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IBM InfoSphere DataStage v8.5 Sample Questions:

1. Which three DataStage elements allow you to create Shared MetaData? (Select three)

A) DB2 Connector
B) Sequential file stage
C) DataStage table definition
D) Oracle Connector
E) Dataset stage

2. You are responsible for deploying objects into your customers production environment. To ensure the stability of the production system the customer does not permit compilers on production machines. They have also protected the project and only development machines have the required compiler. What two options will allow jobs with a parallel transformer to execute in the customers production machines? (Choose two.)

A) Create a package with Information Server Manager and select the option to include executables.
B) Add $APT_COMPILE_OPT=-portable
C) Set $APT_COPY_TRANSFORM_OPERATOR
D) Export the jobs with Information Server Manager with the executables.

3. There is a requirement to transfer a large file using an FTP Enterprise stage. How can you minimize processing time when a transfer failure occurs?

A) Use a sequencer to check transfer status and restart the job from the beginning on failure.
B) Specify restartable mode on a transfer of the single file.
C) Manually split the file into multiple files and specify restartable mode on a transfer.
D) Create multiple readers to transfer file data and specify restartable mode on Input link tab.

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

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

5. Using a DB2 for z/OS source database, a 200 million row source table with 30 million distinct values must be aggregated to calculate the average value of two column attributes. What would provide optimal performance while satisfying the business requirements?

A) Select all source rows using a DB2 API stage. Aggregate using a Sort Aggregator.
B) Select all source rows using a DB2 Enterprise stage, use a parallel Sort stage with the specified sort keys, calculate the average values using a parallel Transformer with stage variables and output link constraints.
C) Using custom SQL with an ORDER BY clause based on key columns, select all source rows using the DB2 API stage. Aggregate using a Hash Aggregator.
D) Using custom SQL with AVG functions and a DISTINCT clause, select all source rows using a DB2 Enterprise stage.

Solutions: