST(
|
||||
-100.0,
|
||||
LEAST(
|
||||
(ta.trend_slope / NULLIF(ta.avg_daily_revenue, 0)) * 365 * 100,
|
||||
999.99
|
||||
)
|
||||
)
|
||||
ELSE
|
||||
GREATEST(
|
||||
-100.0,
|
||||
LEAST(
|
||||
((COALESCE(cp.revenue, 0) - pp.revenue) /
|
||||
NULLIF(ABS(pp.revenue), 0)) * 100.0,
|
||||
999.99
|
||||
)
|
||||
)
|
||||
END as growth_rate,
|
||||
mc.avg_margin
|
||||
FROM current_period cp
|
||||
FULL OUTER JOIN previous_period pp ON cp.cat_id = pp.cat_id
|
||||
LEFT JOIN trend_analysis ta ON COALESCE(cp.cat_id, pp.cat_id) = ta.cat_id
|
||||
LEFT JOIN margin_calc mc ON COALESCE(cp.cat_id, pp.cat_id) = mc.cat_id
|
||||
)
|
||||
UPDATE category_metrics cm
|
||||
SET
|
||||
growth_rate = CASE
|
||||
WHEN pp.revenue = 0 AND COALESCE(cp.revenue, 0) > 0 THEN 100.0
|
||||
WHEN pp.revenue = 0 OR cp.revenue IS NULL THEN 0.0
|
||||
WHEN ta.trend_slope IS NOT NULL THEN
|
||||
GREATEST(
|
||||
-100.0,
|
||||
LEAST(
|
||||
(ta.trend_slope / NULLIF(ta.avg_daily_revenue, 0)) * 365 * 100,
|
||||
999.99
|
||||
)
|
||||
)
|
||||
ELSE
|
||||
GREATEST(
|
||||
-100.0,
|
||||
LEAST(
|
||||
((COALESCE(cp.revenue, 0) - pp.revenue) /
|
||||
NULLIF(ABS(pp.revenue), 0)) * 100.0,
|
||||
999.99
|
||||
)
|
||||
)
|
||||
END,
|
||||
avg_margin = COALESCE(mc.avg_margin, cm.avg_margin),
|
||||
last_calculated_at = NOW()
|
||||
FROM current_period cp
|
||||
FULL OUTER JOIN previous_period pp ON cp.cat_id = pp.cat_id
|
||||
LEFT JOIN trend_analysis ta ON COALESCE(cp.cat_id, pp.cat_id) = ta.cat_id
|
||||
LEFT JOIN margin_calc mc ON COALESCE(cp.cat_id, pp.cat_id) = mc.cat_id
|
||||
WHERE cm.category_id = COALESCE(cp.cat_id, pp.cat_id)
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.97);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Growth rates calculated, updating time-based metrics',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Calculate time-based metrics
|
||||
await connection.query(`
|
||||
INSERT INTO category_time_metrics (
|
||||
category_id,
|
||||
year,
|
||||
month,
|
||||
product_count,
|
||||
active_products,
|
||||
total_value,
|
||||
total_revenue,
|
||||
avg_margin,
|
||||
turnover_rate
|
||||
)
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
EXTRACT(YEAR FROM o.date::timestamp with time zone) as year,
|
||||
EXTRACT(MONTH FROM o.date::timestamp with time zone) as month,
|
||||
COUNT(DISTINCT p.pid) as product_count,
|
||||
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(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(
|
||||
LEAST(
|
||||
SUM(o.quantity) / NULLIF(AVG(GREATEST(p.stock_quantity, 0)), 0),
|
||||
999.99
|
||||
),
|
||||
0
|
||||
) as turnover_rate
|
||||
FROM product_categories pc
|
||||
JOIN products p ON pc.pid = p.pid
|
||||
JOIN orders o ON p.pid = o.pid
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '12 months'
|
||||
GROUP BY pc.cat_id, EXTRACT(YEAR FROM o.date::timestamp with time zone), EXTRACT(MONTH FROM o.date::timestamp with time zone)
|
||||
ON CONFLICT (category_id, year, month) DO UPDATE
|
||||
SET
|
||||
product_count = EXCLUDED.product_count,
|
||||
active_products = EXCLUDED.active_products,
|
||||
total_value = EXCLUDED.total_value,
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
avg_margin = EXCLUDED.avg_margin,
|
||||
turnover_rate = EXCLUDED.turnover_rate
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.99);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Time-based metrics calculated, updating category-sales metrics',
|
||||
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,
|
||||
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
|
||||
CURRENT_DATE - INTERVAL '30 days' as period_start,
|
||||
CURRENT_DATE as period_end
|
||||
UNION ALL
|
||||
SELECT
|
||||
CURRENT_DATE - INTERVAL '90 days',
|
||||
CURRENT_DATE - INTERVAL '31 days'
|
||||
UNION ALL
|
||||
SELECT
|
||||
CURRENT_DATE - INTERVAL '180 days',
|
||||
CURRENT_DATE - INTERVAL '91 days'
|
||||
UNION ALL
|
||||
SELECT
|
||||
CURRENT_DATE - INTERVAL '365 days',
|
||||
CURRENT_DATE - INTERVAL '181 days'
|
||||
),
|
||||
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 CONFLICT (category_id, brand, period_start, period_end) DO UPDATE
|
||||
SET
|
||||
avg_daily_sales = EXCLUDED.avg_daily_sales,
|
||||
total_sold = EXCLUDED.total_sold,
|
||||
num_products = EXCLUDED.num_products,
|
||||
avg_price = EXCLUDED.avg_price,
|
||||
last_calculated_at = EXCLUDED.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 CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating category metrics');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateCategoryMetrics;
|
||||
214
inventory-server/old/metrics/financial-metrics.js
Normal file
214
inventory-server/old/metrics/financial-metrics.js
Normal file
@@ -0,0 +1,214 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateFinancialMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Financial metrics calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
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) >= CURRENT_DATE - INTERVAL '12 months'
|
||||
`);
|
||||
processedOrders = parseInt(orderCount.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting financial metrics calculation',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// First, calculate beginning inventory values (12 months ago)
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE IF NOT EXISTS temp_beginning_inventory AS
|
||||
WITH beginning_inventory_calc AS (
|
||||
SELECT
|
||||
p.pid,
|
||||
p.stock_quantity as current_quantity,
|
||||
COALESCE(SUM(o.quantity), 0) as sold_quantity,
|
||||
COALESCE(SUM(po.received), 0) as received_quantity,
|
||||
GREATEST(0, (p.stock_quantity + COALESCE(SUM(o.quantity), 0) - COALESCE(SUM(po.received), 0))) as beginning_quantity,
|
||||
p.cost_price
|
||||
FROM
|
||||
products p
|
||||
LEFT JOIN
|
||||
orders o ON p.pid = o.pid
|
||||
AND o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '12 months'::interval
|
||||
LEFT JOIN
|
||||
purchase_orders po ON p.pid = po.pid
|
||||
AND po.received_date IS NOT NULL
|
||||
AND po.received_date >= CURRENT_DATE - INTERVAL '12 months'::interval
|
||||
GROUP BY
|
||||
p.pid, p.stock_quantity, p.cost_price
|
||||
)
|
||||
SELECT
|
||||
pid,
|
||||
beginning_quantity,
|
||||
beginning_quantity * cost_price as beginning_value,
|
||||
current_quantity * cost_price as current_value,
|
||||
((beginning_quantity * cost_price) + (current_quantity * cost_price)) / 2 as average_inventory_value
|
||||
FROM
|
||||
beginning_inventory_calc
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.60);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Beginning inventory values calculated, computing financial metrics',
|
||||
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 financial metrics with optimized query and standard formulas
|
||||
await connection.query(`
|
||||
WITH product_financials AS (
|
||||
SELECT
|
||||
p.pid,
|
||||
COALESCE(bi.average_inventory_value, p.cost_price * p.stock_quantity) as avg_inventory_value,
|
||||
p.cost_price * p.stock_quantity as current_inventory_value,
|
||||
SUM(o.quantity * (o.price - COALESCE(o.discount, 0))) as total_revenue,
|
||||
SUM(o.quantity * COALESCE(o.costeach, 0)) as cost_of_goods_sold,
|
||||
SUM(o.quantity * (o.price - COALESCE(o.discount, 0) - COALESCE(o.costeach, 0))) as gross_profit,
|
||||
MIN(o.date) as first_sale_date,
|
||||
MAX(o.date) as last_sale_date,
|
||||
EXTRACT(DAY FROM (MAX(o.date)::timestamp with time zone - MIN(o.date)::timestamp with time zone)) + 1 as calculation_period_days,
|
||||
COUNT(DISTINCT DATE(o.date)) as active_days
|
||||
FROM products p
|
||||
LEFT JOIN orders o ON p.pid = o.pid
|
||||
LEFT JOIN temp_beginning_inventory bi ON p.pid = bi.pid
|
||||
WHERE o.canceled = false
|
||||
AND DATE(o.date) >= CURRENT_DATE - INTERVAL '12 months'::interval
|
||||
GROUP BY p.pid, p.cost_price, p.stock_quantity, bi.average_inventory_value
|
||||
)
|
||||
UPDATE product_metrics pm
|
||||
SET
|
||||
inventory_value = COALESCE(pf.current_inventory_value, 0)::decimal(10,3),
|
||||
total_revenue = COALESCE(pf.total_revenue, 0)::decimal(10,3),
|
||||
cost_of_goods_sold = COALESCE(pf.cost_of_goods_sold, 0)::decimal(10,3),
|
||||
gross_profit = COALESCE(pf.gross_profit, 0)::decimal(10,3),
|
||||
turnover_rate = CASE
|
||||
WHEN COALESCE(pf.avg_inventory_value, 0) > 0 THEN
|
||||
COALESCE(pf.cost_of_goods_sold, 0) / NULLIF(pf.avg_inventory_value, 0)
|
||||
ELSE 0
|
||||
END::decimal(12,3),
|
||||
gmroi = CASE
|
||||
WHEN COALESCE(pf.avg_inventory_value, 0) > 0 THEN
|
||||
COALESCE(pf.gross_profit, 0) / NULLIF(pf.avg_inventory_value, 0)
|
||||
ELSE 0
|
||||
END::decimal(10,3),
|
||||
last_calculated_at = CURRENT_TIMESTAMP
|
||||
FROM product_financials pf
|
||||
WHERE pm.pid = pf.pid
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.65);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Base financial metrics calculated, updating time aggregates',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Clean up temporary tables
|
||||
await connection.query('DROP TABLE IF EXISTS temp_beginning_inventory');
|
||||
|
||||
// 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 CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating financial metrics');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
try {
|
||||
// Make sure temporary tables are always cleaned up
|
||||
await connection.query('DROP TABLE IF EXISTS temp_beginning_inventory');
|
||||
} catch (err) {
|
||||
console.error('Error cleaning up temp tables:', err);
|
||||
}
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateFinancialMetrics;
|
||||
736
inventory-server/old/metrics/product-metrics.js
Normal file
736
inventory-server/old/metrics/product-metrics.js
Normal file
@@ -0,0 +1,736 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
// Helper function to handle NaN and undefined values
|
||||
function sanitizeValue(value) {
|
||||
if (value === undefined || value === null || Number.isNaN(value)) {
|
||||
return null;
|
||||
}
|
||||
return value;
|
||||
}
|
||||
|
||||
async function calculateProductMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
let connection;
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
const BATCH_SIZE = 5000;
|
||||
|
||||
try {
|
||||
connection = await getConnection();
|
||||
// Skip flags are inherited from the parent scope
|
||||
const SKIP_PRODUCT_BASE_METRICS = 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 = parseInt(productCount.rows[0].count);
|
||||
}
|
||||
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Product metrics calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
}
|
||||
|
||||
// First ensure all products have a metrics record
|
||||
await connection.query(`
