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https://issues.apache.org/jira/browse/ARROW-12650?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Antoine Pitrou updated ARROW-12650:
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Fix Version/s: (was: 5.0.0)
6.0.0
> [Doc][Python] Improve documentation regarding dealing with memory mapped files
> ------------------------------------------------------------------------------
>
> Key: ARROW-12650
> URL: https://issues.apache.org/jira/browse/ARROW-12650
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Documentation
> Reporter: Alessandro Molina
> Assignee: Alessandro Molina
> Priority: Minor
> Labels: pull-request-available
> Fix For: 6.0.0
>
> Time Spent: 6h 50m
> Remaining Estimate: 0h
>
> While one of the Arrow promises is that it makes easy to read/write data
> bigger than memory, it's not immediately obvious from the pyarrow
> documentation how to deal with memory mapped files.
> The doc hints that you can open files as memory mapped (
> [https://arrow.apache.org/docs/python/memory.html?highlight=memory_map#on-disk-and-memory-mapped-files]
> ) but then it doesn't explain how to read/write Arrow Arrays or Tables from
> there.
> While most high level functions to read/write formats (pqt, feather, ...)
> have an easy to guess {{memory_map=True}} option, the doc doesn't seem to
> have any example of how that is meant to work for Arrow format itself. For
> example how you can do that using {{RecordBatchFile*}}.
> An addition to the memory mapping section that makes a more meaningful
> example that reads/writes actual arrow data (instead of plain bytes) would
> probably be helpful
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