278 lines
12 KiB
JavaScript
278 lines
12 KiB
JavaScript
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
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const { getConnection } = require('./utils/db');
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async function calculateCategoryMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
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const connection = await getConnection();
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let success = false;
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const BATCH_SIZE = 5000;
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try {
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// Get last calculation timestamp
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const [lastCalc] = await connection.query(`
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SELECT last_calculation_timestamp
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FROM calculate_status
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WHERE module_name = 'category_metrics'
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`);
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const lastCalculationTime = lastCalc[0]?.last_calculation_timestamp || '1970-01-01';
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// Get total count of categories needing updates
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const [categoryCount] = await connection.query(`
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SELECT COUNT(DISTINCT c.cat_id) as count
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FROM categories c
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JOIN product_categories pc ON c.cat_id = pc.cat_id
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LEFT JOIN products p ON pc.pid = p.pid AND p.updated > ?
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LEFT JOIN orders o ON p.pid = o.pid AND o.updated > ?
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WHERE c.status = 'active'
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AND (
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p.pid IS NOT NULL
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OR o.id IS NOT NULL
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)
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`, [lastCalculationTime, lastCalculationTime]);
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const totalCategories = categoryCount[0].count;
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if (totalCategories === 0) {
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console.log('No categories need metric updates');
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return {
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processedProducts: 0,
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processedOrders: 0,
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processedPurchaseOrders: 0,
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success: true
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};
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}
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if (isCancelled) {
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outputProgress({
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status: 'cancelled',
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operation: 'Category metrics calculation cancelled',
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current: processedCount,
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total: totalCategories,
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elapsed: formatElapsedTime(startTime),
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remaining: null,
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalCategories) * 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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return {
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processedProducts: processedCount,
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processedOrders: 0,
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processedPurchaseOrders: 0,
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success
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};
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}
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outputProgress({
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status: 'running',
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operation: 'Starting category metrics calculation',
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current: processedCount,
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total: totalCategories,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalCategories),
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalCategories) * 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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// Process in batches
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let lastCatId = 0;
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while (true) {
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if (isCancelled) break;
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const [batch] = await connection.query(`
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SELECT DISTINCT c.cat_id
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FROM categories c
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FORCE INDEX (PRIMARY)
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JOIN product_categories pc FORCE INDEX (idx_category) ON c.cat_id = pc.cat_id
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LEFT JOIN products p FORCE INDEX (PRIMARY) ON pc.pid = p.pid AND p.updated > ?
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LEFT JOIN orders o FORCE INDEX (idx_orders_metrics) ON p.pid = o.pid AND o.updated > ?
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WHERE c.status = 'active'
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AND c.cat_id > ?
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AND (
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p.pid IS NOT NULL
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OR o.id IS NOT NULL
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)
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ORDER BY c.cat_id
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LIMIT ?
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`, [lastCalculationTime, lastCalculationTime, lastCatId, BATCH_SIZE]);
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if (batch.length === 0) break;
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// Create temporary tables for better performance
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await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_product_stats');
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await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_sales_stats');
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await connection.query(`
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CREATE TEMPORARY TABLE temp_product_stats (
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cat_id BIGINT NOT NULL,
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product_count INT,
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active_products INT,
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total_value DECIMAL(15,2),
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avg_margin DECIMAL(5,2),
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turnover_rate DECIMAL(10,2),
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PRIMARY KEY (cat_id),
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INDEX (product_count),
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INDEX (total_value)
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) ENGINE=MEMORY
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`);
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await connection.query(`
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CREATE TEMPORARY TABLE temp_sales_stats (
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cat_id BIGINT NOT NULL,
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recent_revenue DECIMAL(15,2),
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previous_revenue DECIMAL(15,2),
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PRIMARY KEY (cat_id),
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INDEX (recent_revenue),
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INDEX (previous_revenue)
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) ENGINE=MEMORY
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`);
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// Populate product stats
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await connection.query(`
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INSERT INTO temp_product_stats
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SELECT
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c.cat_id,
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COUNT(DISTINCT p.pid) as product_count,
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COUNT(DISTINCT CASE WHEN p.visible = true THEN p.pid END) as active_products,
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SUM(p.stock_quantity * p.cost_price) as total_value,
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AVG(pm.avg_margin_percent) as avg_margin,
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AVG(pm.turnover_rate) as turnover_rate
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FROM categories c
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FORCE INDEX (PRIMARY)
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JOIN product_categories pc FORCE INDEX (idx_category) ON c.cat_id = pc.cat_id
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LEFT JOIN products p FORCE INDEX (PRIMARY) ON pc.pid = p.pid
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LEFT JOIN product_metrics pm FORCE INDEX (PRIMARY) ON p.pid = pm.pid
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WHERE c.cat_id IN (?)
