In part 3, we ratchet up the complexity once more to see how we handle multiple JSON files with schema structures that require extraction at multiple levels (i.e. highly hierarchical). Using U-SQL via Azure Data Lake Analytics we will transform semi-structured data into flattened CSV files to glean insights on the top restaurants across London.
Read MoreIn part 2, we ratchet up the complexity to see how we handle JSON schema structures more commonly encountered in the wild (i.e. an array of objects, dictionaries, nested fields, etc). Using U-SQL via Azure Data Lake Analytics we will transform semi-structured data into flattened CSV files.
Read MoreIn part 1, we begin by learning how to set up our environment in order to query JSON documents using U-SQL via Azure Data Lake Analytics, then storing the flattened results into a CSV file back into Azure Data Lake Store.
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