krishp091205/gemini-config/bigquery-sql

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Provides BigQuery SQL query optimization techniques, execution best practices,

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SKILL.md

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.

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