[jira] [Updated] (ARROW-1715) [Python] Implement pickling for Column, ChunkedArray, RecordBatch, Table

["Uwe L. Korn (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-1715?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Uwe L. Korn updated ARROW-1715:
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    Description: At the moment the types {{pyarrow.Column/ChunkedArray/RecordBatch/Table}} cannot be pickled. Although it may not be the fastest way to transport them from one process to another, it is a very comfortable one. We should implement a {{__reduce__()}} for all of them.  (was: At the moment the types {{pyarrow.Column/ChunkedArray/RecordBatch/Table}} cannot be pickled. Although it may not be the fastest way to transport them from one process to another, it is a very comfortable one. We should implement a {{__reduce__()}} for all of them. For Array, this means that we need to pickle the buffers and save the array type with them. The other classes require the pickling of the Array class and will need to store the addditional metadata like the schema also in the pickle data.)

> [Python] Implement pickling for Column, ChunkedArray, RecordBatch, Table
> ------------------------------------------------------------------------
>
>                 Key: ARROW-1715
>                 URL: https://issues.apache.org/jira/browse/ARROW-1715
>             Project: Apache Arrow
>          Issue Type: New Feature
>          Components: Python
>            Reporter: Wes McKinney
>            Priority: Major
>              Labels: beginner
>             Fix For: 0.10.0
>
>
> At the moment the types {{pyarrow.Column/ChunkedArray/RecordBatch/Table}} cannot be pickled. Although it may not be the fastest way to transport them from one process to another, it is a very comfortable one. We should implement a {{__reduce__()}} for all of them.



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