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https://issues.apache.org/jira/browse/SPARK-17588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15504350#comment-15504350
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Sean Owen commented on SPARK-17588:
-----------------------------------

I meant more like, what is the size of the input? is it sparse?

> 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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