[SUPPORT] Speeding up S3 Multipart Uploads using Hudi on AWS EMR with EMRFS

[torvalds-dev]

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Describe the problem you faced

Is there a way to speed up S3 Multipart Uploads using Hudi on AWS EMR with EMRFS? Currently, the Multipart Upload parts seem to be written in serial.

To Reproduce

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Expected behavior

A clear and concise description of what you expected to happen.

Environment Description

• Hudi version :

• Spark version :

• Hive version :

• Hadoop version :

• Storage (HDFS/S3/GCS..) :

• Running on Docker? (yes/no) :

Additional context

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Stacktrace

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[torvalds-dev]

Relevant Sources:

https://www.onehouse.ai/blog/apache-hudi-native-aws-integrations

https://medium.com/@devjain1299/apache-hudi-on-aws-glue-a-step-by-step-guide-503c34a9aa95

https://aws.amazon.com/blogs/big-data/part-1-query-an-apache-hudi-dataset-in-an-amazon-s3-data-lake-with-amazon-athena-part-1-read-optimized-queries/

https://www.onehouse.ai/blog/reliable-ingestion-from-aws-s3-using-apache-hudi

apache#10358

[torvalds-dev]

Hello! 👋 Please wait while I search the knowledge base for an answer; this usually takes about 30 seconds

[torvalds-dev]

Yes, it is possible to speed up S3 Multipart Uploads using Hudi on AWS EMR. When using EMRFS, you may notice Multipart Upload parts being written in serial by default, causing potential performance bottlenecks. However, there is a solution available for speeding up writes by configuring Hudi jars in EMR clusters.

To override Hudi jars in your EMR clusters and potentially enhance write speeds, follow these steps:

1. Build Hudi Jars:

   • Clone the Hudi repository and get version 0.7.0.
   • Build jars with the required configurations for EMR clusters, such as Spark 3.0.0 and Scala 2.12.

2. Copy Jars to S3:

   • After building the jars, copy them to a temporary location in S3.

3. Include Hudi Jars as part of the EMR Bootstrap Script:

   • Create a script that downloads the Hudi jars from the S3 location to each node in the EMR cluster.
   • Use the script as a part of the bootstrap-actions while launching the EMR cluster to install the jars on each node.

4. Use the Overridden Jar in Deltastreamer:

   • When invoking DeltaStreamer, specify the location of the overridden jar in the spark-submit command.

By following these steps, you can optimize S3 Multipart Uploads using Hudi on AWS EMR, potentially enhancing write performance. (Source: Apache Hudi - FAQ Integrations)

[torvalds-dev]

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[torvalds-dev]

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[torvalds-dev]

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[torvalds-dev]

Ticket created successfully. Here is the link to the GitHub issue: #59

[torvalds-dev]

Ticket created successfully. Here is the link to the GitHub issue: #59