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Apache Spark commented on SPARK-19313: -------------------------------------- User 'sethah' has created a pull request for this issue: https://github.com/apache/spark/pull/16661 > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org