Presto on ARM – Chunxu Tang & Jiaming Mai, Alluxio

Presto on ARM – Chunxu Tang & Jiaming Mai, Alluxio

Traditionally, the deployment of Presto has been limited to Intel processors with the x86 architecture. However, with the growing popularity of ARM architecture, Chunxu and Jiaming have extended the Presto ecosystem to ARM and conducted a series of benchmark experiments. Their objective is to evaluate the performance of Presto on ARM architecture and identify key insights from the experiments. In this presentation, Chunxu and Jiaming will share the results of their performance evaluation and discuss some of the most significant findings from their research.

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.