Optimizing PostgreSQL Performance: Indexing Strategies and Query Tuning

Database performance issues are often the bottleneck in application performance. Understanding PostgreSQL internals helps you write queries that fly.

Understanding EXPLAIN ANALYZE

EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders
WHERE customer_id = 123
AND created_at > '2024-01-01';

Key metrics to watch: actual time, rows, loops, buffers shared hit/read. High shared read indicates missing indexes or insufficient shared_buffers.

Index Types and When to Use Them

B-tree (default): Equality and range queries on sortable data.

Hash: Equality-only comparisons (rarely better than B-tree in modern Postgres).

GiST: Geometric data, full-text search, range types.

GIN: Arrays, JSONB, full-text search with many distinct values.

BRIN: Very large tables with naturally ordered data.

Composite Index Strategy

-- Query pattern: WHERE status = X AND created_at > Y ORDER BY created_at
CREATE INDEX idx_orders_status_created 
ON orders (status, created_at DESC);

Column order matters! Put equality columns first, then range columns.

Partial Indexes for Hot Data

-- Only index active orders (90% of queries)
CREATE INDEX idx_orders_active 
ON orders (customer_id, created_at)
WHERE status = 'active';

Partial indexes are smaller, faster to update, and more likely to fit in memory.

Covering Indexes (Index-Only Scans)

-- Include columns to avoid table lookups
CREATE INDEX idx_orders_covering 
ON orders (customer_id) 
INCLUDE (total_amount, status);

JSONB Indexing

-- GIN index for flexible JSONB queries
CREATE INDEX idx_metadata_gin ON products USING GIN (metadata);

-- Targeted index for specific key
CREATE INDEX idx_metadata_category 
ON products ((metadata->>'category'));

Query Optimization Techniques

Avoid SELECT *: Fetch only needed columns.

Use EXISTS instead of COUNT: `WHERE EXISTS (...)` is faster than `WHERE (SELECT COUNT(*)) > 0`.

Batch operations: Use `INSERT ... ON CONFLICT` and `UPDATE ... FROM` for bulk operations.

Connection Pooling with PgBouncer

[databases]
mydb = host=localhost dbname=mydb

[pgbouncer]
pool_mode = transaction
max_client_conn = 1000
default_pool_size = 20

PostgreSQL connections are expensive. PgBouncer allows thousands of application connections to share a small pool of database connections.

Monitoring Queries

-- Enable pg_stat_statements
CREATE EXTENSION pg_stat_statements;

-- Find slowest queries
SELECT query, calls, mean_exec_time, rows
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;

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