Women in Open Source & Presto – Getting started in the Presto open source ecosystem

Women in Open Source & Presto – Getting started in the Presto open source ecosystem

Women in Open Source & Presto – Getting Started in the Presto Open Source Ecosystem – Neha Pawar, Startree; Rebecca Schlussel, Meta; RongRong Zhong, Celonis & Moderated By Dipti Borkar, Microsoft Among GitHub users with at least ten contributions, a mere 6% were women. This is way less than the ratio of women in tech that various research shows at 26%. Given the amount of investment going into and the growth / success of companies based on open source as well as the enormous demand for developers in open source, it is a ratio we need to strive to improve for women. In this panel, we will discuss a few areas: – The journey of each panelist into open source projects – The benefits they have seen by participating in open source projects particularly Presto – The challenges women face in male-dominated open source communities – Ideas, suggestions and guidance to budding engineers on getting started with open source including Presto.

Presto Query Analysis for Data Layout Formatting and Query Result Caching – Gurmeet Singh, Uber

Presto Query Analysis for Data Layout Formatting and Query Result Caching – Gurmeet Singh, Uber

In this talk, I will be talking about a microservice that we have built at Uber to be able to analyze Presto queries. The Presto Query Engine does not provide endpoints for query analysis purposes. One has to either execute the query or gather insights from the query explain plan. In this talk, I will talk about 1. The work that we had to do to do the query analysis in a microservice using Presto as a library. 2. Doing predicate analysis on the queries to come up with data formatting recommendations in order to improve query performance. 3. Using the analysis service for query result cache invalidation. The analysis figures out whether the results from a previous run of the query are still valid and can be reused.