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From "Takuya Ueshin (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-22221) Add User Documentation for Working with Arrow in Spark
Date Thu, 25 Jan 2018 01:17:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-22221?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Takuya Ueshin updated SPARK-22221:
----------------------------------
    Target Version/s: 2.3.0

> 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
>            Priority: Major
>
> 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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