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IBM InfoSphere DataStage v8.5 Sample Questions:

1. What are three valid join operations for the Join stage? (Choose three.)

A) Left outer join
B) Bottom inner join
C) Top outer join
D) Right outer join
E) Inner Join

2. When creating a Wrapper stage, which three tasks need to be done? (Select three)

A) Specify the command to be executed by the Wrapper.
B) Specify whether input rows are to be processed automatically or manually.
C) Specify how Wrapper property values are to be converted.
D) Code and compile the C/C++ Wrapper source code.
E) Create Table Definitions that define the Wrapper's input and output columns.

3. What are the three features of Information Server that allow you to deploy DataStage objects? (Select three)

A) dscc.exe
B) Designer Client Export
C) $APT_COPY_TRANSFORMER
D) istool
E) Information Server Manager

4. Which condition is required to use the LastRowInGroup() function to determine a key break on a field?

A) The LastRowInGroup() function requires the data to be grouped by the key field, but the data does not have to be sorted.
B) The input data has to be sorted by the key field, but it is not required that DataStage be able to detect this. For example, the input data might be sorted before it is input to the job. (However, the job will abort at runtime if the data isn't sorted.)
C) The input data has to be sorted by the key field and DataStage must be able to detect that the data is sorted, for example, by the presence of a Sort stage.
D) The LastRowInGroup() function does not require the data to be either sorted or grouped by the key field. If necessary the LastRowInGroup() function will perform a sort.

5. A customer wants to select the entire order details for the largest transaction for each of 2 million customers from a 20 million row DB2 source table containing order history. Which parallel job design would satisfy this functional requirement?

A) Partition on customer key, sort on customer key and transaction amount, remove duplicates on customer key.
B) Partition and sort the input to a Filter stage by customer number. Filter with the clause "MAX(transaction_amount)".
C) Use a Sort Aggregator stage with calculated column based on the maximum value of transaction amount column.
D) Partition and sort the input to a RemoveDuplicates stage using the customer key and transaction amount columns. Remove duplicates on customer key.

Solutions: