Support reporting statistics in spark datasource#8057
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Merging this PR will improve performance by 29.37%
|
| Mode | Benchmark | BASE |
HEAD |
Efficiency | |
|---|---|---|---|---|---|
| ⚡ | Simulation | chunked_bool_canonical_into[(1000, 10)] |
46.7 µs | 31.8 µs | +46.95% |
| ⚡ | Simulation | chunked_varbinview_canonical_into[(1000, 10)] |
197.9 µs | 161.8 µs | +22.34% |
| ⚡ | Simulation | chunked_varbinview_into_canonical[(1000, 10)] |
213.6 µs | 177.3 µs | +20.42% |
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Comparing rk/sparkstats (deb1dc0) with develop (f7f6d10)
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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.