|
||||
INSERT INTO product_metrics (pid, last_calculated_at)
|
||||
SELECT pid, NOW()
|
||||
FROM products
|
||||
ON CONFLICT (pid) DO NOTHING
|
||||
`);
|
||||
|
||||
// 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
|
||||
`);
|
||||
|
||||
// Check if threshold data was returned
|
||||
if (!thresholds.rows || thresholds.rows.length === 0) {
|
||||
console.warn('No default thresholds found in the database. Using explicit type casting in the query.');
|
||||
}
|
||||
|
||||
const defaultThresholds = thresholds.rows[0];
|
||||
|
||||
// Get financial calculation configuration parameters
|
||||
const financialConfig = await connection.query(`
|
||||
SELECT
|
||||
order_cost,
|
||||
holding_rate,
|
||||
service_level_z_score,
|
||||
min_reorder_qty,
|
||||
default_reorder_qty,
|
||||
default_safety_stock
|
||||
FROM financial_calc_config
|
||||
WHERE id = 1
|
||||
LIMIT 1
|
||||
`);
|
||||
const finConfig = financialConfig.rows[0] || {
|
||||
order_cost: 25.00,
|
||||
holding_rate: 0.25,
|
||||
service_level_z_score: 1.96,
|
||||
min_reorder_qty: 1,
|
||||
default_reorder_qty: 5,
|
||||
default_safety_stock: 5
|
||||
};
|
||||
|
||||
// Calculate base product metrics
|
||||
if (!SKIP_PRODUCT_BASE_METRICS) {
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting 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),
|
||||
timing: {
|
||||
start_time: new Date(startTime).toISOString(),
|
||||
end_time: new Date().toISOString(),
|
||||
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
|
||||
}
|
||||
});
|
||||
|
||||
// Get order count that will be processed
|
||||
const orderCount = await connection.query(`
|
||||
SELECT COUNT(*) as count
|
||||
FROM orders o
|
||||
WHERE o.canceled = false
|
||||
`);
|
||||
processedOrders = parseInt(orderCount.rows[0].count);
|
||||
|
||||
// Clear temporary tables
|
||||
await connection.query('DROP TABLE IF EXISTS temp_sales_metrics');
|
||||
await connection.query('DROP TABLE IF EXISTS temp_purchase_metrics');
|
||||
|
||||
// Create temp_sales_metrics
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_sales_metrics (
|
||||
pid BIGINT NOT NULL,
|
||||
daily_sales_avg DECIMAL(10,3),
|
||||
weekly_sales_avg DECIMAL(10,3),
|
||||
monthly_sales_avg DECIMAL(10,3),
|
||||
total_revenue DECIMAL(10,3),
|
||||
avg_margin_percent DECIMAL(10,3),
|
||||
first_sale_date DATE,
|
||||
last_sale_date DATE,
|
||||
stddev_daily_sales DECIMAL(10,3),
|
||||
PRIMARY KEY (pid)
|
||||
)
|
||||
`);
|
||||
|
||||
// Create temp_purchase_metrics
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_purchase_metrics (
|
||||
pid BIGINT NOT NULL,
|
||||
avg_lead_time_days DECIMAL(10,2),
|
||||
last_purchase_date DATE,
|
||||
first_received_date DATE,
|
||||
last_received_date DATE,
|
||||
stddev_lead_time_days DECIMAL(10,2),
|
||||
PRIMARY KEY (pid)
|
||||
)
|
||||
`);
|
||||
|
||||
// Populate temp_sales_metrics with base stats and sales averages
|
||||
await connection.query(`
|
||||
INSERT INTO temp_sales_metrics
|
||||
SELECT
|
||||
p.pid,
|
||||
COALESCE(SUM(o.quantity) / NULLIF(COUNT(DISTINCT DATE(o.date)), 0), 0) as daily_sales_avg,
|
||||
COALESCE(SUM(o.quantity) / NULLIF(CEIL(COUNT(DISTINCT DATE(o.date)) / 7), 0), 0) as weekly_sales_avg,
|
||||
COALESCE(SUM(o.quantity) / NULLIF(CEIL(COUNT(DISTINCT DATE(o.date)) / 30), 0), 0) as monthly_sales_avg,
|
||||
COALESCE(SUM(o.quantity * o.price), 0) as total_revenue,
|
||||
CASE
|
||||
WHEN SUM(o.quantity * o.price) > 0
|
||||
THEN ((SUM(o.quantity * o.price) - SUM(o.quantity * p.cost_price)) / SUM(o.quantity * o.price)) * 100
|
||||
ELSE 0
|
||||
END as avg_margin_percent,
|
||||
MIN(o.date) as first_sale_date,
|
||||
MAX(o.date) as last_sale_date,
|
||||
COALESCE(STDDEV_SAMP(daily_qty.quantity), 0) as stddev_daily_sales
|
||||
FROM products p
|
||||
LEFT JOIN orders o ON p.pid = o.pid
|
||||
AND o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '90 days'
|
||||
LEFT JOIN (
|
||||
SELECT
|
||||
pid,
|
||||
DATE(date) as sale_date,
|
||||
SUM(quantity) as quantity
|
||||
FROM orders
|
||||
WHERE canceled = false
|
||||
AND date >= CURRENT_DATE - INTERVAL '90 days'
|
||||
GROUP BY pid, DATE(date)
|
||||
) daily_qty ON p.pid = daily_qty.pid
|
||||
GROUP BY p.pid
|
||||
`);
|
||||
|
||||
// Populate temp_purchase_metrics with timeout protection
|
||||
await Promise.race([
|
||||
connection.query(`
|
||||
INSERT INTO temp_purchase_metrics
|
||||
SELECT
|
||||
p.pid,
|
||||
AVG(
|
||||
CASE
|
||||
WHEN po.received_date IS NOT NULL AND po.date IS NOT NULL
|
||||
THEN EXTRACT(EPOCH FROM (po.received_date::timestamp with time zone - po.date::timestamp with time zone)) / 86400.0
|
||||
ELSE NULL
|
||||
END
|
||||
) as avg_lead_time_days,
|
||||
MAX(po.date) as last_purchase_date,
|
||||
MIN(po.received_date) as first_received_date,
|
||||
MAX(po.received_date) as last_received_date,
|
||||
STDDEV_SAMP(
|
||||
CASE
|
||||
WHEN po.received_date IS NOT NULL AND po.date IS NOT NULL
|
||||
THEN EXTRACT(EPOCH FROM (po.received_date::timestamp with time zone - po.date::timestamp with time zone)) / 86400.0
|
||||
ELSE NULL
|
||||
END
|
||||
) as stddev_lead_time_days
|
||||
FROM products p
|
||||
LEFT JOIN purchase_orders po ON p.pid = po.pid
|
||||
AND po.received_date IS NOT NULL
|
||||
AND po.date IS NOT NULL
|
||||
AND po.date >= CURRENT_DATE - INTERVAL '365 days'
|
||||
GROUP BY p.pid
|
||||
`),
|
||||
new Promise((_, reject) =>
|
||||
setTimeout(() => reject(new Error('Timeout: temp_purchase_metrics query took too long')), 60000)
|
||||
)
|
||||
]).catch(async (err) => {
|
||||
logError(err, 'Error populating temp_purchase_metrics, continuing with empty table');
|
||||
// Create an empty fallback to continue processing
|
||||
await connection.query(`
|
||||
INSERT INTO temp_purchase_metrics
|
||||
SELECT
|
||||
p.pid,
|
||||
30.0 as avg_lead_time_days,
|
||||
NULL as last_purchase_date,
|
||||
NULL as first_received_date,
|
||||
NULL as last_received_date,
|
||||
0.0 as stddev_lead_time_days
|
||||
FROM products p
|
||||
LEFT JOIN temp_purchase_metrics tpm ON p.pid = tpm.pid
|
||||
WHERE tpm.pid IS NULL
|
||||
`);
|
||||
});
|
||||
|
||||
// Process updates in batches
|
||||
let lastPid = 0;
|
||||
let batchCount = 0;
|
||||
const MAX_BATCHES = 1000; // Safety limit for number of batches to prevent infinite loops
|
||||
|
||||
while (batchCount < MAX_BATCHES) {
|
||||
if (isCancelled) break;
|
||||
|
||||
batchCount++;
|
||||
const batch = await connection.query(
|
||||
'SELECT pid FROM products WHERE pid > $1 ORDER BY pid LIMIT $2',
|
||||
[lastPid, BATCH_SIZE]
|
||||
);
|
||||
|
||||
if (batch.rows.length === 0) break;
|
||||
|
||||
// Process the entire batch in a single efficient query
|
||||
const lowStockThreshold = parseInt(defaultThresholds?.low_stock_threshold) || 5;
|
||||
const criticalDays = parseInt(defaultThresholds?.critical_days) || 7;
|
||||
const reorderDays = parseInt(defaultThresholds?.reorder_days) || 14;
|
||||
const overstockDays = parseInt(defaultThresholds?.overstock_days) || 90;
|
||||
const serviceLevel = parseFloat(finConfig?.service_level_z_score) || 1.96;
|
||||
const defaultSafetyStock = parseInt(finConfig?.default_safety_stock) || 5;
|
||||
const defaultReorderQty = parseInt(finConfig?.default_reorder_qty) || 5;
|
||||
const orderCost = parseFloat(finConfig?.order_cost) || 25.00;
|
||||
const holdingRate = parseFloat(finConfig?.holding_rate) || 0.25;
|
||||
const minReorderQty = parseInt(finConfig?.min_reorder_qty) || 1;
|
||||
|
||||
await connection.query(`
|
||||
UPDATE product_metrics pm
|
||||
SET
|
||||
inventory_value = p.stock_quantity * NULLIF(p.cost_price, 0),
|
||||
daily_sales_avg = COALESCE(sm.daily_sales_avg, 0),
|
||||
weekly_sales_avg = COALESCE(sm.weekly_sales_avg, 0),
|
||||
monthly_sales_avg = COALESCE(sm.monthly_sales_avg, 0),
|
||||
total_revenue = COALESCE(sm.total_revenue, 0),
|
||||
avg_margin_percent = COALESCE(sm.avg_margin_percent, 0),
|
||||
first_sale_date = sm.first_sale_date,
|
||||
last_sale_date = sm.last_sale_date,
|
||||
avg_lead_time_days = COALESCE(lm.avg_lead_time_days, 30.0),
|
||||
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,
|
||||
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,
|
||||
stock_status = CASE
|
||||
WHEN p.stock_quantity <= 0 THEN 'Out of Stock'
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 AND p.stock_quantity <= ${lowStockThreshold} THEN 'Low Stock'
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 THEN 'In Stock'
|
||||
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ${criticalDays} THEN 'Critical'
|
||||
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ${reorderDays} THEN 'Reorder'
|
||||
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ${overstockDays} THEN 'Overstocked'
|
||||
ELSE 'Healthy'
|
||||
END,
|
||||
safety_stock = CASE
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 AND COALESCE(lm.avg_lead_time_days, 0) > 0 THEN
|
||||
CEIL(
|
||||
${serviceLevel} * SQRT(
|
||||
GREATEST(0, COALESCE(lm.avg_lead_time_days, 0)) * POWER(COALESCE(sm.stddev_daily_sales, 0), 2) +
|
||||
POWER(COALESCE(sm.daily_sales_avg, 0), 2) * POWER(COALESCE(lm.stddev_lead_time_days, 0), 2)
|
||||
)
|
||||
)
|
||||
ELSE ${defaultSafetyStock}
|
||||
END,
|
||||
reorder_point = CASE
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 THEN
|
||||
CEIL(sm.daily_sales_avg * GREATEST(0, COALESCE(lm.avg_lead_time_days, 30.0))) +
|
||||
(CASE
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 AND COALESCE(lm.avg_lead_time_days, 0) > 0 THEN
|
||||
CEIL(
|
||||
${serviceLevel} * SQRT(
|
||||
GREATEST(0, COALESCE(lm.avg_lead_time_days, 0)) * POWER(COALESCE(sm.stddev_daily_sales, 0), 2) +
|
||||
POWER(COALESCE(sm.daily_sales_avg, 0), 2) * POWER(COALESCE(lm.stddev_lead_time_days, 0), 2)
|
||||
)
|
||||
)
|
||||
ELSE ${defaultSafetyStock}
|
||||
END)
|
||||
ELSE ${lowStockThreshold}
|
||||
END,
|
||||
reorder_qty = CASE
|
||||
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 AND NULLIF(p.cost_price, 0) IS NOT NULL AND NULLIF(p.cost_price, 0) > 0 THEN
|
||||
GREATEST(
|
||||
CEIL(SQRT(
|
||||
(2 * (sm.daily_sales_avg * 365) * ${orderCost}) /
|
||||
NULLIF(p.cost_price * ${holdingRate}, 0)
|
||||
)),
|
||||
${minReorderQty}
|
||||
)
|
||||
ELSE ${defaultReorderQty}
|
||||
END,
|
||||
overstocked_amt = CASE
|
||||
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ${overstockDays}
|
||||
THEN GREATEST(0, p.stock_quantity - CEIL(sm.daily_sales_avg * ${overstockDays}))
|
||||
ELSE 0
|
||||
END,
|
||||
last_calculated_at = NOW()
|
||||
FROM products p
|
||||
LEFT JOIN temp_sales_metrics sm ON p.pid = sm.pid
|
||||
LEFT JOIN temp_purchase_metrics lm ON p.pid = lm.pid
|
||||
WHERE p.pid = ANY($1::BIGINT[])
|
||||
