Joseph K. Bradley created SPARK-3728:
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Summary: RandomForest: Learn models too large to store in memory
Key: SPARK-3728
URL: https://issues.apache.org/jira/browse/SPARK-3728
Project: Spark
Issue Type: Improvement
Components: MLlib
Reporter: Joseph K. Bradley
Proposal: Write trees to disk as they are learned.
RandomForest currently uses a FIFO queue, which means training all trees at
once via breadth-first search. Using a FILO queue would encourage the code to
finish one tree before moving on to new ones. This would allow the code to
write trees to disk as they are learned.
Note: It would also be possible to write nodes to disk as they are learned
using a FIFO queue, once the example--node mapping is cached [JIRA]. The
[Sequoia Forest package]() does this. However, it could be useful to learn
trees progressively, so that future functionality such as early stopping
(training fewer trees than expected) could be supported.
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