Book Image

Learning Apache Apex

By : Thomas Weise, Ananth Gundabattula, Munagala V. Ramanath, David Yan, Kenneth Knowles
Book Image

Learning Apache Apex

By: Thomas Weise, Ananth Gundabattula, Munagala V. Ramanath, David Yan, Kenneth Knowles

Overview of this book

Apache Apex is a next-generation stream processing framework designed to operate on data at large scale, with minimum latency, maximum reliability, and strict correctness guarantees. Half of the book consists of Apex applications, showing you key aspects of data processing pipelines such as connectors for sources and sinks, and common data transformations. The other half of the book is evenly split into explaining the Apex framework, and tuning, testing, and scaling Apex applications. Much of our economic world depends on growing streams of data, such as social media feeds, financial records, data from mobile devices, sensors and machines (the Internet of Things - IoT). The projects in the book show how to process such streams to gain valuable, timely, and actionable insights. Traditional use cases, such as ETL, that currently consume a significant chunk of data engineering resources are also covered. The final chapter shows you future possibilities emerging in the streaming space, and how Apache Apex can contribute to it.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introduction to Apache Beam


Beam is a programming model—what does that mean, exactly? It means that Beam defines essential primitives, from which you can construct big data processing pipelines. By design, your processing logic is unified across batch and stream processing, infinite and finite, and bounded and unbounded. One important practical benefit is that Beam allows you to reuse your code for processing an incoming stream, reprocessing historical data (for example, after fixing a bug, or receiving a data dump), or running experiments or tests on samples of data:

The essential structure of your computation is independent of what data processing engine executes it. Today there are runners—libraries for executing Beam pipelines on various data processing systems—for example, Apache Apex, Apache Flink, Apache Spark, Google Cloud Dataflow, and Apache Gearpump (incubating), with others underway for JStorm, Apache Tez, and nonTez Apache Hadoop MapReduce.

A Beam pipeline is also independent...