Join Operations

Data Prep supports these join operations.

• Lookup
  In Salesforce Data Pipelines, a lookup returns all rows from the left data stream (recipe data) and only matching rows from the right data stream (lookup source). If multiple matches are found in the right data stream, you can set the lookup to return either a single row or all matching rows. To ensure that the grain of the results doesn’t change, the lookup outputs one row for each row in the left data stream.
• Left Join
  Like a lookup, a left join in Salesforce Data Pipelines includes all rows from the left (recipe data) and only matching rows from the right. Unlike a lookup, a join includes all matched rows in the target when multiple rows match.
• Right Join
  A right join in Salesforce Data Pipelines includes all rows from the right and only matching rows from the left (recipe data). The join includes all matched rows in the target when multiple rows match.
• Full Outer Join
  In Salesforce Data Pipelines, a full outer join includes all rows from the left (recipe data) and right, regardless of whether they have matches. The join includes all matched rows in the target when multiple rows match.
• Inner Join
  In Salesforce Data Pipelines, an inner join includes only matching rows from the left (recipe data) and right. The join includes all matched rows in the target when multiple rows match.
• Cross Join
  In Salesforce Data Pipelines, a cross join combines unrelated records and includes all rows from the left (recipe data) and the right. Unlike other joins that use keys to find matches, the cross join pairs every row from one dataset with every row of another dataset (known as the Cartesian Product).
• Considerations When Using Joins
  In Salesforce Data Pipelines, unlike a lookup, a join creates a separate record for each match in the target dataset when multiple rows match. Before using a join, ensure that you understand the implications of duplicate rows.