bigtable-basics

Bigtable Basics

This skill provides core workflows and guidance for administering and developing with Google Bigtable.

Core Principles

• Control Plane vs. Data Plane:
  • Use gcloud for Control Plane operations: Manage Instances, Clusters, App Profiles, Backups and IAM. Create Tables, Logical Views, Materialized Views and Authorized Views.
  • Use cbt for Data Plane operations: Update Tables, Column Families, and reading/writing data.
• Performance First: Bigtable is a NoSQL database. Efficiency is tied to Row Key design. Always warn about Full Table Scans.
• Client Selection: For production use cases, prefer Java or Go for their superior performance and feature coverage compared to other languages.
• Observability: When diagnosing performance or hotspotting, always mention Key Visualizer (via Cloud Console) as the primary diagnostic tool because it provides the most granular view of access patterns across row keys. This should be followed by the hot-tablets tool and table stats in gcloud CLI and include-stats=full option under cbt read to diagnose slow queries.

[!IMPORTANT] Safety Rule: You MUST obtain explicit user confirmation before making non-emulator database changes. You MUST mention this safety requirement when providing commands or instructions that modify the database structure or data.

Quick Recipes

1. Querying Data

Use SQL for complex transforms or aggregations and key-value APIs for simpler query patterns. Note: Use exact match, prefix (_key LIKE 'myprefix%'), or range predicates on _key to avoid expensive unbounded scans. Recommend explicit row ranges (_key BETWEEN 'start' AND 'end') as a more performant alternative to prefix matches where possible.

If expensive scans (either unbounded or prefix or range queries scanning a large range) are unavoidable due to multiple access patterns that can’t all be accommodated in a single schema, consider one of these two options: