On Demand Video

Optimizing Query Performance by Decoupling Presto and Hive Data Warehouse


Presto, an open-source distributed SQL engine, is commonly used to query an existing Hive data warehouse. Due to existing applications, tech debt or operational challenges in the past, Presto may not be able to achieve its full potential but bound and limited by the past decisions. Particularly, challenges include overloaded Hive Metastore with slow and unpredictable access, unoptimized data formats and layouts such as too many small files, or lack of influence over the existing Hive system and other Hive applications. 

Ideally, Presto would access data independently from how the data was originally stored or managed. Alluxio, as a data orchestration layer provides the physical data independence, for Presto to interact with the data more efficiently. In addition to caching for IO acceleration, Alluxio also provides a catalog service to abstract the metadata in the Hive Metastore, and transformations to expose the data in compute-optimized way. In this talk, we describe some of the challenges of using Presto with Hive, and introduce Alluxio data orchestration for solving those challenges.

In this Office Hour, we will go over:

  • Typical challenges of using Presto with Hive
  • Overview of the different services of Alluxio Structured Data Management in Alluxio 2.1
  • A demo of using Alluxio Structured Data Management with Presto


Gene Pang is the PMC Maintainer of the Alluxio open source project and a founding member of Alluxio, Inc. He graduated with a Ph.D. from the AMPLab at UC Berkeley, working on distributed database systems. Before starting at Berkeley, he worked at Google and has an M.S. from Stanford University, and a B.S. from Cornell University.

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