Join Operations

Batch data transforms support these join operations.

• Lookup
  A lookup returns all rows from the left Data 360 input data source object and only matching rows from the right object, the lookup source. To ensure that the grain of the results doesn’t change, the lookup output data includes one row for each row in the left object.
• Left Join
  Like a lookup, a left join includes all rows from the left input data source object and only matching rows from the right object. Unlike a lookup, a join includes all matched rows in the output data when multiple rows match.
• Right Join
  A right join includes all rows from the right and only matching rows from the left input data source objects. The join includes all matched rows in the data output when multiple rows match.
• Full Outer Join
  A full outer join includes all rows from the left and right input data source objects, regardless of whether they have matches. The join includes all matched rows in the output data when multiple rows match.
• Inner Join
  An inner join includes only matching rows from the left and right input data source objects. The join includes all matched rows in the output data when multiple rows match.
• Cross Join
  A cross join combines unrelated records and includes all rows from the left and the right input data source objects. Unlike other joins that use keys to find matches, the cross join pairs every row from one data source with every row of another data source.
• Considerations for Using Joins
  Unlike a lookup, a join creates a separate record for each match in the output data when multiple rows match. Before using a join, ensure that you understand the implications of duplicate rows.