[jira] [Updated] (ARROW-18063) [C++][Python]

["Ben Kietzman (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-18063?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ben Kietzman updated ARROW-18063:
---------------------------------
    Component/s: C++

> [C++][Python] 
> --------------
>
>                 Key: ARROW-18063
>                 URL: https://issues.apache.org/jira/browse/ARROW-18063
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Ben Kietzman
>            Priority: Major
>
> [Mailing list thread|https://lists.apache.org/thread/r484sqrd6xjdd058prbrcwh3t5vg91so]
> The goal is to:
> - generate a substrait plan in Python using Ibis
> - ... wherein tables are specified using custom URLs
> - use the python API {{run_query}} to execute the plan
> - ... against source data which is *streamed* from those URLs rather than pulled fully into local memory
> The obstacles include:
> - The API for constructing a data stream from the custom URLs is only available in c++
> - The python {{run_query}} function requires tables as input and cannot accept a RecordBatchReader even if one could be constructed from a custom URL
> - Writing custom cython is not preferred
> Some potential solutions:
> - Use ExecuteSerializedPlan() directly usable from c++ so that construction of data sources need not be handled in python. Passing a buffer from python/ibis down to C++ is much simpler and can be navigated without writing cython
> - Refactor NamedTableProvider from a lambda mapping {{names -> data source}} into a registry so that data source factories can be added from c++ then referenced by name from python
> - Extend {{run_query}} to support non-Table sources and require the user to write a python mapping from URLs to {{pa.RecordBatchReader}}



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