jgperrin / net.jgp.books.spark.ch07

Spark in Action, 2nd edition - chapter 7 - Ingestion from files

The examples in this repository are support to the Spark in Action, 2nd edition book by Jean-Georges Perrin and published by Manning. Find out more about the book on Manning's website.

Spark in Action, 2nd edition - chapter 7

Welcome to Spark in Action, 2nd edition, chapter 7. This chapter covers file ingestion from CSV, JSON, XML, text, and more.

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

Labs

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.

Lab #200

The ComplexCsvToDataframeApp application does the following:

1. It acquires a session (a SparkSession).
2. It asks Spark to load (ingest) a dataset in CSV format.
3. It demonstrates how to add input options for the underlying data source.

Lab #201

Based on lab #200, illustrates the push down filter().

This lab is not described in the Spark in Action, 2nd edition. It was added in July 2020.

Lab #300

TBD

Lab #400

TBD

Lab #401

TBD

Lab #500

TBD

Lab #501

TBD

Lab #600

The XmlToDataframeApp application reads an XML file and displays its content and schema. Updated to use Spark-XML v0.12.0.

Lab #700

TBD

Lab #910

TBD

Lab #920

TBD

Lab #930

TBD

Lab #990

TBD

Lab #991

Based on video game sales prior to 2016, dataset from Kaggle (https://www.kaggle.com/gregorut/videogamesales).

This lab is not described in the Spark in Action, 2nd edition. It was added in July 2020.

Running the labs

Java

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

PySpark

You will need:

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

Step by step direction for lab #200. You will need to adapt some steps for the other labs.

1. Clone this project

   git clone https://github.com/jgperrin/net.jgp.books.spark.ch07

2. Go to the lab in the Python directory

   cd net.jgp.books.spark.ch07/src/main/python/lab200_csv_ingestion/

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

   spark-submit complexCsvToDataframeApp.py

Scala

You will need:

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

Step by step direction for lab #200. You will need to adapt some steps for the other labs.

1. Clone this project

   git clone https://github.com/jgperrin/net.jgp.books.spark.ch07

2. Go to the right directory

   cd net.jgp.books.spark.ch07

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.ch07.lab200_csv_ingestion.ComplexCsvToDataframeScalaApp target/scala-2.12/SparkInAction2-Chapter07-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. Erratas and additional examples are added and the labs may slightly differ from the once in the book (update in July 2020).
4. 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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