Alex B.

this is how the metrics look for the glue job that we ran to train the model with 70k labels, it's close to 0% CPU usage all the time

thank you, scheduled some time!

Thank you, we tried tuning the labelDataSampleSize but it didn't help. We are interested in the feature of enforcing matches that you mentioned is available in the enterprise version. When could we meet to discuss our options?

thank you! we are going to try

Thanks! We tried to use the 10M labels in Glue with 64 G.8X workers but it failed after 10min:

An error occurred while calling o166.execute. Job aborted due to stage failure: ResultStage 51 (collectAsList at BlockingTreeUtil.java:52) has failed the maximum allowable number of times: 4

We tried with a much smaller set of labels, around 70k, using 32 G.4X workers and it was still running after 11h so we stopped it. Our label dataset contains multiple labels per cluster. Would that be an issue? Should we have our labels organized in pairs?

Thanks! We are exploring Zingg to replace AWS Record Matching feature