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bigquery-sql

Provides BigQuery SQL query optimization techniques, execution best practices, and performance tuning rules for high-efficiency querying.

Skill by nguyenhungtran18

IndexedMIT★ 1
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

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.

Use cases: backend, data

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/bigquery-sql

What's inside

Skill name
bigquery-sql
Description
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.
License
MIT
Metadata
version: v1
Instructions
42 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • name: "bigquery-sql" does not match folder "bigquery_sql"

Files (2)

  • OWNERS
  • SKILL.md

SKILL.md (first lines)

# 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.

From nguyenhungtran18/skill-and-tool-tracker, MIT.

Signals

Stars
1
Forks
0
Open issues
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Last commit (this folder)
Aug 31, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
v1
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

bigquery-sql skill. Agent Mart. https://agentmart.dev/skills/nguyenhungtran18-bigquery-sql (last updated 2026-10-24)