Issues:MatchUp Object
Fuzzy Algorithms: Accurate Near , Frequency, and other Levenshtein based algorithms
Using the Accurate Near fuzzy algorithm on one or more components, running the same data set repeatedly could sporadically return different dupe counts.
This may not be apparent for a single run because the fuzzy algorithms do not return a percent difference for used algorithms, only returning a status whether the algorithm found a match between records.
We identified a new compiler issue and have also reviewed our other fuzzy algorithms which use similar computations and compiler variable initialization.
If you use any of the Fuzzy algorithms, please contact us and we will provide you with the available patch.
Large KeyFile Size effect on Memory resources
By default, MatchUp object allocates a large SetUserInfo, the unique identifier attached to built match key - 1024 bytes. See MatchUp Object Best Practices for override instructions.
Fuzzy: Legacy Matchcodes
Legacy Matchcodes, imported from previous versions, allowed a Fuzzy: Near setting of '0'. This is incompatible with the current version and can cause an error. Using the interface to edit the matchcode by changing the Distance to 1 will resolve the problem
Fuzzy: First component with set distance missing dupes
Setting a distance for a first component forces the component to use the Intersecting deduper. This may result in records within a set distance to be put in different clusters, and therefore may never get compared.
Workaround: Use an exact algorithm in the first component and keep a distance component, if required further down the component list. This will prevent missed dupes (and give you better speed benchmarks.
Resolution: This may require an advanced change to the deduper. Development is aware of the issue and is exploring options.