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Learning Real-time Processing with Spark Streaming

Building scalable and fault-tolerant streaming applications made easy with Spark streaming

Learning Real-time Processing with Spark Streaming

Sumit Gupta

1 customer reviews
Building scalable and fault-tolerant streaming applications made easy with Spark streaming
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Book Details

ISBN 139781783987665
Paperback202 pages

Book Description

Using practical examples with easy-to-follow steps, this book will teach you how to build real-time applications with Spark Streaming.

Starting with installing and setting the required environment, you will write and execute your first program for Spark Streaming. This will be followed by exploring the architecture and components of Spark Streaming along with an overview of libraries/functions exposed by Spark. Next you will be taught about various client APIs for coding in Spark by using the use-case of distributed log file processing. You will then apply various functions to transform and enrich streaming data. Next you will learn how to cache and persist datasets. Moving on you will integrate Apache Spark with various other libraries/components of Spark like Mlib, GraphX, and Spark SQL. Finally, you will learn about deploying your application and cover the different scenarios ranging from standalone mode to distributed mode using Mesos, Yarn, and private data centers or on cloud infrastructure.

Table of Contents

Chapter 1: Installing and Configuring Spark and Spark Streaming
Installation of Spark
Configuring and running the Spark cluster
Your first Spark program
Tools and utilities for administrators/developers
Troubleshooting
Summary
Chapter 2: Architecture and Components of Spark and Spark Streaming
Batch versus real-time data processing
Architecture of Spark
Architecture of Spark Streaming
Your first Spark Streaming program
Summary
Chapter 3: Processing Distributed Log Files in Real Time
Spark packaging structure and client APIs
Resilient distributed datasets and discretized streams
Data loading from distributed and varied sources
Summary
Chapter 4: Applying Transformations to Streaming Data
Understanding and applying transformation functions
Performance tuning
Summary
Chapter 5: Persisting Log Analysis Data
Output operations in Spark Streaming
Integration with Cassandra
Summary
Chapter 6: Integration with Advanced Spark Libraries
Querying streaming data in real time
Graph analysis – Spark GraphX
Summary
Chapter 7: Deploying in Production
Spark deployment models
High availability and fault tolerance
Monitoring streaming jobs
Summary

What You Will Learn

  • Install and configure Spark and Spark Streaming to execute applications
  • Explore the architecture and components of Spark and Spark Streaming to use it as a base for other libraries
  • Process distributed log files in real-time to load data from distributed sources
  • Apply transformations on streaming data to use its functions
  • Integrate Apache Spark with the various advance libraries like MLib and GraphX
  • Apply production deployment scenarios to deploy your application

Authors

Table of Contents

Chapter 1: Installing and Configuring Spark and Spark Streaming
Installation of Spark
Configuring and running the Spark cluster
Your first Spark program
Tools and utilities for administrators/developers
Troubleshooting
Summary
Chapter 2: Architecture and Components of Spark and Spark Streaming
Batch versus real-time data processing
Architecture of Spark
Architecture of Spark Streaming
Your first Spark Streaming program
Summary
Chapter 3: Processing Distributed Log Files in Real Time
Spark packaging structure and client APIs
Resilient distributed datasets and discretized streams
Data loading from distributed and varied sources
Summary
Chapter 4: Applying Transformations to Streaming Data
Understanding and applying transformation functions
Performance tuning
Summary
Chapter 5: Persisting Log Analysis Data
Output operations in Spark Streaming
Integration with Cassandra
Summary
Chapter 6: Integration with Advanced Spark Libraries
Querying streaming data in real time
Graph analysis – Spark GraphX
Summary
Chapter 7: Deploying in Production
Spark deployment models
High availability and fault tolerance
Monitoring streaming jobs
Summary

Book Details

ISBN 139781783987665
Paperback202 pages
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