[jira] [Created] (SPARK-17588) java.lang.AssertionError: assertion failed: lapack.dppsv returned 105. when running glm using gaussian link function.

["sai pavan kumar chitti (JIRA)" <ji...@apache.org>]

sai pavan kumar chitti created SPARK-17588:
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             Summary: java.lang.AssertionError: assertion failed: lapack.dppsv returned 105. when running glm using gaussian link function.
                 Key: SPARK-17588
                 URL: https://issues.apache.org/jira/browse/SPARK-17588
             Project: Spark
          Issue Type: Question
          Components: SparkR
    Affects Versions: 2.0.0
            Reporter: sai pavan kumar chitti


hi, 

i am getting java.lang.AssertionError error when running glm, using gaussian link function, on a dataset with 109 columns and 33 
Below is the call trace. Can someone please tell me what the issues is related to and how to go about resolving it. Is it because native acceleration is not working as i am also seeing following warning messages.

WARN netlib.BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS
WARN netlib.LAPACK: Failed to load implementation from: com.github.fommil.netlib.NativeSystemLAPACK
WARN netlib.LAPACK: Failed to load implementation from: com.github.fommil.netlib.NativeRefLAPACK

16/09/17 13:08:13 ERROR r.RBackendHandler: fit on org.apache.spark.ml.r.GeneralizedLinearRegressionWrapper failed
Error in invokeJava(isStatic = TRUE, className, methodName, ...) : 
  java.lang.AssertionError: assertion failed: lapack.dppsv returned 105.
        at scala.Predef$.assert(Predef.scala:170)
        at org.apache.spark.mllib.linalg.CholeskyDecomposition$.solve(CholeskyDecomposition.scala:40)
        at org.apache.spark.ml.optim.WeightedLeastSquares.fit(WeightedLeastSquares.scala:140)
        at org.apache.spark.ml.regression.GeneralizedLinearRegression.train(GeneralizedLinearRegression.scala:265)
        at org.apache.spark.ml.regression.GeneralizedLinearRegression.train(GeneralizedLinearRegression.scala:139)
        at org.apache.spark.ml.Predictor.fit(Predictor.scala:90)
        at org.apache.spark.ml.Predictor.fit(Predictor.scala:71)
        at org.apache.spark.ml.Pipeline$$anonfun$fit$2.apply(Pipeline.scala:149)
        at org.apache.spark.ml.Pipeline$$anonfun$fit$2.apply(Pipeline.scala:145)
        at scala.collection.Iterator$class.foreach(Iterator.scala:893)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
        at scala.collection.IterableViewLike$Transformed$class.foreach(IterableViewLike.sc

thanks,
pavan.



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