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We need two Snaps—one to load the data from the CSV file in an S3 location and another to read the data loaded in the target table and generate some insights.
We configure the Databricks - Bulk Load Snap to load employee data from the CSV into a new table, company_employees. We configure this Snap’s account to connect to the AWS S3 service using Source Location Credentials to read the CSV file.
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Here is how we do it:
Select the Drop and create table as the Load action.
Define the schema for the new table in the Target Table Columns fieldset.
Choose the source data type and indicate that the file contains a valid header.
Specify the file names (with relative paths, here) to load the data from.
As our CSV file in the S3 location is not encrypted, we leave the corresponding fields blank.
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Upon validation, the Snap retrieves and displays the data from the company_employees table that matches the WHERE condition specified.
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