Minor Description
Multiple places in MLlib, we broadcast a model before prediction. Since prediction may be called many times, we should store the broadcast variable in a private var so that we broadcast at most once.
I'll link subtasks for each problem case I find.
Attachments
1.
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ML model broadcasts should be stored in private vars: spark.ml tree ensembles |
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Closed | Unassigned |
2.
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ML model broadcasts should be stored in private vars: spark.ml Word2Vec |
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Closed | Unassigned |
3.
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ML model broadcasts should be stored in private vars: mllib NaiveBayes |
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Closed | Unassigned |
4.
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ML model broadcasts should be stored in private vars: mllib clustering |
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Closed | Unassigned |
5.
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ML model broadcasts should be stored in private vars: mllib IDFModel |
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Closed | Unassigned |
6.
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ML model broadcasts should be stored in private vars: mllib GeneralizedLinearModel |
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Closed | Unassigned |