Mastering Apache Flink

Key Features

• Build your experitse in processing realtime data with Apache Flink and its ecosystem
• Gain insights into the working of all components of Apache Flink such as FlinkML, Gelly, and Table APIFilled with real world use cases,
• Your guide to take advantage of Apache Flink for solving real world problems

Book Description

With the advent of massive computer systems, organizations in different domains generate large amounts of data at a realtime basis. The latest entrant to big data processing, Apache Flink, is designed to process continuous streams of data at a lightning fast pace.

This book will be your definitive guide to batch and stream data processing with Apache Flink. The book begins with introducing the Apache Flink ecosystem, setting it up and using the DataSet and DataStream API for processing batch and streaming datasets. Bringing the power of SQL to Flink, this book will then explore the Table API for querying and manipulating data. In the latter half of the book, readers will get to learn the remaining ecosystem of Apache Flink to achieve complex tasks such as event processing, machine learning, and graph processing. The final part of the book would consist of topics such as scaling Flink solutions, performance optimization and integrating Flink with other tools such as ElasticSearch.

Whether you want to dive deeper into Apache Flink, or want to investigate how to get more out of this powerful technology, you’ll find everything inside

What you will learn

• Learn how to build end to end real time analytics projects
• Integrate with existing big data stack and utilize existing infrastructure.
• Build predictive analytics applications using FlinkML
• Use graph library to perform graph querying and search.

Table of Contents

Chapter 1. Introduction to Apache Flink
Chapter 2. Data Processing Using the DataStream API
Chapter 3. Data Processing Using the Batch Processing API
Chapter 4. Data Processing Using the Table API
Chapter 5. Complex Event Processing
Chapter 6. Machine Learning Using FlinkML
Chapter 7. Flink Graph API – Gelly
Chapter 8. Distributed Data Processing with Flink and Hadoop
Chapter 9. Deploying Flink on Cloud
Chapter 10. Best Practices