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Learning Apache Apex

You're reading from   Learning Apache Apex Real-time streaming applications with Apex

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Product type Paperback
Published in Nov 2017
Publisher
ISBN-13 9781788296403
Length 290 pages
Edition 1st Edition
Languages
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Authors (5):
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Munagala V. Ramanath Munagala V. Ramanath
Author Profile Icon Munagala V. Ramanath
Munagala V. Ramanath
David Yan David Yan
Author Profile Icon David Yan
David Yan
Ananth Gundabattula Ananth Gundabattula
Author Profile Icon Ananth Gundabattula
Ananth Gundabattula
Thomas Weise Thomas Weise
Author Profile Icon Thomas Weise
Thomas Weise
Kenneth Knowles Kenneth Knowles
Author Profile Icon Kenneth Knowles
Kenneth Knowles
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Apex FREE CHAPTER 2. Getting Started with Application Development 3. The Apex Library 4. Scalability, Low Latency, and Performance 5. Fault Tolerance and Reliability 6. Example Project – Real-Time Aggregation and Visualization 7. Example Project – Real-Time Ride Service Data Processing 8. Example Project – ETL Using SQL 9. Introduction to Apache Beam 10. The Future of Stream Processing

Distributed systems need to be resilient


As discussed in Chapter 2, Getting Started with Application Development, Apex applications run on a cluster as a distributed set of processes. Distribution enables scalability, and with the correct architecture, adding more resources to a compute cluster (such as YARN) allows applications to scale horizontally (refer to Chapter 4, Scalability, Low Latency, and Performance). At the same time, growing number of processes and machines also increases the likelihood of failure. Hardware or software failures cannot be avoided.

In order to prevent failure resulting in downtime or incorrect results, the system has to be resilient. Fault-tolerance mechanisms should cover high availability (HA) as well as provide with processing correctness guarantee to the user. For a production-quality and business-critical system, these aspects should be important evaluation criteria. A stream data processing platform should provide fault-tolerance along with scalability...

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