AND pm.pid = p.pid
|
||||
`, [batch.rows.map(row => row.pid)]);
|
||||
|
||||
lastPid = batch.rows[batch.rows.length - 1].pid;
|
||||
processedCount += batch.rows.length;
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Processing base metrics batch',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: estimateRemaining(startTime, processedCount, totalProducts),
|
||||
rate: calculateRate(startTime, processedCount),
|
||||
percentage: ((processedCount / totalProducts) * 100).toFixed(1),
|
||||
timing: {
|
||||
start_time: new Date(startTime).toISOString(),
|
||||
end_time: new Date().toISOString(),
|
||||
elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Add safety check if the loop processed MAX_BATCHES
|
||||
if (batchCount >= MAX_BATCHES) {
|
||||
logError(new Error(`Reached maximum batch count (${MAX_BATCHES}). Process may have entered an infinite loop.`), 'Batch processing safety limit reached');
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate forecast accuracy and bias in batches
|
||||
let forecastPid = 0;
|
||||
while (true) {
|
||||
if (isCancelled) break;
|
||||
|
||||
const forecastBatch = await connection.query(
|
||||
'SELECT pid FROM products WHERE pid > $1 ORDER BY pid LIMIT $2',
|
||||
[forecastPid, BATCH_SIZE]
|
||||
);
|
||||
|
||||
if (forecastBatch.rows.length === 0) break;
|
||||
|
||||
const forecastPidArray = forecastBatch.rows.map(row => row.pid);
|
||||
|
||||
// Use array_to_string to convert the array to a string of comma-separated values
|
||||
await connection.query(`
|
||||
WITH forecast_metrics AS (
|
||||
SELECT
|
||||
sf.pid,
|
||||
AVG(CASE
|
||||
WHEN o.quantity > 0
|
||||
THEN ABS(sf.forecast_quantity - o.quantity) / o.quantity * 100
|
||||
ELSE 100
|
||||
END) as avg_forecast_error,
|
||||
AVG(CASE
|
||||
WHEN o.quantity > 0
|
||||
THEN (sf.forecast_quantity - o.quantity) / o.quantity * 100
|
||||
ELSE 0
|
||||
END) as avg_forecast_bias,
|
||||
MAX(sf.forecast_date) as last_forecast_date
|
||||
FROM sales_forecasts sf
|
||||
JOIN orders o ON sf.pid = o.pid
|
||||
AND DATE(o.date) = sf.forecast_date
|
||||
WHERE o.canceled = false
|
||||
AND sf.forecast_date >= CURRENT_DATE - INTERVAL '90 days'
|
||||
AND sf.pid = ANY('{${forecastPidArray.join(',')}}'::BIGINT[])
|
||||
GROUP BY sf.pid
|
||||
)
|
||||
UPDATE product_metrics pm
|
||||
SET
|
||||
forecast_accuracy = GREATEST(0, 100 - LEAST(fm.avg_forecast_error, 100)),
|
||||
forecast_bias = GREATEST(-100, LEAST(fm.avg_forecast_bias, 100)),
|
||||
last_forecast_date = fm.last_forecast_date,
|
||||
last_calculated_at = NOW()
|
||||
FROM forecast_metrics fm
|
||||
WHERE pm.pid = fm.pid
|
||||
`);
|
||||
|
||||
forecastPid = forecastBatch.rows[forecastBatch.rows.length - 1].pid;
|
||||
}
|
||||
|
||||
// Calculate product time aggregates
|
||||
if (!SKIP_PRODUCT_TIME_AGGREGATES) {
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting product time aggregates calculation',
|
||||
current: processedCount || 0,
|
||||
total: totalProducts || 0,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
|
||||
rate: calculateRate(startTime, processedCount || 0),
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// Note: The time-aggregates calculation has been moved to time-aggregates.js
|
||||
// This module will not duplicate that functionality
|
||||
processedCount = Math.floor(totalProducts * 0.6);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Product time aggregates calculation delegated to time-aggregates module',
|
||||
current: processedCount || 0,
|
||||
total: totalProducts || 0,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
|
||||
rate: calculateRate(startTime, processedCount || 0),
|
||||
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 {
|
||||
processedCount = Math.floor(totalProducts * 0.6);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Skipping product time aggregates calculation',
|
||||
current: processedCount || 0,
|
||||
total: totalProducts || 0,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: estimateRemaining(startTime, processedCount || 0, totalProducts || 0),
|
||||
rate: calculateRate(startTime, processedCount || 0),
|
||||
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 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.rows[0] || { a_threshold: 20, b_threshold: 50 };
|
||||
|
||||
// Extract values and ensure they are valid numbers
|
||||
const aThreshold = parseFloat(abcThresholds.a_threshold) || 20;
|
||||
const bThreshold = parseFloat(abcThresholds.b_threshold) || 50;
|
||||
|
||||
// First, create and populate the rankings table with an index
|
||||
await connection.query('DROP 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)
|
||||
)
|
||||
`);
|
||||
await connection.query('CREATE INDEX ON temp_revenue_ranks (rank_num)');
|
||||
await connection.query('CREATE INDEX ON temp_revenue_ranks (dense_rank_num)');
|
||||
await connection.query('CREATE INDEX ON temp_revenue_ranks (percentile)');
|
||||
|
||||
// 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 = parseInt(rankingCount.rows[0].total_count) || 1;
|
||||
|
||||
// Process updates in batches
|
||||
let abcProcessedCount = 0;
|
||||
const batchSize = 5000;
|
||||
const maxPid = await connection.query('SELECT MAX(pid) as max_pid FROM products');
|
||||
const maxProductId = parseInt(maxPid.rows[0].max_pid);
|
||||
|
||||
while (abcProcessedCount < maxProductId) {
|
||||
if (isCancelled) return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
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.pid > $1
|
||||
AND (pm.abc_class IS NULL
|
||||
OR pm.abc_class !=
|
||||
CASE
|
||||
WHEN tr.pid IS NULL THEN 'C'
|
||||
WHEN tr.percentile <= ${aThreshold} THEN 'A'
|
||||
WHEN tr.percentile <= ${bThreshold} THEN 'B'
|
||||
ELSE 'C'
|
||||
END)
|
||||
ORDER BY pm.pid
|
||||
LIMIT $2
|
||||
`, [abcProcessedCount, batchSize]);
|
||||
|
||||
if (pids.rows.length === 0) break;
|
||||
|
||||
const pidValues = pids.rows.map(row => row.pid);
|
||||
|
||||
await connection.query(`
|
||||
UPDATE product_metrics pm
|
||||
SET abc_class =
|
||||
CASE
|
||||
WHEN tr.pid IS NULL THEN 'C'
|
||||
WHEN tr.percentile <= ${aThreshold} THEN 'A'
|
||||
WHEN tr.percentile <= ${bThreshold} THEN 'B'
|
||||
ELSE 'C'
|
||||
END,
|
||||
last_calculated_at = NOW()
|
||||
FROM (SELECT pid, percentile FROM temp_revenue_ranks) tr
|
||||
WHERE pm.pid = tr.pid AND pm.pid = ANY($1::BIGINT[])
|
||||
OR (pm.pid = ANY($1::BIGINT[]) AND tr.pid IS NULL)
|
||||
`, [pidValues]);
|
||||
|
||||
// Now update turnover rate with proper handling of zero inventory periods
|
||||
await connection.query(`
|
||||
UPDATE product_metrics pm
|
||||
SET
|
||||
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,
|
||||
last_calculated_at = NOW()
|
||||
FROM (
|
||||
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 >= CURRENT_DATE - INTERVAL '90 days'
|
||||
AND o.pid = ANY($1::BIGINT[])
|
||||
GROUP BY o.pid
|
||||
) sales
|
||||
WHERE pm.pid = sales.pid
|
||||
`, [pidValues]);
|
||||
|
||||
abcProcessedCount = pids.rows[pids.rows.length - 1].pid;
|
||||
|
||||
// Calculate progress proportionally to total products
|
||||
processedCount = Math.floor(totalProducts * (0.60 + (abcProcessedCount / maxProductId) * 0.2));
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'ABC classification progress',
|
||||
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 ('product_metrics', NOW())
|
||||
ON CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount || 0,
|
||||
processedOrders: processedOrders || 0,
|
||||
processedPurchaseOrders: 0, // This module doesn't process POs
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating product metrics');
|
||||
throw error;
|
||||
} finally {
|
||||
// Always clean up temporary tables, even if an error occurred
|
||||
if (connection) {
|
||||
try {
|
||||
await connection.query('DROP TABLE IF EXISTS temp_sales_metrics');
|
||||
await connection.query('DROP TABLE IF EXISTS temp_purchase_metrics');
|
||||
} catch (err) {
|
||||
console.error('Error cleaning up temporary tables:', err);
|
||||
}
|
||||
|
||||
// Make sure to release the connection
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function calculateStockStatus(stock, config, daily_sales_avg, weekly_sales_avg, monthly_sales_avg) {
|
||||
if (stock <= 0) {
|
||||
return 'Out of Stock';
|
||||
}
|
||||
|
||||
// Use the most appropriate sales average based on data quality
|
||||
let sales_avg = daily_sales_avg;
|
||||
if (sales_avg === 0) {
|
||||
sales_avg = weekly_sales_avg / 7;
|
||||
}
|
||||
if (sales_avg === 0) {
|
||||
sales_avg = monthly_sales_avg / 30;
|
||||
}
|
||||
|
||||
if (sales_avg === 0) {
|
||||
return stock <= config.low_stock_threshold ? 'Low Stock' : 'In Stock';
|
||||
}
|
||||
|
||||
const days_of_stock = stock / sales_avg;
|
||||
|
||||
if (days_of_stock <= config.critical_days) {
|
||||
return 'Critical';
|
||||
} else if (days_of_stock <= config.reorder_days) {
|
||||
return 'Reorder';
|
||||
} else if (days_of_stock > config.overstock_days) {
|
||||
return 'Overstocked';
|
||||
}
|
||||
|
||||
return 'Healthy';
|
||||
}
|
||||
|
||||
// Note: calculateReorderQuantities function has been removed as its logic has been incorporated
|
||||
// in the main SQL query with configurable parameters
|
||||
|
||||
module.exports = calculateProductMetrics;
|
||||
440
inventory-server/old/metrics/sales-forecasts.js
Normal file
440
inventory-server/old/metrics/sales-forecasts.js
Normal file
@@ -0,0 +1,440 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateSalesForecasts(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Sales forecasts calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
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 >= CURRENT_DATE - INTERVAL '90 days'
|
||||
`);
|
||||
processedOrders = parseInt(orderCount.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting sales forecasts calculation',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// First, create a temporary table for forecast dates
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE IF NOT EXISTS temp_forecast_dates (
|
||||
forecast_date DATE,
|
||||
day_of_week INT,
|
||||
month INT,
|
||||
PRIMARY KEY (forecast_date)
|
||||
)
|
||||
`);
|
||||
|
||||
await connection.query(`
|
||||
INSERT INTO temp_forecast_dates
|
||||
SELECT
|
||||
CURRENT_DATE + (n || ' days')::INTERVAL as forecast_date,
|
||||
EXTRACT(DOW FROM CURRENT_DATE + (n || ' days')::INTERVAL) + 1 as day_of_week,
|
||||
EXTRACT(MONTH FROM CURRENT_DATE + (n || ' days')::INTERVAL) as month
|
||||
FROM (
|
||||
SELECT a.n + b.n * 10 as n
|
||||
FROM
|
||||
(SELECT 0 as n UNION SELECT 1 UNION SELECT 2 UNION SELECT 3 UNION SELECT 4 UNION
|
||||
