Scala and Spark for big data analytics : explore the concepts of functional programming, data streaming, and machine learning [E-Book] / Rezaul Karim, Sridhar Alla
Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data,...
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Full text |
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Personal Name(s): | Karim, Rezaul, author |
Alla, Sridhar, author | |
Edition: |
1st edition |
Imprint: |
Birmingham :
Packt Publishing,
2017
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Physical Description: |
778 pages (online resource) |
Note: |
englisch |
ISBN: |
9781783550500 1785280848 9781785280849 1783550503 |
Subject (LOC): |
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505 | 0 | |a Scala and Spark for big data analytics : explore the concepts of functional programming, data streaming, and machine learning -- Credits -- About the Authors -- About the Reviewers -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Introduction to Scala -- Chapter 2: Object-Oriented Scala -- Chapter 3: Functional Programming Concepts -- Chapter 4: Collection APIs -- Chapter 5: Tackle Big Data - Spark Comes to the Party -- Chapter 6: Start Working with Spark REPL and RDDs -- Chapter 7: Special RDD Operations -- Chapter 8: Introduce a Little Structure - Spark SQL -- Chapter 9: Stream Me Up, Scotty - Spark Streaming -- Chapter 10: Everything is Connected - GraphX -- Chapter 11: Learning Machine Learning - Spark MLlib and Spark ML -- Chapter 12: My Name is Bayes, Naive Bayes -- Chapter 13: Time to Put Some Order - Cluster Your Data with Spark MLlib -- Chapter 14: Text Analytics Using Spark ML -- Chapter 15: Spark Tuning -- Chapter 16: Time to Go to ClusterLand - Deploying Spark on a Cluster -- Chapter 17: Testing and Debugging Spark -- Chapter 18: PySpark and SparkR -- Index. | |
520 | 3 | |a Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. | |
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