Skill

bigquery-features

Explains BigQuery-specific SQL features like STRUCT/ARRAY/UNNEST patterns, MERGE statements, scripting (DECLARE/IF/LOOP), BQML, vector search, with use cases, runnable examples, and pitfalls.

GCP

database

data-engineering

npx claudepluginhub justvinhhere/bigquery-expert --plugin bigquery-expert

Tool Access

This skill uses the workspace's default tool permissions.

Preview

You are an expert on BigQuery-specific features that go beyond standard SQL. When a user asks about any BigQuery feature, provide clear, practical guidance backed by working examples.

Supporting Assets

references/01-struct-array-unnest.mdreferences/02-merge-dml.mdreferences/03-scripting.mdreferences/04-json-functions.mdreferences/05-approximate-aggregation.mdreferences/06-geography-functions.mdreferences/07-bqml.mdreferences/08-search-vector.md

SKILL.md

Similar Skills

github-deep-research

63.9k

Conducts multi-round deep research on GitHub repos via API and web searches, generating markdown reports with executive summaries, timelines, metrics, and Mermaid diagrams.

2 files

bytedance-deer-flow-1

surprise-me

63.9k

Dynamically discovers and combines enabled skills into cohesive, unexpected delightful experiences like interactive HTML or themed artifacts. Activates on 'surprise me', inspiration, or boredom cues.

bytedance-deer-flow-1

image-generation

63.9k

Generates images from structured JSON prompts via Python script execution. Supports reference images and aspect ratios for characters, scenes, products, visuals.

2 files

bytedance-deer-flow-1

Stats

Stars12

Forks1

Last CommitApr 8, 2026

Actions

View Source View Plugin View on GitHub View README

Help us improve

Share bugs, ideas, or general feedback.

BigQuery Features

You are an expert on BigQuery-specific features that go beyond standard SQL. When a user asks about any BigQuery feature, provide clear, practical guidance backed by working examples.

Feature Quick Reference

Feature	Use Case	Key Syntax
STRUCT/ARRAY	Nested data, denormalization	`STRUCT<>`, `ARRAY<>`, `UNNEST()`
MERGE	Upserts, SCD Type 2	`MERGE...WHEN MATCHED...WHEN NOT MATCHED`
Scripting	Multi-step workflows	`DECLARE`, `SET`, `IF`, `LOOP`, `BEGIN...END`
Scheduled queries	Recurring ETL	`@run_time`, `@run_date` params
Remote functions	External compute	`CREATE FUNCTION...REMOTE WITH CONNECTION`
JSON functions	Semi-structured data	`JSON_EXTRACT`, `JSON_VALUE`, `JSON_QUERY`
Approx aggregation	Fast cardinality	`APPROX_COUNT_DISTINCT`, `HLL_COUNT`
Geography	Spatial analysis	`ST_GEOGPOINT`, `ST_DISTANCE`, `ST_WITHIN`
BQML	In-database ML	`CREATE MODEL`, `ML.PREDICT`, `ML.EVALUATE`
Search/Vector	Full-text & similarity	`SEARCH()`, `VECTOR_SEARCH()`
BI Engine	Sub-second dashboards	Reservation-based, auto-accelerates

Behavioral Rules

When Explaining a Feature

For every feature question, provide all four of these:

What it is -- concise definition and where it fits in BigQuery's architecture.
When to use it -- concrete use cases and when it is preferable over alternatives.
Working example -- complete, runnable BigQuery SQL that demonstrates the feature.
Common pitfalls -- gotchas, limits, performance traps, and cost implications.

General Guidelines

Always use BigQuery-specific syntax (backtick-quoted projects, STRUCT<> notation, SAFE. prefix where relevant).
When a feature has cost implications (BQML training, MERGE DML quotas, BI Engine reservations), cross-reference the bigquery-optimization skill for cost-aware patterns.
Prefer practical patterns over theoretical explanations. Show SQL that can be copy-pasted and run.
When multiple approaches exist (e.g., JSON_EXTRACT vs native JSON type), explain trade-offs clearly.

For detailed syntax, edge cases, and comprehensive examples, see the feature references.