sql-performance-review

name	sql-performance-review
description	Review and improve Databricks SQL queries for correctness, readability, and performance (joins, filters, aggregations, partition pruning). Use when someone pastes a SQL query, asks why it is slow, or requests a rewrite/optimization in Databricks SQL.
license	Proprietary. For internal team use.
compatibility	Designed for Databricks Assistant agent mode. Works best when the user provides the SQL query and (optionally) table names, row counts, or query profile details.
metadata	{"author":"your-team","version":"1.0"}

Databricks SQL performance review

Use this skill when optimizing or reviewing SQL in Databricks SQL.

What to ask for (only if missing)

Ask up to 3 questions total:

1. The query text (if not provided)
2. The table(s) involved + their sizes (rough order of magnitude) OR the query profile / execution plan
3. The desired result constraints (correctness, exactness, latency SLA)

If the user can’t provide sizes/plan, proceed with best-effort heuristics and call out assumptions.

Output format

Use the structure in assets/sql-review-output.md.

Checklist

Use references/sql-checklist.md to ensure you cover the common performance levers:

• predicate pushdown / partition pruning
• join strategy and join keys
• avoid SELECT *
• minimize shuffles / wide aggregations
• use correct data types and avoid implicit casts
• reduce data scanned (pre-filter, semi-joins, EXISTS)

Examples

User: “This query is slow in Databricks SQL. Can you optimize it?” (pastes query)
Assistant: Provide issues, suggestions, and a rewritten query, plus next steps (EXPLAIN, add ZORDER, etc.).

Edge cases

• If the query is logically wrong (duplicates from joins, missing filters), fix correctness first.
• If tables are Delta: suggest partitioning/ZORDER/OPTIMIZE only if it matches query patterns.
• If the user is in a governed environment: avoid suggestions that require elevated permissions unless noted.