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What is a Joiner Transformation and why it is an Active one? Answer: A Joiner is an Active and Connected transformation used to join two source data streams coming from same or heterogeneous databases or files. The Joiner transformation joins sources with at least one matching column. The Joiner transformation uses a condition that matches one or more pairs of columns between the two sources. In the Joiner transformation, we must configure the transformation properties namely Join Condition, Join Type and optionally Sorted Input option to improve Integration Service performance. The join condition contains ports from both input sources that must match for the Integration Service to join two rows. Depending on the join condition and the type of join selected, the Integration Service either adds the row to the result set or discards the row. Because of this reason, the number of rows in Joiner output may not be equal to the number of rows in Joiner Input. This is why ...
Describe the approach for the requirement. Suppose the input is: The desired output is: Answer: Use an Expression transformation:- Expression Transformation Interview Question ( Part - 2) Keep in mind the string length of the variable and output ports. CUME function is used to calculate the cumulative amount based on the argument of the cumulative function. This means, if we call CUME with argument 1, e.g. CUME(1); then on the first call it will re-turn 1; on the second call, it will return 2; on the third call, it will return 3 and so on. Since Informatica process data row by row, this means that when the first row is processed CUME(1) will return 1; for the next row, it will return 2 and so on. How can we implement aggregation operation without using an Aggregator Transformation in Informatica? Answer: We will use the very basic concept of the Expression Transformation, that at a time we can access the pr...
A Filter transformation is an Active and Connected transformation that can filter rows in a mapping. Only the rows that meet the Filter Condition pass through the Filter transformation to the next transformation in the pipeline. TRUE and FALSE are the implicit return values from any filter condition we set. If the filter condition evaluates to NULL, the row is assumed to be FALSE. The numeric equivalent of FALSE is zero (0) and any non-zero value is the equivalent of TRUE. Filter Transformation and why it is an Active one? As an ACTIVE transformation, the Filter transformation may change the number of rows passed through it. A filter condition returns TRUE or FALSE for each row that passes through the transformation, depending on whether a row meets the specified condition. Only rows that return TRUE pass through this transformation. Discarded rows do not appear in the session log or reject files.
Source Qualifier Transformations Filter Vs Filter Transformation SQ Source Filter Source Qualifier transformation filters rows when read from a source. Source Qualifier transformation can only filter rows from relational sources. Source Qualifier limits the row set extracted from a source. Source Qualifier reduces the number of rows used throughout the mapping and hence it provides better performance. The filter condition in the Source Qualifier transformation only uses standard SQL as it runs in the database. Filter Transformation Filter transformation filters rows from within a mapping Filter transformation filters rows coming from any type of source system in the map-ping level. Filter transformation limits the row set sent to a target. To maximize session performance, include the Filter transformation as close to the sources in the mapping as possible to filter out unwanted data early in the flow of data from sources to targets. Filter Transformation can define a condition...
What is an Expression Transform? Answer: Expression is a Passive connected transformation used to calculate values in a single row before you write to the target. We can use the Expression transformation to perform any non-aggregate calculations. We can al-so use the Expression transformation to test conditional statements before you output the results to target tables or other transformations. For example, we might need to adjust employee salaries, concatenate first and last names, or convert strings to numbers. Expression Transformation Interview Question How many types of ports are there in Expression transform? Answer: There are three types of ports- INPUT, OUTPUT, and VARIABLE What is the execution order of the ports in an expression? Answer: All ports are executed TOP TO BOTTOM in a serial physical ordering fashion, but they are done in the following groups: All input ports are pushed values first. Then all variables are executed (top to bottom ...
Aggregator Transformation In Informatica Scenarios Suppose in our Source Table we have data as given below Aggregator Transformation In Informatica Scenarios We want to load our Target Table as Aggregator Transformation In Informatica Scenarios Describe your approach. Answer: Here our scenario is to convert many rows to one row, and the transformation which will help us to achieve this is Aggregator. Our Mapping will look like this: Aggregator Transformation In Informatica Scenarios We will sort the source data based on STUDENT_NAME ascending followed by SUBJECT ascending. Aggregator Transformation In Informatica Scenarios Now based on STUDENT_NAME in GROUP BY clause the following output subject columns are populated as MATHS: MAX( MARKS, SUBJECT = ’Maths’ ) LIFE_SC: MAX( MARKS, SUBJECT = ’Life Science’ ) PHY_SC: MAX( MARKS, SUBJECT = ’Physical Science’ ) Aggregator Transformation In Informatica Scenarios Scena...