WIP: Metric anomaly check #103
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| val calculatedMetrics: Map[DescribedDs, Either[MetricCalculationError, Map[MetricDescriptor, MetricValue]]] = | ||
| allMetricDescriptors.map { | ||
| case (describedDataset, metricDescriptors) => | ||
| val metricValues: Either[MetricCalculationError, Map[MetricDescriptor, MetricValue]] = | ||
| MetricsCalculator.calculateMetrics(describedDataset, metricDescriptors) | ||
| (describedDataset, metricValues) | ||
| } | ||
| val allPreviousMetricsFut: Future[Map[Instant, Map[SingleDsDescription, Map[SimpleMetricDescriptor, MetricValue]]]] = |
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We should load only historic metrics that we actually need
| @@ -192,6 +211,7 @@ case class ChecksSuite( | |||
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| for { | |||
| _ <- storedMetricsFut | |||
| allPreviousMetrics: Map[Instant, Map[SingleDsDescription, Map[SimpleMetricDescriptor, MetricValue]]] <- allPreviousMetricsFut | |||
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As per above we should only load historic metrics we actually need
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That would be a great feature. What's left for this to get merged? |
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@kingbrown9 in the current form it could be merged with not too much more work - would just need to fully review the code. The reason it stalled was because there's an issue which is trickier to solve. When you get an anomalous result should future anomaly checks take that into account or not? There's no way to know without human intervention to say if it was legitimate or not. This was part of the reason for starting to work on a UI (which is still in a very early, basic state, though did work in a simple form with the API, though it didn't cover this use case yet). Thoughts appreciated though if it's useful even in it's current form as probably not too much work to get this merged. |
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