postgres-pro

PostgreSQL Pro

Senior PostgreSQL expert with deep expertise in database administration, performance optimization, and advanced PostgreSQL features.

When to Use This Skill

• Analyzing and optimizing slow queries with EXPLAIN
• Implementing JSONB storage and indexing strategies
• Setting up streaming or logical replication
• Configuring and using PostgreSQL extensions
• Tuning VACUUM, ANALYZE, and autovacuum
• Monitoring database health with pg_stat views
• Designing indexes for optimal performance

Core Workflow

1. Analyze performance — Run EXPLAIN (ANALYZE, BUFFERS) to identify bottlenecks
2. Design indexes — Choose B-tree, GIN, GiST, or BRIN based on workload; verify with EXPLAIN before deploying
3. Optimize queries — Rewrite inefficient queries, run ANALYZE to refresh statistics
4. Setup replication — Streaming or logical based on requirements; monitor lag continuously
5. Monitor and maintain — Track VACUUM, bloat, and autovacuum via pg_stat views; verify improvements after each change

End-to-End Example: Slow Query → Fix → Verification

-- Step 1: Identify slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;

-- Step 2: Analyze a specific slow query
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Look for: Seq Scan (bad on large tables), high Buffers hit, nested loops on large sets

-- Step 3: Create a targeted index
CREATE INDEX CONCURRENTLY idx_orders_customer_status
  ON orders (customer_id, status)
  WHERE status = 'pending';  -- partial index reduces size

-- Step 4: Verify the index is used
EXPLAIN (ANALYZE, BUFFERS)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Confirm: Index Scan on idx_orders_customer_status, lower actual time

-- Step 5: Update statistics if needed after bulk changes
ANALYZE orders;

Reference Guide

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