Suriya S.

Hi Sonal, I’ve been working on Singl3.3 and ran tests using 10k records. Initially, the output seemed consistent across consecutive runs. However, when I repeated the process the following day, I noticed variations in the scores, and some records that were previously marked as duplicates appeared as unique. I tried running the same process again the next day and observed further inconsistencies in the output. It seems the results are not consistent across runs, may i know, which is causing concern.

Hi Sonal, "I’m currently working with Zingg version 3.3 and have successfully created a new model using my own dataset. I encountered a scenario where two records appear to represent the same individual: Data 1: Name: C.V. RAVISEKAR VASUDEVAN PAN: APPER5089R Mobile: 9876543210 Data 2: Name: RAVISEKAR CV PAN: APPER5089R Mobile: 9876543210 Despite the strong similarities—especially in PAN and mobile number—the model has classified them as unique records instead of a match. I defined the config in the same order (Name, PAN, Mobile) using the fuzzy match type. Would Zingg work in this manner, or am I missing something?" This is a scenario we had previously discussed at the help desk. Unfortunately, the issue still remains unresolved on my end. I’ve tried adding similar data as training samples, but these types of scenarios are still being classified as unique. We also attempted creating a new model using different datasets, but these records continue to be treated as unique cases. Would Zingg work in this manner, or am I missing something?"

Hi all, May I know how many nodes are required to process 9 million records in approximately 8 hours on a local Spark cluster with 8 cores and 256 GB RAM? Can Someone please help here.