The BigQuery Execution Graph is now generally available

Summary

Google BigQuery's Query Execution Graph, a tool for diagnosing and improving query performance, is now generally available, offering insights and suggestions through an intuitive user interface.

Abstract

Google BigQuery has released its Query Execution Graph to the public, providing a visual tool to help users understand and optimize the performance of their SQL queries. This graph serves as a critical component for both data analysts and data warehouse administrators to diagnose performance issues in queries, which can be impacted by the complexities of BigQuery's distributed system. The interface allows for the examination of query plans both during and after query execution, and it offers performance insights to enhance query efficiency. Despite the multifaceted nature of query performance, the Query Execution Plan aims to give users a clearer picture of potential improvements.

Opinions

The author views the Query Execution Plan as a beneficial feature for diagnosing slow query performance and for providing optimization suggestions.
It is noted that while the tool provides valuable insights, it may not capture all aspects of query performance due to the complexity of the system.
The author appreciates the ability to analyze the causes of long-running queries and suggests that users interested in query tuning and cost reduction may find additional resources linked within the article useful.
The article implies that both data analysts and data warehouse or data lake administrators will find the Execution Plan feature particularly useful for managing query performance and resources within their organizations.

How to use the Query Execution Graph to diagnose Query Performance Issues

Google BigQuery offers high query performance but is also a complex distributed system with many internal and external factors that can impact query speed. Due to the declarative nature of the SQL language, the complexity of query execution can be hidden, making it difficult to identify the cause if your queries are running slower than expected or slower than previous executions. Therefore, Google now made the Query Execution Plan for anyone available[1][2].

The in BigQuery built-in Query Execution Plan provides an intuitive user interface for retrieving query performance details. It allows you to examine the query plan information in a graphical format for each query, whether it is currently running or already completed[2]. After you started/finished a query, you can find the function under “Execution Graph”.

Result presented within the Query Visualization — Image by Author

Google has developed the Query Execution Plan to provide suggestions to improve query performance. As query performance is multifaceted, the performance insights may only provide an incomplete picture of the overall query performance[1][2].

There are two main use cases: The Data Analysts who execute queries within a project. They want to understand why a previously executed query is running unexpectedly slower and how to improve the performance of a query and the Data Lake or Data Warehouse administrators, who manage the BigQuery resources and reservations of your organization.

So for me, this is a pretty nice new feature. From time to time, you will encounter some long running queries — with the Execution Plan you will now be able to analyze why. If you are interested in other tips and tricks on how to tune your queries and/or reduce costs, the following article might be also interesting for you.

The BigQuery Execution Graph is now generally available

How to use the Query Execution Graph to diagnose Query Performance Issues

3 Best Practices for Data Engineers in BigQuery

How to easily improve Query Performance in Google’s Data Warehouse

How to optimize BigQuery Usage and Costs

Best Practices you should know about when working with Google’s Data Warehouse

Sources and Further Readings