const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
const { getConnection } = require('./utils/db');

async function calculateBrandMetrics(startTime, totalProducts, processedCount, isCancelled = false) {
    const connection = await getConnection();
    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 processedCount;
        }

        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 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
            ),
            sales_periods AS (
                SELECT 
                    p.brand,
                    SUM(o.quantity * o.price) as period_revenue,
                    CASE 
                        WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) THEN 'current'
                        WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH) AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) 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 >= DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH)
                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), 0) as total_revenue,
                    CASE 
                        WHEN SUM(o.quantity * o.price) > 0 THEN 
                            (SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
                        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 LEAST(
                        GREATEST(
                            ((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(MAX(CASE WHEN sp.period_type = 'previous' THEN sp.period_revenue END), 0)) * 100.0,
                            -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 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 = 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 processedCount;

        // 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,
                    YEAR(o.date) as year,
                    MONTH(o.date) 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 
                            (SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
                        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 >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
                GROUP BY p.brand, YEAR(o.date), MONTH(o.date)
            )
            SELECT *
            FROM monthly_metrics
            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)
        `);

        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)
            }
        });

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

module.exports = calculateBrandMetrics;