IBM 000-421 : InfoSphere DataStage v8.5

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IBM 000-421 Exam Syllabus Topics:

IBM InfoSphere DataStage v8.5 Sample Questions:

1. The Teradata Enterprise stage uses a distributed FastExport to access data. What is a limitation to distributed FastExport?

A) Non-data access (e.g., pseudo-tables like DATE or USER) is allowed.
B) Aggregates and most arithmetic operators in the SELECT statement are allowed.
C) Multiple-AMP requests are allowed.
D) The use of the USING modifier is allowed.

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

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

3. You are asked to convert a relational source, as shown in the exhibit, into three separate XML files. How would you accomplish this task?

A) Set "Output mode" setting "Segregate" on column "Customer ID" under "Transformation Settings" of the Output link of an XML Output stage.
B) Set "Output mode" setting "Break" on column "Customer ID" under "Transformation Settings" of the Output link of an XML Output stage.
C) Set "Output mode" setting" Split rows" under "Transformation Settings" of the Output link of an XML Output stage.
D) Set "Output mode" setting "Single row" under "Transformation Settings" of the Output link of an XML Output stage.

4. Which two statements are true about the usage of scratch disk? (Choose two.)

A) The Sort stage always uses the scratch disk.
B) You can define multiple scratch disk spaces to distribute disk I/O.
C) The parallel framework uses the disk space specified in the scratch disk setting to buffer virtual data set records.
D) If "buffer" scratch disk pool is defined, the framework uses this disk pool and the default disk pool.

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: