dialect-bigquery

What problem does it solve?

BigQuery SQL often requires precise identifiers, safe casting, and specialized functions. This dialect helps you write and debug SQL for BigQuery by guiding the correct use of backtick-quoted identifiers, casts, and BigQuery-specific functions.

Core Features & Use Cases

• Backtick-qualified identifiers: Use project.dataset.table notation to avoid ambiguity in multi-project environments.
• Type handling: Employ CAST and SAFE_CAST to manage data types safely and predictably.
• BigQuery functions: Utilize REGEXP_CONTAINS, FORMAT_DATE, and UNNEST for nested and repeated fields.
• Use Case: Build robust queries for dashboards and data pipelines that rely on precise date formatting and safe casting.

Quick Start

Write a BigQuery SQL query that selects from a fully-qualified table like my_project.my_dataset.orders and formats order_date with FORMAT_DATE.