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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.
- AWS Glue
CREATING — The index is currently being created, and is not...
- Optimize data
Narrow the scope of possible values to avoid unnecessary...
- Top 10 Performance Tuning Tips
Athena is easy to use, simply point to your data in Amazon...
- Optimize queries
Use the query optimization techniques described in this...
- AWS Glue
Narrow the scope of possible values to avoid unnecessary Amazon S3 listings. Imagine a partition key that has a range of one million values and a query that does not have any filters on that partition key. To run the query, Athena must perform at least one million Amazon S3 list operations.
- 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.
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.
Jul 8, 2024 · Optimize Amazon Athena performance with these 5 tuning tips. Amazon Athena can provide an efficient, cost-effective method of data analysis. But did you properly optimize Athena performance to see these benefits? By. Ernesto Marquez, Concurrency Labs. Published: 08 Jul 2024.
- Ernesto Marquez
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.
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What are optimizations in Amazon Athena?
How does Athena's new cost-based optimizer improve query performance?
What is Amazon Athena?
How does Athena work?
Nov 17, 2023 · Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena.
