What is the use of rank transformation?
What is the use of rank transformation?
Rank is an active and connected transformation that performs the filtering of data based on the group and ranks. The rank transformation also provides the feature to do ranking based on groups. The rank transformation has an output port, and it is used to assign a rank to the rows.
Why filter is an active transformation?
A transformation can be active or passive. For example, the Filter transformation is active because it removes rows that do not meet the filter condition. A passive transformation does not change the number of rows that pass through the transformation.
Why aggregator transformation is active in Informatica?
Aggregator transformation is an active transformation is used to performs aggregate calculations like sum, average, etc. For example, if you want to calculate the sum of salaries of all employees department wise, we can use the Aggregator Transformation. For this, we require a new column to store this sum.
Why source qualifier is active transformation in Informatica?
The source qualifier transformation is active and connected. It is used to represent the rows that the integrations service reads when it runs a session. We need to join the source qualifier transformation with the relational or flat file definition in a mapping.
What type of a transformation is the rank transformation?
Rank transformation is an active transformation, as it affects the number of output rows. The rank transformation has an output port by which it assigns a rank to the rows.
Which is the minimum transformation required in mapping?
Whenever we add a relational source or a flat file to a mapping, a source qualifier transformation is required. When we add a source to a mapping, source qualifier transformation is added automatically.
How is active transformation determined?
When you configure the Lookup transformation to return a single row, the Lookup transformation is a passive transformation. When you configure the Lookup transformation to return multiple rows, the Lookup transformation is an active transformation. Retrieve a value from the lookup table based on a value in the source.
Is rank transformation active or passive?
Does Union transformation remove duplicates in Informatica?
The Union transformation does not remove duplicate rows. To remove Duplicate rows, we must add another transformation such as a Router or Filter Transformation.
What is the default Behaviour of aggregator transformation?
By default, the aggregator transformation treats null values as NULL in aggregate functions. But we can specify to treat null values in aggregate functions as NULL or zero.
Which is the minimum transformation required in a mapping?
source qualifier transformation
Whenever we add a relational source or a flat file to a mapping, a source qualifier transformation is required. When we add a source to a mapping, source qualifier transformation is added automatically.
What is AMG sq in Informatica?
The source qualifier transformation is an active,connected transformation used to represent the rows that the integrations service reads when it runs a session. The source qualifier transformation converts the source data types to the Informatica native data types.
How is the rank transformation in Informatica active?
Rank transformation is an active transformation, as it affects the number of output rows. The rank transformation has an output port by which it assigns a rank to the rows.
Which is the function of the rank transformation?
Rank transformation is an active and connected transformation. The rank transformation is used to select the top or bottom rank of data. The rank transformation is used to select the smallest or largest numeric/string values. The integration service caches the input data and then performs the rank calculations.
How are filter transformations and ETL-Informatica similar?
It is similar to filter transformation. The only difference is, filter transformation drops the data that do not meet the condition whereas router has an option to capture the data that do not meet the condition. It is useful to test multiple conditions. It has input, output and default groups.
How are joiner transformations used in ETL-Informatica?
The Joiner transformation supports the following types of joins: Normal join discards all the rows of data from the master and detail source that do not match, based on the condition. Master outer join discards all the unmatched rows from the master source and keeps all the rows from the detail source and the matching rows from the master source.