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[processor/metricstransformprocessor]: Support median aggregation type #33655
[processor/metricstransformprocessor]: Support median aggregation type #33655
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**Description:** <Describe what has changed.> - duplicated and enhanced aggregation business logic (with median function) for common usage in follow-up tickets - tests **Link to tracking Issue:** #16224 **Follow-ups:** - #33655 - #33334 - #33423 --------- Signed-off-by: odubajDT <ondrej.dubaj@dynatrace.com>
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Looks good to me based on the fact that the tests have been minimally changed.
processor/metricstransformprocessor/metrics_transform_processor_otlp.go
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@dmitryax Could you take a look? This bridges what I believe is the final gap between the metrics transform processor and transform processor, and will let us confidently merge #33334. I'll do a review after this to confirm, but I think once we know there is parity between the two, we can start pointing users to the transform processor as a meaningful replacement. |
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Signed-off-by: odubajDT <ondrej.dubaj@dynatrace.com>
…r_otlp.go Co-authored-by: Evan Bradley <11745660+evan-bradley@users.noreply.github.com>
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LGTM
**Description:** <Describe what has changed.> It is a valid use case to aggregate against an empty label set, which will functionally clear all attributes. This behaviour was removed in #33655, which simplified the check to `len() == 0`, which covers the case of the label set being `nil` and having 0 elements as the same scenario. However, these are not the same scenario and have different meanings. This PR reintroduces the original behaviour, but in a more efficient way by recognizing a label set with 0 elements and clearing the attributes, which would be the logical conclusion after running the filter anyway. **Link to tracking Issue:** #34430 **Testing:** <Describe what testing was performed and which tests were added.> **Documentation:** <Describe the documentation added.> --------- Co-authored-by: Tyler Helmuth <12352919+TylerHelmuth@users.noreply.github.com>
…metry#35006) **Description:** <Describe what has changed.> It is a valid use case to aggregate against an empty label set, which will functionally clear all attributes. This behaviour was removed in open-telemetry#33655, which simplified the check to `len() == 0`, which covers the case of the label set being `nil` and having 0 elements as the same scenario. However, these are not the same scenario and have different meanings. This PR reintroduces the original behaviour, but in a more efficient way by recognizing a label set with 0 elements and clearing the attributes, which would be the logical conclusion after running the filter anyway. **Link to tracking Issue:** open-telemetry#34430 **Testing:** <Describe what testing was performed and which tests were added.> **Documentation:** <Describe the documentation added.> --------- Co-authored-by: Tyler Helmuth <12352919+TylerHelmuth@users.noreply.github.com>
Description:
interval/core
median
aggregation typeLink to tracking Issue: #16224
Depends on #33669