PostgreSQL

PostgreSQL is an advanced open-source relational database with extensive support for SQL standards, JSONB, full-text search, PL/pgSQL, and extensibility.

Quick Reference

Connection Patterns

# URI format
"postgresql://app:secret@localhost:5432/mydb?sslmode=require&application_name=myapp"

# Multiple hosts (failover)
"postgresql://app:secret@primary:5432,standby:5432/mydb?target_session_attrs=read-write"

# asyncpg (async)
pool = await asyncpg.create_pool("postgresql://app:secret@localhost/mydb", min_size=5, max_size=20)
async with pool.acquire() as conn:
    rows = await conn.fetch("SELECT id, name FROM users WHERE status = $1", "active")

# psycopg v3 (async)
async with await psycopg.AsyncConnection.connect(conninfo) as conn:
    async with conn.cursor() as cur:
        await cur.execute("SELECT id, name FROM users WHERE id = %s", (42,))

Indexing Essentials

Type	Best For	Example
B-tree (default)	Equality, range on scalars	CREATE INDEX idx ON orders (created_at DESC)
GIN	JSONB, arrays, full-text, trigram	CREATE INDEX idx ON docs USING gin (data)
GiST	Geometry, range types, nearest-neighbor	CREATE INDEX idx ON events USING gist (during)
BRIN	Large, naturally ordered (time-series)	CREATE INDEX idx ON logs USING brin (ts)

Partial indexes -- index only the rows that matter:

CREATE INDEX idx_orders_active ON orders (user_id)
 WHERE status IN ('pending', 'processing');

Key JSONB Patterns

-- Navigation
SELECT data->>'name' FROM docs;             -- text extraction
SELECT data @> '{"status": "active"}' FROM docs;  -- containment

-- GIN index for containment
CREATE INDEX idx_docs_data ON docs USING gin (data jsonb_path_ops);

-- Build objects
SELECT jsonb_build_object('id', u.id, 'name', u.name) FROM users u;

EXPLAIN Usage

-- Full diagnostic
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT ...;

-- Safe for mutating queries (no execution)
EXPLAIN (COSTS, VERBOSE) DELETE FROM orders WHERE created_at < '2020-01-01';

Symptom	Likely Cause	Fix
Seq Scan on large table	Missing/unused index	Create index, check predicate
Sort Method: external merge Disk	work_mem too low	Increase work_mem
High Rows Removed by Filter	Index not selective	Refine index, add partial index

<workflow>

Workflow

Step 1: Schema Design

Define tables with appropriate types. Use JSONB for semi-structured data, arrays for small sets, and normalized tables for relational data. Always define primary keys.

Step 2: Write Queries

Use parameterized queries ($1 for asyncpg, %s for psycopg). Use CTEs for readability. Prefer EXISTS over IN for correlated subqueries.

Step 3: Index Strategy

Start with B-tree indexes on WHERE/JOIN/ORDER BY columns. Use partial indexes to limit index size. Add GIN indexes for JSONB containment queries. Prefer expression indexes for computed predicates.

Step 4: Performance Tuning

Run EXPLAIN (ANALYZE, BUFFERS) on slow queries. Check pg_stat_statements for top queries by total time. Tune shared_buffers, work_mem, and autovacuum settings.

Step 5: Validate

Confirm EXPLAIN plans use indexes. Check pg_stat_user_tables for sequential scan counts on large tables. Verify connection pooling (pgbouncer) is configured for production.

</workflow> <guardrails>

Guardrails

• Always use parameterized queries -- never interpolate user input. Use $1 placeholders (asyncpg) or %s (psycopg).
• Prefer partial indexes -- indexing only relevant rows reduces size and improves write performance.
• EXPLAIN before optimizing -- always measure before adding indexes or rewriting queries. Use EXPLAIN (ANALYZE, BUFFERS) for real execution stats.
• Use JSONB, not JSON -- JSONB is decomposed binary, supports GIN indexing and operators. Plain JSON is only for exact text preservation.
• Connection pooling in production -- use pgbouncer or built-in pool. Never open unbounded connections from application servers.
• pg_stat_statements for production monitoring -- identifies top queries by time, calls, and cache hit ratio.
• Avoid SELECT * -- name columns to enable covering indexes and prevent schema-change breakage.

</guardrails> <validation>

Validation Checkpoint

Before delivering PostgreSQL code, verify:

• All queries use parameterized placeholders (no string interpolation)
• EXPLAIN output confirms index usage for critical queries
• Partial indexes are used where only a subset of rows is queried
• JSONB columns use GIN indexes for containment queries
• Connection pooling is addressed (pgbouncer or pool parameter)
• sslmode is set to at least require for non-local connections

</validation> <example>

Example

Task: EXPLAIN ANALYZE and index optimization for a slow orders query.

