Seth Hendrickson created SPARK-19313:
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Summary: GaussianMixture throws cryptic error when number of
features is too high
Key: SPARK-19313
URL: https://issues.apache.org/jira/browse/SPARK-19313
Project: Spark
Issue Type: Bug
Components: ML, MLlib
Reporter: Seth Hendrickson
Priority: Minor
The following fails
{code}
val df = Seq(
Vectors.sparse(46400, Array(0, 4), Array(3.0, 8.0)),
Vectors.sparse(46400, Array(1, 5), Array(4.0, 9.0)))
.map(Tuple1.apply).toDF("features")
val gm = new GaussianMixture()
gm.fit(df)
{code}
It fails because GMMs allocate an array of size {{numFeatures * numFeatures}}
and in this case we'll get integer overflow. We should limit the number of
features appropriately.
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