Introducing Apache Pinot: Real-time Analytics for Large-Scale Data

Explore Apache Pinot in this conference talk from Devoxx Poland 2022. Dive into the fundamentals of this real-time distributed OLAP datastore, understanding its architecture, data model, and query language. Learn about Pinot's ability to handle both batch and streaming data ingestion, its segmenting and replication strategies, and cluster management techniques. Discover how Pinot addresses nonfunctional requirements like low latency, using the Uber Eats example to illustrate its real-world applications. Gain insights into Pinot's indexing capabilities, including various index types, and how it enables real-time aggregation for efficient data analysis. Understand the technology behind "the feed" and how Pinot supports community-driven development. This comprehensive overview equips developers and data engineers with the knowledge to leverage Apache Pinot for high-performance analytics on large-scale datasets.

Introduction
What is Pinot
Textiles
Thread
Charging cables
Disruptive Innovation
Nonfunctional requirements
Uber Eats example
Restaurant managers
Latency requirements
Users
Technology
The feed
Realtime aggregation
Community
Data Model
Query Language
Architecture
Batch ingestion
Segments
Segment Structure
Segmenting
Replication
Cluster management
Batch upload
Offline table
Streaming data
Queryability
Indexes
Index Types
Discount Code