Austin Jordan created SPARK-32271:
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Summary: Update CrossValidator to parallelize fit method across
folds
Key: SPARK-32271
URL: https://issues.apache.org/jira/browse/SPARK-32271
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 3.1.0
Reporter: Austin Jordan
Currently, fitting a CrossValidator is only parallelized across models. This
means that a CrossValidator will only fit as quickly as the slowest-to-train
model would fit by itself.
If a 2x2x3 parameter grid is provided for 10-fold cross validation, all 12
models will begin training on the first fold. However, if 6 of these models
will train for 1 hour/fold and the other 6 will train for 3 hours/fold (e.g.
tuning number of early stopping rounds in XGBoost), the first 6 models will not
move on to the second fold until the last 6 are finished.
If fitting was parallelized across folds, the first 6 models would finish after
10 hours, freeing up cluster resources to run multiple folds for the last 6
models in parallel.
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