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PySpark recipes : a problem-solution approach with PySpark2

Author: Raju Kumar Mishra
Publisher: [United States] : Apress, [2018] ©2018
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Mishra, Raju Kumar.
PySpark recipes.
[United States] : Apress, [2018]
(OCoLC)1004042658
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Raju Kumar Mishra
ISBN: 9781484231418 1484231414
OCLC Number: 1015239900
Notes: Includes index.
Description: 1 online resource : illustrations
Contents: Chapter 1: The Era of Big Data, Hadoop, and Other Big Data Processing Frameworks --
Chapter 2: Installation --
Chapter 3: Introduction to Python and NumPy --
Chapter 4: Spark Architecture and Resilient Distributed Dataset --
Chapter 5: The Power of Pairs: Paired RDD --
Chapter 6: IO in PySpark --
Chapter 7: Optimizing PySpark and PySpark Streaming --
Chapter 8: PySparkSQL --
Chapter 9: PySpark MLlib and Linear Regression.
Responsibility: Raju Kumar Mishra.

Abstract:

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model. What You Will Learn: Understand the advanced features of PySpark and SparkSQL Optimize your code Program SparkSQL with Python Use Spark Streaming and Spark MLlib with Python Perform graph analysis with GraphFrames.

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