Informatica Job Interview Questions Set 6

Informatica Job Interview Questions and Answers Set 6

Q51: What do you mean by code page compatibility?

A51: Code page compatibility is a characteristic to measure data movement between two code pages. When data moves from one code page to another and both code pages have the same character sets then there is no data loss. The target page must have all the characters of the source page. In other words the target page can be a superset of the source page. But if the target page does not have all the characters of the source page then it is just a subset and data loss will occur during transformation as the two code pages are not compatible.

Q52: Data Transformation Manager creates which different threads?

A52: The Data Transformation Manager creates the following different threads:

a)      The single master thread which is responsible for coordinating the other threads ,

b)      The mapping thread which supervises mapping parameters of each session,

c)      The pre session, session and post session operations are performed by different threads,

d)     The reader session reads from the source and the writer session writes to the target,

e)      Every partition has its individual transformation thread.

Q53: Explain sessions. Explain how batches are used to combine executions.

A53: A session is an instruction set that needs to be executed to transform data from a source to a target. Sessions can be executed using the sessions manager or pmcmd command. Batch execution can be used to club session executions either in a parallel or a serial manner. Batches can have multiple sessions executing in a serial or parallel manner.

 Q54: Explain the difference between mapping parameter and mapping variable.

A54: Value that can change during the session’s execution is called mapping variable. The end value of the variable is stored by Informatica server upon completion and reused when the session is restarted. On the other hand values that do not change during the session’s execution are called mapping parameters. Mapping parameters and their usage is defined within the mapping procedure. The values of these parameters are assigned before starting the session.

Q55: Explain the use of aggregator cache file.

A55: The aggregator transformations are handled in blocks of instructions during each run. The aggregator performs the function of storing the intermediate values which are encountered in the local buffer memory. If extra memory is required for the processing, the aggregator provides additional cache files for storing the transformation values.

Q56: Explain lookup transformation.

A56: Transformations which have access to RDBMS based datasets are called lookup transformations. The Informatica server quickens access by using the look up tables to point at specific table data or views from the database. Final data is retrieved by matching the look up condition for all look up ports issued during transformation.

Q57: Explain stand alone sessions. In case of failure how can they be recovered?

A57: A stand alone session is a session not attached to any batch. The pmcmd command or server manager interface can be used for recovering a standalone session from a failed run. For every session the server manager possesses the server request menu. You need to highlight the session that you want recovered and select server requests then stop and start it. The pmcmd command can be similarly used.

Q58: How can repository reports be accessed without SQL or other transformations?

A58: Reports about the repository are generated by the metadata reporter. It is a web app and doesn’t need SQL queries or other transformations.

Q59: Is fact a denormalized or a normalized table?

A59: Fact table is a denormalized table. It contains foreign keys against the numerous primary key attributes of the dimension tables.

Q60: Differentiate between router and filter transformations.

A60: Filter transformations check a single condition. Records which fail to meet the condition are discarded. Router transformation checks for many conditions. Rows not meeting the conditions are categorized separately.
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