Support reporting statistics in spark datasource#8057
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Merging this PR will not alter performance
|
| Mode | Benchmark | BASE |
HEAD |
Efficiency | |
|---|---|---|---|---|---|
| ❌ | Simulation | bitwise_not_vortex_buffer_mut[128] |
215.3 ns | 244.4 ns | -11.93% |
| ⚡ | WallTime | cuda/bitpacked_u8/unpack/3bw[100M] |
352.4 µs | 301.6 µs | +16.84% |
| ⚡ | Simulation | chunked_varbinview_canonical_into[(100, 100)] |
308.5 µs | 273.5 µs | +12.78% |
| ⚡ | Simulation | chunked_varbinview_into_canonical[(100, 100)] |
361.4 µs | 326.2 µs | +10.81% |
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Signed-off-by: Robert Kruszewski <github@robertk.io>
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Spark mostly focuses on sizeInBytes which we populate from file sizes with
scaling. We also report numRows since that exists in our datasource.