1.
A client has multiple servers connected with a high bandwidth switch and has installed DataStage on one of them. There are five files (with the same record layout) that must be retrieved from three other servers using FTP. Which approach will retrieve and process all five files in the minimal amount of time?
2.
What is the correct method to process a file containing multiple record types using a Complex Flat File stage?
3.
Which job design technique can be used to give unique names to sequential output files that are used in multi-instance jobs?
4.
You are assigned to correct a job from another developer. The job contains 20 stages sourcing data from two Data Sets and many sequential files. The annotation in the job indicates who wrote the job and when, not the objective of the job. All link and stage names use the default names. One of the output columns has an incorrect value which should have been obtained using a lookup. What could the original developer have done to make this task easier for maintenance purposes?
5.
The given job processes large volumes of data using default partitioning, with sort/partition insertion enabled. Both source Data Sets are partitioned and sorted on the merge key. Assuming that the business logic allows all of the following actions, which design change would improve the performance of this job?
6.
Which of the following describes a type two update in a Slowly Changing Dimensions (SCD) stage?
7.
What are the three features of Information Server that allow you to deploy DataStage objects? (Select three)
8.
You have a dataset that is range-partitioned and sorted. Which technique is most efficient to create globally sorted data file?
9.
A scenario requires selecting only the most recent transactions for each of 2 million unique customers, from a 20 million row DB2 source table containing order history. Which parallel job design would satisfy this functional requirement?
10.
What three statements are true with regards to restartable mode for an FTP Enterprise stage? (Select three)