SELECT 5 UNION SELECT 6 UNION SELECT 7 UNION SELECT 8 UNION SELECT 9) a,
|
||||
(SELECT 0 as n UNION SELECT 1 UNION SELECT 2) b
|
||||
ORDER BY n
|
||||
LIMIT 31
|
||||
) numbers
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.92);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Forecast dates prepared, calculating daily sales stats',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Create temporary table for daily sales stats
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_daily_sales AS
|
||||
SELECT
|
||||
o.pid,
|
||||
EXTRACT(DOW FROM o.date) + 1 as day_of_week,
|
||||
SUM(o.quantity) as daily_quantity,
|
||||
SUM(o.price * o.quantity) as daily_revenue,
|
||||
COUNT(DISTINCT DATE(o.date)) as day_count
|
||||
FROM orders o
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '90 days'
|
||||
GROUP BY o.pid, EXTRACT(DOW FROM o.date) + 1
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.94);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Daily sales stats calculated, preparing product stats',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Create temporary table for product stats
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_product_stats AS
|
||||
SELECT
|
||||
pid,
|
||||
AVG(daily_revenue) as overall_avg_revenue,
|
||||
SUM(day_count) as total_days
|
||||
FROM temp_daily_sales
|
||||
GROUP BY pid
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.96);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Product stats prepared, calculating product-level forecasts',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Calculate product-level forecasts
|
||||
await connection.query(`
|
||||
INSERT INTO sales_forecasts (
|
||||
pid,
|
||||
forecast_date,
|
||||
forecast_quantity,
|
||||
confidence_level,
|
||||
created_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
|
||||
ds.pid,
|
||||
fd.forecast_date,
|
||||
GREATEST(0,
|
||||
ROUND(
|
||||
ds.avg_daily_qty *
|
||||
(1 + COALESCE(sf.seasonality_factor, 0))
|
||||
)
|
||||
) as forecast_quantity,
|
||||
CASE
|
||||
WHEN ds.total_days >= 60 AND ds.daily_variance_ratio < 0.5 THEN 90
|
||||
WHEN ds.total_days >= 60 THEN 85
|
||||
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
|
||||
END as confidence_level,
|
||||
NOW() as created_at
|
||||
FROM daily_stats ds
|
||||
JOIN temp_product_stats ps ON ds.pid = ps.pid
|
||||
CROSS JOIN temp_forecast_dates fd
|
||||
LEFT JOIN sales_seasonality sf ON fd.month = sf.month
|
||||
GROUP BY ds.pid, fd.forecast_date, ps.overall_avg_revenue, sf.seasonality_factor,
|
||||
ds.avg_daily_qty, ds.std_daily_qty, ds.avg_daily_qty, ds.total_days, ds.daily_variance_ratio
|
||||
ON CONFLICT (pid, forecast_date) DO UPDATE
|
||||
SET
|
||||
forecast_quantity = EXCLUDED.forecast_quantity,
|
||||
confidence_level = EXCLUDED.confidence_level,
|
||||
created_at = NOW()
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.98);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Product forecasts calculated, preparing category stats',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Create temporary table for category stats
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_category_sales AS
|
||||
SELECT
|
||||
pc.cat_id,
|
||||
EXTRACT(DOW FROM o.date) + 1 as day_of_week,
|
||||
SUM(o.quantity) as daily_quantity,
|
||||
SUM(o.price * o.quantity) as daily_revenue,
|
||||
COUNT(DISTINCT DATE(o.date)) as day_count
|
||||
FROM orders o
|
||||
JOIN product_categories pc ON o.pid = pc.pid
|
||||
WHERE o.canceled = false
|
||||
AND o.date >= CURRENT_DATE - INTERVAL '90 days'
|
||||
GROUP BY pc.cat_id, EXTRACT(DOW FROM o.date) + 1
|
||||
`);
|
||||
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE temp_category_stats AS
|
||||
SELECT
|
||||
cat_id,
|
||||
AVG(daily_revenue) as overall_avg_revenue,
|
||||
SUM(day_count) as total_days
|
||||
FROM temp_category_sales
|
||||
GROUP BY cat_id
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.99);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Category stats prepared, calculating category-level forecasts',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Calculate category-level forecasts
|
||||
await connection.query(`
|
||||
INSERT INTO category_forecasts (
|
||||
category_id,
|
||||
forecast_date,
|
||||
forecast_units,
|
||||
forecast_revenue,
|
||||
confidence_level,
|
||||
created_at
|
||||
)
|
||||
SELECT
|
||||
cs.cat_id::bigint as category_id,
|
||||
fd.forecast_date,
|
||||
GREATEST(0,
|
||||
ROUND(AVG(cs.daily_quantity) *
|
||||
(1 + COALESCE(sf.seasonality_factor, 0)))
|
||||
) as forecast_units,
|
||||
GREATEST(0,
|
||||
COALESCE(
|
||||
CASE
|
||||
WHEN SUM(cs.day_count) >= 4 THEN AVG(cs.daily_revenue)
|
||||
ELSE ct.overall_avg_revenue
|
||||
END *
|
||||
(1 + COALESCE(sf.seasonality_factor, 0)),
|
||||
0
|
||||
)
|
||||
) as forecast_revenue,
|
||||
CASE
|
||||
WHEN ct.total_days >= 60 THEN 90
|
||||
WHEN ct.total_days >= 30 THEN 80
|
||||
WHEN ct.total_days >= 14 THEN 70
|
||||
ELSE 60
|
||||
END as confidence_level,
|
||||
NOW() as created_at
|
||||
FROM temp_category_sales cs
|
||||
JOIN temp_category_stats ct ON cs.cat_id = ct.cat_id
|
||||
CROSS JOIN temp_forecast_dates fd
|
||||
LEFT JOIN sales_seasonality sf ON fd.month = sf.month
|
||||
GROUP BY
|
||||
cs.cat_id,
|
||||
fd.forecast_date,
|
||||
ct.overall_avg_revenue,
|
||||
ct.total_days,
|
||||
sf.seasonality_factor,
|
||||
sf.month
|
||||
HAVING AVG(cs.daily_quantity) > 0
|
||||
ON CONFLICT (category_id, forecast_date) DO UPDATE
|
||||
SET
|
||||
forecast_units = EXCLUDED.forecast_units,
|
||||
forecast_revenue = EXCLUDED.forecast_revenue,
|
||||
confidence_level = EXCLUDED.confidence_level,
|
||||
created_at = NOW()
|
||||
`);
|
||||
|
||||
// Clean up temporary tables
|
||||
await connection.query(`
|
||||
DROP TABLE IF EXISTS temp_forecast_dates;
|
||||
DROP TABLE IF EXISTS temp_daily_sales;
|
||||
DROP TABLE IF EXISTS temp_product_stats;
|
||||
DROP TABLE IF EXISTS temp_category_sales;
|
||||
DROP TABLE IF EXISTS temp_category_stats;
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 1.0);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Category forecasts calculated and temporary tables cleaned up',
|
||||
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 ('sales_forecasts', NOW())
|
||||
ON CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating sales forecasts');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
try {
|
||||
// Ensure temporary tables are cleaned up
|
||||
await connection.query(`
|
||||
DROP TABLE IF EXISTS temp_forecast_dates;
|
||||
DROP TABLE IF EXISTS temp_daily_sales;
|
||||
DROP TABLE IF EXISTS temp_product_stats;
|
||||
DROP TABLE IF EXISTS temp_category_sales;
|
||||
DROP TABLE IF EXISTS temp_category_stats;
|
||||
`);
|
||||
} catch (err) {
|
||||
console.error('Error cleaning up temporary tables:', err);
|
||||
}
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateSalesForecasts;
|
||||
344
inventory-server/old/metrics/time-aggregates.js
Normal file
344
inventory-server/old/metrics/time-aggregates.js
Normal file
@@ -0,0 +1,344 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateTimeAggregates(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Time aggregates calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
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 = parseInt(orderCount.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting time aggregates calculation',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// Create a temporary table for end-of-month inventory values
|
||||
await connection.query(`
|
||||
CREATE TEMPORARY TABLE IF NOT EXISTS temp_monthly_inventory AS
|
||||
WITH months AS (
|
||||
-- Generate all year/month combinations for the last 12 months
|
||||
SELECT
|
||||
EXTRACT(YEAR FROM month_date)::INTEGER as year,
|
||||
EXTRACT(MONTH FROM month_date)::INTEGER as month,
|
||||
month_date as start_date,
|
||||
(month_date + INTERVAL '1 month'::interval - INTERVAL '1 day'::interval)::DATE as end_date
|
||||
FROM (
|
||||
SELECT generate_series(
|
||||
DATE_TRUNC('month', CURRENT_DATE - INTERVAL '12 months'::interval)::DATE,
|
||||
DATE_TRUNC('month', CURRENT_DATE)::DATE,
|
||||
INTERVAL '1 month'::interval
|
||||
) as month_date
|
||||
) dates
|
||||
),
|
||||
monthly_inventory_calc AS (
|
||||
SELECT
|
||||
p.pid,
|
||||
m.year,
|
||||
m.month,
|
||||
m.end_date,
|
||||
p.stock_quantity as current_quantity,
|
||||
-- Calculate sold during period (before end_date)
|
||||
COALESCE(SUM(
|
||||
CASE
|
||||
WHEN o.date <= m.end_date THEN o.quantity
|
||||
ELSE 0
|
||||
END
|
||||
), 0) as sold_after_end_date,
|
||||
-- Calculate received during period (before end_date)
|
||||
COALESCE(SUM(
|
||||
CASE
|
||||
WHEN po.received_date <= m.end_date THEN po.received
|
||||
ELSE 0
|
||||
END
|
||||
), 0) as received_after_end_date,
|
||||
p.cost_price
|
||||
FROM
|
||||
products p
|
||||
CROSS JOIN
|
||||
months m
|
||||
LEFT JOIN
|
||||
orders o ON p.pid = o.pid
|
||||
AND o.canceled = false
|
||||
AND o.date > m.end_date
|
||||
AND o.date <= CURRENT_DATE
|
||||
LEFT JOIN
|
||||
purchase_orders po ON p.pid = po.pid
|
||||
AND po.received_date IS NOT NULL
|
||||
AND po.received_date > m.end_date
|
||||
AND po.received_date <= CURRENT_DATE
|
||||
GROUP BY
|
||||
p.pid, m.year, m.month, m.end_date, p.stock_quantity, p.cost_price
|
||||
)
|
||||
SELECT
|
||||
pid,
|
||||
year,
|
||||
month,
|
||||
-- End of month quantity = current quantity - sold after + received after
|
||||
GREATEST(0, current_quantity - sold_after_end_date + received_after_end_date) as end_of_month_quantity,
|
||||
-- End of month inventory value
|
||||
GREATEST(0, current_quantity - sold_after_end_date + received_after_end_date) * cost_price as end_of_month_value,
|
||||
cost_price
|
||||
FROM
|
||||
monthly_inventory_calc
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.40);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Monthly inventory values calculated, processing time aggregates',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// Initial insert of time-based aggregates
|
||||
await connection.query(`
|
||||
INSERT INTO product_time_aggregates (
|
||||
pid,
|
||||
year,
|
||||
month,
|
||||
total_quantity_sold,
|
||||
total_revenue,
|
||||
total_cost,
|
||||
order_count,
|
||||
stock_received,
|
||||
stock_ordered,
|
||||
avg_price,
|
||||
profit_margin,
|
||||
inventory_value,
|
||||
gmroi
|
||||
)
|
||||
WITH monthly_sales AS (
|
||||
SELECT
|
||||
o.pid,
|
||||
EXTRACT(YEAR FROM o.date::timestamp with time zone)::INTEGER as year,
|
||||
EXTRACT(MONTH FROM o.date::timestamp with time zone)::INTEGER as month,
|
||||
SUM(o.quantity) as total_quantity_sold,
|
||||
SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) as total_revenue,
|
||||
SUM(COALESCE(o.costeach, 0) * o.quantity) as total_cost,
|
||||
COUNT(DISTINCT o.order_number) as order_count,
|
||||
AVG(o.price - COALESCE(o.discount, 0)) as avg_price,
|
||||
CASE
|
||||
WHEN SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) > 0
|
||||
THEN ((SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) - SUM(COALESCE(o.costeach, 0) * o.quantity))
|
||||
/ SUM((o.price - COALESCE(o.discount, 0)) * o.quantity)) * 100
|
||||
ELSE 0
|
||||
END as profit_margin,
|
||||
COUNT(DISTINCT DATE(o.date)) as active_days
|
||||
FROM orders o
|
||||
JOIN products p ON o.pid = p.pid
|
||||
WHERE o.canceled = false
|
||||
GROUP BY o.pid, EXTRACT(YEAR FROM o.date::timestamp with time zone), EXTRACT(MONTH FROM o.date::timestamp with time zone)
|
||||
),
|
||||
monthly_stock AS (
|
||||
SELECT
|
||||
pid,
|
||||
EXTRACT(YEAR FROM date::timestamp with time zone)::INTEGER as year,
|
||||
EXTRACT(MONTH FROM date::timestamp with time zone)::INTEGER as month,
|
||||
SUM(received) as stock_received,
|
||||
SUM(ordered) as stock_ordered
|
||||
FROM purchase_orders
|
||||
GROUP BY pid, EXTRACT(YEAR FROM date::timestamp with time zone), EXTRACT(MONTH FROM date::timestamp with time zone)
|
||||
)
|
||||
SELECT
|
||||
COALESCE(s.pid, ms.pid, mi.pid) as pid,
|
||||
COALESCE(s.year, ms.year, mi.year) as year,
|
||||
COALESCE(s.month, ms.month, mi.month) as month,
|
||||
COALESCE(s.total_quantity_sold, 0)::INTEGER as total_quantity_sold,
|
||||
COALESCE(s.total_revenue, 0)::DECIMAL(10,3) as total_revenue,
|
||||
COALESCE(s.total_cost, 0)::DECIMAL(10,3) as total_cost,
|
||||
COALESCE(s.order_count, 0)::INTEGER as order_count,
|
||||
COALESCE(ms.stock_received, 0)::INTEGER as stock_received,
|
||||
COALESCE(ms.stock_ordered, 0)::INTEGER as stock_ordered,
|
||||
COALESCE(s.avg_price, 0)::DECIMAL(10,3) as avg_price,
|
||||
COALESCE(s.profit_margin, 0)::DECIMAL(10,3) as profit_margin,
|
||||
COALESCE(mi.end_of_month_value, 0)::DECIMAL(10,3) as inventory_value,
|
||||
CASE
|
||||
WHEN COALESCE(mi.end_of_month_value, 0) > 0
|
||||
THEN (COALESCE(s.total_revenue, 0) - COALESCE(s.total_cost, 0))
|
||||
/ NULLIF(COALESCE(mi.end_of_month_value, 0), 0)
|
||||
ELSE 0
|
||||
END::DECIMAL(10,3) as gmroi
|
||||
FROM (
|
||||
SELECT * FROM monthly_sales s
|
||||
UNION ALL
|
||||
SELECT
|
||||
pid,
|
||||
year,
|
||||
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,
|
||||
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
|
||||
)
|
||||
UNION ALL
|
||||
SELECT
|
||||
pid,
|
||||
year,
|
||||
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,
|
||||
0 as active_days
|
||||
FROM temp_monthly_inventory mi
|
||||
WHERE NOT EXISTS (
|
||||
SELECT 1 FROM monthly_sales s3
|
||||
WHERE s3.pid = mi.pid
|
||||
AND s3.year = mi.year
|
||||
AND s3.month = mi.month
|
||||
)
|
||||
AND NOT EXISTS (
|
||||
SELECT 1 FROM monthly_stock ms3
|
||||
WHERE ms3.pid = mi.pid
|
||||
AND ms3.year = mi.year
|
||||
AND ms3.month = mi.month
|
||||
)
|
||||
) s
|
||||
LEFT JOIN monthly_stock ms
|
||||
ON s.pid = ms.pid
|
||||
AND s.year = ms.year
|
||||
AND s.month = ms.month
|
||||
LEFT JOIN temp_monthly_inventory mi
|
||||
ON s.pid = mi.pid
|
||||
AND s.year = mi.year
|
||||
AND s.month = mi.month
|
||||
ON CONFLICT (pid, year, month) DO UPDATE
|
||||
SET
|
||||
total_quantity_sold = EXCLUDED.total_quantity_sold,
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
total_cost = EXCLUDED.total_cost,
|
||||
order_count = EXCLUDED.order_count,
|
||||
stock_received = EXCLUDED.stock_received,
|
||||
stock_ordered = EXCLUDED.stock_ordered,
|
||||
avg_price = EXCLUDED.avg_price,
|
||||
profit_margin = EXCLUDED.profit_margin,
|
||||
inventory_value = EXCLUDED.inventory_value,
|
||||
gmroi = EXCLUDED.gmroi
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.60);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Base time aggregates 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 (isCancelled) return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
// Clean up temporary tables
|
||||
await connection.query('DROP TABLE IF EXISTS temp_monthly_inventory');
|
||||
|
||||
// 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 CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders: 0,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating time aggregates');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
try {
|
||||
// Ensure temporary tables are cleaned up
|
||||
await connection.query('DROP TABLE IF EXISTS temp_monthly_inventory');
|
||||
} catch (err) {
|
||||
console.error('Error cleaning up temporary tables:', err);
|
||||
}
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateTimeAggregates;
|
||||
39
inventory-server/old/metrics/utils/db.js
Normal file
39
inventory-server/old/metrics/utils/db.js
Normal file
@@ -0,0 +1,39 @@
|
||||
const { Pool } = require('pg');
|
||||
const path = require('path');
|
||||
require('dotenv').config({ path: path.resolve(__dirname, '../../..', '.env') });
|
||||
|
||||
// Database configuration
|
||||
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,
|
||||
ssl: process.env.DB_SSL === 'true',
|
||||
// Add performance optimizations
|
||||
max: 10, // connection pool max size
|
||||
idleTimeoutMillis: 30000,
|
||||
connectionTimeoutMillis: 60000
|
||||
};
|
||||
|
||||
// Create a single pool instance to be reused
|
||||
const pool = new Pool(dbConfig);
|
||||
|
||||
// Add event handlers for pool
|
||||
pool.on('error', (err, client) => {
|
||||
console.error('Unexpected error on idle client', err);
|
||||
});
|
||||
|
||||
async function getConnection() {
|
||||
return await pool.connect();
|
||||
}
|
||||
|
||||
async function closePool() {
|
||||
await pool.end();
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
dbConfig,
|
||||
getConnection,
|
||||
closePool
|
||||
};
|
||||
158
inventory-server/old/metrics/utils/progress.js
Normal file
158
inventory-server/old/metrics/utils/progress.js
Normal file
@@ -0,0 +1,158 @@
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
// Helper function to format elapsed time
|
||||
function formatElapsedTime(elapsed) {
|
||||
// If elapsed is a timestamp, convert to elapsed milliseconds
|
||||
if (elapsed instanceof Date || elapsed > 1000000000000) {
|
||||
elapsed = Date.now() - elapsed;
|
||||
} else {
|
||||
// If elapsed is in seconds, convert to milliseconds
|
||||
elapsed = elapsed * 1000;
|
||||
}
|
||||
|
||||
const seconds = Math.floor(elapsed / 1000);
|
||||
const minutes = Math.floor(seconds / 60);
|
||||
const hours = Math.floor(minutes / 60);
|
||||
|
||||
if (hours > 0) {
|
||||
return `${hours}h ${minutes % 60}m`;
|
||||
} else if (minutes > 0) {
|
||||
return `${minutes}m ${seconds % 60}s`;
|
||||
} else {
|
||||
return `${seconds}s`;
|
||||
}
|
||||
}
|
||||
|
||||
// Helper function to estimate remaining time
|
||||
function estimateRemaining(startTime, current, total) {
|
||||
if (current === 0) return null;
|
||||
const elapsed = Date.now() - startTime;
|
||||
const rate = current / elapsed;
|
||||
const remaining = (total - current) / rate;
|
||||
|
||||
const minutes = Math.floor(remaining / 60000);
|
||||
const seconds = Math.floor((remaining % 60000) / 1000);
|
||||
|
||||
if (minutes > 0) {
|
||||
return `${minutes}m ${seconds}s`;
|
||||
} else {
|
||||
return `${seconds}s`;
|
||||
}
|
||||
}
|
||||
|
||||
// Helper function to calculate rate
|
||||
function calculateRate(startTime, current) {
|
||||
const elapsed = (Date.now() - startTime) / 1000; // Convert to seconds
|
||||
return elapsed > 0 ? Math.round(current / elapsed) : 0;
|
||||
}
|
||||
|
||||
// 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');
|
||||
const STATUS_FILE = path.join(LOG_DIR, 'metrics-status.json');
|
||||
|
||||
// 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: ${error.stack}\n\n`;
|
||||
|
||||
// Log to error file
|
||||
fs.appendFileSync(ERROR_LOG, errorMessage);
|
||||
|
||||
// Also log to console
|
||||
console.error(`\n${context}\nError: ${error.message}`);
|
||||
}
|
||||
|
||||
// Helper function to log import progress
|
||||
function logImport(message) {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logMessage = `[${timestamp}] ${message}\n`;
|
||||
fs.appendFileSync(IMPORT_LOG, logMessage);
|
||||
}
|
||||
|
||||
// Helper function to output progress
|
||||
function outputProgress(data) {
|
||||
// Save progress to file for resumption
|
||||
saveProgress(data);
|
||||
// Format as SSE event
|
||||
const event = {
|
||||
progress: data
|
||||
};
|
||||
// Always send to stdout for frontend
|
||||
process.stdout.write(JSON.stringify(event) + '\n');
|
||||
|
||||
// Log significant events to disk
|
||||
const isSignificant =
|
||||
// Operation starts
|
||||
(data.operation && !data.current) ||
|
||||
// Operation completions and errors
|
||||
data.status === 'complete' ||
|
||||
data.status === 'error' ||
|
||||
// Major phase changes
|
||||
data.operation?.includes('Starting ABC classification') ||
|
||||
data.operation?.includes('Starting time-based aggregates') ||
|
||||
data.operation?.includes('Starting vendor metrics');
|
||||
|
||||
if (isSignificant) {
|
||||
logImport(`${data.operation || 'Operation'}${data.message ? ': ' + data.message : ''}${data.error ? ' Error: ' + data.error : ''}${data.status ? ' Status: ' + data.status : ''}`);
|
||||
}
|
||||
}
|
||||
|
||||
function saveProgress(progress) {
|
||||
try {
|
||||
fs.writeFileSync(STATUS_FILE, JSON.stringify({
|
||||
...progress,
|
||||
timestamp: Date.now()
|
||||
}));
|
||||
} catch (err) {
|
||||
console.error('Failed to save progress:', err);
|
||||
}
|
||||
}
|
||||
|
||||
function clearProgress() {
|
||||
try {
|
||||
if (fs.existsSync(STATUS_FILE)) {
|
||||
fs.unlinkSync(STATUS_FILE);
|
||||
}
|
||||
} catch (err) {
|
||||
console.error('Failed to clear progress:', err);
|
||||
}
|
||||
}
|
||||
|
||||
function getProgress() {
|
||||
try {
|
||||
if (fs.existsSync(STATUS_FILE)) {
|
||||
const progress = JSON.parse(fs.readFileSync(STATUS_FILE, 'utf8'));
|
||||
// Check if the progress is still valid (less than 1 hour old)
|
||||
if (progress.timestamp && Date.now() - progress.timestamp < 3600000) {
|
||||
return progress;
|
||||
} else {
|
||||
// Clear old progress
|
||||
clearProgress();
|
||||
}
|
||||
}
|
||||
} catch (err) {
|
||||
console.error('Failed to read progress:', err);
|
||||
clearProgress();
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
formatElapsedTime,
|
||||
estimateRemaining,
|
||||
calculateRate,
|
||||
logError,
|
||||
logImport,
|
||||
outputProgress,
|
||||
saveProgress,
|
||||
clearProgress,
|
||||
getProgress
|
||||
};
|
||||
378
inventory-server/old/metrics/vendor-metrics.js
Normal file
378
inventory-server/old/metrics/vendor-metrics.js
Normal file
@@ -0,0 +1,378 @@
|
||||
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
|
||||
const { getConnection } = require('./utils/db');
|
||||
|
||||
async function calculateVendorMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
|
||||
const connection = await getConnection();
|
||||
let success = false;
|
||||
let processedOrders = 0;
|
||||
let processedPurchaseOrders = 0;
|
||||
|
||||
try {
|
||||
if (isCancelled) {
|
||||
outputProgress({
|
||||
status: 'cancelled',
|
||||
operation: 'Vendor metrics calculation cancelled',
|
||||
current: processedCount,
|
||||
total: totalProducts,
|
||||
elapsed: formatElapsedTime(startTime),
|
||||
remaining: null,
|
||||
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)
|
||||
}
|
||||
});
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders,
|
||||
success
|
||||
};
|
||||
}
|
||||
|
||||
// Get counts of records that will be processed
|
||||
const [orderCountResult, poCountResult] = 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 = parseInt(orderCountResult.rows[0].count);
|
||||
processedPurchaseOrders = parseInt(poCountResult.rows[0].count);
|
||||
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Starting vendor metrics calculation',
|
||||
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)
|
||||
}
|
||||
});
|
||||
|
||||
// First ensure all vendors exist in vendor_details
|
||||
await connection.query(`
|
||||
INSERT INTO vendor_details (vendor, status, created_at, updated_at)
|
||||
SELECT DISTINCT
|
||||
vendor,
|
||||
'active' as status,
|
||||
NOW() as created_at,
|
||||
NOW() as updated_at
|
||||
FROM products
|
||||
WHERE vendor IS NOT NULL
|
||||
ON CONFLICT (vendor) DO NOTHING
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.8);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Vendor details updated, calculating metrics',
|
||||
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,
|
||||
success
|
||||
};
|
||||
|
||||
// Now calculate vendor metrics
|
||||
await connection.query(`
|
||||
INSERT INTO vendor_metrics (
|
||||
vendor,
|
||||
total_revenue,
|
||||
total_orders,
|
||||
total_late_orders,
|
||||
avg_lead_time_days,
|
||||
on_time_delivery_rate,
|
||||
order_fill_rate,
|
||||
avg_order_value,
|
||||
active_products,
|
||||
total_products,
|
||||
total_purchase_value,
|
||||
avg_margin_percent,
|
||||
status,
|
||||
last_calculated_at
|
||||
)
|
||||
WITH vendor_sales AS (
|
||||
SELECT
|
||||
p.vendor,
|
||||
SUM(o.quantity * o.price) as total_revenue,
|
||||
COUNT(DISTINCT o.id) as total_orders,
|
||||
COUNT(DISTINCT p.pid) as active_products,
|
||||
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 >= CURRENT_DATE - INTERVAL '12 months'
|
||||
GROUP BY p.vendor
|
||||
),
|
||||
vendor_po AS (
|
||||
SELECT
|
||||
p.vendor,
|
||||
COUNT(DISTINCT CASE WHEN po.receiving_status = 40 THEN po.id END) as received_orders,
|
||||
COUNT(DISTINCT po.id) as total_orders,
|
||||
AVG(CASE
|
||||
WHEN po.receiving_status = 40
|
||||
AND po.received_date IS NOT NULL
|
||||
AND po.date IS NOT NULL
|
||||
THEN EXTRACT(EPOCH FROM (po.received_date::timestamp with time zone - po.date::timestamp with time zone)) / 86400.0
|
||||
ELSE NULL
|
||||
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 >= CURRENT_DATE - INTERVAL '12 months'
|
||||
GROUP BY p.vendor
|
||||
),
|
||||
vendor_products AS (
|
||||
SELECT
|
||||
vendor,
|
||||
COUNT(DISTINCT pid) as total_products
|
||||
FROM products
|
||||
GROUP BY vendor
|
||||
)
|
||||
SELECT
|
||||
vs.vendor,
|
||||
COALESCE(vs.total_revenue, 0) as total_revenue,
|
||||
COALESCE(vp.total_orders, 0) as total_orders,
|
||||
COALESCE(vp.total_orders - vp.received_orders, 0) as total_late_orders,
|
||||
COALESCE(vp.avg_lead_time_days, 0) as avg_lead_time_days,
|
||||
CASE
|
||||
WHEN vp.total_orders > 0
|
||||
THEN (vp.received_orders / vp.total_orders) * 100
|
||||
ELSE 0
|
||||
END as on_time_delivery_rate,
|
||||
CASE
|
||||
WHEN vp.total_orders > 0
|
||||
THEN (vp.received_orders / vp.total_orders) * 100
|
||||
ELSE 0
|
||||
END as order_fill_rate,
|
||||
CASE
|
||||
WHEN vs.total_orders > 0
|
||||
THEN vs.total_revenue / vs.total_orders
|
||||
ELSE 0
|
||||
END as avg_order_value,
|
||||
COALESCE(vs.active_products, 0) as active_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,
|
||||
NOW() as last_calculated_at
|
||||
FROM vendor_sales vs
|
||||
LEFT JOIN vendor_po vp ON vs.vendor = vp.vendor
|
||||
LEFT JOIN vendor_products vpr ON vs.vendor = vpr.vendor
|
||||
WHERE vs.vendor IS NOT NULL
|
||||
ON CONFLICT (vendor) DO UPDATE
|
||||
SET
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
total_orders = EXCLUDED.total_orders,
|
||||
total_late_orders = EXCLUDED.total_late_orders,
|
||||
avg_lead_time_days = EXCLUDED.avg_lead_time_days,
|
||||
on_time_delivery_rate = EXCLUDED.on_time_delivery_rate,
|
||||
order_fill_rate = EXCLUDED.order_fill_rate,
|
||||
avg_order_value = EXCLUDED.avg_order_value,
|
||||
active_products = EXCLUDED.active_products,
|
||||
total_products = EXCLUDED.total_products,
|
||||
total_purchase_value = EXCLUDED.total_purchase_value,
|
||||
avg_margin_percent = EXCLUDED.avg_margin_percent,
|
||||
status = EXCLUDED.status,
|
||||
last_calculated_at = EXCLUDED.last_calculated_at
|
||||
`);
|
||||
|
||||
processedCount = Math.floor(totalProducts * 0.9);
|
||||
outputProgress({
|
||||
status: 'running',
|
||||
operation: 'Vendor metrics calculated, updating time-based metrics',
|
||||
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,
|
||||
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,
|
||||
EXTRACT(YEAR FROM o.date::timestamp with time zone) as year,
|
||||
EXTRACT(MONTH FROM o.date::timestamp with time zone) 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 >= CURRENT_DATE - INTERVAL '12 months'
|
||||
AND p.vendor IS NOT NULL
|
||||
GROUP BY p.vendor, EXTRACT(YEAR FROM o.date::timestamp with time zone), EXTRACT(MONTH FROM o.date::timestamp with time zone)
|
||||
),
|
||||
monthly_po AS (
|
||||
SELECT
|
||||
p.vendor,
|
||||
EXTRACT(YEAR FROM po.date::timestamp with time zone) as year,
|
||||
EXTRACT(MONTH FROM po.date::timestamp with time zone) 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
|
||||
AND po.received_date IS NOT NULL
|
||||
AND po.date IS NOT NULL
|
||||
THEN EXTRACT(EPOCH FROM (po.received_date::timestamp with time zone - po.date::timestamp with time zone)) / 86400.0
|
||||
ELSE NULL
|
||||
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 >= CURRENT_DATE - INTERVAL '12 months'
|
||||
AND p.vendor IS NOT NULL
|
||||
GROUP BY p.vendor, EXTRACT(YEAR FROM po.date::timestamp with time zone), EXTRACT(MONTH FROM po.date::timestamp with time zone)
|
||||
)
|
||||
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 CONFLICT (vendor, year, month) DO UPDATE
|
||||
SET
|
||||
total_orders = EXCLUDED.total_orders,
|
||||
late_orders = EXCLUDED.late_orders,
|
||||
avg_lead_time_days = EXCLUDED.avg_lead_time_days,
|
||||
total_purchase_value = EXCLUDED.total_purchase_value,
|
||||
total_revenue = EXCLUDED.total_revenue,
|
||||
avg_margin_percent = EXCLUDED.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 CONFLICT (module_name) DO UPDATE
|
||||
SET last_calculation_timestamp = NOW()
|
||||
`);
|
||||
|
||||
return {
|
||||
processedProducts: processedCount,
|
||||
processedOrders,
|
||||
processedPurchaseOrders,
|
||||
success
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
success = false;
|
||||
logError(error, 'Error calculating vendor metrics');
|
||||
throw error;
|
||||
} finally {
|
||||
if (connection) {
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = calculateVendorMetrics;
|
||||
378
inventory-server/old/reset-metrics.js
Normal file
378
inventory-server/old/reset-metrics.js
Normal file
@@ -0,0 +1,378 @@
|
||||
const { Client } = require('pg');
|
||||
const path = require('path');
|
||||
const fs = require('fs');
|
||||
require('dotenv').config({ path: path.resolve(__dirname, '../.env') });
|
||||
|
||||
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 outputProgress(data) {
|
||||
if (!data.status) {
|
||||
data = {
|
||||
status: 'running',
|
||||
...data
|
||||
};
|
||||
}
|
||||
console.log(JSON.stringify(data));
|
||||
}
|
||||
|
||||
// Explicitly define all metrics-related tables in dependency order
|
||||
const METRICS_TABLES = [
|
||||
'brand_metrics',
|
||||
'brand_time_metrics',
|
||||
'category_forecasts',
|
||||
'category_metrics',
|
||||
'category_sales_metrics',
|
||||
'category_time_metrics',
|
||||
'product_metrics',
|
||||
'product_time_aggregates',
|
||||
'sales_forecasts',
|
||||
'temp_purchase_metrics',
|
||||
'temp_sales_metrics',
|
||||
'vendor_metrics',
|
||||
'vendor_time_metrics',
|
||||
'vendor_details'
|
||||
];
|
||||
|
||||
// Tables to always protect from being dropped
|
||||
const PROTECTED_TABLES = [
|
||||
'users',
|
||||
'permissions',
|
||||
'user_permissions',
|
||||
'calculate_history',
|
||||
'import_history',
|
||||
'ai_prompts',
|
||||
'ai_validation_performance',
|
||||
'templates',
|
||||
'reusable_images'
|
||||
];
|
||||
|
||||
// Split SQL into individual statements
|
||||
function splitSQLStatements(sql) {
|
||||
sql = sql.replace(/\r\n/g, '\n');
|
||||
let statements = [];
|
||||
let currentStatement = '';
|
||||
let inString = false;
|
||||
let stringChar = '';
|
||||
|
||||
for (let i = 0; i < sql.length; i++) {
|
||||
const char = sql[i];
|
||||
const nextChar = sql[i + 1] || '';
|
||||
|
||||
if ((char === "'" || char === '"') && sql[i - 1] !== '\\') {
|
||||
if (!inString) {
|
||||
inString = true;
|
||||
stringChar = char;
|
||||
} else if (char === stringChar) {
|
||||
inString = false;
|
||||
}
|
||||
}
|
||||
|
||||
if (!inString && char === '-' && nextChar === '-') {
|
||||
while (i < sql.length && sql[i] !== '\n') i++;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (!inString && char === '/' && nextChar === '*') {
|
||||
i += 2;
|
||||
while (i < sql.length && (sql[i] !== '*' || sql[i + 1] !== '/')) i++;
|
||||
i++;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (!inString && char === ';') {
|
||||
if (currentStatement.trim()) {
|
||||
statements.push(currentStatement.trim());
|
||||
}
|
||||
currentStatement = '';
|
||||
} else {
|
||||
currentStatement += char;
|
||||
}
|
||||
}
|
||||
|
||||
if (currentStatement.trim()) {
|
||||
statements.push(currentStatement.trim());
|
||||
}
|
||||
|
||||
return statements;
|
||||
}
|
||||
|
||||
async function resetMetrics() {
|
||||
let client;
|
||||
try {
|
||||
outputProgress({
|
||||
operation: 'Starting metrics reset',
|
||||
message: 'Connecting to database...'
|
||||
});
|
||||
|
||||
client = new Client(dbConfig);
|
||||
await client.connect();
|
||||
|
||||
// Explicitly begin a transaction
|
||||
await client.query('BEGIN');
|
||||
|
||||
// First verify current state
|
||||
const initialTables = await client.query(`
|
||||
SELECT tablename as name
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
AND tablename = ANY($1)
|
||||
AND tablename NOT IN (SELECT unnest($2::text[]))
|
||||
`, [METRICS_TABLES, PROTECTED_TABLES]);
|
||||
|
||||
outputProgress({
|
||||
operation: 'Initial state',
|
||||
message: `Found ${initialTables.rows.length} existing metrics tables: ${initialTables.rows.map(t => t.name).join(', ')}`
|
||||
});
|
||||
|
||||
// Disable foreign key checks at the start
|
||||
await client.query('SET session_replication_role = \'replica\'');
|
||||
|
||||
// Drop all metrics tables in reverse order to handle dependencies
|
||||
outputProgress({
|
||||
operation: 'Dropping metrics tables',
|
||||
message: 'Removing existing metrics tables...'
|
||||
});
|
||||
|
||||
for (const table of [...METRICS_TABLES].reverse()) {
|
||||
// Skip protected tables
|
||||
if (PROTECTED_TABLES.includes(table)) {
|
||||
outputProgress({
|
||||
operation: 'Protected table',
|
||||
message: `Skipping protected table: ${table}`
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
try {
|
||||
// Use NOWAIT to avoid hanging if there's a lock
|
||||
await client.query(`DROP TABLE IF EXISTS "${table}" CASCADE`);
|
||||
|
||||
// Verify the table was actually dropped
|
||||
const checkDrop = await client.query(`
|
||||
SELECT COUNT(*) as count
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
AND tablename = $1
|
||||
`, [table]);
|
||||
|
||||
if (parseInt(checkDrop.rows[0].count) > 0) {
|
||||
throw new Error(`Failed to drop table ${table} - table still exists`);
|
||||
}
|
||||
|
||||
outputProgress({
|
||||
operation: 'Table dropped',
|
||||
message: `Successfully dropped table: ${table}`
|
||||
});
|
||||
|
||||
// Commit after each table drop to ensure locks are released
|
||||
await client.query('COMMIT');
|
||||
// Start a new transaction for the next table
|
||||
await client.query('BEGIN');
|
||||
// Re-disable foreign key constraints for the new transaction
|
||||
await client.query('SET session_replication_role = \'replica\'');
|
||||
} catch (err) {
|
||||
outputProgress({
|
||||
status: 'error',
|
||||
operation: 'Drop table error',
|
||||
message: `Error dropping table ${table}: ${err.message}`
|
||||
});
|
||||
await client.query('ROLLBACK');
|
||||
// Re-start transaction for next table
|
||||
await client.query('BEGIN');
|
||||
await client.query('SET session_replication_role = \'replica\'');
|
||||
}
|
||||
}
|
||||
|
||||
// Verify all tables were dropped
|
||||
const afterDrop = await client.query(`
|
||||
SELECT tablename as name
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
AND tablename = ANY($1)
|
||||
`, [METRICS_TABLES]);
|
||||
|
||||
if (afterDrop.rows.length > 0) {
|
||||
throw new Error(`Failed to drop all tables. Remaining tables: ${afterDrop.rows.map(t => t.name).join(', ')}`);
|
||||
}
|
||||
|
||||
// Make sure we have a fresh transaction here
|
||||
await client.query('COMMIT');
|
||||
await client.query('BEGIN');
|
||||
await client.query('SET session_replication_role = \'replica\'');
|
||||
|
||||
// Read metrics schema
|
||||
outputProgress({
|
||||
operation: 'Reading schema',
|
||||
message: 'Loading metrics schema file...'
|
||||
});
|
||||
|
||||
const schemaPath = path.resolve(__dirname, '../db/metrics-schema.sql');
|
||||
if (!fs.existsSync(schemaPath)) {
|
||||
throw new Error(`Schema file not found at: ${schemaPath}`);
|
||||
}
|
||||
|
||||
const schemaSQL = fs.readFileSync(schemaPath, 'utf8');
|
||||
const statements = splitSQLStatements(schemaSQL);
|
||||
|
||||
outputProgress({
|
||||
operation: 'Schema loaded',
|
||||
message: `Found ${statements.length} SQL statements to execute`
|
||||
});
|
||||
|
||||
// Execute schema statements
|
||||
for (let i = 0; i < statements.length; i++) {
|
||||
const stmt = statements[i];
|
||||
try {
|
||||
const result = await client.query(stmt);
|
||||
|
||||
// If this is a CREATE TABLE statement, verify the table was created
|
||||
if (stmt.trim().toLowerCase().startsWith('create table')) {
|
||||
const tableName = stmt.match(/create\s+table\s+(?:if\s+not\s+exists\s+)?["]?(\w+)["]?/i)?.[1];
|
||||
if (tableName) {
|
||||
const checkCreate = await client.query(`
|
||||
SELECT tablename as name
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
AND tablename = $1
|
||||
`, [tableName]);
|
||||
|
||||
if (checkCreate.rows.length === 0) {
|
||||
throw new Error(`Failed to create table ${tableName} - table does not exist after CREATE statement`);
|
||||
}
|
||||
|
||||
outputProgress({
|
||||
operation: 'Table created',
|
||||
message: `Successfully created table: ${tableName}`
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
outputProgress({
|
||||
operation: 'SQL Progress',
|
||||
message: {
|
||||
statement: i + 1,
|
||||
total: statements.length,
|
||||
preview: stmt.substring(0, 100) + (stmt.length > 100 ? '...' : ''),
|
||||
rowCount: result.rowCount
|
||||
}
|
||||
});
|
||||
|
||||
// Commit every 10 statements to avoid long-running transactions
|
||||
if (i > 0 && i % 10 === 0) {
|
||||
await client.query('COMMIT');
|
||||
await client.query('BEGIN');
|
||||
await client.query('SET session_replication_role = \'replica\'');
|
||||
}
|
||||
} catch (sqlError) {
|
||||
outputProgress({
|
||||
status: 'error',
|
||||
operation: 'SQL Error',
|
||||
message: {
|
||||
error: sqlError.message,
|
||||
statement: stmt,
|
||||
statementNumber: i + 1
|
||||
}
|
||||
});
|
||||
await client.query('ROLLBACK');
|
||||
throw sqlError;
|
||||
}
|
||||
}
|
||||
|
||||
// Final commit for any pending statements
|
||||
await client.query('COMMIT');
|
||||
|
||||
// Start new transaction for final checks
|
||||
await client.query('BEGIN');
|
||||
|
||||
// Re-enable foreign key checks after all tables are created
|
||||
await client.query('SET session_replication_role = \'origin\'');
|
||||
|
||||
// Verify metrics tables were created
|
||||
outputProgress({
|
||||
operation: 'Verifying metrics tables',
|
||||
message: 'Checking all metrics tables were created...'
|
||||
});
|
||||
|
||||
const metricsTablesResult = await client.query(`
|
||||
SELECT tablename as name
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
AND tablename = ANY($1)
|
||||
`, [METRICS_TABLES]);
|
||||
|
||||
outputProgress({
|
||||
operation: 'Tables found',
|
||||
message: `Found ${metricsTablesResult.rows.length} tables: ${metricsTablesResult.rows.map(t => t.name).join(', ')}`
|
||||
});
|
||||
|
||||
const existingMetricsTables = metricsTablesResult.rows.map(t => t.name);
|
||||
const missingMetricsTables = METRICS_TABLES.filter(t => !existingMetricsTables.includes(t));
|
||||
|
||||
if (missingMetricsTables.length > 0) {
|
||||
// Do one final check of the actual tables
|
||||
const finalCheck = await client.query(`
|
||||
SELECT tablename as name
|
||||
FROM pg_tables
|
||||
WHERE schemaname = 'public'
|
||||
`);
|
||||
outputProgress({
|
||||
operation: 'Final table check',
|
||||
message: `All database tables: ${finalCheck.rows.map(t => t.name).join(', ')}`
|
||||
});
|
||||
await client.query('ROLLBACK');
|
||||
throw new Error(`Failed to create metrics tables: ${missingMetricsTables.join(', ')}`);
|
||||
}
|
||||
|
||||
// Commit final transaction
|
||||
await client.query('COMMIT');
|
||||
|
||||
outputProgress({
|
||||
status: 'complete',
|
||||
operation: 'Reset complete',
|
||||
message: 'All metrics tables have been reset successfully'
|
||||
});
|
||||
} catch (error) {
|
||||
outputProgress({
|
||||
status: 'error',
|
||||
operation: 'Reset failed',
|
||||
message: error.message,
|
||||
stack: error.stack
|
||||
});
|
||||
|
||||
if (client) {
|
||||
try {
|
||||
await client.query('ROLLBACK');
|
||||
} catch (rollbackError) {
|
||||
console.error('Error during rollback:', rollbackError);
|
||||
}
|
||||
// Make sure to re-enable foreign key checks even if there's an error
|
||||
await client.query('SET session_replication_role = \'origin\'').catch(() => {});
|
||||
}
|
||||
throw error;
|
||||
} finally {
|
||||
if (client) {
|
||||
// One final attempt to ensure foreign key checks are enabled
|
||||
await client.query('SET session_replication_role = \'origin\'').catch(() => {});
|
||||
await client.end();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Export if required as a module
|
||||
if (typeof module !== 'undefined' && module.exports) {
|
||||
module.exports = resetMetrics;
|
||||
}
|
||||
|
||||
// Run if called from command line
|
||||
if (require.main === module) {
|
||||
resetMetrics().catch(error => {
|
||||
console.error('Error:', error);
|
||||
process.exit(1);
|
||||
});
|
||||
}
|
||||
337
inventory-server/old/update-order-costs.js
Normal file
337
inventory-server/old/update-order-costs.js
Normal file
@@ -0,0 +1,337 @@
|
||||
/**
|
||||
* This script updates the costeach values for existing orders from the original MySQL database
|
||||
* without needing to run the full import process.
