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https://issues.apache.org/jira/browse/DATALAB-2342?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17372561#comment-17372561
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Vira Vitanska commented on DATALAB-2342:
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*Closed:*
Commit ID ** 8fc4d6313ab0359ac18a3c23985001b8300584a8
It works for all Notebooks as expected except for Apache Zeppelin:
!image-2021-07-01-11-00-04-390.png!
Appropriate ticket for Apache Zeppelin is created:
https://issues.apache.org/jira/browse/DATALAB-2482
> [Notebook]: Allocate spark driver/spark executor memory according to the Best
> practice
> --------------------------------------------------------------------------------------
>
> Key: DATALAB-2342
> URL: https://issues.apache.org/jira/browse/DATALAB-2342
> Project: Apache DataLab
> Issue Type: Task
> Security Level: Public(Regular Issues)
> Components: DataLab Main
> Reporter: Vira Vitanska
> Assignee: Mykola Bodnar
> Priority: Major
> Labels: AWS, AZURE, Debian, DevOps, GCP, RedHat
> Fix For: v.2.5
>
> Attachments: image-2021-07-01-11-00-04-390.png
>
>
> Total executor memory = total RAM per instance / number of executors per
> instance
> Spark.executors.memory = total executor memory * 0.90
> Spark.driver.memory = spark.executors.memory
> According to
> [https://aws.amazon.com/blogs/big-data/best-practices-for-successfully-managing-memory-for-apache-spark-applications-on-amazon-emr/]
>
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