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Increased sample size makes train very slow
See original GitHub issueAfter increasing sample size (as in https://github.com/dedupeio/dedupe/commit/da29f24823c4066b81f558fb8794452a04a8b15a), training has become extremely slow; in particular it gets stuck at:
comparison_count = self.comparisons(self.total_cover, compound_length)
I stopped execution after over 20 minutes (getting no result) while the entire run previously took about 30 seconds (with the exact same data and previous sample sizes (200 for RecordLink, 900 for Dedupe)). The data has about 2000 rows for the messy data and 6000 rows for the canonical data; I am linking on three fields (address, name, and area code all declared as Strings)
Issue Analytics
- State:
- Created 6 years ago
- Comments:9 (8 by maintainers)
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I had the same problem, I solved by replacing the values NULL of my data base with empty fields
could you check this again?