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

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

Ben Kietzman created ARROW-18063:
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             Summary: [C++][Python] 
                 Key: ARROW-18063
                 URL: https://issues.apache.org/jira/browse/ARROW-18063
             Project: Apache Arrow
          Issue Type: Improvement
            Reporter: Ben Kietzman


[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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