|
||||
*/
|
||||
const dotenv = require("dotenv");
|
||||
const path = require("path");
|
||||
const fs = require("fs");
|
||||
const { setupConnections, closeConnections } = require('../scripts/import/utils');
|
||||
const { outputProgress, formatElapsedTime } = require('./metrics/utils/progress');
|
||||
|
||||
dotenv.config({ path: path.join(__dirname, "../.env") });
|
||||
|
||||
// SSH configuration
|
||||
const sshConfig = {
|
||||
ssh: {
|
||||
host: process.env.PROD_SSH_HOST,
|
||||
port: process.env.PROD_SSH_PORT || 22,
|
||||
username: process.env.PROD_SSH_USER,
|
||||
privateKey: process.env.PROD_SSH_KEY_PATH
|
||||
? fs.readFileSync(process.env.PROD_SSH_KEY_PATH)
|
||||
: undefined,
|
||||
compress: true, // Enable SSH compression
|
||||
},
|
||||
prodDbConfig: {
|
||||
// MySQL config for production
|
||||
host: process.env.PROD_DB_HOST || "localhost",
|
||||
user: process.env.PROD_DB_USER,
|
||||
password: process.env.PROD_DB_PASSWORD,
|
||||
database: process.env.PROD_DB_NAME,
|
||||
port: process.env.PROD_DB_PORT || 3306,
|
||||
timezone: 'Z',
|
||||
},
|
||||
localDbConfig: {
|
||||
// PostgreSQL config for local
|
||||
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,
|
||||
ssl: process.env.DB_SSL === 'true',
|
||||
connectionTimeoutMillis: 60000,
|
||||
idleTimeoutMillis: 30000,
|
||||
max: 10 // connection pool max size
|
||||
}
|
||||
};
|
||||
|
||||
async function updateOrderCosts() {
|
||||
const startTime = Date.now();
|
||||
let connections;
|
||||
let updatedCount = 0;
|
||||
let errorCount = 0;
|
||||
|
||||
try {
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: "Initializing SSH tunnel..."
|
||||
});
|
||||
|
||||
connections = await setupConnections(sshConfig);
|
||||
const { prodConnection, localConnection } = connections;
|
||||
|
||||
// 1. Get all orders from local database that need cost updates
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: "Getting orders from local database..."
|
||||
});
|
||||
|
||||
const [orders] = await localConnection.query(`
|
||||
SELECT DISTINCT order_number, pid
|
||||
FROM orders
|
||||
WHERE costeach = 0 OR costeach IS NULL
|
||||
ORDER BY order_number
|
||||
`);
|
||||
|
||||
if (!orders || !orders.rows || orders.rows.length === 0) {
|
||||
console.log("No orders found that need cost updates");
|
||||
return { updatedCount: 0, errorCount: 0 };
|
||||
}
|
||||
|
||||
const totalOrders = orders.rows.length;
|
||||
console.log(`Found ${totalOrders} orders that need cost updates`);
|
||||
|
||||
// Process in batches of 1000 orders
|
||||
const BATCH_SIZE = 500;
|
||||
for (let i = 0; i < orders.rows.length; i += BATCH_SIZE) {
|
||||
try {
|
||||
// Start transaction for this batch
|
||||
await localConnection.beginTransaction();
|
||||
|
||||
const batch = orders.rows.slice(i, i + BATCH_SIZE);
|
||||
|
||||
const orderNumbers = [...new Set(batch.map(o => o.order_number))];
|
||||
|
||||
// 2. Fetch costs from production database for these orders
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: `Fetching costs for orders ${i + 1} to ${Math.min(i + BATCH_SIZE, totalOrders)} of ${totalOrders}`,
|
||||
current: i,
|
||||
total: totalOrders,
|
||||
elapsed: formatElapsedTime((Date.now() - startTime) / 1000)
|
||||
});
|
||||
|
||||
const [costs] = await prodConnection.query(`
|
||||
SELECT
|
||||
oc.orderid as order_number,
|
||||
oc.pid,
|
||||
oc.costeach
|
||||
FROM order_costs oc
|
||||
INNER JOIN (
|
||||
SELECT
|
||||
orderid,
|
||||
pid,
|
||||
MAX(id) as max_id
|
||||
FROM order_costs
|
||||
WHERE orderid IN (?)
|
||||
AND pending = 0
|
||||
GROUP BY orderid, pid
|
||||
) latest ON oc.orderid = latest.orderid AND oc.pid = latest.pid AND oc.id = latest.max_id
|
||||
`, [orderNumbers]);
|
||||
|
||||
// Create a map of costs for easy lookup
|
||||
const costMap = {};
|
||||
if (costs && costs.length) {
|
||||
costs.forEach(c => {
|
||||
costMap[`${c.order_number}-${c.pid}`] = c.costeach || 0;
|
||||
});
|
||||
}
|
||||
|
||||
// 3. Update costs in local database by batches
|
||||
// Using a more efficient update approach with a temporary table
|
||||
|
||||
// Create a temporary table for each batch
|
||||
await localConnection.query(`
|
||||
DROP TABLE IF EXISTS temp_order_costs;
|
||||
CREATE TEMP TABLE temp_order_costs (
|
||||
order_number VARCHAR(50) NOT NULL,
|
||||
pid BIGINT NOT NULL,
|
||||
costeach DECIMAL(10,3) NOT NULL,
|
||||
PRIMARY KEY (order_number, pid)
|
||||
);
|
||||
`);
|
||||
|
||||
// Insert cost data into the temporary table
|
||||
const costEntries = [];
|
||||
for (const order of batch) {
|
||||
const key = `${order.order_number}-${order.pid}`;
|
||||
if (key in costMap) {
|
||||
costEntries.push({
|
||||
order_number: order.order_number,
|
||||
pid: order.pid,
|
||||
costeach: costMap[key]
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Insert in sub-batches of 100
|
||||
const DB_BATCH_SIZE = 50;
|
||||
for (let j = 0; j < costEntries.length; j += DB_BATCH_SIZE) {
|
||||
const subBatch = costEntries.slice(j, j + DB_BATCH_SIZE);
|
||||
if (subBatch.length === 0) continue;
|
||||
|
||||
const placeholders = subBatch.map((_, idx) =>
|
||||
`($${idx * 3 + 1}, $${idx * 3 + 2}, $${idx * 3 + 3})`
|
||||
).join(',');
|
||||
|
||||
const values = subBatch.flatMap(item => [
|
||||
item.order_number,
|
||||
item.pid,
|
||||
item.costeach
|
||||
]);
|
||||
|
||||
await localConnection.query(`
|
||||
INSERT INTO temp_order_costs (order_number, pid, costeach)
|
||||
VALUES ${placeholders}
|
||||
`, values);
|
||||
}
|
||||
|
||||
// Perform bulk update from the temporary table
|
||||
const [updateResult] = await localConnection.query(`
|
||||
UPDATE orders o
|
||||
SET costeach = t.costeach
|
||||
FROM temp_order_costs t
|
||||
WHERE o.order_number = t.order_number AND o.pid = t.pid
|
||||
RETURNING o.id
|
||||
`);
|
||||
|
||||
const batchUpdated = updateResult.rowCount || 0;
|
||||
updatedCount += batchUpdated;
|
||||
|
||||
// Commit transaction for this batch
|
||||
await localConnection.commit();
|
||||
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: `Updated ${updatedCount} orders with costs from production (batch: ${batchUpdated})`,
|
||||
current: i + batch.length,
|
||||
total: totalOrders,
|
||||
elapsed: formatElapsedTime((Date.now() - startTime) / 1000)
|
||||
});
|
||||
} catch (error) {
|
||||
// If a batch fails, roll back that batch's transaction and continue
|
||||
try {
|
||||
await localConnection.rollback();
|
||||
} catch (rollbackError) {
|
||||
console.error("Error during batch rollback:", rollbackError);
|
||||
}
|
||||
|
||||
console.error(`Error processing batch ${i}-${i + BATCH_SIZE}:`, error);
|
||||
errorCount++;
|
||||
}
|
||||
}
|
||||
|
||||
// 4. For orders with no matching costs, set a default based on price
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: "Setting default costs for remaining orders..."
|
||||
});
|
||||
|
||||
// Process remaining updates in smaller batches
|
||||
const DEFAULT_BATCH_SIZE = 10000;
|
||||
let totalDefaultUpdated = 0;
|
||||
|
||||
try {
|
||||
// Start with a count query to determine how many records need the default update
|
||||
const [countResult] = await localConnection.query(`
|
||||
SELECT COUNT(*) as count FROM orders
|
||||
WHERE (costeach = 0 OR costeach IS NULL)
|
||||
`);
|
||||
|
||||
const totalToUpdate = parseInt(countResult.rows[0]?.count || 0);
|
||||
|
||||
if (totalToUpdate > 0) {
|
||||
console.log(`Applying default cost to ${totalToUpdate} orders`);
|
||||
|
||||
// Apply the default in batches with separate transactions
|
||||
for (let i = 0; i < totalToUpdate; i += DEFAULT_BATCH_SIZE) {
|
||||
try {
|
||||
await localConnection.beginTransaction();
|
||||
|
||||
const [defaultUpdates] = await localConnection.query(`
|
||||
WITH orders_to_update AS (
|
||||
SELECT id FROM orders
|
||||
WHERE (costeach = 0 OR costeach IS NULL)
|
||||
LIMIT ${DEFAULT_BATCH_SIZE}
|
||||
)
|
||||
UPDATE orders o
|
||||
SET costeach = price * 0.5
|
||||
FROM orders_to_update otu
|
||||
WHERE o.id = otu.id
|
||||
RETURNING o.id
|
||||
`);
|
||||
|
||||
const batchDefaultUpdated = defaultUpdates.rowCount || 0;
|
||||
totalDefaultUpdated += batchDefaultUpdated;
|
||||
|
||||
await localConnection.commit();
|
||||
|
||||
outputProgress({
|
||||
status: "running",
|
||||
operation: "Order costs update",
|
||||
message: `Applied default costs to ${totalDefaultUpdated} of ${totalToUpdate} orders`,
|
||||
current: totalDefaultUpdated,
|
||||
total: totalToUpdate,
|
||||
elapsed: formatElapsedTime((Date.now() - startTime) / 1000)
|
||||
});
|
||||
} catch (error) {
|
||||
try {
|
||||
await localConnection.rollback();
|
||||
} catch (rollbackError) {
|
||||
console.error("Error during default update rollback:", rollbackError);
|
||||
}
|
||||
|
||||
console.error(`Error applying default costs batch ${i}-${i + DEFAULT_BATCH_SIZE}:`, error);
|
||||
errorCount++;
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error counting or updating remaining orders:", error);
|
||||
errorCount++;
|
||||
}
|
||||
|
||||
updatedCount += totalDefaultUpdated;
|
||||
|
||||
const endTime = Date.now();
|
||||
const totalSeconds = (endTime - startTime) / 1000;
|
||||
|
||||
outputProgress({
|
||||
status: "complete",
|
||||
operation: "Order costs update",
|
||||
message: `Updated ${updatedCount} orders (${totalDefaultUpdated} with default values) in ${formatElapsedTime(totalSeconds)}`,
|
||||
elapsed: formatElapsedTime(totalSeconds)
|
||||
});
|
||||
|
||||
return {
|
||||
status: "complete",
|
||||
updatedCount,
|
||||
errorCount
|
||||
};
|
||||
} catch (error) {
|
||||
console.error("Error during order costs update:", error);
|
||||
|
||||
return {
|
||||
status: "error",
|
||||
error: error.message,
|
||||
updatedCount,
|
||||
errorCount
|
||||
};
|
||||
} finally {
|
||||
if (connections) {
|
||||
await closeConnections(connections).catch(err => {
|
||||
console.error("Error closing connections:", err);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Run the script only if this is the main module
|
||||
if (require.main === module) {
|
||||
updateOrderCosts().then((results) => {
|
||||
console.log('Cost update completed:', results);
|
||||
// Force exit after a small delay to ensure all logs are written
|
||||
setTimeout(() => process.exit(0), 500);
|
||||
}).catch((error) => {
|
||||
console.error("Unhandled error:", error);
|
||||
// Force exit with error code after a small delay
|
||||
setTimeout(() => process.exit(1), 500);
|
||||
});
|
||||
}
|
||||
|
||||
// Export the function for use in other scripts
|
||||
module.exports = updateOrderCosts;
|
||||
Reference in New Issue
Block a user