Many organizations are leveraging Hive to run big data analytics on public cloud. However, reading and writing data to S3 directly can result in slow and inconsistent performance. Alluxio is a data orchestration layer for the cloud, and in this use case it caches data for S3, ensuring high and predictable performance as well as reduced network traffic.
In this Office Hour we’ll go over:
- Bazaarvoice’s use case leveraging Apache Spark, Hive, and Alluxio on S3
- How to set up Hive with Alluxio such that Hive jobs can seamlessly read from and write to S3
- Open Session for discussion on any topics such as solving the separation of compute and storage problem, and more
Many organizations are leveraging Hive to run big data analytics on public cloud. However, reading and writing data to S3 directly can result in slow and inconsistent performance. Alluxio is a data orchestration layer for the cloud, and in this use case it caches data for S3, ensuring high and predictable performance as well as reduced network traffic.
In this Office Hour we’ll go over:
- Bazaarvoice’s use case leveraging Apache Spark, Hive, and Alluxio on S3
- How to set up Hive with Alluxio such that Hive jobs can seamlessly read from and write to S3
- Open Session for discussion on any topics such as solving the separation of compute and storage problem, and more
Videos:
Presentation Slides:
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Videos
In this talk, Bin Fan, VP of Technology at Alluxio, explores how to enable efficient data access across distributed GPU infrastructure, achieving low-latency performance for feature stores and RAG workloads.