Refactor connection pool diagnostics in diagnose-db-performance.js: Update pool configuration retrieval to use Sequelize config, improve error handling, and enhance console output for better clarity on pool status. This change ensures more accurate diagnostics and user feedback regarding database connection pooling.
This commit is contained in:
Torsten Schulz (local)
184
backend/analyze-indexes.js
Executable file
184
backend/analyze-indexes.js
Executable file
@@ -0,0 +1,184 @@
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#!/usr/bin/env node
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/**
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* Script zur Analyse und Empfehlung von Indizes
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*
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* Analysiert:
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* - Tabellen mit vielen Sequential Scans
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* - Fehlende Composite Indizes für häufige JOINs
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* - Ungenutzte Indizes
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*/
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import './config/loadEnv.js';
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import { sequelize } from './utils/sequelize.js';
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async function main() {
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try {
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console.log('🔍 Index-Analyse und Empfehlungen\n');
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console.log('='.repeat(60) + '\n');
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// 1. Tabellen mit vielen Sequential Scans
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await analyzeSequentialScans();
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// 2. Prüfe häufige JOIN-Patterns
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await analyzeJoinPatterns();
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// 3. Ungenutzte Indizes
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await analyzeUnusedIndexes();
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console.log('='.repeat(60));
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console.log('✅ Analyse abgeschlossen\n');
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await sequelize.close();
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process.exit(0);
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} catch (error) {
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console.error('❌ Fehler:', error.message);
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console.error(error.stack);
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process.exit(1);
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}
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}
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async function analyzeSequentialScans() {
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console.log('📊 1. Tabellen mit vielen Sequential Scans\n');
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const [tables] = await sequelize.query(`
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SELECT
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schemaname || '.' || relname as table_name,
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seq_scan,
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seq_tup_read,
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idx_scan,
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seq_tup_read / NULLIF(seq_scan, 0) as avg_rows_per_scan,
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CASE
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WHEN seq_scan + idx_scan > 0
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THEN round((seq_scan::numeric / (seq_scan + idx_scan)) * 100, 2)
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ELSE 0
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END as seq_scan_percent
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FROM pg_stat_user_tables
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WHERE schemaname IN ('falukant_data', 'falukant_type', 'community', 'logs')
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AND seq_scan > 1000
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ORDER BY seq_tup_read DESC
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LIMIT 10;
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`);
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if (tables.length > 0) {
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console.log(' ⚠️ Tabellen mit vielen Sequential Scans:');
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tables.forEach(t => {
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console.log(`\n ${t.table_name}:`);
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console.log(` Sequential Scans: ${parseInt(t.seq_scan).toLocaleString()}`);
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console.log(` Zeilen gelesen: ${parseInt(t.seq_tup_read).toLocaleString()}`);
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console.log(` Index Scans: ${parseInt(t.idx_scan).toLocaleString()}`);
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console.log(` Seq Scan Anteil: ${t.seq_scan_percent}%`);
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console.log(` Ø Zeilen pro Scan: ${parseInt(t.avg_rows_per_scan).toLocaleString()}`);
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if (t.seq_scan_percent > 50) {
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console.log(` ⚠️ KRITISCH: Mehr als 50% Sequential Scans!`);
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}
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});
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console.log('');
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}
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}
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async function analyzeJoinPatterns() {
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console.log('🔗 2. Analyse häufiger JOIN-Patterns\n');
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// Prüfe welche Indizes auf knowledge existieren
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const [knowledgeIndexes] = await sequelize.query(`
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SELECT
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indexname,
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indexdef
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FROM pg_indexes
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WHERE schemaname = 'falukant_data'
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AND tablename = 'knowledge'
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ORDER BY indexname;
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`);
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console.log(' Indizes auf falukant_data.knowledge:');
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if (knowledgeIndexes.length > 0) {
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knowledgeIndexes.forEach(idx => {
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console.log(` - ${idx.indexname}: ${idx.indexdef}`);
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});
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} else {
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console.log(' Keine Indizes gefunden');
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}
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console.log('');
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// Empfehlung: Composite Index auf (character_id, product_id)
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const [knowledgeUsage] = await sequelize.query(`
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SELECT
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idx_scan,
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idx_tup_read,
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idx_tup_fetch
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FROM pg_stat_user_indexes
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WHERE schemaname = 'falukant_data'
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AND relname = 'knowledge'
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AND indexrelname = 'idx_knowledge_character_id';
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`);
