BigQuery Query

Rules: Follow coding-standards for SQL naming and readability.

Prerequisites

Check gcloud configuration before running queries:

gcloud config get-value project

• If authentication error: prompt user to run gcloud auth login, then resume
• If project unset: prompt user to run gcloud config set project <PROJECT_ID>

Workflow

1. Clarify requirements: Understand what data is needed and why. If requirements are already in context, proceed to next step.

2. Understand schema: Explore available datasets. If schema is already in context, proceed to next step.

   bq ls project:dataset                           # List tables
   bq show --schema project:dataset.table          # Show table schema
   

3. Design query: Write SQL based on requirements and schema.

   • Use CTEs for readability
   • Use fully-qualified table names: project.dataset.table
   • Specify exact date ranges to limit scanned data
   • Filter partitioned tables by partition key
   • Avoid correlated subqueries (use JOINs/CTEs)
   • Filter early with CTEs before joining large tables
   • Use LIMIT for exploration queries

4. Dry run: Validate syntax and estimate cost

   bq query --use_legacy_sql=false --dry_run "SELECT ..."
   

   Cost: ~$5/TB. If >2GB, ask user before executing.

5. Execute: Run after successful dry run, once any required user confirmation has been given

   bq query --use_legacy_sql=false --format=csv "SELECT ..."