[ 
https://issues.apache.org/jira/browse/SPARK-17588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

sai pavan kumar chitti updated SPARK-17588:
-------------------------------------------
    Description: 
hi, 

i am getting java.lang.AssertionError error when running glm, using gaussian 
link function, on a dataset with 109 columns and  81318461 rows
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.

  was:
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.


> 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
>              Labels: newbie
>
> hi, 
> i am getting java.lang.AssertionError error when running glm, using gaussian 
> link function, on a dataset with 109 columns and  81318461 rows
> 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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