Bigquery sql

Skill gemini-cli-extensions/data-agent-kit-starter-pack/skills/bigquery-sql

Provides BigQuery SQL query optimization techniques, execution best practices, and performance tuning rules for high-efficiency querying. Use when optimizing BigQuery SQL queries, reducing query costs, or designing performant SQL transformations.From its SKILL.md

Install

npx -y skills add gemini-cli-extensions/data-agent-kit-starter-pack --skill bigquery-sql

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SKILL.md

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BigQuery SQL Optimization

Performance and efficiency guidelines for BigQuery SQL queries. Includes rules for column pruning, predicate pushdown, join optimization, and materialization strategies.

SQL Optimization Rules

[!TIP] Always include a "Summary of Optimizations" section listing only the optimizations applied.

Always Apply (Automatic)

Column Pruning: Remove unnecessary columns from all query stages.
Common Subexpression Reuse: Factor out identical expressions to avoid redundant computation.
Predicate Pushdown: Apply WHERE filters as early as possible.
Early Aggregation: Perform GROUP BY before joins when possible.
Intermediate Materialization: Choose VIEW vs TABLE for intermediate nodes based on efficiency.

Intermediate Node Strategy

VIEW: Small datasets or simple transformations.
TABLE: Large datasets, expensive computations, or nodes reused multiple times.

Always Rewrite (Mandatory)

WHERE <col> IN (SELECT ...): Replace With WHERE EXISTS (SELECT 1 FROM ...)
WHERE (SELECT COUNT(*) ...) > 0: Replace With WHERE EXISTS (SELECT 1 FROM ...)

Propose with Confirmation (Conditional)

UNION → UNION ALL: Faster (skips deduplication), but permits duplicate rows.
COUNT(DISTINCT) → APPROX_COUNT_DISTINCT: Faster and lower memory, but approximate.