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From Simone <>
Subject Pyspark ML - Unable to finish cross validation
Date Mon, 26 Sep 2016 17:23:46 GMT

I am using pyspark to train a Logistic Regression model using cross validation with ML. My
dataset is - for testing purposes very small - like no more than 50 records for train.
On the other hand, my "feature" column has a very large size - i.e., 1500+ columns.

I am running on yarn using 3 executors, with 4gb and 4 cores each. I am using cache to store

Unfortunately, my process does not finish and hangs in doing cross validation. 

Any clues? 

Thanks guys

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