Introduction

Amazon Aurora is a popular choice for database workloads due to its compatibility with MySQL and PostgreSQL, as well as its performance and scalability capabilities. One of the powerful features of Amazon Aurora is the SQL Query Store, which helps in query plan analysis and optimization.

In this blog post, we will explore how to leverage the SQL Query Store in Amazon Aurora to analyze query plans, identify performance bottlenecks, and optimize query performance.

What is the SQL Query Store?

The SQL Query Store in Amazon Aurora is a repository that captures and stores query plans, runtime statistics, and execution history for individual queries. It provides valuable insights into query performance, allowing you to track changes in query performance over time.

Enabling the SQL Query Store

To enable the SQL Query Store in Amazon Aurora, you need to modify the database parameter group associated with your Aurora instance. Set the aurora_query_store_capture_enabled parameter to 1 to enable query plan capture.

CALL rds_modify_db_cluster_parameter_group('your-parameter-group-name', 'aurora_query_store_capture_enabled', '1');

Analyzing Query Plans

Once the SQL Query Store is enabled, you can start analyzing query plans for your workload. The Query Store provides several views and functions to query the captured query plans and statistics.

Identifying Top Resource Consumers

The aurora_$$query_snapshot_summary view can be used to identify the top resource consumers. It provides information about the total duration, execution count, and average duration of each query plan.

SELECT *
FROM aurora_$$query_snapshot_summary
ORDER BY total_duration DESC;

Investigating Query Execution Details

Using the aurora_$$query_execution_details view, you can gather detailed information about query execution, including the execution time, CPU time, and wait time.

SELECT *
FROM aurora_$$query_execution_details
WHERE query_plan_hash = 'your-query-plan-hash';

Getting Query Performance Statistics

The aurora_$$query_aggregation_statistics function allows you to retrieve various statistics related to query performance, such as the average and maximum execution time, CPU time, and wait time.

SELECT *
FROM aurora_$$query_aggregation_statistics('your-start-time', 'your-end-time');

Optimizing Query Performance

Once you have analyzed query plans and identified performance bottlenecks, you can take measures to optimize query performance.

Updating Statistics and Indexes

Outdated statistics and missing or poorly designed indexes can significantly impact query performance. Regularly updating statistics and ensuring the presence of appropriate indexes can improve query plan selection.

Query Plan Forcing

In some cases, the optimizer may choose a sub-optimal query plan. You can force the use of a specific query plan using the FORCE_PLAN hint in your queries.

SELECT /*+ FORCE_PLAN(your-plan-hint) */ column1, column2
FROM your_table
WHERE condition;

Query Rewrite

Analyzing query plans can help identify opportunities for query rewrite. Simplifying complex queries or breaking them down into multiple smaller queries can improve performance.

Conclusion

The SQL Query Store in Amazon Aurora provides a powerful tool for query plan analysis and optimization. By analyzing query plans and making appropriate changes to indexes, statistics, and query structures, you can significantly improve your database performance. Enable the SQL Query Store, leverage its views and functions, and experiment with different optimization techniques to get the most out of your Amazon Aurora database.

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