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GROUP BY c.cat_id
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`, [batch.map(row => row.cat_id)]);
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// Populate sales stats
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await connection.query(`
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INSERT INTO temp_sales_stats
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SELECT
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c.cat_id,
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COALESCE(SUM(CASE
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WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY)
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THEN o.quantity * o.price
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ELSE 0
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END), 0) as recent_revenue,
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COALESCE(SUM(CASE
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WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 60 DAY) AND DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY)
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THEN o.quantity * o.price
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ELSE 0
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END), 0) as previous_revenue
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FROM categories c
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FORCE INDEX (PRIMARY)
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JOIN product_categories pc FORCE INDEX (idx_category) ON c.cat_id = pc.cat_id
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LEFT JOIN products p FORCE INDEX (PRIMARY) ON pc.pid = p.pid
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LEFT JOIN orders o FORCE INDEX (idx_orders_metrics) ON p.pid = o.pid
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AND o.canceled = false
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AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 60 DAY)
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WHERE c.cat_id IN (?)
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GROUP BY c.cat_id
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`, [batch.map(row => row.cat_id)]);
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// Update metrics using temp tables
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await connection.query(`
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INSERT INTO category_metrics (
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category_id,
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product_count,
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active_products,
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total_value,
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avg_margin,
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turnover_rate,
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growth_rate,
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status,
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last_calculated_at
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)
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SELECT
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c.cat_id,
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COALESCE(ps.product_count, 0) as product_count,
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COALESCE(ps.active_products, 0) as active_products,
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COALESCE(ps.total_value, 0) as total_value,
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COALESCE(ps.avg_margin, 0) as avg_margin,
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COALESCE(ps.turnover_rate, 0) as turnover_rate,
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CASE
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WHEN ss.previous_revenue = 0 AND ss.recent_revenue > 0 THEN 100
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WHEN ss.previous_revenue = 0 THEN 0
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ELSE LEAST(999.99, GREATEST(-100,
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((ss.recent_revenue / NULLIF(ss.previous_revenue, 0) - 1) * 100)
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))
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END as growth_rate,
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c.status,
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NOW() as last_calculated_at
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FROM categories c
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FORCE INDEX (PRIMARY)
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LEFT JOIN temp_product_stats ps ON c.cat_id = ps.cat_id
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LEFT JOIN temp_sales_stats ss ON c.cat_id = ss.cat_id
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WHERE c.cat_id IN (?)
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ON DUPLICATE KEY UPDATE
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product_count = VALUES(product_count),
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active_products = VALUES(active_products),
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total_value = VALUES(total_value),
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avg_margin = VALUES(avg_margin),
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turnover_rate = VALUES(turnover_rate),
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growth_rate = VALUES(growth_rate),
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status = VALUES(status),
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last_calculated_at = NOW()
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`, [batch.map(row => row.cat_id)]);
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// Clean up temp tables
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await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_product_stats');
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await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_sales_stats');
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lastCatId = batch[batch.length - 1].cat_id;
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processedCount += batch.length;
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outputProgress({
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status: 'running',
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operation: 'Processing category metrics batch',
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current: processedCount,
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total: totalCategories,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalCategories),
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalCategories) * 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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}
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// If we get here, everything completed successfully
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success = true;
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// Update calculate_status
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await connection.query(`
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INSERT INTO calculate_status (module_name, last_calculation_timestamp)
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VALUES ('category_metrics', NOW())
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ON DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
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`);
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return {
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processedProducts: processedCount,
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processedOrders: 0,
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processedPurchaseOrders: 0,
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success
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};
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} catch (error) {
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success = false;
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logError(error, 'Error calculating category metrics');
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throw error;
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} finally {
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if (connection) {
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connection.release();
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}
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}
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}
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module.exports = calculateCategoryMetrics;
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