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;
    const BATCH_SIZE = 5000;
    let myProcessedProducts = 0; // Not *directly* processing products, tracking brands

    try {
        // Get last calculation timestamp
        const [lastCalc] = await connection.query(`
            SELECT last_calculation_timestamp 
            FROM calculate_status 
            WHERE module_name = 'brand_metrics'
        `);
        const lastCalculationTime = lastCalc[0]?.last_calculation_timestamp || '1970-01-01';

        // Get total count of brands needing updates
        const [brandCount] = await connection.query(`
            SELECT COUNT(DISTINCT p.brand) as count 
            FROM products p
            LEFT JOIN orders o ON p.pid = o.pid AND o.updated > ?
            WHERE p.brand IS NOT NULL
              AND (
                  p.updated > ?
                  OR o.id IS NOT NULL
              )
        `, [lastCalculationTime, lastCalculationTime]);
        const totalBrands = brandCount[0].count; // Track total *brands*

        if (totalBrands === 0) {
            console.log('No brands need metric updates');
            return {
                processedProducts: 0, // Not directly processing products
                processedOrders: 0,
                processedPurchaseOrders: 0,
                success: true
            };
        }

        if (isCancelled) {
            outputProgress({
                status: 'cancelled',
                operation: 'Brand metrics calculation cancelled',
                current: processedCount, // Use passed-in value
                total: totalBrands,   // Report total *brands*
                elapsed: formatElapsedTime(startTime),
                remaining: null,
                rate: calculateRate(startTime, processedCount),
                percentage: ((processedCount / totalBrands) * 100).toFixed(1), // Base on brands
                timing: {
                    start_time: new Date(startTime).toISOString(),
                    end_time: new Date().toISOString(),
                    elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
                }
            });
            return {
                processedProducts: 0, // Not directly processing products
                processedOrders: 0,
                processedPurchaseOrders: 0,
                success
            };
        }

        outputProgress({
            status: 'running',
            operation: 'Starting brand metrics calculation',
            current: processedCount, // Use passed-in value
            total: totalBrands,   // Report total *brands*
            elapsed: formatElapsedTime(startTime),
            remaining: estimateRemaining(startTime, processedCount, totalBrands),
            rate: calculateRate(startTime, processedCount),
            percentage: ((processedCount / totalBrands) * 100).toFixed(1), // Base on brands
            timing: {
                start_time: new Date(startTime).toISOString(),
                end_time: new Date().toISOString(),
                elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
            }
        });

        // Process in batches
        let lastBrand = '';
        let processedBrands = 0; // Track processed brands
        while (true) {
            if (isCancelled) break;

            const [batch] = await connection.query(`
                SELECT DISTINCT p.brand 
                FROM products p
                    FORCE INDEX (idx_brand)
                    LEFT JOIN orders o FORCE INDEX (idx_orders_metrics) ON p.pid = o.pid AND o.updated > ?
                WHERE p.brand IS NOT NULL
                  AND p.brand > ?
                  AND (
                      p.updated > ?
                      OR o.id IS NOT NULL
                  )
                ORDER BY p.brand 
                LIMIT ?
            `, [lastCalculationTime, lastBrand, lastCalculationTime, BATCH_SIZE]);

            if (batch.length === 0) break;

            // Create temporary tables for better performance
            await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_product_stats');
            await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_sales_stats');

            await connection.query(`
                CREATE TEMPORARY TABLE temp_product_stats (
                    brand VARCHAR(100) NOT NULL,
                    product_count INT,
                    active_products INT,
                    total_stock_units INT,
                    total_stock_cost DECIMAL(15,2),
                    total_stock_retail DECIMAL(15,2),
                    total_revenue DECIMAL(15,2),
                    avg_margin DECIMAL(5,2),
                    PRIMARY KEY (brand),
                    INDEX (total_revenue),
                    INDEX (product_count)
                ) ENGINE=MEMORY
            `);

            await connection.query(`
                CREATE TEMPORARY TABLE temp_sales_stats (
                    brand VARCHAR(100) NOT NULL,
                    current_period_sales DECIMAL(15,2),
                    previous_period_sales DECIMAL(15,2),
                    PRIMARY KEY (brand),
                    INDEX (current_period_sales),
                    INDEX (previous_period_sales)
                ) ENGINE=MEMORY
            `);

