[SPARK-41442][SQL][FOLLOWUP] SQLMetric should not expose -1 value as it's invalid #39311
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…ulator update event ### What changes were proposed in this pull request? Some `SQLMetrics` set the initial value to `-1`, so that we can recognize no-update metrics (e.g. there is no input data and the metric is not updated at all) and filter them out later in the UI. However, there is a bug here. Spark turns accumulator updates into `AccumulableInfo`, using `AccumulatorV2#value`. To avoid exposing the internal `-1` value to end users, `SQLMetric#value` turns `-1` into `0` before returning the value. See more details in #39311 . UI can no longer see `-1` and filter them out. This PR fixes the bug by using the raw value of `SQLMetric` to create `AccumulableInfo`, so that UI can still see `-1` and filters it. ### Why are the changes needed? To avoid getting the wrong min value for certain SQL metrics when some partitions have no data. ### Does this PR introduce _any_ user-facing change? Yes, if people write spark listeners to watch the `SparkListenerExecutorMetricsUpdate` event, they can see the correct value of SQL metrics. ### How was this patch tested? manual UI tests. We do not have an end-to-end UI test framework for SQL metrics yet. ### Was this patch authored or co-authored using generative AI tooling? no Closes #47721 from cloud-fan/metrics. Authored-by: Wenchen Fan <wenchen@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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…ulator update event Some `SQLMetrics` set the initial value to `-1`, so that we can recognize no-update metrics (e.g. there is no input data and the metric is not updated at all) and filter them out later in the UI. However, there is a bug here. Spark turns accumulator updates into `AccumulableInfo`, using `AccumulatorV2#value`. To avoid exposing the internal `-1` value to end users, `SQLMetric#value` turns `-1` into `0` before returning the value. See more details in apache#39311 . UI can no longer see `-1` and filter them out. This PR fixes the bug by using the raw value of `SQLMetric` to create `AccumulableInfo`, so that UI can still see `-1` and filters it. To avoid getting the wrong min value for certain SQL metrics when some partitions have no data. Yes, if people write spark listeners to watch the `SparkListenerExecutorMetricsUpdate` event, they can see the correct value of SQL metrics. manual UI tests. We do not have an end-to-end UI test framework for SQL metrics yet. no Closes apache#47721 from cloud-fan/metrics. Authored-by: Wenchen Fan <wenchen@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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Aug 14, 2024
…accumulator update event backport #47721 to 3.5 ### What changes were proposed in this pull request? Some `SQLMetrics` set the initial value to `-1`, so that we can recognize no-update metrics (e.g. there is no input data and the metric is not updated at all) and filter them out later in the UI. However, there is a bug here. Spark turns accumulator updates into `AccumulableInfo`, using `AccumulatorV2#value`. To avoid exposing the internal `-1` value to end users, `SQLMetric#value` turns `-1` into `0` before returning the value. See more details in #39311 . UI can no longer see `-1` and filter them out. This PR fixes the bug by using the raw value of `SQLMetric` to create `AccumulableInfo`, so that UI can still see `-1` and filters it. ### Why are the changes needed? To avoid getting the wrong min value for certain SQL metrics when some partitions have no data. ### Does this PR introduce _any_ user-facing change? Yes, if people write spark listeners to watch the `SparkListenerExecutorMetricsUpdate` event, they can see the correct value of SQL metrics. ### How was this patch tested? manual UI tests. We do not have an end-to-end UI test framework for SQL metrics yet. ### Was this patch authored or co-authored using generative AI tooling? no Closes #47749 from cloud-fan/branch-3.5. Authored-by: Wenchen Fan <wenchen@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
dongjoon-hyun
pushed a commit
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Aug 14, 2024
…accumulator update event backport #47721 to 3.5 Some `SQLMetrics` set the initial value to `-1`, so that we can recognize no-update metrics (e.g. there is no input data and the metric is not updated at all) and filter them out later in the UI. However, there is a bug here. Spark turns accumulator updates into `AccumulableInfo`, using `AccumulatorV2#value`. To avoid exposing the internal `-1` value to end users, `SQLMetric#value` turns `-1` into `0` before returning the value. See more details in #39311 . UI can no longer see `-1` and filter them out. This PR fixes the bug by using the raw value of `SQLMetric` to create `AccumulableInfo`, so that UI can still see `-1` and filters it. To avoid getting the wrong min value for certain SQL metrics when some partitions have no data. Yes, if people write spark listeners to watch the `SparkListenerExecutorMetricsUpdate` event, they can see the correct value of SQL metrics. manual UI tests. We do not have an end-to-end UI test framework for SQL metrics yet. no Closes #47749 from cloud-fan/branch-3.5. Authored-by: Wenchen Fan <wenchen@databricks.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com> (cherry picked from commit bd2cbd6) Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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What changes were proposed in this pull request?
This is a followup of #38969 to fix a regression.
SQL UI is not the only way for end users to see the SQL metrics. They can also access the accumulator values in the physical plan programmatically via query execution listener. We should be consistent with the SQL UI and not expose the -1 value.
Why are the changes needed?
make SQL UI and the accumulator value consistent
Does this PR introduce any user-facing change?
Yes, as end users can access accumulator values directly.
How was this patch tested?
existing tests