Data Stage

DataStage EE provides a number of environment variables to control how jobs operate on a UNIX system.  In addition to providing required information, environment variables can be used to enable or disable various DataStage features, and to tune pe

The configuration file tells DataStage Enterprise Edition how to exploit underlying system resources (processing, temporary storage, and dataset storage).

The alternative to the first configuration method is more careful planning of the I/O behavior to reduce contention.

Improving Sequential File PerformanceIf the source file is fixed/de-limited, the Readers Per Nodeoption can be used to read a single input file in parallel at evenly-spaced offsets.

Choosing Appropriate StagesThe parallel Transformer stage always generates “C” code which is then compiled to a parallel component.

The Lookup stage is most appropriate when the reference data for all lookup stages in a job is small enough to fit into available physical memory. Each lookup reference requires a contiguous block of physical memory.

The Join stage does not provide reject handling for unmatched records (such as in an InnerJoin scenario). If un-matched rows must be captured or logged, an OUTER join operation must be performed.

How did you handle reject data?

What are conformed dimensions?

Does the selection of 'Clear the table and Insert rows' in the ODBC stage send a Truncate statement to the DB or does it do some kind of Delete logic.