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[SPARK-49038][SQL][3.5] SQLMetric should report the raw value in the accumulator update event #47749
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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>
dongjoon-hyun
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+1, LGTM (Pending CIs).
Thank you so much, @cloud-fan .
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…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
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that referenced
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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>
Merged to branch-3.5/3.4. |
szehon-ho
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Sep 24, 2024
…accumulator update event backport apache#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 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#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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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
, usingAccumulatorV2#value
. To avoid exposing the internal-1
value to end users,SQLMetric#value
turns-1
into0
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 createAccumulableInfo
, 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