224 lines
9.9 KiB
JavaScript
224 lines
9.9 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 calculateBrandMetrics(startTime, totalProducts, processedCount, isCancelled = false) {
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const connection = await getConnection();
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try {
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if (isCancelled) {
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outputProgress({
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status: 'cancelled',
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operation: 'Brand metrics calculation cancelled',
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current: processedCount,
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total: totalProducts,
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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 / totalProducts) * 100).toFixed(1)
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});
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return processedCount;
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}
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outputProgress({
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status: 'running',
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operation: 'Starting brand metrics calculation',
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current: processedCount,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalProducts),
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalProducts) * 100).toFixed(1)
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});
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// Calculate brand metrics with optimized queries
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await connection.query(`
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INSERT INTO brand_metrics (
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brand,
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product_count,
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active_products,
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total_stock_units,
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total_stock_cost,
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total_stock_retail,
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total_revenue,
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avg_margin,
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growth_rate
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)
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WITH filtered_products AS (
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SELECT
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p.*,
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CASE WHEN p.stock_quantity <= 5000 THEN p.pid END as valid_pid,
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CASE WHEN p.visible = true AND p.stock_quantity <= 5000 THEN p.pid END as active_pid,
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CASE
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WHEN p.stock_quantity IS NULL OR p.stock_quantity < 0 OR p.stock_quantity > 5000 THEN 0
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ELSE p.stock_quantity
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END as valid_stock
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FROM products p
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WHERE p.brand IS NOT NULL
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),
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sales_periods AS (
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SELECT
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p.brand,
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SUM(o.quantity * o.price) as period_revenue,
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CASE
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WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) THEN 'current'
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WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH) AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) THEN 'previous'
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END as period_type
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FROM filtered_products p
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JOIN orders o ON p.pid = o.pid
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WHERE o.canceled = false
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AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH)
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GROUP BY p.brand, period_type
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),
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brand_data AS (
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SELECT
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p.brand,
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COUNT(DISTINCT p.valid_pid) as product_count,
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COUNT(DISTINCT p.active_pid) as active_products,
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SUM(p.valid_stock) as total_stock_units,
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SUM(p.valid_stock * p.cost_price) as total_stock_cost,
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SUM(p.valid_stock * p.price) as total_stock_retail,
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COALESCE(SUM(o.quantity * o.price), 0) as total_revenue,
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CASE
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WHEN SUM(o.quantity * o.price) > 0 THEN
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(SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
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ELSE 0
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END as avg_margin
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FROM filtered_products p
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LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
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GROUP BY p.brand
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)
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SELECT
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bd.brand,
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bd.product_count,
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bd.active_products,
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bd.total_stock_units,
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bd.total_stock_cost,
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bd.total_stock_retail,
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bd.total_revenue,
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bd.avg_margin,
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CASE
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WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0
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AND MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) > 0 THEN 100.0
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WHEN MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END) = 0 THEN 0.0
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ELSE LEAST(
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GREATEST(
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((MAX(CASE WHEN sp.period_type = 'current' THEN sp.period_revenue END) -
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MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END)) /
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NULLIF(MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END), 0)) * 100.0,
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-100.0
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),
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999.99
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)
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END as growth_rate
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FROM brand_data bd
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LEFT JOIN sales_periods sp ON bd.brand = sp.brand
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GROUP BY bd.brand, bd.product_count, bd.active_products, bd.total_stock_units,
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bd.total_stock_cost, bd.total_stock_retail, bd.total_revenue, bd.avg_margin
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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_stock_units = VALUES(total_stock_units),
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total_stock_cost = VALUES(total_stock_cost),
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total_stock_retail = VALUES(total_stock_retail),
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total_revenue = VALUES(total_revenue),
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avg_margin = VALUES(avg_margin),
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growth_rate = VALUES(growth_rate),
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last_calculated_at = CURRENT_TIMESTAMP
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`);
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processedCount = Math.floor(totalProducts * 0.97);
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outputProgress({
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status: 'running',
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operation: 'Brand metrics calculated, starting time-based metrics',
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current: processedCount,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalProducts),
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalProducts) * 100).toFixed(1)
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});
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if (isCancelled) return processedCount;
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// Calculate brand time-based metrics with optimized query
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await connection.query(`
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INSERT INTO brand_time_metrics (
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brand,
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year,
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month,
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product_count,
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active_products,
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total_stock_units,
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total_stock_cost,
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total_stock_retail,
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total_revenue,
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avg_margin
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)
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WITH filtered_products AS (
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SELECT
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p.*,
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CASE WHEN p.stock_quantity <= 5000 THEN p.pid END as valid_pid,
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CASE WHEN p.visible = true AND p.stock_quantity <= 5000 THEN p.pid END as active_pid,
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CASE
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WHEN p.stock_quantity IS NULL OR p.stock_quantity < 0 OR p.stock_quantity > 5000 THEN 0
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ELSE p.stock_quantity
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END as valid_stock
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FROM products p
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WHERE p.brand IS NOT NULL
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),
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monthly_metrics AS (
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SELECT
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p.brand,
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YEAR(o.date) as year,
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MONTH(o.date) as month,
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COUNT(DISTINCT p.valid_pid) as product_count,
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COUNT(DISTINCT p.active_pid) as active_products,
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SUM(p.valid_stock) as total_stock_units,
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SUM(p.valid_stock * p.cost_price) as total_stock_cost,
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SUM(p.valid_stock * p.price) as total_stock_retail,
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SUM(o.quantity * o.price) as total_revenue,
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CASE
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WHEN SUM(o.quantity * o.price) > 0 THEN
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(SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
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ELSE 0
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END as avg_margin
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FROM filtered_products p
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LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
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WHERE o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
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GROUP BY p.brand, YEAR(o.date), MONTH(o.date)
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)
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SELECT *
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FROM monthly_metrics
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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_stock_units = VALUES(total_stock_units),
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total_stock_cost = VALUES(total_stock_cost),
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total_stock_retail = VALUES(total_stock_retail),
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total_revenue = VALUES(total_revenue),
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avg_margin = VALUES(avg_margin)
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`);
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processedCount = Math.floor(totalProducts * 0.99);
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outputProgress({
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status: 'running',
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operation: 'Brand time-based metrics calculated',
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current: processedCount,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalProducts),
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rate: calculateRate(startTime, processedCount),
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percentage: ((processedCount / totalProducts) * 100).toFixed(1)
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});
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return processedCount;
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} catch (error) {
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logError(error, 'Error calculating brand 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 = calculateBrandMetrics;
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