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PySpark Algorithms Book:

Author: Mahmoud Parsian (mahmoud.parsian@yahoo.com)

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Publication date: August 2019

About PySpark Algorithms Book

• This book is about PySpark (Python API for Spark)
• Introductory book on how to solve data problems using PySpark
• Learn how to use mappers, filters, and reducers
• Learn how to partition data for fast queries
• Learn how to use the mapPartitions() transformation
• Learn how to use reduceByKey(), groupByKey(), and combineByKey() transformations
• Learn how to use Spark's transformations and actions for solving real problems
• Learn how to use RDDs and DataFrames
• Learn how to read/write data from many data sources
• Learn how to use Logistic regression
• Learn how to use Spark's reduction transformations
• Learn how to use GraphFrames
• Learn how to use Motifs in GraphFrames
• Learn how to use Monoids in MapReduce algorithms

Software

• Spark 2.4.3
• Python 3.7.2
  • Plan for dropping Python 2 support
• Java 8

Table of Contents

chap01: Introduction to PySpark
chap02: Hello World
chap03: Data Abstractions
chap04: Getting Started -- Sample Chapter
chap05: Transformations in Spark
chap06: Reductions in Spark
chap07: DataFrames and SQL
chap08: Spark DataSources
chap09: Logistic Regression
chap10: Movie Recommendations
chap11: Graph Algorithms
chap12: Design Patterns and Monoids

Appendix A: How To Install Spark
Appendix B: How to Use Lambda Expressions
Appendix C: Questions And Answers (50+ QA)

Future chapters:

chap13: FP-Growth
chap14: LDA
chap15: Linear Regression