Add GPU metrics to GpuFileSourceScanExec #547
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Signed-off-by: Jason Lowe <jlowe@nvidia.com>
jlowe
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It looks OK to me. A lot of the scan code appears to be related to partitioning and planning how to read bucketed code. We probably should add in more tests for reading bucketed code, and look at the code coverage for these areas just to be sure we didn't mess anything up, and to give us more confidence that we are doing it right in newer versions of Spark. |
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fyi spark 3.1.0 has another param in the FileSourceScanExec - optionalNumCoalescedBuckets. so probably still need a shim or some sort if we want to keep that functionality. (https://issues.apache.org/jira/browse/SPARK-31350) I was actually in process of adding a bucketing test because I ended up copying a bunch of functions as well for the small file optimization, I was trying to use tables and its being a bit of a pain to add, seeing some weirdness the catalog. One issue, like you mention, which we already had but this makes it worse is how we keep this code up to date and discover changes in spark side. One example of this is already the optionalNumCoalescedBuckets we could have worked fine without noticing that was there. We may need to think up more extensive auditing mechanisms. |
Signed-off-by: Jason Lowe <jlowe@nvidia.com>
Signed-off-by: Jason Lowe <jlowe@nvidia.com>
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@tgravescs @revans2 I found what I think is a cleaner way to implement the metrics, which is leveraging the fact that we know we're using a file format that we control. That seems cleaner than abusing the options map to piggyback metrics on it. This is just about ready to go. Running into a single, weird test failure in the Mortgage test where the first query results in zero rows. Not sure how that's happening yet. |
Signed-off-by: Jason Lowe <jlowe@nvidia.com>
Signed-off-by: Jason Lowe <jlowe@nvidia.com>
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Thanks to @revans2 the test failure has been fixed. This is now ready for review. |
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sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuReadFileFormatWithMetrics.scala
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Signed-off-by: Jason Lowe <jlowe@nvidia.com>
| @@ -94,6 +94,8 @@ class Spark300dbShims extends Spark300Shims { | |||
| wrapped.requiredSchema, | |||
| wrapped.partitionFilters, | |||
| wrapped.optionalBucketSet, | |||
| // TODO: Does Databricks have coalesced bucketing implemented? | |||
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we probably need to go look at the source code for the various runtimes, if we have a jira we may be able to look at the release notes for each one as well. added a comment to #502
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* Add GPU metrics to GpuFileSourceScanExec Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Extract GpuFileSourceScanExec from shims Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Pass metrics via GPU file format rather than custom options map Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Update code checking for DataSourceScanExec Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Fix scaladoc warning and unused imports Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Fix copyright Signed-off-by: Jason Lowe <jlowe@nvidia.com>
* Add GPU metrics to GpuFileSourceScanExec Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Extract GpuFileSourceScanExec from shims Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Pass metrics via GPU file format rather than custom options map Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Update code checking for DataSourceScanExec Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Fix scaladoc warning and unused imports Signed-off-by: Jason Lowe <jlowe@nvidia.com> * Fix copyright Signed-off-by: Jason Lowe <jlowe@nvidia.com>
…IDIA#547) Signed-off-by: spark-rapids automation <70000568+nvauto@users.noreply.github.com> Signed-off-by: spark-rapids automation <70000568+nvauto@users.noreply.github.com>
Fixes #524.
This provides GPU-specific metrics to the
FileSourceScanExecoverride in the plugin. Apache Spark doesn't support format-specific metrics directly, so this adds a workaround by piggybacking the metrics map onto the format options map.This looks like it's adding a ton of code to
GpuFileSourceScanExec, and it is, but almost all the code comes from Spark'sFileSourceScanExec. With this change,GpuFileSourceScanExecno longer tries to construct a wrapped instance ofFileSourceScanExec(which lead to a number of cases where shims needed to be built across the Spark versions), but instead provides implementations of the overridden methods directly.Opening this PR in draft form first to get some feedback on the approach. The key part of the implementation is the new
ReaderOptionsWithMetricsclass (I'm terrible at naming things). I'm open to other suggestions on how to handle the GPU metrics. This PR only updates the Spark 3.0.0 shim version ofGpuFileSourceScanExecfor now. If the approach is approved then I will apply a similar change to the other shim versions and potentially be able to combine the implementations such that it can be extracted from the shim layer.