SteNicholas commented on code in PR #3010: URL: https://github.com/apache/celeborn/pull/3010#discussion_r1891374174
########## docs/developers/java-columnar-shuffle.md: ########## @@ -0,0 +1,36 @@ +# Introduction to Celeborn's Java Columnar Shuffle Review Comment: Add license etc. ########## docs/developers/java-columnar-shuffle.md: ########## @@ -0,0 +1,36 @@ +# Introduction to Celeborn's Java Columnar Shuffle + +## Overview + +Celeborn presents a Java Columnar Shuffle designed to enhance performance and efficiency in SparkSQL and DataFrame operations. This innovative approach leverages a columnar format for shuffle operations, achieving a higher compression rate than traditional Row-based Shuffle methods. This improvement leads to significant savings in disk space usage during shuffle operations. + +## Benefits + +- **High Compression Rate**: By organizing data into a columnar format, this feature significantly increases the compression ratio, reducing the disk space required for Shuffle data. + +## Configuration + +To leverage Celeborn's Java Columnar Shuffle, you need to apply a patch and configure certain settings in Spark 3.x. Follow the steps below for implementation: + +### Step 1: Apply the Patch + +1. Obtain the `Celeborn_Columnar_Shuffle_spark3.patch` file that contains the modifications needed for enabling Columnar Shuffle in Spark 3.x. Review Comment: Please add the link of this patch. Meanwhile, explain what changes is introduced in this patch like `ShuffleDependecy adds schema field.`. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
