Stage to OPerator in DataStage - the Real Driver

The parallel job stages are built on operators. Or Operators are individual parallel engine stages where the data actually flows. In a typical job flow, operators are end-points, and data sets are the links between the operators.

Each operator listed in the DUMP SCORE is a number of processes that are dependent on:

• the job's established configuration file (APT_CONFIG_FILE)
• constrained by the node pool settings
• the operator configuration in the parallel engine code
• Several environment variables, such as APT_DISABLE_COMBINATION, being set/unset.

Optimzie your DataStage Job Performance with relevant Environment Variables

DataStage has many parameters which can be tweaked and used to optimize the performance of various DataStage Jobs. Even many available to collect more information during the event of crash to get more traces.

For any DataStage Job if you run into problem or want to get more details need to check following variables.

Tips & Tricks for debugging a DataStage job

The article talks about DataStage debugging techniques. This can be applied to a job which

• is not producing proper output data or
• to a job that is aborting or generating warnings

1. Use the Data Set Management utility, which is available in the Tools menu of the DataStage Designer or the DataStage Manager, to examine the schema, look at row counts, and delete a Parallel Data Set. You can also view the data itself.