Support faster copy for a custom DataSource V2 which supplies Arrow data #1622
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Signed-off-by: Thomas Graves <tgraves@nvidia.com>
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sql-plugin/src/main/scala/com/nvidia/spark/rapids/HostColumnarToGpu.scala
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| "access its Arrow ValueVector", e) | ||
| } | ||
| case av: AccessibleArrowColumnVector => | ||
| // val arrowVec = av.asInstanceOf[AccessibleArrowColumnVector] |
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nit: I think this can be removed.
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oops missed that
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…ata (NVIDIA#1622) * Add in data source v2, csv file and test for arrow copy * remove commented out line
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…ata (NVIDIA#1622) * Add in data source v2, csv file and test for arrow copy * remove commented out line
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This provides support for more efficiently copying data to the GPU when a datasource V2 source provides the data as an ArrowColumnVector. The CUDF side of this has already been merged. rapidsai/cudf#7222
This currently only supports primitive types and strings. Decimal types and nested types are not supported. It will fallback to the regular copy code if it sees one of those types not supported.
The integration test require an extra jar which contains a datasource v2 which supplies ArrowColumnVector. I'm looking into pulling that code in and how best to automate those tests, filed #1620 to track that.
You will notice I added a new AccessibleArrowColumnVector. This is because the Spark ArrowColumnVector doesn't have the Arrow ValueVector publicly accessible. I use reflection in here to get a hold of that, but another option is just for user to use AccessibleArrowColumnVector. I would like peoples feedback on whether to keep that or not?
I had to add a shim layer for the Arrow code because Spark 3.1.0 changed the arrow version and ArrowBuf class is now different.