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if (knowledgeUsage.length > 0) {
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const usage = knowledgeUsage[0];
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console.log(' Aktuelle Nutzung von idx_knowledge_character_id:');
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console.log(` Scans: ${parseInt(usage.idx_scan).toLocaleString()}`);
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console.log(` Zeilen gelesen: ${parseInt(usage.idx_tup_read).toLocaleString()}`);
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console.log('');
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console.log(' 💡 Empfehlung:');
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console.log(' CREATE INDEX IF NOT EXISTS idx_knowledge_character_product');
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console.log(' ON falukant_data.knowledge(character_id, product_id);');
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console.log(' → Wird häufig für JOINs mit character_id UND product_id verwendet\n');
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}
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// Prüfe character Indizes
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const [characterIndexes] = await sequelize.query(`
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SELECT
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indexname,
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indexdef
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FROM pg_indexes
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WHERE schemaname = 'falukant_data'
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AND tablename = 'character'
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ORDER BY indexname;
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`);
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console.log(' Indizes auf falukant_data.character:');
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if (characterIndexes.length > 0) {
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characterIndexes.forEach(idx => {
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console.log(` - ${idx.indexname}: ${idx.indexdef}`);
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});
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}
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console.log('');
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}
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async function analyzeUnusedIndexes() {
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console.log('🗑️ 3. Ungenutzte Indizes\n');
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const [unused] = await sequelize.query(`
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SELECT
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schemaname || '.' || indexrelname as index_name,
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schemaname || '.' || relname as table_name,
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pg_size_pretty(pg_relation_size(indexrelid)) as index_size,
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idx_scan as scans,
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pg_relation_size(indexrelid) as size_bytes
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FROM pg_stat_user_indexes
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WHERE schemaname IN ('falukant_data', 'falukant_type', 'community', 'logs')
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AND idx_scan = 0
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AND pg_relation_size(indexrelid) > 1024 * 1024 -- Größer als 1MB
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ORDER BY pg_relation_size(indexrelid) DESC
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LIMIT 10;
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`);
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if (unused.length > 0) {
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console.log(' ⚠️ Ungenutzte Indizes (> 1MB):');
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unused.forEach(idx => {
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console.log(` ${idx.index_name} auf ${idx.table_name}`);
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console.log(` Größe: ${idx.index_size}, Scans: ${idx.scans}`);
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});
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console.log('');
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console.log(' 💡 Überlege, ob diese Indizes gelöscht werden können:');
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console.log(' DROP INDEX IF EXISTS <index_name>;');
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console.log('');
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} else {
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console.log(' ✅ Keine großen ungenutzten Indizes gefunden\n');
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}
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}
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main();
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@@ -445,17 +445,21 @@ async function checkQueryStats() {
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async function checkConnectionPool() {
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console.log('🏊 8. Connection Pool Status\n');
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const pool = sequelize.connectionManager.pool;
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try {
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// Hole Pool-Konfiguration aus Sequelize Config
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const config = sequelize.config;
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const poolConfig = config.pool || {};
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console.log(` Pool-Konfiguration:`);
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console.log(` Max: ${pool.max}`);
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console.log(` Min: ${pool.min}`);
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console.log(` Acquire Timeout: ${pool.acquire}ms`);
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console.log(` Idle Timeout: ${pool.idle}ms`);
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console.log(` Evict Interval: ${pool.evict}ms\n`);
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console.log(` Max: ${poolConfig.max || 'N/A'}`);
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console.log(` Min: ${poolConfig.min || 'N/A'}`);
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console.log(` Acquire Timeout: ${poolConfig.acquire || 'N/A'}ms`);
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console.log(` Idle Timeout: ${poolConfig.idle || 'N/A'}ms`);
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console.log(` Evict Interval: ${poolConfig.evict || 'N/A'}ms\n`);
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// Versuche Pool-Status zu bekommen (falls verfügbar)
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try {
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// Versuche Pool-Status zu bekommen
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const pool = sequelize.connectionManager.pool;
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if (pool) {
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const poolSize = pool.size || 0;
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const poolUsed = pool.used || 0;
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const poolPending = pool.pending || 0;
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@@ -464,9 +468,11 @@ async function checkConnectionPool() {
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console.log(` Größe: ${poolSize}`);
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console.log(` Verwendet: ${poolUsed}`);
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console.log(` Wartend: ${poolPending}\n`);
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} else {
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console.log(` ℹ️ Pool-Objekt nicht verfügbar\n`);
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}
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} catch (error) {
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// Pool-Status möglicherweise nicht verfügbar
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console.log(` ℹ️ Detaillierter Pool-Status nicht verfügbar\n`);
