Chinmay Soman

PMC Member/Commiter @SamzaStream

Chinmay Soman has been working in the distributed systems domain for the past 10+ years. He started out in IBM where he worked on distributed file systems and replication technologies. He then joined the Data Infrastructure team in LinkedIn and worked on open source technologies such as Voldemort and Apache Samza. Until recently, he was a Senior Staff Software Engineer in Uber where he led the Streaming and Real-Time Analytics Platform team. Currently, he’s a founding engineer in a stealth mode company.

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Building Latency Sensitive User Facing Analytics via Apache Pinot

Real-time analytics has become the need of the hour for modern Internet companies. The ability to derive internal insights around business metrics, user growth & adoption as well as security incidents from all the raw logs is crucial for day to day operation. Even more critical is enabling access to usage analytics for the millions of customers which is non-trivial to achieve.

A good example of this is LinkedIn’s ‘Who Viewed My Profile’ which allows all 700 million+ users to slice and dice their page view data. Another example is Uber’s Restaurant Manager which enables restaurant owners across the globe to gain insights around menu preference, sales metrics, busy hours and so on. All such user facing applications need an analytical store that can support 1000s of queries per second at a millisecond response time granularity while ingesting millions of events/second.

In this talk, we will elaborate on how this is made possible using Apache Pinot - a popular, open source, distributed OLAP store. Specifically, we will talk about how to maintain the p99th latency SLA in the presence of organic data growth and concurrent queries.


Tuesday Nov 17 / 11:40AM PST (40 minutes )

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