I have a quite challenging task and have not found a solution for my problem, yet.
I created a multi-metric anomalies detection machine learning job which is running a forecast as well. My aim is now to compare the forecast results with the actual results to get a sense of the accuracy and quality of the calculated forecast. In my knowledge the only possible way of solving this task would be to create a scripted field. I am not sure if it is already possible within Kibana to compare fields from different index pattern. I hope someone is able to help me with that challenge!
Concept, use transforms with the source index containing the actual data. Add a lookup runtime field that searches against the forecast index to add the forecast data to the actual data document. Transform will then index this result into a new index/document which will contain all of the needed information where you can then perform the comparison.
Note: You need to do this round-about transform method because of the limitations with the lookup runtime field not being able to be aggregated against directly.
thank you for your answer! The past days I tried to implement your solution. I can transform the actual data over into a separate index. Unfortunately I am struggling with the second transform from the forecast index pulling the data over to the new index. Is that possible with a transform as well or do I need to implement a runtime field. How could such a runtime lookup look like? Maybe you can help me with that. Thank you!
Hmm, so I think you should only need one transform. In that transform you should use your "real" data index, then add a lookup runtime field that queries your "forecast" index.
This is just a theoretical example, I'm not 100% sure it will work. Just more to demonstrate the idea.
Note, it looks like you can't add lookup runtimes via the Kibana UI, I opened this issue about it. So, you'll need to create the transform via the Elasticsearch API.
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