How Apache Pinot Achieves 200,000 Queries per Second (with Tim Berglund)
Developer Voices
Apache Pinot Architecture and Query Optimization
The chapter delves into the architecture of Apache Pinot in terms of segments, servers, and querying processes, explaining the significance of segments as chunks of table data and the role of servers in storing segment data and computing queries efficiently. It discusses the design choices of Pinot towards optimizing queries with sensible date ranges and tailoring the system for interactive user queries, focusing on latency, concurrency, and data freshness. The conversation also covers the origins of Apache Pinot at LinkedIn, detailing its evolution from a reluctance to build a new database to becoming a user-facing analytics tool adopted by various companies like Uber Eats.
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