This repository contains Scala and Python versions of the Java code used in Manning Publication’s Spark in Action, 2nd edition, by Jean-Georges Perrin.

Spark in Action, 2nd edition – Java, Python, and Scala code for chapter 1

Chapter 1 introduces the book and offers a basic example.

This code is designed to work with Apache Spark v3.1.2.

Lab

Each chapter has one or more labs. Labs are examples used for teaching in the book. You are encouraged to take ownership of the code and modify it, experiment with it, hence the use of the term lab. This chapter has only one lab.

Lab #100

The CsvToDataframeApp application does the following:

1. It acquires a session (a SparkSession).
2. It asks Spark to load (ingest) a dataset in CSV format.
3. Spark stores the contents in a dataframe, then displays the first five rows of the dataset.

Running the lab in Java

For information on running the Java lab, see chapter 1 in Spark in Action, 2nd edition.

Running the lab using PySpark

Prerequisites:

You will need:

• git.
• Apache Spark (please refer Appendix K - 'Spark in production: installation and a few tips').

1. Clone this project

git clone https://github.com/jgperrin/net.jgp.books.spark.ch01

2. Go to the lab in the Python directory

cd net.jgp.books.spark.ch01/src/main/python/lab100_csv_to_dataframe/

3. Execute the following spark-submit command to create a jar file to our this application

spark-submit csvToDataframeApp.py

Running the lab in Scala

Prerequisites:

You will need:

• git.
• Apache Spark (please refer Appendix P - 'Spark in production: installation and a few tips').

1. Clone this project

git clone https://github.com/jgperrin/net.jgp.books.spark.ch01

2. cd net.jgp.books.spark.ch01

3. Package application using sbt command

sbt clean assembly

4. Run Spark/Scala application using spark-submit command as shown below:

spark-submit --class net.jgp.books.spark.ch01.lab100_csv_to_dataframe.CsvToDataframeScalaApp target/scala-2.11/SparkInAction2-Chapter01-assembly-1.0.0.jar

News

1. [2020-06-07] Updated the pom.xml to support Apache Spark v3.1.2.
2. [2020-06-07] As we celebrate the first anniversary of Spark in Action, 2nd edition is the best-rated Apache Spark book on Amazon.

Notes

1. [Java] Due to renaming the packages to match more closely Java standards, this project is not in sync with the book's MEAP prior to v10 (published in April 2019).
2. [Scala, Python] As of MEAP v14, we have introduced Scala and Python examples (published in October 2019).
3. The master branch contains the last version of the code running against the latest supported version of Apache Spark. Look in specifics branches for specific versions.

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