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  2. Sep 9, 2024 · This topic provides general information and specific suggestions for improving the performance of your Athena queries, and how to work around errors related to limits and resource usage. Broadly speaking, optimizations can be grouped into service, query, and data structure categories.

    • Optimize queries

      Use the query optimization techniques described in this...

    • Optimize data

      To run the query, Athena must perform at least one million...

    • Storage
    • Creating Optimized Datasets
    • Query Tuning
    • Bonus Tips
    • Conclusion

    This section discusses how to structure your data so that you can get the most out of Athena. You can apply the same practices to Amazon EMRdata processing applications such as Spark, Trino, Presto, and Hive when your data is stored in Amazon S3. We discuss the following best practices: 1. Partition your data 2. Bucket your data 3. Use compression ...

    In this section, we show you how to use Athena Spark to transform a dataset and apply the optimizations that we discussed in the previous sections. You can also use this code in most other Spark runtimes, for example Amazon EMR Serverless or AWS Glue ETL. You can also use Athena SQL to transform data and apply many of the optimizations described in...

    The Athena SQL engine is built on the open source distributed query engines Trino and Presto. Understanding how it works provides insight into how you can optimize queries when running them. This section details the following best practices: 1. Optimize ORDER BY 2. Optimize joins 3. Optimize GROUP BY 4. Use approximate functions 5. Only include the...

    In this section, we provide additional performance tuning tips, and new performance-oriented features launched since the first version of this post.

    This post covered our top 10 tips for optimizing your interactive analysis on Athena SQL. You can apply these same practices when using Trino on Amazon EMR. You can also view the Turkic translated version of this post.

  3. Use the query optimization techniques described in this section to make queries run faster or as workarounds for queries that exceed resource limits in Athena.

  4. To run the query, Athena must perform at least one million Amazon S3 list operations. Queries are fastest when you query on specific values, regardless of whether you use partition projection or store partition information in the catalog.

  5. Nov 17, 2023 · In summary, Athena’s new cost-based optimizer significantly speeds up queries by choosing superior run plans. CBO optimizes based on table statistics stored in the AWS Glue Data Catalog. This automatic optimization improves productivity for Athena users through more responsive query performance.

  6. Nov 8, 2022 · Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run on datasets at petabyte scale.

  7. Jul 8, 2024 · Athena simplifies the execution of queries on large amounts of data. Applications with a high volume of queries should evaluate server-based services such as EMR or Redshift. A good practice is to monitor CloudWatch , and use tools such as DPUAllocated, DPUConsumed and ProcessedBytes.