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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/10/25 18:14:00 UTC
[jira] [Assigned] (SPARK-22221) Add User Documentation for Working
with Arrow in Spark
[ https://issues.apache.org/jira/browse/SPARK-22221?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-22221:
------------------------------------
Assignee: Apache Spark
> Add User Documentation for Working with Arrow in Spark
> ------------------------------------------------------
>
> Key: SPARK-22221
> URL: https://issues.apache.org/jira/browse/SPARK-22221
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 2.3.0
> Reporter: Bryan Cutler
> Assignee: Apache Spark
>
> There needs to be user facing documentation that will show how to enable/use Arrow with Spark, what the user should expect, and describe any differences with similar existing functionality.
> A comment from Xiao Li on https://github.com/apache/spark/pull/18664
> Given the users/applications contain the Timestamp in their Dataset and their processing algorithms also need to have the codes based on the corresponding time-zone related assumptions.
> * For the new users/applications, they first enabled Arrow and later hit an Arrow bug? Can they simply turn off spark.sql.execution.arrow.enable? If not, what should they do?
> * For the existing users/applications, they want to utilize Arrow for better performance. Can they just turn on spark.sql.execution.arrow.enable? What should they do?
> Note Hopefully, the guides/solutions are user-friendly. That means, it must be very simple to understand for most users.
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