IBM InfoSphere DataStage v9.1 : C2090-303

C2090-303 testking pdf
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Exam Code: C2090-303

Exam Name: IBM InfoSphere DataStage v9.1

Updated: Aug 05, 2026

Q & A: 134 Questions and Answers

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IBM C2090-303 Exam Syllabus Topics:

SectionObjectives
DataStage Fundamentals- Architecture Overview
  • 1. Parallel processing architecture concepts
    • 2. InfoSphere DataStage components (Designer, Director, Administrator)
      Performance Tuning- Optimization Techniques
      • 1. Partitioning strategies
        • 2. Buffer tuning and resource management
          Data Integration and Processing- Data Sources and Targets
          • 1. Sequential file handling
            • 2. Database connectivity and connectors
              Job Design and Development- Parallel and Server Jobs
              • 1. Job types and design considerations
                • 2. Stages and links configuration
                  - Transformations
                  • 1. Transformer stage usage
                    • 2. Derivations and expressions
                      Job Control and Administration- Scheduling and Monitoring
                      • 1. Job sequences and control flow
                        • 2. Logging and troubleshooting

                          IBM InfoSphere DataStage v9.1 Sample Questions:

                          1. You have created three parallel jobs (Job A, B and C) in which the output of one job is the input to the other job. You are required to create processing that manages this data relationship of the jobs and provide job level restart-ability. What two tasks will accomplish these objectives? (Choose two.)

                          A) Create two parallel shared containers that has the logic of Job B and Job C and include those shared containers in the correct flow order within the design of Job A.
                          B) Enable the 'Add checkpoints so container is restartable' option for each of the parallel shared containers.
                          C) Set the 'Add checkpoints so sequence is restartable' option in the Sequencer job.
                          D) Create a Sequencer job that has triggered events configured allowing Job A to run first, then Job B to run when A completes successfully, and then Job C to run when Job B completes successfully.
                          E) Enable runtime column propagation for the job sequence running the jobs.


                          2. A DataStage job uses an Inner Join to combine data from two source parallel datasets that were written to disk in sort order based on the join key columns. Which two methods could be used to dramatically improve performance of this job? (Choose two.)

                          A) Disable job monitoring.
                          B) Explicitly specify hash partitioning and sorting on each input to the Join stage.
                          C) Unset the Preserve Partitioning flag on the output of each parallel dataset.
                          D) Set the environment variable $APT_SORT_INSERTION_CHECK_ONLY.
                          E) Add a parallel sort stage before each Join input, specifying the "Don't Sort, Previously Grouped" sort key mode for each key.


                          3. When using the loop functionality in a transformer, which statement is true regarding Transformer processing.

                          A) Stage variables can be executed after loop variable expressions.
                          B) Output links can be excluded from being associated with a True loop condition.
                          C) Loop variable expressions are executed before input link column expressions.
                          D) Stage variables can be referenced in loop conditions.


                          4. A 100MB input dataset has even distribution across 400 unique key values. When you run with a 4-node configuration file, which two changes could improve sort performance in this scenario? (Choose two.)

                          A) Set $APT_TSORT_STRESS_BLOCKSIZE to 50M
                          B) Alter the Sort stage properties to perform a stable sort.
                          C) Specify "Restrict Memory Usage" to 60MB on the Sort stage properties.
                          D) Convert all numeric fields to varchars.
                          E) Specify Round Robin partitioning on the input link to the Sort stage.


                          5. How is DataStage table metadata shared among DataStage projects?

                          A) Use the "Shared Table Creation Wizard" to place the table in the shared repository.
                          B) Import another copy of the table metadata into the project where it is required.
                          C) Use the InfoSphere Metadata Asset Manager (IMAM) to move the DataStage table definition to the projects where it is needed.
                          D) Export DataStage table definitions from one project and importing them into another project.


                          Solutions:

                          Question # 1
                          Answer: C,D
                          Question # 2
                          Answer: D,E
                          Question # 3
                          Answer: D
                          Question # 4
                          Answer: A,C
                          Question # 5
                          Answer: A

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