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In the above image, the platform has determined that the item number (Item_Nbr) field of Region 1 data and the item number (ITEM_NBR)  field from REF_PROD should be used as the keys for performing the join.  


NOTE: By default,

D s product
displays a maximum of three rows of data for each join key value in your sample. So, when you specify your join, it may seem like there are joined values that are missing from the data grid panel. When the job is run across the entire dataset, however, the join generates the appropriate number of rows. For more information on changing the maximum number of rows that are previewed in the join, see Miscellaneous Configuration.

  • To make changes to the two join keys, mouse over the specified keys:
    • To remove the two columns as join keys, click the X icon.
    • To edit the keys to use and other key options, click the Pencil icon. See below.
    • To add more join keys, click Add


      NOTE: Be careful applying multiple join keys. Depending on the join type, this type of join can greatly expand the size of the generated data.


fuzzy match

Use a fuzzy matching algorithm for key value matching.


Tip: Use this option to perform fuzzy join matching of primary keys between datasets.


NOTE: Fuzzy joins can only be applied to String data types. Other data types cannot be fuzzy-matched using the algorithm.

Fuzzy matching uses the doublemetaphone algorithm for matching strings (keys). Both primary encodings of each key value must match. See DOUBLEMETAPHONEEQUALS Function.

Ignore caseIgnore case differences between the join key values for matching purposes.
Ignore special charactersIgnore all characters that are not alphanumeric, accented Latin characters, or whitespace, prior to testing for a match.
Ignore whitespaceIgnore all whitespace characters, including spaces, tabs, carriage returns, and newlines.


From the selected datasets, you can specify the columns to include in the output.


D caption
Select output columns