Rank Processor
Use rank functions (rank, dense_rank, percent_rank, ntile, row_number) while configuring the Rank processor.
Rank Processor computes the rank of a value in a group of values. The result is one plus the number of rows preceding or equal to the current row in the ordering of the partition.
dense_rank() - Computes the rank of a value in a group of values. The result is one plus the previously assigned rank value. Unlike the function rank, dense_rank will not produce gaps in the rankings.
percent_rank() - Computes the percentage ranking of a value in a group of values.
ntile(n) - Divides the rows for each window partition into n buckets ranging from 1 to at most n.
row_number() - Assigns a unique, sequential number to each row, starting with one, according to the ordering of rows within the window partition.
Rank Processor Configuration
To add a Rank processor to your pipeline, drag the processor onto the pipeline canvas and right-click on it to configure.
| Field | Description |
|---|---|
| Rank Function Type | This drop down has five options (rank, dense_rank, percent_rank, ntile, row_number). |
| Input Fields | This is the list of columns that you want to calculate the rank for. |
| Output Fields | This is the list of columns in which masked value of selected column will be stored. New Column name can be added to this field (This column will be added to dataset.) |
| Group by | This radio button enables grouping the of the input fields. |
| Grouping Fields | This is the list of columns that you want to be grouped. You can select multiple columns from input field for them masking simultaneously. |
Click on NEXT button. Enter the notes in the space provided.
Click on the SAVE button for saving the configuration details.
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