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.
Welcome to Spark in Action, 2e, chapter 9. This chapter covers advanced ingestion, including writing your own custom data source with Java.
This code is designed to work with Apache Spark v3.0.0.
Each chapter has one or more labs. Labs are examples used for teaching in the book(https://www.manning.com/books/spark-in-action-second-edition?a_aid=jgp). 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.
The PhotoMetadataIngestionApp
application does the following:
- It acquires a session (a
SparkSession
). - It asks Spark to load (ingest) a dataset in 'exif' format.
- Spark stores the contents in a dataframe, then print the records.
For information on running the Java lab, see chapter 1 in Spark in Action, 2nd edition.
Prerequisites:
You will need:
git
.- Apache Spark (please refer Appendix P - "Spark in production: installation and a few tips").
-
Clone this project
git clone https://github.com/jgperrin/net.jgp.books.spark.ch09
-
cd net.jgp.books.spark.ch09
-
Package application using sbt command
sbt clean assembly
-
Run Spark/Scala application using spark-submit command as shown below:
spark-submit --class net.jgp.books.spark.ch09.lab100_photo_datasource.PhotoMetadataIngestionScalaApp target/scala-2.12/SparkInAction2-Chapter09-assembly-1.0.0.jar
Notes:
- [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).
- [Scala, Python] As of MEAP v14, we have introduced Scala and Python examples (published in October 2019).
Follow me on Twitter to get updates about the book and Apache Spark: @jgperrin. Join the book's community on Facebook or in Manning's community site.