Awesome-claude-code-toolkit postgres-optimization
PostgreSQL optimization including indexes, query plans, partitioning, JSONB operations, and connection pooling
install
source · Clone the upstream repo
git clone https://github.com/rohitg00/awesome-claude-code-toolkit
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/rohitg00/awesome-claude-code-toolkit "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/postgres-optimization" ~/.claude/skills/rohitg00-awesome-claude-code-toolkit-postgres-optimization && rm -rf "$T"
manifest:
skills/postgres-optimization/SKILL.mdsource content
PostgreSQL Optimization
Index Strategies
-- B-tree index for equality and range queries (default) CREATE INDEX idx_orders_customer_id ON orders (customer_id); -- Composite index (column order matters: equality columns first, range last) CREATE INDEX idx_orders_status_created ON orders (status, created_at DESC); -- Partial index (smaller, faster for filtered queries) CREATE INDEX idx_orders_pending ON orders (created_at) WHERE status = 'pending'; -- Covering index (avoids table lookup entirely) CREATE INDEX idx_users_email_name ON users (email) INCLUDE (name, avatar_url); -- GIN index for JSONB containment queries CREATE INDEX idx_products_metadata ON products USING GIN (metadata); -- GiST index for full-text search CREATE INDEX idx_articles_search ON articles USING GiST ( to_tsvector('english', title || ' ' || body) ); -- Concurrent index creation (no table lock) CREATE INDEX CONCURRENTLY idx_large_table_col ON large_table (col);
Reading Query Plans
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT o.id, o.total, u.name FROM orders o JOIN users u ON o.user_id = u.id WHERE o.status = 'shipped' AND o.created_at > NOW() - INTERVAL '30 days' ORDER BY o.created_at DESC LIMIT 20;
Key things to look for in the plan:
on large tables indicates a missing indexSeq Scan
with high row estimates suggests missing join indexNested Loop
withoutSort
means the sort is happening in memory/diskIndex Scan
vsBuffers: shared hit
shows cache efficiencyshared read
Partitioning
CREATE TABLE events ( id BIGINT GENERATED ALWAYS AS IDENTITY, event_type TEXT NOT NULL, payload JSONB NOT NULL, created_at TIMESTAMPTZ NOT NULL DEFAULT NOW() ) PARTITION BY RANGE (created_at); CREATE TABLE events_2024_q1 PARTITION OF events FOR VALUES FROM ('2024-01-01') TO ('2024-04-01'); CREATE TABLE events_2024_q2 PARTITION OF events FOR VALUES FROM ('2024-04-01') TO ('2024-07-01'); -- Index on each partition (inherited automatically in PG 11+) CREATE INDEX ON events (created_at, event_type);
Partition tables with more than 10M rows when queries consistently filter on the partition key.
JSONB Operations
-- Query nested JSONB fields SELECT * FROM products WHERE metadata @> '{"category": "electronics"}' AND (metadata ->> 'price')::numeric < 500; -- Update nested JSONB UPDATE products SET metadata = jsonb_set(metadata, '{stock}', to_jsonb(stock - 1)) WHERE id = 'abc'; -- Aggregate JSONB arrays SELECT id, jsonb_array_elements_text(metadata -> 'tags') AS tag FROM products WHERE metadata ? 'tags';
Connection Pooling
# pgbouncer.ini [databases] app = host=localhost port=5432 dbname=app [pgbouncer] pool_mode = transaction max_client_conn = 1000 default_pool_size = 25 min_pool_size = 5 reserve_pool_size = 5 server_idle_timeout = 300
Use transaction-level pooling for web applications. Session-level pooling for apps that use prepared statements or temp tables.
Common Tuning Parameters
-- Check for slow queries SELECT query, calls, mean_exec_time, total_exec_time FROM pg_stat_statements ORDER BY total_exec_time DESC LIMIT 10; -- Find unused indexes SELECT indexrelname, idx_scan, pg_size_pretty(pg_relation_size(indexrelid)) FROM pg_stat_user_indexes WHERE idx_scan = 0 ORDER BY pg_relation_size(indexrelid) DESC;
Anti-Patterns
- Creating indexes on every column instead of analyzing actual query patterns
- Using
when only a few columns are neededSELECT * - Not using
to verify index usageEXPLAIN ANALYZE - Storing large blobs in JSONB when a separate table with proper types is better
- Missing connection pooling (each connection uses ~10MB of server memory)
- Running
during peak hours (locks the entire table)VACUUM FULL
Checklist
- Indexes match actual query patterns (check
)pg_stat_statements - Composite indexes ordered: equality, then sort, then range columns
-
run on all critical queriesEXPLAIN ANALYZE - Partial indexes used for frequently filtered subsets
- Connection pooler (PgBouncer/pgcat) in front of PostgreSQL
- Table partitioning considered for tables over 10M rows
- Unused indexes identified and dropped
-
enabled for query performance monitoringpg_stat_statements