-- Step 1: Check current plan
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT o.id, o.total, o.created_at, u.name
  FROM orders o
  JOIN users u ON u.id = o.user_id
 WHERE o.status = 'pending'
   AND o.created_at > NOW() - INTERVAL '7 days'
 ORDER BY o.created_at DESC
 LIMIT 50;

-- Step 2: If Seq Scan on orders, add a partial composite index
CREATE INDEX CONCURRENTLY idx_orders_pending_recent
    ON orders (created_at DESC)
 WHERE status = 'pending';

-- Step 3: Re-run EXPLAIN to confirm Index Scan
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT o.id, o.total, o.created_at, u.name
  FROM orders o
  JOIN users u ON u.id = o.user_id
 WHERE o.status = 'pending'
   AND o.created_at > NOW() - INTERVAL '7 days'
 ORDER BY o.created_at DESC
 LIMIT 50;

-- Step 4: Check pg_stat_statements for overall impact
SELECT calls, round(mean_exec_time::numeric, 1) AS mean_ms, query
  FROM pg_stat_statements
 ORDER BY total_exec_time DESC
 LIMIT 10;

</example>

---

Monitoring Strategy

pg_stat_statements Setup

Enable in postgresql.conf (requires restart):

shared_preload_libraries = 'pg_stat_statements'
pg_stat_statements.track = all
pg_stat_statements.max = 10000

CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

Key pg_stat_statements Queries

-- Top queries by total execution time
SELECT
    round(total_exec_time::numeric, 1) AS total_ms,
    calls,
    round(mean_exec_time::numeric, 1)  AS mean_ms,
    round(stddev_exec_time::numeric, 1) AS stddev_ms,
    round((100 * total_exec_time / sum(total_exec_time) OVER ())::numeric, 1) AS pct,
    left(query, 120) AS query
FROM pg_stat_statements
ORDER BY total_exec_time DESC
LIMIT 20;

-- Top queries by average latency (outliers)
SELECT
    calls,
    round(mean_exec_time::numeric, 2) AS mean_ms,
    left(query, 120) AS query
FROM pg_stat_statements
WHERE calls > 100
ORDER BY mean_exec_time DESC
LIMIT 20;

-- Cache hit ratio per query
SELECT
    calls,
    round(100.0 * shared_blks_hit / nullif(shared_blks_hit + shared_blks_read, 0), 1) AS cache_hit_pct,
    left(query, 120) AS query
FROM pg_stat_statements
ORDER BY shared_blks_read DESC
LIMIT 20;

-- Reset stats
SELECT pg_stat_statements_reset();

Sequential Scan Detection (pg_stat_user_tables)

-- Tables with high sequential scan counts
SELECT
    schemaname,
    relname AS table_name,
    seq_scan,
    seq_tup_read,
    idx_scan,
    round(100.0 * seq_scan / nullif(seq_scan + idx_scan, 0), 1) AS seq_pct,
    n_live_tup
FROM pg_stat_user_tables
WHERE seq_scan > 0
  AND n_live_tup > 10000
ORDER BY seq_scan DESC
LIMIT 20;

Bloat Detection

-- Table bloat estimate
SELECT
    schemaname,
    tablename,
    pg_size_pretty(pg_total_relation_size(schemaname || '.' || tablename)) AS total_size,
    n_dead_tup,
    n_live_tup,
    round(100.0 * n_dead_tup / nullif(n_live_tup + n_dead_tup, 0), 1) AS dead_pct,
    last_autovacuum,
    last_autoanalyze
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC
LIMIT 20;

-- Index bloat (using pg_relation_size vs estimated used)
SELECT
    indexrelname,
    pg_size_pretty(pg_relation_size(indexrelid)) AS index_size,
    idx_scan,
    idx_tup_read,
    idx_tup_fetch
FROM pg_stat_user_indexes
ORDER BY pg_relation_size(indexrelid) DESC
LIMIT 20;

Active Query Monitoring (pg_stat_activity)

-- Long-running queries
SELECT
    pid,
    now() - query_start AS duration,
    state,
    wait_event_type,
    wait_event,
    left(query, 100) AS query
FROM pg_stat_activity
WHERE state != 'idle'
  AND query_start < now() - INTERVAL '30 seconds'
ORDER BY duration DESC;

-- Blocking and blocked queries
SELECT
    blocked.pid          AS blocked_pid,
    blocking.pid         AS blocking_pid,
    left(blocked.query, 80)  AS blocked_query,
    left(blocking.query, 80) AS blocking_query
FROM pg_stat_activity blocked
JOIN pg_stat_activity blocking
  ON blocking.pid = ANY(pg_blocking_pids(blocked.pid))
WHERE cardinality(pg_blocking_pids(blocked.pid)) > 0;

-- Terminate a specific pid (superuser only)
SELECT pg_terminate_backend(pid) FROM pg_stat_activity WHERE pid = <target_pid>;

---

Autovacuum Tuning

Per-Table Settings

Override global autovacuum settings for high-churn tables:

