Right Join

Example

Our company's marketing team captures demographic data in an external data source for opportunities stored in Salesforce. To help create more targeted campaigns, the team is segmenting our current opportunities by the Education Level demographic. Let’s use a right join to add the opportunity data to the demographic data.

Consider the following two data streams that feed the recipe’s target dataset. To illustrate how this recipe function handles unmatched rows and duplicate keys, we included them in both data streams.

After performing the right join based on the matching keys, the recipe produces the following target dataset.

All rows from the right, including rows without a match and rows with multiple matches, are included in the target. Because Opp_id 2 has two matches on the left (Amy and Bob), the target contains a separate record for each of them. Also, because Opp_id 5 doesn’t have a match, the Opp_ID and Customer Name columns are null for that record.

Warning If duplicate records contain measures (as shown for Opp_id 1 in the following screenshot), don’t double count the measures when aggregating the records. To prevent duplicate records, use a lookup instead of a join.