Learning Apache Flink

Learning Apache FlinkReviews
Author: Tanmay Deshpande
Pub Date: 2017
ISBN: 978-1786466228
Pages: 323
Language: English
Size: 17 Mb


Discover the definitive guide to crafting lightning-fast data processing for distributed systems with Apache Flink
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

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