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Forum Posts

youssefmrini
by Honored Contributor III
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  • 1 replies
  • 1 kudos
  • 598 Views
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youssefmrini
Honored Contributor III
  • 1 kudos

Yes You can. With Databricks Runtime 12.2 LTS ML and above, you can use existing feature tables in Feature Store to augment the original input dataset for all of your AutoML problems: classification, regression, and forecasting.This capability requi...

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NSRBX
by Contributor
  • 1396 Views
  • 2 replies
  • 4 kudos

Feature Store - Feature Lookup Engine with join on partial key and Filter

Hello ,I am working with lookupEngine functions. However, we have some feature tables with granularity level most detailled of dataframe input.Please find an example :table A with unique keys on two features : numero_p, numero_s So while performing F...

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Debayan
Esteemed Contributor III
  • 4 kudos

Hi @SERET Nathalie​ , I can check internally on the ask here. In the meantime please let us know if this helps: https://docs.databricks.com/machine-learning/feature-store/feature-tables.htmlhttps://docs.databricks.com/machine-learning/feature-store/i...

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Direo
by Contributor
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Feature store errors

HiWhen I open feature store, I get an error saying that "Failed to load some job schedules". When I open one of the feature store tables, I get several additional errors:"Failed to laod lates run for some job producers","Failed to laod some job produ...

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Kaniz
Community Manager
  • 2 kudos

Hi @Direo Direo​ , Just a friendly follow-up. Do you still need help, or @Hubert Dudek (Customer)​ 's response help you to find the solution? Please let us know.

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thib
by New Contributor III
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Resolved! Feature store : Can create_training_set() be implemented to execute an inner join?

For timeseries feature tables, an inner join is made at the creation of the feature table. For the other type of feature tables, a left join is made, so NaN values can show up in the training set. Can the inner join in create_training_set() method be...

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thib
New Contributor III
  • 4 kudos

Thank you Hubert, that's a good alternative, I just thought I'd stick to the api as much as possible, but this solves it.

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