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Learning Apache Apex

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

Product type Paperback

Published in Nov 2017

Publisher

ISBN-13 9781788296403

Length 290 pages

Edition 1st Edition

Languages

Apex

Tools

Apache Apex

Concepts

Data Processing

Authors (5):

Munagala V. Ramanath

David Yan

Ananth Gundabattula

Thomas Weise

Kenneth Knowles

+1 more

View More author details

Table of Contents (11) Chapters

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

Running the application on GCP Dataproc

This section will provide a tutorial on how to run the Apex application on a real Hadoop cluster in the cloud. Dataproc (https://cloud.google.com/dataproc/) is one of several options that exist (Amazon EMR is another one, and the instructions here can be easily adapted to EMR as well).

The general instructions on how to work on a cluster were already covered in Chapter 2, Getting Started with Application Development, where a Docker container was used. This section will focus on the differences of adding Apex to an existing multi-node cluster.

To start with, we are heading over to the GCP console (https://console.cloud.google.com/dataproc/clusters) to create a new cluster.

For better illustration we will use the UI, but these steps can be fully automated using the REST API or command line as well:

The first step is to decide what size of cluster and what type of machines we want. For this example, 3 worker nodes of a small machine type will suffice (for...

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Authors (5)

David Yan

David Yan

David Yan is based in the Silicon Valley, California. He is a senior software engineer at Google. Prior to Google, he worked at DataTorrent, Yahoo!, and the Jet Propulsion Laboratory. David holds a master of science in Computer Science from Stanford University and a bachelor of science in Electrical Engineering and Computer Science from the University of California at Berkeley

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Munagala V. Ramanath

Munagala V. Ramanath

Dr. Munagala V. Ramanath got his PhD in Computer Science from the University of Wisconsin, USA and an MSc in Mathematics from Carleton University, Ottawa, Canada. After that, he taught Computer Science courses as Assistant/Associate Professor at the University of Western Ontario in Canada for a few years, before transitioning to the corporate sphere. Since then, he has worked as a senior software engineer at a number of technology companies in California including SeeBeyond, EMC, Sun Microsystems, DataTorrent, and Cloudera. He has published papers in peer reviewed journals in several areas including code optimization, graph theory, and image processing.

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Thomas Weise

Thomas Weise

Thomas Weise is the Apache Apex PMC Chair and cofounder at Atrato. Earlier, he worked at a number of other technology companies in the San Francisco Bay Area, including DataTorrent, where he was a cofounder of the Apex project. Thomas is also a committer to Apache Beam and has contributed to several more of the ecosystem projects. He has been working on distributed systems for 20 years and has been a speaker at international big data conferences. Thomas received the degree of Diplom-Informatiker (MSc in computer science) from TU Dresden, Germany. He can be reached on Twitter at: @thweise.

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Gundabattula

Gundabattula

Ananth is a senior application architect in the Decisioning and Advanced Analytics architecture team for Commonwealth Bank of Australia. Ananth holds a Ph.D degree in the domain of computer science security and is interested in all things data including low latency distributed processing systems, machine learning and data engineering domains. He holds 3 patents granted by USPTO and has one application pending. Prior to joining to CBA, he was an architect at Threatmetrix and the member of the core team that scaled Threatmetrix architecture to 100 million transactions per day that runs at very low latencies using Cassandra, Zookeeper and Kafka. He also migrated Threatmetrix data warehouse into the next generation architecture based on Hadoop and Impala. Prior to Threatmetrix, he worked for the IBM software labs and IBM CIO labs enabling some of the first IBM CIO projects onboarding HBase, Hadoop and Mahout stack. Ananth is a committer for Apache Apex and is currently working for the next generation architectures for CBA fraud platform and Advanced Analytics Omnia platform at CBA.

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Kenneth Knowles

Kenneth Knowles

Kenneth Knowles is a founding PMC member of Apache Beam. Kenn has been working on Google Cloud Dataflow—Google's Beam backend—since 2014. Prior to that, he built backends for startups such as Cityspan, Inkling, and Dimagi. Kenn holds a PhD in Programming Language Theory from the University of California, Santa Cruz.

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