7.00.02 - SQL-MapReduce Call - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
September 2017
Content Type
Programming Reference
User Guide
Publication ID
English (United States)
Last Update

The objective is to correctly match the information in Input to the applicant from Input and thus accurately identify the applicant’s credit score. Assume a default threshold of 0.5. A higher threshold means that the matching accuracy is higher. Look for exact matches (NominalMatchColumns) to the email address and allow approximate matches (FuzzyMatchColumns) for lastname, firstname, zipcode, city and department columns, with different match metrics and match weights.

SELECT * FROM IdentityMatch (
  ON applicant_reference AS a PARTITION BY ANY
  ON applicant_external AS b DIMENSION
  IDColumn ('a.id: b.id')
  NominalMatchColumns ('a.email: b.email')
  FuzzyMatchColumns ('a.lastname: b.lastname, JARO-WINKLER, 3',
                     'a.firstname: b.firstname, JARO-WINKLER, 2',
                     'a.zipcode: b.zipcode, JD, 2',
                     'a.city: b.city, LD, 2',
                     'a.department: b.department, COSINE, 1')
  Accumulate ('a.firstname','a.lastname' ,'b.lastname', 'a.email',
              'b.email','a.zipcode', 'b.zipcode', 'a.department',
  Threshold (0.5)
) ORDER BY "a.id", score DESC;