How to Optimize Queries in PostgreSQL

Galaxy Glossary

How do I optimize slow PostgreSQL queries?

Improve execution speed by profiling queries, adding the right indexes, rewriting statements, and tuning configuration.

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Description

Example H2

Example H3

What causes slow queries in PostgreSQL?

Large table scans, missing indexes, sub-optimal joins, and misconfigured work_mem are the usual culprits. Start by identifying which factor dominates.

How do I measure query performance?

Run EXPLAIN ANALYZE. It returns the execution plan and actual timing so you can see which step consumes the most time.

Should I use EXPLAIN or EXPLAIN ANALYZE?

Use EXPLAIN for a quick estimate that does not execute the query. Use EXPLAIN ANALYZE in staging to get real runtimes. Avoid on production unless the query is harmless.

How can indexes speed up my query?

Indexes allow the planner to locate rows quickly instead of scanning the full table. B-tree indexes serve equality and range filters; partial indexes target frequent, selective predicates.

Which columns should get indexes?

Index columns used in WHERE, JOIN, and ORDER BY clauses that filter many rows down to few. Verify benefit with EXPLAIN before committing.

How do I rewrite joins and filters?

Filter early, select only needed columns, and join on indexed keys. Replace SELECT * with specific fields to reduce I/O.

Which server settings affect query speed?

work_mem decides in-memory sort/hash size; effective_cache_size hints at OS cache; random_page_cost adjusts index vs. seq-scan choice. Tune conservatively and monitor.

What is a quick optimization checklist?

Run EXPLAIN ANALYZE and inspect slow nodes.
Create or refine indexes for filters and joins.
Rewrite queries to avoid unnecessary work.
Increase work_mem if sorts spill to disk.
Vacuum/Analyze tables to keep statistics fresh.

Common mistakes

Guessing without data: Always profile first.

Selecting entire rows: Use column lists to shrink buffers.

Why How to Optimize Queries in PostgreSQL is important

How to Optimize Queries in PostgreSQL Example Usage


-- Find top-spending customers in the last month
EXPLAIN ANALYZE
SELECT c.id, c.name, SUM(o.total_amount) AS spend
FROM Customers c
JOIN Orders o ON o.customer_id = c.id
WHERE o.order_date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY c.id, c.name
ORDER BY spend DESC
LIMIT 10;

How to Optimize Queries in PostgreSQL Syntax


-- Profile the query
EXPLAIN [ (ANALYZE TRUE, BUFFERS TRUE, VERBOSE FALSE) ]
SELECT o.id, o.order_date, c.name
FROM Orders o
JOIN Customers c ON c.id = o.customer_id
WHERE o.order_date >= CURRENT_DATE - INTERVAL '30 days';

-- Create an index to speed up the filter
CREATE INDEX idx_orders_recent
    ON Orders (order_date DESC)
    WHERE order_date >= CURRENT_DATE - INTERVAL '90 days';

-- Tune memory for large sorts in this session
SET work_mem = '128MB';

Common Mistakes

Relying on intuition instead of running EXPLAIN ANALYZE. Fix by always profiling and basing changes on actual plan output.
Creating too many generic indexes. Fix by adding targeted, selective indexes and dropping unused ones to keep writes fast.