Data Algorithms with Spark by Mahmoud Parsian

"... This book will be a great resource for both readers looking to implement existing algorithms in a scalable fashion and readers who are developing new, custom algorithms using Spark. ..." Dr. Matei Zaharia Original Creator of Apache Spark FOREWORD by Dr. Matei Zaharia

---

Data Algorithms with Spark by Mahmoud Parsian

Foreword by Dr. Matei Zaharia (Original Creator of Apache Spark)

Author: Mahmoud Parsian

Goal of this book: enable writing efficient & simpler PySpark code for data algorithms using Spark

---

• Mahmoud Parsian's Author Page @Amazon

• Mahmoud Parsian's Author Page @LinkedIn

• This new O'Reilly book is the successor Edition of Data Algorithms (published by O'Reilly)

• This book uses PySpark (much simpler and readable)

• Published date: April 8, 2022

• @OReillyMedia: Data Algorithms with Spark, By @mahmoudparsian

• Autor Contact: [ Email ] [ Mahmoud Parsian @LinkedIn ][ Mahmoud Parsian @GitHub ]

---

Github Chapter Solutions

• This GitHub repository will host all source code and scripts for Data Algorithms with Spark

• Chapter solutions are provided in PySpark and Scala

  • PySpark solutions are provided by Mahmoud Parsian
  • Scala solutions are provided by Deepak Kumar and Biman Mandal

---

Software:

Spark	Python	Scala	Java
Apache Spark 3.2.0	Python 3.7.2	Scala 2.13	Java 8

---

Table of Contents

Chapter	Title
Bonus Chapters	Tutorials: RDDs and DataFrames Top-N, UDF, Partitioning, TF-IDF, Correlation Correlation, K-mers, anagrams, wordcount, ...
Chapter 1	Introduction to Data Algorithms
Chapter 2	Transformations in Action
Chapter 3	Mapper Transformations
Chapter 4	Reductions in Spark
Chapter 5	Partitioning Data
Chapter 6	Graph Algorithms
Chapter 7	Interacting with External Data Sources
Chapter 8	Ranking Algorithms
Chapter 9	Fundamental Data Design Patterns
Chapter 10	Common Data Design Patterns
Chapter 11	Join Design Patterns
Chapter 12	Feature Engineering in PySpark

---

---