Investigate performance tradeoff in compressing spill files
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Beschreibung
### Is your feature request related to a problem or challenge?
Part of https://github.com/apache/datafusion/issues/16065 , Related to https://github.com/apache/datafusion/issues/14078
### Background
PR https://github.com/apache/datafusion/pull/16268 will introduce compression option when writing spill files in disk. These options are limited to compression options to what Arrow IPC Stream Writer supports : `zstd`, `lz4_frame` (compression level is not configurable)
To further enhance spilling execution, we need to investigate
- CPU / I/O tradeoff when `zstd` or `lz4_frame` compression is enabled i.e. compression ratio, extra latency spent for compression
- Current arrow ipc stream writer always write `batch` at a time in `append_batch`. In terms of compression, it is not sure yet how much single batch can benefit from compression.
- whether we need separate `Writer` or `Reader` implementation instead of IPC Stream Writer.
- how to introduce sort of `adaptiveness`.
### Describe the solution you'd like
First, we need to track (or update) how many bytes are written in spill files. Datafusion currently tracks `spilled_bytes` as part of `SpillMetrics`, but it is calculated based on in memory array size, which would be different from actual spill files size especially when we compress spill files.
Second, update the benchmarks or write a separate benchmarks to see the performance characteristics. One possible way is writing out spill-related metrics to output.json when running benches like tpch with `debug` option. Another idea is to generate some spill files for microbenchmark testing only spill writing - reading process.
### Describe alternatives you've considered
_No response_
### Additional context
_No response_
Beitragsleitfaden
Rechercherichtung
Beginne damit, SpillMetrics und seine Berechnung von spilled_bytes nachzuverfolgen, überprüfe dann den Spill-Pfad des Arrow IPC Stream Writer und die vorhandenen tpch-Benchmarks mit der debug-Option. Vergleiche das Schreiben und Lesen komprimierter und unkomprimierter Spills, einschließlich Kompressionsverhältnis und Latenz. Als erledigt gilt die Aufgabe, wenn die tatsächlichen Bytes der Spill-Dateien erfasst werden und die Benchmark-Ausgabe genügend Metriken offenlegt, um die Abwägungen zu bewerten.
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Bewertung
- Tech-Stack
- rust
- Bereich
- data-engineering, performance
- Issue-Typ
- Feature
- Schwierigkeit
- 5/5
- Geschätzter Aufwand
- Über eine Woche
- Aktivitätsstatus
- Veraltet
- Klarheit
- Muss geklärt werden
- Anfängerfreundlichkeit
- 25/100