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…rom arrow streams, which are lazy, to implement the table registration, which in the default df library, is not lazy enough.
…(XarrayContext). This leads to two failed tests, but this could be caused by test errors.
The previous implementation stored a single Arrow stream that could only be consumed once, causing subsequent queries on the same table to return empty results. This broke filters and aggregations. Changes: - Modify Rust PyArrowStreamPartition to accept a factory function instead of a stream object. The factory is called on each execute() to create a fresh stream, allowing multiple queries on the same table. - Update LazyArrowStreamTable to take a factory and schema instead of consuming a stream directly. - Update Python read_xarray_table to create a factory function that produces fresh XarrayRecordBatchReader instances. - Update tests to use the new factory-based API via read_xarray_table. This enables proper lazy evaluation while supporting multiple queries on registered tables, fixing the failing filter and aggregation tests.
alxmrs
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Jan 16, 2026
xarray_sql/reader.py
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| reader = XarrayRecordBatchReader( | ||
| ds, chunks, _iteration_callback=_iteration_callback | ||
| ) | ||
| return pa.RecordBatchReader.from_stream(reader) |
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Why do we do this? Can't we just return the custom stream class?
XarrayRecordBatchReader already implements __arrow_c_stream__, so there's no need to wrap it in pa.RecordBatchReader.from_stream(). The Rust code can consume it directly via ArrowArrayStreamReader::from_pyarrow_bound.
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Integrating into #100. |
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TODO(alxmrs): merge into #100.