PrestoDB in HPE Ezmeral Unified Analytics – Milind Bhandarkar, HPE

PrestoDB in HPE Ezmeral Unified Analytics – Milind Bhandarkar, HPE


HPE Ezmeral Unified Analytics is an end-to-end data & AI/ML platform that consists of several popular open-source frameworks for data engineering, data analytics, data science, & ML engineering in a well-integrated packaging. These open-source frameworks include Apache Spark, Apache Airflow, Apache Superset, PrestoDB, MLFlow, Kubeflow, and Feast. This platform is built atop Kubernetes and provides built in security. In this talk we will focus on the role of PrestoDB in Unified Analytics as a fast SQL query engine, and also as a secure data access layer. We will discuss some of our value-additions to PrestoDB, such as a distributed memory-centric columnar caching layer that provides both explicit and transparent caching for dataset fragments, often leading to 3x to 4x query performance. We will conclude by proposing to make caching pluggable in PrestoDB and discussing future directions.

The Past, Present, and Future of Presto – Philip Bell, Meta

The Past, Present, and Future of Presto – Philip Bell, Meta

PrestoDB recently underwent major architectural updates as the Presto Foundation grows membership and is looking to vastly grow the number of new commits and forks. Achieving this desired end state required successful refactoring and improving of Presto’s already impressive speed, efficiency, reliability, and extensibility. Establishing PrestoDB as a premier Open Source project required a major commitment of time and resources from Meta to ensure the community can benefit from this project for years to come, as well as positioning PrestoDB to evolve beyond what Meta alone could create. Members of the Presto Foundation need more of you to be involved in this major evolution in Presto’s history and core components, and bring your own inventive ideas to the mix.