-- High-churn table: trigger vacuum more aggressively
ALTER TABLE orders SET (
    autovacuum_vacuum_scale_factor     = 0.01,   -- 1% dead tuples (default 20%)
    autovacuum_analyze_scale_factor    = 0.005,  -- 0.5% changed for analyze
    autovacuum_vacuum_cost_delay       = 2,      -- ms; lower = faster vacuum
    autovacuum_vacuum_threshold        = 50,     -- minimum dead tuples before trigger
    autovacuum_analyze_threshold       = 50
);

-- Large append-only table: raise threshold to reduce noise
ALTER TABLE events SET (
    autovacuum_vacuum_scale_factor  = 0.001,
    autovacuum_analyze_scale_factor = 0.001
);

Dead Tuple Threshold Formula

Autovacuum triggers when:

dead_tuples > autovacuum_vacuum_threshold + autovacuum_vacuum_scale_factor * n_live_tup

For a 10M-row table at the default scale_factor=0.20:

• Threshold = 50 + 0.20 × 10,000,000 = 2,000,050 dead tuples before vacuum runs.
• Reduce scale_factor to 0.01 for tables with frequent UPDATE/DELETE.

Global postgresql.conf Tuning

# Reduce I/O impact of autovacuum
autovacuum_vacuum_cost_delay = 2ms          # default 2ms (pg14+); was 20ms
autovacuum_vacuum_cost_limit = 400          # default 200; allows faster passes

# Scale factor defaults (override per-table for hot tables)
autovacuum_vacuum_scale_factor  = 0.05     # default 0.20
autovacuum_analyze_scale_factor = 0.02     # default 0.10

# Worker count
autovacuum_max_workers = 5                  # default 3

---

Connection Pooling

PgBouncer vs pgpool-II

Feature	PgBouncer	pgpool-II
Primary purpose	Connection pooling	Pooling + load balancing + HA
Modes	Session, Transaction, Statement	Session, Transaction
Overhead	Very low (C, single process)	Higher (more features)
Read scaling	No built-in	Routes SELECTs to replicas
HA / failover	No (use external)	Yes (watchdog, VIP)
Complexity	Simple config	More complex
Typical use	Application → single primary	Need query routing or HA middleware

PgBouncer Configuration (pgbouncer.ini)

[databases]
mydb = host=127.0.0.1 port=5432 dbname=mydb

[pgbouncer]
listen_port        = 6432
listen_addr        = 0.0.0.0
auth_type          = scram-sha-256
auth_file          = /etc/pgbouncer/userlist.txt
pool_mode          = transaction        ; transaction mode = best performance
max_client_conn    = 1000
default_pool_size  = 25
min_pool_size      = 5
reserve_pool_size  = 5
reserve_pool_timeout = 3
server_idle_timeout = 600
log_connections    = 0
log_disconnections = 0

Transaction vs Session Mode

Mode	Behaviour	Use Case
Transaction	Server connection held only during transaction	Stateless apps; highest concurrency
Session	Server connection held for full client session	Requires session state (temp tables, prepared statements)
Statement	Released after each statement	Rarely used; autocommit only

Transaction mode caveat: prepared statements and advisory locks are incompatible with transaction mode. Disable prepared_statements at the driver level or use DEALLOCATE ALL at transaction end.

---

Cross-References

• Gemini PostgreSQL extension: gemini extensions install https://github.com/gemini-cli-extensions/postgresql — 24 tools for query execution, schema inspection, EXPLAIN analysis, and more.

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References Index

For detailed guides and code examples, refer to the following documents in references/:

• Advanced SQL Patterns -- CTEs, window functions, JSONB operations, array ops, lateral joins, recursive queries.
• Indexing & Performance -- Index types (B-tree, GIN, GiST, BRIN), partial indexes, expression indexes.
• Administration -- Configuration, roles, connection pooling (pgbouncer), vacuuming, WAL.
• psql CLI -- psql commands, \d meta-commands, .psqlrc customization.
• PL/pgSQL Development -- Functions, procedures, triggers, exception handling, DO blocks.
• Performance Tuning -- EXPLAIN, pg_stat_statements, autovacuum, parallel query.
• Connection Patterns -- psycopg v3, asyncpg, SQLAlchemy, node-postgres, Rust sqlx.
• JSON/JSONB Patterns -- JSONB operators, SQL/JSON path, GIN indexing, generated columns.
• Security -- Role management, RLS, column privileges, SSL/TLS, pgAudit.
• Key Extensions -- PostGIS, pgvector, pg_cron, pg_stat_statements, pg_trgm, TimescaleDB.
• Replication & HA -- Streaming replication, logical replication, Patroni, PITR.
• Schema Migrations & DevOps -- Alembic, Flyway, zero-downtime migrations, pgTAP testing.

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Official References

• https://www.postgresql.org/docs/current/
• https://wiki.postgresql.org/

Shared Styleguide Baseline

• Use shared styleguides for generic language/framework rules to reduce duplication in this skill.
• General Principles
• PostgreSQL
• Keep this skill focused on tool-specific workflows, edge cases, and integration details.