Using Inner Join - 7.1

Talend Real-time Big Data Platform Studio User Guide

author
Talend Documentation Team
EnrichVersion
7.1
EnrichProdName
Talend Real-Time Big Data Platform
task
Design and Development
EnrichPlatform
Talend Studio
Warning: For Big Data users only: In a MapReduce Job, only one expression key is allowed per mapping component. If you need to use multiple expression keys to join different input tables, use multiple tMap components one after another. For more information about MapReduce Jobs, see How a Talend MapReduce Job works.

The Inner join is a particular type of Join that distinguishes itself by the way the rejection is performed.

This option avoids that null values are passed on to the main output flow. It allows also to pass on the rejected data to a specific table called Inner Join Reject table.

If the data searched cannot be retrieved through the explicit Join or the filter Join, in other words, the Inner Join cannot be established for any reason, then the requested data will be rejected to the Output table defined as Inner Join Reject table if any.

Simply drop column names from one table to a subordinate one, to create a Join relationship between the two tables. The Join is displayed graphically as a purple link and creates automatically a key that will be used as a hash key to speed up the match search.

About this task

To define the type of an explicit Join:

Procedure

  1. Click the tMap settings button at the top of the table to which the Join links to display the table properties.
  2. Click in the Value field corresponding to Join Model and then click the three-dot button that appears to open the Options dialog box.
  3. In the Options dialog box, double-click the wanted Join type, or select it and click OK to validate the setting and close the dialog box.
    Note: An Inner Join table should always be coupled to an Inner Join Reject table. For how to define an output table as an Inner Join Reject table, see Lookup Inner Join rejection.

    You can also use the filter button to decrease the number of rows to be searched and improve the performance (in Java).

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