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How to read feature table without target_df / online inference based on filter_condition in databricks feature store
I'm using databricks feature store == 0.6.1. After I register my feature table with `create_feature_table` and write data with `write_Table` I want to read that feature_table based on filter conditions ( may be on time stamp column ) without calling ...
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create_training_set is just a simple Select from delta tables. All feature tables are just registered delta tables. Here is an example code that I used to handle that: customer_features_df = spark.sql("SELECT * FROM recommender_system.customer_fea...
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How Delta Lake parses through the files on querying the table with a filter condition
Consider a table that gets partitioned on a date field. But, I'm filtering a column that is not partitioned. Now, with this filter condition whether all the files are parsed to attain the required result set, or does any data skipping happens?
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