FuzzyMatch
Spark Gem
Use the FuzzyMatch gem to identify non-identical duplicates in your data.
Input and Output
| DataFrame | Description |
|---|---|
| in0 | Includes the DataFrame on which duplicates will be checked. |
| out | Generates one record per fuzzy match. |
Parameters
| Parameter | Tab | Description |
|---|---|---|
| Merge/Purge Mode | Configuration | Records are either compared from a single source (Purge) or across multiple sources (Merge). |
| Source ID Field | Configuration | Unique identifier for each source when using Merge mode. |
| Record ID Field | Configuration | Unique identifier for each record. |
| Match threshold percentage | Configuration | If the match score is less than the threshold, the record does not qualify as a match. |
| Include similarity score | Configuration | Checkbox to enable for an additional output column that includes the similarity score. |
| Field name | Match Fields | Name of the column that you want to check for duplicates. |
| Match function | Match Fields | The method that generates the similarity score. |
Example
One common use case for the FuzzyMatch gem is to match similarly spelled names. This can be useful for identifying accidentally misspelled names.
Create a FuzzyMatch gem and use the customer_id as the Record ID. Then, add a match field for the first_name column.
Run the gem and see that the output includes the Record IDs of the records with fuzzy matches.
Join the output with the original dataset to view the matched names.
