> For the complete documentation index, see [llms.txt](https://docs.pentaho.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pentaho.com/pdia-data-integration/10.2-data-integration/pdi-job-entries-reference-overview/pentaho-mapreduce/use-pdi-outside-and-inside-the-hadoop-cluster/pentaho-mapreduce-workflow/pdi-job.md).

# PDI Job

Once you have created the Mapper transformation, you are ready to include it in a Pentaho MapReduce job entry and build a MapReduce job.

Open a PDI job and drag the specifically-designed Pentaho MapReduce job entry onto the canvas. In addition to ordinary transformation work, this entry is designed to execute mapper/reducer functions within PDI. Again, no need to provide a Java class to achieve this.

Configure the Pentaho MapReduce entry to use the transformation as a mapper. Drag and drop a Start job entry, other job entries as needed, and result job entries to handle the output onto the canvas. Add hops to sequence the entries into a job that you execute in PDI.

The workflow for the job should look something like this.

![Transformation Job Workflow Word Count Example](/files/TyMvFu3DY3m95Yqg0pH2)

The Pentaho MapReduce dialog box enables you to configure the Pentaho MapReduceentry.

![Pentaho MapReduce dialog Mapper tab](/files/RTb2GdF8j3GKmcSElmf9)


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