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

Sample application for dynamic partitioning


In this section, we will take a detailed look at an example application that illustrates the use of dynamic partitioning of an operator. It uses an input operator that generates random numbers and outputs them to a DevNull library operator (which, as the name suggests, simply discards them). The input operator starts out with two partitions; after some tuples have been processed, a dynamic repartition is triggered via the StatsListener interface discussed above to increase the number of partitions to four. The source code is available atthe following link: https://github.com/apache/apex-malhar/tree/master/examples/dynamic-partition.

The populateDAG() method is, as expected, very simple:

@Override 
public void populateDAG(DAG dag, Configuration conf) 
{ 
  Gen gen         = dag.addOperator("gen",     Gen.class); 
  DevNull devNull = dag.addOperator("devNull", DevNull.class); 
  dag.addStream("data", gen.out, devNull.data); 
} 

The interesting code...