BigQuery is a serverless, highly-scalable, and cost-effective cloud data warehouse with an in-memory BI Engine and machine learning built in. This repository provides useful utilities to assist you in migration and usage of BigQuery.

This repository is broken up into:

• Dashboards - Pre-built dashboards for common use cases
• Performance Testing - Examples for doing performance testing
  • JMeter - Examples for using JMeter to test BigQuery performance
• Scripts - Python, Shell, & SQL scripts
  • billing - Example queries over the GCP billing export
  • optimization - Scripts to help identify areas for optimization in your BigQuery warehouse.
• Stored Procedures - Example stored procedures
• Third Party - Relevant third party libraries for BigQuery
  • compilerworks - BigQuery UDFs which mimic the behavior of proprietary functions in other databases
• Tools - Custom tooling for working with BigQuery
  • Cloud Functions - Cloud Functions to automate common use cases
• UDFs - User-defined functions for common usage as well as migration
  • community - Community contributed user-defined functions
  • migration - UDFs which mimic the behavior of proprietary functions in the following databases:
    • netezza
    • oracle
    • redshift
    • snowflake
    • teradata
    • vertica
• Views - Views over system tables such as audit logs or the INFORMATION_SCHEMA
  • query_audit - View to simplify querying the audit logs which can be used to power dashboards (example).

For more information on UDFs and using those provided in the repository with BigQuery, see the README in the udfs folder.

See the contributing instructions to get started contributing.

To contribute UDFs to this repository, see the instructions in the udfs folder.

Except as otherwise noted, the solutions within this repository are provided under the Apache 2.0 license. Please see the LICENSE file for more detailed terms and conditions.

This repository and its contents are not an official Google Product.