https://github.com/databricks/learningsparkv2

This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]
https://github.com/databricks/learningsparkv2

apache-spark delta-lake mlflow mllib spark spark-mllib spark-sql structured-streaming

Last synced: about 21 hours ago
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This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

• Host: GitHub
• URL: https://github.com/databricks/learningsparkv2
• Owner: databricks
• License: apache-2.0
• Created: 2019-02-10T05:17:50.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2025-01-28T04:30:40.000Z (5 days ago)
• Last Synced: 2025-02-01T07:41:44.619Z (about 22 hours ago)
• Topics: apache-spark, delta-lake, mlflow, mllib, spark, spark-mllib, spark-sql, structured-streaming
• Language: Scala
• Homepage: https://learning.oreilly.com/library/view/learning-spark-2nd/9781492050032/
• Size: 75.2 MB
• Stars: 1,240
• Watchers: 41
• Forks: 750
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Learning Spark 2nd Edition

Welcome to the GitHub repo for Learning Spark 2nd Edition.

Chapters [2](chapter2/README.md), [3](chapter3/README.md), [6](chapter6/README.md), and [7](chapter7/README.md) contain stand-alone Spark applications. You can build all the JAR files for each chapter by running the Python script: `python build_jars.py`.

Or you can cd to the chapter directory and build jars as specified in each README. Also, include `$SPARK_HOME/bin` in `$PATH`  so that you

don't have to prefix `SPARK_HOME/bin/spark-submit` for these standalone applications.

For all the other chapters, we have provided notebooks in the [notebooks](notebooks) folder. We have also included notebook equivalents for a few of the stand-alone Spark applications in the aforementioned chapters.

Have Fun, Cheers!