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Posted to issues@spark.apache.org by "sai pavan kumar chitti (JIRA)" <ji...@apache.org> on 2016/09/20 20:44:21 UTC
[jira] [Closed] (SPARK-17588) java.lang.AssertionError: assertion
failed: lapack.dppsv returned 105. when running glm using gaussian link
function.
[ https://issues.apache.org/jira/browse/SPARK-17588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
sai pavan kumar chitti closed SPARK-17588.
------------------------------------------
Resolution: Fixed
> 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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