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

Testing in the IDE


This section will show how the previously created example application can be configured and run as a JUnit test within the IDE. Setting up an integration test that can be executed after every change will avoid a full package/deploy cycle to run on a cluster just to find basic issues. It allows for efficient debugging and will also come in handy when setting up continuous integration for a project.

Writing the integration test

The test covers the entire DAG and will run the application in embedded mode. In embedded mode, all operators and containers share the JUnit JVM. Containers are threads (instead of separate processes) but the data flow still behaves as if operators lived in separate processes. This means operators execute asynchronously as they would in a distributed cluster and data is transferred over the loopback interface (if that's how the streams are configured).

@Test 
public void testApplication() throws Exception { 
  EmbeddedAppLauncher<?> launcher =...