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golang-database

golang-database

Implement Go database access with context, pool tuning, transaction boundaries, and repository seams. Use when building repositories, tuning `sql.DB` or `pgx`, or reviewing DB transaction flow in Go.

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name: golang-database description: Implement Go database access with context, pool tuning, transaction boundaries, and repository seams. Use when building repositories, tuning sql.DB or pgx, or reviewing DB transaction flow in Go. metadata: triggers: files: - 'internal/adapter/repository/**' keywords: - database - sql - postgres - gorm - sqlc - pgx

Golang Database

Priority: P0 (CRITICAL)

Rules

  • Prefer explicit SQL or generated query layers when performance and shape matter.
  • Configure the pool; defaults are rarely enough for real traffic.
  • Pass context.Context as the first argument to every query path.
  • Strict Parameterization: Always use parameterized placeholders (?, $1); never interpolate user strings into queries.
  • Dynamic IN Batching: Generate safe placeholders (strings.Repeat("?,", len(ids))) or sqlx.In and partition lists into chunks ≤ 1,000 items to avoid driver parameter limits.
  • Explicit Column Aliasing: Always alias duplicate column names in multi-table queries (e.g. m.code AS code); drivers map by name and silently collide on joins.
  • Transaction Boundaries: Manage transactions at the service layer using withTx(ctx, db, fn) with mandatory defer tx.Rollback(). Keep transactions short and focused on writes.
  • Streaming & Keyset Pagination: Stream large result sets using rows.Next() directly into models to prevent unbounded memory allocation.

Recipe

  1. Choose the access layer: database/sql, pgx, sqlx, sqlc, or ORM only if standardized.
  2. Tune the pool: max open, max idle, connection lifetime, and idle lifetime.
  3. Hide storage details behind repository methods or query services.
  4. Close rows and inspect rows.Err().
  5. Wrap multi-step writes in one transaction using a withTx helper with defer tx.Rollback().
  6. Chunk large slice lookups: partition slices into batches of ≤ 1,000 before running IN queries.

Verify

  • Query methods accept context.Context.
  • Pool settings are explicit.
  • Rows are closed and iteration errors checked (rows.Err()).
  • Large IN (...) queries chunk parameters into batches of ≤ 1,000.
  • Joined queries use explicit column aliases without SELECT *.
  • Transaction scope matches one business action and uses defer tx.Rollback().
  • Retry/idempotency policy is clear for contested writes.

Anti-Patterns

  • No global db var: inject DB connection via constructor.
  • No context-less queries: use QueryContext/ExecContext; bare queries ignore timeouts.
  • No string concatenation in SQL: never build dynamic clauses with fmt.Sprintf or +.
  • No unbounded IN lists: avoid passing un-chunked slices with > 1,000 items into a single query.
  • No SELECT * on Joins: avoid unaliased duplicate column names across joined tables.
  • No leaked rows: always defer rows.Close() and check rows.Err().
  • No transaction split-brain: handler, repo, and service cannot each open their own transaction for one unit of work.

References

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