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.

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Table of Contents (17 chapters)
Title Page
Title Page
Credits
Credits
About the Authors
About the Authors
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Introduction to Apex
Introduction to Apex
Unbounded data and continuous processing
Use cases and case studies
Application Model and API
Value proposition of Apex
Summary
2
Getting Started with Application Development
Getting Started with Application Development
Development process and methodology
Setting up the development environment
Creating a new Maven project
Application specifications
Custom operator development
Application configuration
Testing in the IDE
Running the application on YARN
Working on the cluster
Summary
3
The Apex Library
The Apex Library
An overview of the library
Integrations
Transformations
Summary
4
Scalability, Low Latency, and Performance
Scalability, Low Latency, and Performance
Partitioning and how it works
Elasticity
Partitioning toolkit
Custom dynamic partitioning
Performance optimizations
Low-latency versus throughput
Sample application for dynamic partitioning
Performance – other aspects for custom operators
Summary
5
Fault Tolerance and Reliability
Fault Tolerance and Reliability
Distributed systems need to be resilient
Fault-tolerance components and mechanism in Apex
Checkpointing
Processing guarantees
Summary
6
Example Project – Real-Time Aggregation and Visualization
Example Project – Real-Time Aggregation and Visualization
Streaming ETL and beyond
The application pattern in a real-world use case
Analyzing Twitter feed
Running the application
The Pub/Sub server
Grafana visualization
Summary
7
Example Project – Real-Time Ride Service Data Processing
Example Project – Real-Time Ride Service Data Processing
The goal
Datasource
The pipeline
Simulation of a real-time feed using historical data
Parsing the data
Looking up of the zip code and preparing for the windowing operation
Windowed operator configuration
Serving the data with WebSocket
Running the application
Running the application on GCP Dataproc
Summary
8
Example Project – ETL Using SQL
Example Project – ETL Using SQL
The application pipeline
Building and running the application
Application configuration
The application code
Partitioning
Application testing
Understanding application logs
Calcite integration
Summary
9
Introduction to Apache Beam
Introduction to Apache Beam
Introduction to Apache Beam
Beam concepts
WordCount in Apache Beam
Running Apache Beam WordCount on Apache Apex
Summary
10
The Future of Stream Processing
The Future of Stream Processing
Lower barrier for building streaming pipelines
Summary

About the Authors

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.

 

 

I'd like to thank the Apache Apex community and project cofounder, Chetan Narsude, for creating this advanced streaming platform. I'd also like to thank Dean Lockgaard, Ananth G., and my coauthors for their help with the book, and Packt editors for their support.

 

 

 

 

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.

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.

 

 

 

 

 

 

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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