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console.log(` ⚠️ Fehler beim Abrufen der Pool-Informationen: ${error.message}\n`);
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}
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}
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113
backend/vacuum-database.js
Executable file
113
backend/vacuum-database.js
Executable file
@@ -0,0 +1,113 @@
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#!/usr/bin/env node
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/**
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* Script zum Ausführen von VACUUM auf Tabellen mit hohem Bloat
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*
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* Führt VACUUM ANALYZE auf Tabellen aus, die:
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* - Hohen Bloat-Anteil haben (> 20% tote Zeilen)
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* - Seit mehr als 7 Tagen nicht gevacuumt wurden
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* - Viele tote Zeilen haben (> 1000)
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*/
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import './config/loadEnv.js';
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import { sequelize } from './utils/sequelize.js';
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async function main() {
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try {
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console.log('🧹 Datenbank-Vacuum\n');
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console.log('='.repeat(60) + '\n');
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// Finde Tabellen, die Vacuum benötigen
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const [tablesToVacuum] = await sequelize.query(`
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SELECT
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schemaname || '.' || relname as table_name,
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n_dead_tup,
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n_live_tup,
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CASE
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WHEN n_live_tup > 0 THEN round((n_dead_tup::numeric / n_live_tup::numeric) * 100, 2)
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ELSE 0
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END as dead_percent,
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last_vacuum,
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last_autovacuum,
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pg_size_pretty(pg_total_relation_size(schemaname||'.'||relname)) as table_size
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FROM pg_stat_user_tables
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WHERE schemaname IN ('falukant_data', 'falukant_type', 'community', 'logs')
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AND (
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(n_dead_tup > 1000 AND (n_live_tup = 0 OR (n_dead_tup::numeric / NULLIF(n_live_tup, 0)) > 0.2))
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OR (last_vacuum IS NULL AND last_autovacuum IS NULL AND n_dead_tup > 0)
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OR (
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(last_vacuum < now() - interval '7 days' OR last_vacuum IS NULL)
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AND (last_autovacuum < now() - interval '7 days' OR last_autovacuum IS NULL)
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AND n_dead_tup > 100
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)
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)
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ORDER BY n_dead_tup DESC;
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`);
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if (tablesToVacuum.length === 0) {
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console.log('✅ Keine Tabellen benötigen Vacuum.\n');
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await sequelize.close();
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process.exit(0);
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}
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console.log(`📋 Gefunden: ${tablesToVacuum.length} Tabellen benötigen Vacuum\n`);
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// Zeige Tabellen
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console.log('Tabellen, die gevacuumt werden:');
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tablesToVacuum.forEach((t, i) => {
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console.log(` ${i + 1}. ${t.table_name}`);
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console.log(` Größe: ${t.table_size}, Tote Zeilen: ${parseInt(t.n_dead_tup).toLocaleString()} (${t.dead_percent}%)`);
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});
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console.log('');
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// Frage Bestätigung
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const readline = require('readline');
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const rl = readline.createInterface({
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input: process.stdin,
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output: process.stdout
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});
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const answer = await new Promise((resolve) => {
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rl.question('Möchtest du VACUUM ANALYZE auf diesen Tabellen ausführen? (j/n): ', resolve);
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});
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rl.close();
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if (answer.toLowerCase() !== 'j' && answer.toLowerCase() !== 'y' && answer.toLowerCase() !== 'ja' && answer.toLowerCase() !== 'yes') {
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console.log('❌ Abgebrochen.\n');
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await sequelize.close();
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process.exit(0);
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}
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console.log('\n🧹 Starte Vacuum...\n');
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// Führe VACUUM ANALYZE aus
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for (let i = 0; i < tablesToVacuum.length; i++) {
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const table = tablesToVacuum[i];
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const startTime = Date.now();
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try {
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console.log(`[${i + 1}/${tablesToVacuum.length}] Vacuuming ${table.table_name}...`);
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await sequelize.query(`VACUUM ANALYZE ${table.table_name};`);
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const duration = ((Date.now() - startTime) / 1000).toFixed(2);
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console.log(` ✅ Fertig in ${duration}s\n`);
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} catch (error) {
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console.error(` ❌ Fehler: ${error.message}\n`);
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}
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}
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console.log('='.repeat(60));
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console.log('✅ Vacuum abgeschlossen\n');
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await sequelize.close();
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process.exit(0);
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} catch (error) {
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console.error('❌ Fehler:', error.message);
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console.error(error.stack);
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process.exit(1);
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}
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}
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main();
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Reference in New Issue
Block a user