[CORE] Gluten should honor the spark configs as much as possible

[FelixYBW]

Description

During the analysis of spill in issue #8025, we noted some issues are common between Gluten and Vanilla spark, like the spill read/write buffer size. Some configuration are even not documented in Spark like spark.unsafe.sorter.spill.reader.buffer.size.

Furthermore, I noted Gluten doesn't have a list of honored spark configurations. We should create such a list in documents. @zhouyuan

[FelixYBW]

@marin-ma which of following shuffle configurations are used by Gluten? Can you help to fill the missing one, feel free to correct. Gluten Config is the config renamed by Gluten. if so we should either remove the Gluten config or set Gluten Config's default value as spark config's value.

Spark Config	Respected by Gluten	Gluten Config	Transparent to Gluten
spark.reducer.maxSizeInFlight	Y		Y
spark.reducer.maxReqsInFlight	Y		Y
spark.reducer.maxBlocksInFlightPerAddress	Y		Y
spark.shuffle.compress	Y
spark.io.compression.codec	Only if spark.gluten.sql.columnar.shuffle.codec is not set
spark.shuffle.file.buffer	N Gluten uses fixed 16k buffer
spark.shuffle.unsafe.file.output.buffer	N
spark.shuffle.spill.diskWriteBufferSize	N Gluten uses fixed 16k buffer
spark.shuffle.io.maxRetries	Y		Y
spark.shuffle.io.numConnectionsPerPeer	Y		Y
spark.shuffle.io.preferDirectBufs	Y		Y
spark.shuffle.io.retryWait	Y		Y
spark.shuffle.io.backLog	Y		Y
spark.shuffle.io.connectionTimeout	Y		Y
spark.shuffle.io.connectionCreationTimeout	Y		Y
spark.shuffle.service.enabled	Y		Y
spark.shuffle.service.port	Y		Y
spark.shuffle.service.name	Y		Y
spark.shuffle.service.index.cache.size	Y		Y
spark.shuffle.service.removeShuffle	Y		Y
spark.shuffle.maxChunksBeingTransferred	Y		Y
spark.shuffle.sort.bypassMergeThreshold	N
spark.shuffle.sort.io.plugin.class	N
spark.shuffle.spill.compress	N Gluten uses spark.shuffle.compress
spark.shuffle.accurateBlockThreshold	Y		Y
spark.shuffle.registration.timeout	Y		Y
spark.shuffle.registration.maxAttempts	Y		Y
spark.shuffle.reduceLocality.enabled	Y		Y
spark.shuffle.mapOutput.minSizeForBroadcast	Y		Y
spark.shuffle.mapOutput.dispatcher.numThreads	Y		Y
spark.shuffle.detectCorrupt	Y		Y
spark.shuffle.detectCorrupt.useExtraMemory	Y		Y
spark.shuffle.useOldFetchProtocol	Y		Y
spark.shuffle.readHostLocalDisk	Y		Y
spark.files.io.connectionTimeout	Y		Y
spark.files.io.connectionCreationTimeout	Y		Y
spark.shuffle.checksum.enabled	N Gluten currently doesn't support it
spark.shuffle.checksum.algorithm	N Gluten currently doesn't support it
spark.shuffle.service.fetch.rdd.enabled	Y		Y
spark.shuffle.service.db.enabled	Y		Y
spark.shuffle.service.db.backend	Y		Y

[yikf]

@FelixYBW thank you for initiating this matter, and at the same time, I noticed some configuration related to table write. Please correct me if missing something.

Spark Config	Respected by Gluten	Gluten Config	Transparent to Gluten
spark.sql.parquet.compression.codec	Y	N/A	Y

the Parquet configuration options in the table options are also respected by Gluten, as follows:

Options	Respected by Gluten	Gluten Config	Transparent to Gluten
compression	Y	N/A	Y
parquet.compression	Y	N/A	Y
parquet.block.size	Y	spark.gluten.sql.columnar.parquet.write.blockSize	Y
parquet.block.rows	Y	spark.gluten.sql.native.parquet.write.blockRows	Y
parquet.gzip.windowSize	Y	N/A	Y

In addition to the above configuration, any other Spark configuration related to table write will not be respected by Gluten at the moment.

[marin-ma]

@FelixYBW Updated the table. PTAL. Thanks!

[FelixYBW]

spark.shuffle.file.buffer

Thank you! Can you submit a PR to support the configs:

• spark.shuffle.file.buffer
• spark.shuffle.spill.diskWriteBufferSize
• spark.shuffle.spill.compress

[jinchengchenghh]

We may also need to document the config Spark and Velox mapping.

[zhouyuan]

looks like a long tail task again. There are also some gaps on the data loading part: the configs on HDFS, Iceberg, Hudi and DeltaLake. As these are newly implemented in native C++.
For other operators(other than Spill and table scan) and expressions(other than ANSI) it should be aligned with Spark.

[FelixYBW]

looks like a long tail task again. There are also some gaps on the data loading part: the configs on HDFS, Iceberg, Hudi and DeltaLake. As these are newly implemented in native C++. For other operators(other than Spill and table scan) and expressions(other than ANSI) it should be aligned with Spark.

Let's start from spark3.5's configurations here. GO through the category one by one.

https://spark.apache.org/docs/3.5.1/configuration.html