Learning Real-time Processing with Spark Streaming, by Sumit Gupta
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Learning Real-time Processing with Spark Streaming, by Sumit Gupta
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Building scalable and fault-tolerant streaming applications made easy with Spark streaming
About This Book
- Process live data streams more efficiently with better fault recovery using Spark Streaming
- Implement and deploy real-time log file analysis
- Learn about integration with Advance Spark Libraries – GraphX, Spark SQL, and MLib.
Who This Book Is For
This book is intended for big data developers with basic knowledge of Scala but no knowledge of Spark. It will help you grasp the basics of developing real-time applications with Spark and understand efficient programming of core elements and applications.
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
In Detail
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.
Style and approach
A Step-by-Step approach to learn Spark Streaming in a structured manner, with detailed explanation of basic and advance features in an easy-to-follow Style. Each topic is explained sequentially and supported with real world examples and executable code snippets that appeal to the needs of readers with the wide range of experiences.
Learning Real-time Processing with Spark Streaming, by Sumit Gupta- Amazon Sales Rank: #943254 in eBooks
- Published on: 2015-09-28
- Released on: 2015-09-28
- Format: Kindle eBook
About the Author
Sumit Gupta
Sumit Gupta is a seasoned professional, innovator, and technology evangelist with over 100 months of experience in architecting, managing, and delivering enterprise solutions revolving around a variety of business domains such as hospitality, healthcare, risk management, insurance, and so on. He is passionate about technology with an overall 14 years of hands-on experience in the software industry and has been using big data and cloud technologies over the past 4 to 5 years to solve complex business problems. He is also the author of Neo4j Essentials and Building Web Applications with Python and Neo4j both by Packt Publishing.
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Most helpful customer reviews
1 of 1 people found the following review helpful. Excellent book on Streaming analytics with Spark By Sumit Pal Excellent book - very well written, well organized - not too verbose up to the point and lot of material covered as well.The book contains exactly what one needs to get up and running with Spark - it is an intermediate level book. Programs are well written and have detailed comments on why the code is written in the way it is written. Both Scala and Java code have been covered.Good coverage of SQL in Streaming, especially chapter 6 also discusses a novel way to use SQL to query GraphX.I would definitely recommend this book.
0 of 0 people found the following review helpful. Spark Streaming captured clearly, adequately By Samar Spark Streaming has many moving parts and initially proved to be a somewhat tough area of spark programming to sort out. The spark site has the introductory, elementary examples that whet your appetite and excite one's imagination about the interesting possibilities. However how to set up the various sources , analyze the data in real time , and direct the output to system output and or persistent storage initiaally had me struggling and lost many a times. This work turned out to be a great helping hand enabling me to rapidly comprehend the exciting technology. One has to have some familiarity with basics of spark to be able to understand relatively advanced, specialized streams such as grpxh, spark-streaming, machine learning. In any book on the specialized aspects, a critical bit is the balance between detailing the foundations necessary to understand the subject and the subject itself. The minimum neccessary basics are captured – should be an easy decision for a reader to breezily peruse or skip them all together. Many combinations beggining from a basic word counting example streaming data from a terminal window to various input sources such as flume, cassandra and finer grained, more specialized analysis such as graphx, spark sql are presented clearly. The supporting data and source code simplify one's life setting the examples up and udnerstand by running, coding the examples oneself. Setting up , packaging and runnng spark jobs, deploying them in varied setup scenarios – standalone, on a yarn , mesos cluster are adequately captured. On the whole, a work that competently acquaints you with enough facets of the subject to make you feell knowledgable of the subject and at ease with it.It would be amiss to not mention the audhor's helffullness in resolving problems readily. Stuck in one example on account of libraries carelessly copied into the spark library directory – aftet having tried myriad combinations – found the author's email address in the README in the source code– referred the problem and was pleased to receive prompt responses and have the problem resolved over few email exchanges.A useful book that helped me to quickly grasp Spark Streaming adequately
0 of 0 people found the following review helpful. Very comprehensive treatment of Spark Streaming By Sujit Pal This book provides a very comprehensive treatment of Spark Streaming. It begins with Spark installation and configuration and setting up your IDE (Eclipse) and goes all the way to packaging your Streaming application and deploying (standalone / Yarn / Mesos) and monitoring your application. It uses a Distributed Log Processing example to demonstrate various functionalities as one proceeds through the book. For external input and output, the book provides examples for Flume and Cassandra respectively. It also provides an example of integrating Streaming with GraphX. Examples are provided in both Java and Scala. The book also has quite a bit of theory about Spark to explain the reasoning behind Streaming configuration choices, as well as background to DStreams and windowing.Overall the book should be a useful guide to anyone building Spark Streaming applications, either in Java or Scala. If you are already familiar with Spark, some of the material may be redundant, but the book is aimed at people who are new to Spark and who want to get into Spark Streaming.DISCLAIMER: I was one of the reviewers of this book (during publishing). However, I have tried to provide an unbiased review. Hopefully readers of the review will feel the same way.
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