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IBM Assessment: InfoSphere DataStage v8.5 Sample Questions:

1. You are setting up the parallel engine configuration file. Which two statements are true about file system efficiency? (Select two)

A) Creating scratch disk space on an internal disk improves sort performance than NFS drive.
B) In a clustered environment where NAS is used for a common storage, specify the internal disk for scratch disk.
C) Specify a directory for the resource disk in the partition where the engine is installed.
D) Using multiple scratch spaces in a logical node improves performance.

2. In the job fragment shown in the exhibit, there are two Sort stages: the first (Sort1) sorts the data by state, the second (Sort2) sorts the data by state and area, No repartitioning occurs between the stages.
You have been asked to reduce the number of sorts to improve the performance of the job.

Which two ways might be used to accomplish this without changing how the job functions? (Select two)

A) Remove the second Sort stage. Add area as an additional sort key.
B) Remove the first Sort stage. Retain the existing sort keys in the second Sort stage.
C) In the second Sort stage change the Sort Mode property of the state column to "Don't sort, previously sorted.".
D) In the second Sort stage change the Sort Mode property of the area column to "Don't sort, previously sorted.".

3. 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) Column Import Stage
D) Make Subrecord Stage

4. A customer is complaining of poor performance from the job shown in the exhibit, which aggregates and joins on ZIP code. Currently all partitioning is set to "Auto" and sort/partition insertion is allowed.

What would give the best performance improvement for the job?

A) Hash partition and sort on ZIP code prior to the Copy stage and use entire partitioning on the output of the Aggregator stage.
B) Hash partition and sort on ZIP code prior to the Copy stage, and use same partitioning on the Aggregator and Join stages.
C) Hash partition and sort on ZIP code on the input links to the Aggregator and Join stages.
D) Use same partitioning on all input links in the job; create the input data set by hash-partitioning its input on ZIP code.

5. You found there were common functional requirements in the data mapping specification. The required functions are same but the record formats are different. Which action will allow you to effectively implement common logic?

A) Create parallel shared containers and define columns combining all data formats.
B) Create separate jobs and choose appropriate job within a job sequence.
C) Create parallel routines.
D) Create parallel shared containers with Runtime Column Propagation (RCP) ON and define only necessary columns needed for the logic.

Solutions: