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Currently, if a job fails due to memory issues, a DS must manually override the enrollments query to do downsampling. This is complex, time-consuming, and error-prone. It would be helpful if support could be built for easy downsampling. Something like:
For posterity: the solution for this issue was to add the config option sample_size, which is an integer 1-100 representing the sample rate (e.g., sample_size = 20 would use a 20% sample).
Currently, if a job fails due to memory issues, a DS must manually override the enrollments query to do downsampling. This is complex, time-consuming, and error-prone. It would be helpful if support could be built for easy downsampling. Something like:
to explicitly use
0 <= sample_id <= 10
or
to implicitly use
sample_id <= 75
┆Issue is synchronized with this Jira Task
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