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IBM InfoSphere DataStage v8.5 Sample Questions:

1. How must the input data set be organized for input into the join stage? (Choose two.)

A) Key partitioned
B) Unsorted
C) Entire partitioned
D) Hash partitioned
E) Sorted in ascending order

2. A DataStage job uses an Inner Join to combine data from two source parallel datasets that were written to disk in sort order based on the join key columns. Which two methods could be used to dramatically improve performance of this job? (Choose two.)

A) Explicitly specify hash partitioning and sorting on each input to the Join stage.
B) Unset the Preserve Partitioning flag on the output of each parallel dataset.
C) Set the environment variable $APT_SORT_INSERTION_CHECK_ONLY.
D) Add a parallel sort stage before each Join input, specifying the "Don't Sort, Previously Grouped" sort key mode for each key.
E) Disable job monitoring.

3. In which two situations is it appropriate to use a Sparse Lookup? (Choose two.)

A) When accessing DB2 data using the DB2 API stage.
B) When invoking a stored procedure within a database per row in the streaming link.
C) When the output of the Lookup stage needs to be hashed partitioned.
D) When reference data is significantly larger than the streaming data (100:1).

4. What two features enable a job with a Sequential File stage to read from sequential files with different numbers of columns and types? (Select two)

A) Subrecord data type
B) Schema File property
C) Vector data type
D) Runtime Column Propagation

5. What is the correct restructure stage to extract data from four input columns (three of which carry vectors) and output them into two columns with one vectors in a subrecord and the non-vector carrying column being passed through the stage?

A) Split Subrecord Stage
B) Column Export Stage
C) Make Subrecord Stage
D) Column Import Stage

Solutions: