Conversation
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
Merging this PR will not alter performance
|
| Mode | Benchmark | BASE |
HEAD |
Efficiency | |
|---|---|---|---|---|---|
| ❌ | Simulation | chunked_varbinview_opt_canonical_into[(1000, 10)] |
187.5 µs | 224.8 µs | -16.62% |
| ⚡ | Simulation | chunked_varbinview_canonical_into[(100, 100)] |
308 µs | 273.3 µs | +12.7% |
Tip
Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.
Comparing ad/cudf (1060cc7) with develop (ba5064a)
ArrowDeviceArray implArrowDeviceArray
Signed-off-by: Alexander Droste <alexander.droste@protonmail.com>
| /// In particular, Vortex string/binary arrays may convert to Arrow view types, but the current CUDA | ||
| /// exporter materializes them as standard variable-size Arrow `Utf8`/`Binary` arrays with null, | ||
| /// offsets, and data buffers. Struct children are normalized recursively. | ||
| fn normalize_device_data_type(data_type: &DataType) -> DataType { |
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Is this still the case? @0ax1 mentioned that cudf added the adapter layer for this in their code
| // 1 (optional) buffer for nulls, one buffer for the data | ||
| n_buffers: 2, | ||
| // Arrow Utf8/Binary layout: optional null bitmap, offsets, and data bytes. | ||
| n_buffers: 3, | ||
| buffers: private_data.buffer_ptrs.as_mut_ptr(), |
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it's worth noting that i think cudf now supports varbinview
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looks like it was integrated into cud 26.04 release
Changes
n_buffers = 3ArrowArraylifetime/release handlingUtf8View/BinaryView→Utf8/Binary)Notes
This PR is scoped to Arrow Device array export. The intent is to build cuDF support in a follow up on top of this.