Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot (Paperback)

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

深入了解即時分析，包括這些系統的功能和它們解決的問題。這本實用書籍針對使用Kafka、Google Pub/Sub和AWS Kinesis等事件處理系統的數據工程師，教授如何實時分析數據流。您越快獲得洞察力，就越能及時發現業務變化並做出相應的行動。

在本書的第一部分，作者Mark Needham和Dunith Dhanushka來自StarTree的團隊提供了即時分析領域的概述，以及構建實時應用程序所需的理解。第二部分提供了一系列實踐教程，展示如何結合多個軟件產品為一個虛構的披薩外賣服務構建實時分析應用程序。

通過這本書，您將能夠：
- 學習實時分析的常見架構
- 了解事件處理與實時分析的區別
- 將Apache Kafka的事件數據輸入Apache Pinot
- 使用Kafka Streams將事件流與靜態數據結合
- 對存儲在Apache Pinot中的事件數據進行實時查詢
- 構建實時儀表板、欺詐檢測流程、訂單追蹤應用程序和異常檢測系統
- 了解Uber、Stripe和Just Eat等組織如何使用實時分析技術。