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Spark Cookbook, by Rishi Yadav
Free Ebook Spark Cookbook, by Rishi Yadav
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Over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries
About This Book- Become an expert at graph processing using GraphX
- Use Apache Spark as your single big data compute platform and master its libraries
- Learn with recipes that can be run on a single machine as well as on a production cluster of thousands of machines
If you are a data engineer, an application developer, or a data scientist who would like to leverage the power of Apache Spark to get better insights from big data, then this is the book for you.
What You Will Learn- Install and configure Apache Spark with various cluster managers
- Set up development environments
- Perform interactive queries using Spark SQL
- Get to grips with real-time streaming analytics using Spark Streaming
- Master supervised learning and unsupervised learning using MLlib
- Build a recommendation engine using MLlib
- Develop a set of common applications or project types, and solutions that solve complex big data problems
- Use Apache Spark as your single big data compute platform and master its libraries
By introducing in-memory persistent storage, Apache Spark eliminates the need to store intermediate data in filesystems, thereby increasing processing speed by up to 100 times.
This book will focus on how to analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting up development environments. You will then cover various recipes to perform interactive queries using Spark SQL and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will then focus on machine learning, including supervised learning, unsupervised learning, and recommendation engine algorithms. After mastering graph processing using GraphX, you will cover various recipes for cluster optimization and troubleshooting.
- Sales Rank: #745336 in Books
- Published on: 2015-08-03
- Released on: 2015-07-27
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .51" w x 7.50" l, .95 pounds
- Binding: Paperback
- 221 pages
About the Author
Rishi Yadav
Rishi Yadav has 17 years of experience in designing and developing enterprise applications. He is an open source software expert and advises American companies on big data trends. Rishi was honored as one of Silicon Valley's 40 under 40 in 2014. He finished his bachelor's degree at the prestigious Indian Institute of Technology (IIT) Delhi in 1998. About 10 years ago, Rishi started InfoObjects, a company that helps data-driven businesses gain new insights into data. InfoObjects combines the power of open source and big data to solve business challenges for its clients and has a special focus on Apache Spark. The company has been on the Inc. 5000 list of the fastest growing companies for 4 years in a row. InfoObjects has also been awarded with the #1 best place to work in the Bay Area in 2014 and 2015. Rishi is an open source contributor and active blogger.
Most helpful customer reviews
2 of 2 people found the following review helpful.
Spark Cookbook is a great book for venturing into Spark and get a hands ...
By Vasanth Nair
Spark Cookbook is a great book for venturing into Spark and get a hands on understanding of different Spark features via recipes .
This book covers recipes across different Spark Libraries namely Spark Core, Spark Streaming, Spark SQL, MLlib, GraphX etc.
Highly recommended for anybody who wants to get their feet wet in this bleeding edge technology of Big Data !!
1 of 1 people found the following review helpful.
unbaked
By SAS
I can't believe this book is being sold in the Cookbook family that I have come to associate with quality (ref: Scala Cookbook etc). The english is terrible (and its not just aesthetics - some sentences just don't make sense (e.g "Spark RDDs are a great way to store datasets in memory while ending up with multiple copies of the same data in different applications"). Then sometime soon after:
"Please SSH to master node and start slaves: hduser@ s1. zettabytes.com ~] spark-class org.apache.spark.deploy.worker.Worker spark:// m1. zettabytes.com: 7077") You ssh to master node, and what is shown is a slave node (...Slaves s1. zettabytes.com...)
I kept going thinking that maybe I was not following and it was my fault, but the subsequent examples were all half-baked. The tachyon sample doesn't clarify anything about the words folder or file. In the next chapter ("Hadoop MapReduce's word count becomes very simple with the Spark shell. In this recipe, we are going to create a simple 1-line text file, upload it to the Hadoop distributed file system (HDFS) "). If this is going to be a cookbook, it needs to be complete. There is an earlier chapter on installing Spark with Hadoop YARN, but this chapter doesn't mention anything about HDFS installation (I kept getting a port error on 9000).
amazon thankfully accepted my kindle return. I will just take my chances with online resources.
3 of 4 people found the following review helpful.
Fast food of the books
By Dimitri K
The book is written not too thoroughly. Simple stuff is clear, but it also can be found in online spec. The more complicated topics, like Kafka, are written hastily, figures don't explain the concepts, notations in the figures are not explained, etc. In other words, everything that is easy is presented okay. Everything that is not clear from other sources, is messy and not explained well. No deep knowledge or extensive experience or thorough work on the book.
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