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Resolved! I am saving a new feature table to the Databricks feature store, and it won't write the data sources of the tables used to create the feature table, because they are Hive tables that point to Azure Data Lake Storage Gen1 Delta tables
My notebook is pulling in Hive tables from DBFS, that point to ADLS Gen1 file locations for their data (Delta tables), creating the feature table as a data frame within the notebook, then calling on the feature store client to save down the feature t...
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@Jack Watson​ Could you please confirm the write is succeeding ? If yes, as per my understanding This is a warning for some validation that we will be removing shortly. We’ll likely remove the validation which save the data source.Thanks.
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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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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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MlFlow and Feature Store: mlflow.spark.autolog, using feature store on Databricks, FeatureStoreClient.log_model()?
As I am moving my first steps within the Databricks Machine Learning Workspace, I am getting confused by some features that by "documentation" seem to overlap. Does autolog for spark on mlflow provide different tracking than using a training set crea...
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Resolved! Get FeatureStore write date
Hi,is there a way to get the time stamp of the last update of a feature store table with the feature store client API? The creation time stamp can be querried as: feature_store.FeatureStoreClient().get_feature_table(name="my.table").creation_timestam...
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(The question is about querying table metadata, not creating one)I can confirm that there isn't a way to query this, not that I can see in the current API in 10.2
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Data is stored in the control plane. Metadata (eg feature table descriptions, column types, etc) is stored in the control plane. The location where the Delta table is stored is determined by the database location. The customer could call CREATE DATA...
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When would you use the Feature Store?
For example would you use a feature store on your raw data or what's is the granularity of the features in the store?
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I'll try to answer the broad question first, followed by the specific ones.When would you use the Feature Store?A Feature Store is primarily used to solve 2 challenges.(1) Discoverability and governance of featuresChallenge: In a large team or organi...
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The feature store has both online / offline components. The offline feature store is used for feature discovery, model training, and batch inference and is backed by Delta tables. You could read/write to offline store from Databricks clusters that...
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When should we use offline store vs online store for Feature Store?
Looking at the docs we see both options, can we use both e.g.?
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Online store is for real time inferencing, in most case you will use the offline store.
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