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PDF Version (.pdf)](https://www.amazon.com/PySpark-Algorithms-Mahmoud-Parsian-ebook/dp/B07WQHTVCJ/)\n\n## [Buy PySpark Algorithms Book \u0026rarr; Kindle Version (.kpf)](https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2)\n\n---\n\n\n## PySpark Algorithms Book:\n#### Author: Mahmoud Parsian (\u003cmahmoud.parsian@yahoo.com\u003e)\n#### [Purchase PySpark Algorithms Book from amazon.com](https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2)\n#### Publication date: August 2019\n\n---\n\n## About PySpark Algorithms Book\n* This book is about PySpark (Python API for Spark)\n* Introductory book on how to solve data problems using PySpark\n* Learn how to use mappers, filters, and reducers\n* Learn how to partition data for fast queries\n* Learn how to use the `mapPartitions()` transformation\n* Learn how to use `reduceByKey()`, `groupByKey()`, and `combineByKey()` transformations\n* Learn how to use Spark's transformations and actions for solving real problems\n* Learn how to use RDDs and DataFrames\n* Learn how to read/write data from many data sources\n* Learn how to use Logistic regression\n* Learn how to use Spark's reduction transformations\n* Learn how to use GraphFrames\n* Learn how to use Motifs in GraphFrames\n* Learn how to use Monoids in MapReduce algorithms \n\n---\n\n[![PySpark Algorithms Book](./images/pyspark_algorithms0.jpg)](https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2)\n\n---\n\n## Software\n\n* [Spark 2.4.3](http://spark.apache.org)\n* [Python 3.7.2](https://www.python.org/ftp/python/3.7.4/python-3.7.4-macosx10.9.pkg)\n\t* [Plan for dropping Python 2 support](http://spark.apache.org/news/plan-for-dropping-python-2-support.html)\n* [Java 8](https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html)\n\n---\n\n## Table of Contents\n\nchap01: Introduction to PySpark  \nchap02: Hello World  \nchap03: Data Abstractions  \n[chap04: Getting Started -- Sample Chapter](./sample_chapters/)  \nchap05: Transformations in Spark  \nchap06: Reductions in Spark  \nchap07: DataFrames and SQL  \nchap08: Spark DataSources  \nchap09: Logistic Regression  \nchap10: Movie Recommendations  \nchap11: Graph Algorithms  \nchap12: Design Patterns and Monoids  \n\nAppendix A: How To Install Spark  \nAppendix B: How to Use Lambda Expressions  \n[Appendix C: Questions And Answers (50+ QA)](./sample_chapters/) \n\n---\n\n## Future chapters:\n\nchap13: FP-Growth  \nchap14: LDA  \nchap15: Linear Regression  \n\n[//]: # (metadata:)\n[//]: # (Spark, PySpark, Python, GraphFrames, Distributed Computing)\n[//]: # (MapReduce, Distributed Algorithms, map, mappers, filters, reduce, reducers, reductions)\n[//]: # (partitioners, partitioning data, data partitioner, Parquet, NoSQL)\n[//]: # (big data, Transformations, Actions, RDDs, DataFrames, SQL, Graph Algorithms)\n[//]: # (Data Abstractions, Reductions in Spark, Design Patterns and Monoids)\n[//]: # (Machine Learning, Logistic Regression, Spark Data Sources)\n[//]: # (Resilient Distributed Datasets, Partitioning, Data Partitioning)\n\n---\n\n[![PySpark Algorithms Book](./images/pyspark_algorithms0.jpg)](https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahmoudparsian%2Fpyspark-algorithms","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmahmoudparsian%2Fpyspark-algorithms","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahmoudparsian%2Fpyspark-algorithms/lists"}