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[ML] Single Metric Viewer should require the end-user to select a partitioning field #18090

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elasticmachine opened this issue Nov 30, 2017 · 3 comments · Fixed by #48235
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@elasticmachine
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Original comment by @sophiec20:

Based on customer feedback and the balance of personal opinions, we should protect the end-user from themselves and force them to select the partitioning fields when using the Single Metric Viewer.

Currently, we show average values for all partitioning fields on page load. This has the advantage of showing something other than a warning and is usually fine for smaller/simple jobs...

However for jobs with many partitioning fields, then this can cause the single metric viewer to display many critical anomalies and be mostly red. From experience, not all end-users realise that they need to narrow the scope and pick a "single metric".

@elasticmachine
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Original comment by @sophiec20:

Deferring to 6.3

@pheyos
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pheyos commented Sep 7, 2018

👍 because the current behavior is also sometimes not ideal when showing forecasts:
multi_metric_forecast

@sophiec20 sophiec20 added Feature:Anomaly Detection ML anomaly detection and removed Feature:ml-results legacy - do not use labels Jun 19, 2019
@tveasey
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tveasey commented Sep 26, 2019

I have always found this behaviour odd as well. This is the single metric viewer and I really think it shouldn't be displaying some combination of multiple metrics. Personally, I'd be happy with one of:

  1. Don't draw the chart and display a message in its place that you need to select a metric
  2. Have a pop up which forces you to select the metric if job is multi-metric and none is supplied when navigating to the page
  3. Select an arbitrary (say the first) metric from the drop down and show that if none is supplied. Maybe we could somehow highlight that a metric was chosen automatically if this happened

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6 participants