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Pre-Aggregation in Apache Pinot

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Pre-Aggregation in Apache Pinot

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Apache Pinot is a high-performance real-time OLAP database designed for ultra-fast analytics at scale. To accelerate data filtering, it employs various indexing techniques, including sorted index, inverted index, and range index. However, even with efficient filtering, query performance can be significantly impacted by the volume of data that needs to be processed. In this talk, we will explore the different types of pre-aggregation strategies in Apache Pinot that reduce the amount of data processed, thereby enhancing query performance. Join us to learn how these techniques can optimize your data analytics workflows.

Xiaotian (Jackie) Jiang
Founding Engineer & Chief Architect at StarTree, PMC for Apache Pinot
I am profoundly passionate about real-time user-facing analytics, constantly striving to enhance its value for businesses. I relish the opportunity to solve complex challenges associated with achieving low latency and high throughput in analytics, ensuring seamless performance and insightful user experiences.
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