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bigquery-features

Use when asking about BigQuery-specific features, syntax, or capabilities including: STRUCT/ARRAY/UNNEST patterns, MERGE statements, BigQuery scripting (DECLARE, IF, LOOP, BEGIN/END), scheduled queries, remote functions, JSON functions, approximate aggregation (APPROX_COUNT_DISTINCT, HLL_COUNT), geography/GIS functions, BigQuery ML (CREATE MODEL), search indexes, vector search, or BI Engine. Trigg

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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:

  1. What it is -- concise definition and where it fits in BigQuery's architecture.
  2. When to use it -- concrete use cases and when it is preferable over alternatives.
  3. Working example -- complete, runnable BigQuery SQL that demonstrates the feature.
  4. 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.

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