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          Right Join

          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.

          Example
          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.

          To illustrate how this batch data transform handles unmatched rows and duplicate keys, we included them in both input data sources.

          The left data stream shows the opportunity ID, customer name, and opportunity amount. The right data stream shows the opportunity ID and educational level.

          After performing the right join based on the matching keys, the data transform produces the following output data.

          The new dataset contains columns from both data streams.

          All rows from the right, including those without a match and those with multiple matches, are included in the output. 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 fields are null for that record.

          Warning
          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.
          The new dataset contains duplicate records for Alice, which makes it possible to doublecount her annual income.
           
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          Salesforce Help | Article