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Accelerate queries on Apache Iceberg tables through AWS Glue auto compaction
- AWS Glue Data Catalog now supports improved automatic compaction of Iceberg tables for streaming data. Using Apache Iceberg helps to manage transactional support and handling the inflow of small files generated by real-time data streams. The open table formats also support built-in transactional capabilities and mechanisms for compaction.
- AWS Glue’s automatic compaction is helpful in making Iceberg tables in optimal condition by monitoring table partitions and starting the compaction process when specific thresholds for the number of files and file sizes are met. Compaction makes sure that updates to the data result in new files being created, which are then compacted to improve query performance.
- Mentioned features enable businesses to handle large data sets efficiently, enhancing performance, saving costs, and providing faster data processing, shorter query times, and efficient resource utilization. AWS Glue Iceberg with auto compaction proves to be a robust solution for managing high-throughput IoT data streams.
- Data lakes were originally designed to store large volumes of raw, unstructured or semi-structured data at a low cost, serving big data and analytics use cases, but now, data lakes have become essential for various data-driven processes beyond reporting and analytics.
- The organizations have traditionally addressed challenges posed by data lakes through complex extract, transform, and load (ETL) processes, which often led to data duplication and increased complexity in data pipelines. However, to cope with the proliferation of small files, organizations had to develop custom mechanisms to merge these files, leading to the creation of bespoke solutions that were challenging to scale and manage.
- To simplify these challenges, organizations have adopted open table formats (OTFs) like Apache Iceberg, which provide built-in transactional capabilities and mechanisms for compaction. OTFs also address key limitations in traditional data lakes by providing features like ACID transactions, which maintain data consistency across concurrent operations.
- AWS Glue Data Catalog now supports improved automatic compaction of Iceberg tables for streaming data. Using Apache Iceberg helps to manage transactional support and handling the inflow of small files generated by real-time data streams. The open table formats also support built-in transactional capabilities and mechanisms for compaction.
- Automatic compaction in the AWS Glue Data Catalog makes sure that Iceberg tables are always in optimal condition. It constantly monitors table partitions and starts the compaction process when specific thresholds for the number of files and file sizes are met.
- AWS Glue’s automatic compaction is beneficial in making Iceberg tables in optimal condition by monitoring table partitions and starting the compaction process when specific thresholds for the number of files and file sizes are met. Compaction ensures that data updates result in the creation of new files, which are then compacted to improve query performance.
- Mentioned features enable businesses to handle large data sets efficiently, enhancing performance, saving costs, and providing faster data processing, shorter query times, and efficient resource utilization.
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