            // Populate product stats with optimized index usage
            await connection.query(`
                INSERT INTO temp_product_stats
                SELECT 
                    p.brand,
                    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), 0) as total_stock_units,
                    COALESCE(SUM(p.stock_quantity * p.cost_price), 0) as total_stock_cost,
                    COALESCE(SUM(p.stock_quantity * p.price), 0) as total_stock_retail,
                    COALESCE(SUM(pm.total_revenue), 0) as total_revenue,
                    COALESCE(AVG(NULLIF(pm.avg_margin_percent, 0)), 0) as avg_margin
                FROM products p
                    FORCE INDEX (idx_brand)
                    LEFT JOIN product_metrics pm FORCE INDEX (PRIMARY) ON p.pid = pm.pid
                WHERE p.brand IN (?)
                    AND (
                        p.updated > ?
                        OR EXISTS (
                            SELECT 1 FROM orders o FORCE INDEX (idx_orders_metrics)
                            WHERE o.pid = p.pid 
                            AND o.updated > ?
                        )
                    )
                GROUP BY p.brand
            `, [batch.map(row => row.brand), lastCalculationTime, lastCalculationTime]);

            // Populate sales stats with optimized date handling
            await connection.query(`
                INSERT INTO temp_sales_stats
                WITH date_ranges AS (
                    SELECT 
                        DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) as current_start,
                        CURRENT_DATE as current_end,
                        DATE_SUB(CURRENT_DATE, INTERVAL 60 DAY) as previous_start,
                        DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) as previous_end
                )
                SELECT 
                    p.brand,
                    COALESCE(SUM(
                        CASE WHEN o.date >= dr.current_start 
                        THEN o.quantity * o.price 
                        ELSE 0 
                        END
                    ), 0) as current_period_sales,
                    COALESCE(SUM(
                        CASE WHEN o.date >= dr.previous_start AND o.date < dr.current_start
                        THEN o.quantity * o.price 
                        ELSE 0 
                        END
                    ), 0) as previous_period_sales
                FROM products p
                    FORCE INDEX (idx_brand)
                    INNER JOIN orders o FORCE INDEX (idx_orders_metrics) ON p.pid = o.pid 
                CROSS JOIN date_ranges dr
                WHERE p.brand IN (?)
                    AND o.canceled = false
                    AND o.date >= dr.previous_start
                    AND o.updated > ?
                GROUP BY p.brand
            `, [batch.map(row => row.brand), lastCalculationTime]);

            // Update metrics using temp tables with optimized calculations
            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,
                    last_calculated_at
                )
                SELECT 
                    ps.brand,
                    ps.product_count,
                    ps.active_products,
                    ps.total_stock_units,
                    ps.total_stock_cost,
                    ps.total_stock_retail,
                    ps.total_revenue,
                    ps.avg_margin,
                    CASE
                        WHEN COALESCE(ss.previous_period_sales, 0) = 0 AND COALESCE(ss.current_period_sales, 0) > 0 THEN 100
                        WHEN COALESCE(ss.previous_period_sales, 0) = 0 THEN 0
                        ELSE ROUND(LEAST(999.99, GREATEST(-100, 
                            ((ss.current_period_sales / NULLIF(ss.previous_period_sales, 0)) - 1) * 100
                        )), 2)
                    END as growth_rate,
                    NOW() as last_calculated_at
                FROM temp_product_stats ps
                LEFT JOIN temp_sales_stats ss ON ps.brand = ss.brand
                ON DUPLICATE KEY UPDATE
                    product_count = VALUES(product_count),
                    active_products = VALUES(active_products),
                    total_stock_units = VALUES(total_stock_units),
                    total_stock_cost = VALUES(total_stock_cost),
                    total_stock_retail = VALUES(total_stock_retail),
                    total_revenue = VALUES(total_revenue),
                    avg_margin = VALUES(avg_margin),
                    growth_rate = VALUES(growth_rate),
                    last_calculated_at = NOW()
            `);

            // Clean up temp tables
            await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_product_stats');
            await connection.query('DROP TEMPORARY TABLE IF EXISTS temp_sales_stats');

            lastBrand = batch[batch.length - 1].brand;
            processedBrands += batch.length; // Increment processed *brands*

            outputProgress({
                status: 'running',
                operation: 'Processing brand metrics batch',
                current: processedCount + processedBrands, // Use cumulative brand count
                total: totalBrands,   // Report total *brands*
                elapsed: formatElapsedTime(startTime),
                remaining: estimateRemaining(startTime, processedCount + processedBrands, totalBrands),
                rate: calculateRate(startTime, processedCount + processedBrands),
                percentage: (((processedCount + processedBrands) / totalBrands) * 100).toFixed(1), // Base on brands
                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 DUPLICATE KEY UPDATE last_calculation_timestamp = NOW()
        `);

        return {
            processedProducts: 0, // Not directly processing products
            processedOrders: 0,
            processedPurchaseOrders: 0,
            success
        };

    } catch (error) {
        success = false;
        logError(error, 'Error calculating brand metrics');
        throw error;
    } finally {
        if (connection) {
            connection.release();
        }
    }
}

module.exports = calculateBrandMetrics;