Concept: Join Recipe

The primary use case for the Join recipe is to enrich one dataset with columns from another. DSS matches values using a key column that is common to both datasets. The Left join is a common join type used in data enrichment. It lets you keep all the records in your main dataset regardless if there is a match in the enrichment dataset.

While the default join type is a Left join, you can set the join type that best fits your use case.

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You can always change the detected key column by selecting your own columns to match on and setting the conditions.

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In the Selected columns step, you can tell DSS which columns you want to see in the output dataset.

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There are a few other options including Pre-filters which allows you to keep or drop rows based on your criteria.

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You can use the Post-filter to inform DSS if duplicate rows are allowed and when you want to be able to select only the rows that match a condition.

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Finally, you can use the Output step to review the execution specs, for example the generated SQL query and execution plan.

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There are a lot of reasons to use joins when building a Flow. In the following hands-on lesson, you can practice using the Join Recipe to enrich the customers dataset.