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PySpark recipesa problem-solution ap...

Mishra, Raju Kumar.

PySpark recipesa problem-solution approach with PySpark2 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	PySpark recipesby Raju Kumar Mishra.
Reminder of title:	a problem-solution approach with PySpark2 /
Author:	Mishra, Raju Kumar.
Published:	Berkeley, CA :Apress :2018.
Description:	xxiii, 265 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Python (Computer program language)
Online resource:	http://dx.doi.org/10.1007/978-1-4842-3141-8
ISBN:	9781484231418$q(electronic bk.)

PySpark recipesa problem-solution approach with PySpark2 /
Mishra, Raju Kumar.

PySpark recipesa problem-solution approach with PySpark2 /[electronic resource] :by Raju Kumar Mishra. - Berkeley, CA :Apress :2018. - xxiii, 265 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9781484231418$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-3141-8doiSubjects--Topical Terms:

215247
Python (Computer program language)

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

PySpark recipesa problem-solution approach with PySpark2 /
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505 0 $a 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.
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