Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot (Paperback)
暫譯: 構建即時分析系統：從事件到洞察，使用 Apache Kafka 和 Apache Pinot

Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly.

In the first part of this book, authors Mark Needham and Dunith Dhanushka from StarTree provide an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service.

With this book, you will:

• Learn common architectures for real-time analytics
• Discover how event processing differs from real-time analytics
• Ingest event data from Apache Kafka into Apache Pinot
• Combine event streams with static data using Kafka Streams
• Write real-time queries against event data stored in Apache Pinot
• Build a real-time dashboard, fraud detection pipeline, order tracking app, and anomaly detection system
• Learn how organizations like Uber, Stripe, and Just Eat use real-time analytics