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https://issues.apache.org/jira/browse/SPARK-17588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15587790#comment-15587790
]
Prasann modi commented on SPARK-17588:
--------------------------------------
I'm getting same issue.I'm using sparkr in Rstudio(Os - windows) trying to
build glm model(binomial) but getting error and while executing that code it is
taking so much time.Please suggest me what to do...
R Code:
# Set Spark Home
Sys.setenv(SPARK_HOME="C:/spark/spark-2.0.0-bin-hadoop2.7")
# set library path
.libPaths(c(file.path(Sys.getenv("SPARK_HOME"),"R","lib"), .libPaths()))
Sys.setenv(JAVA_HOME="C:/Program Files/Java/jdk1.7.0_71")
# loading SparkR library
library(SparkR)
library(rJava)
sc <- sparkR.session(enableHiveSupport = FALSE,master = "local[*]",appName =
"SparkR-Modi",sparkConfig =
list(spark.sql.warehouse.dir="file:///c:/tmp/spark-warehouse"))
sqlContext <- sparkRSQL.init(sc)
spdf <- read.df(sqlContext, "C:/Users/prasann/Desktop/V/bigdata11.csv", source
= "com.databricks.spark.csv", header = "true")
showDF(spdf)
# glm model
md <- glm(NP_OfferCurrentResponse ~., family = "binomial", data = spdf)
Error :
> md <- glm(NP_OfferCurrentResponse ~., family = "binomial", data = spdf)
Error in invokeJava(isStatic = TRUE, className, methodName, ...) :
java.lang.AssertionError: assertion failed: lapack.dppsv returned 226.
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$FamilyAndLink.initialize(GeneralizedLinearRegression.scala:340)
at
org.apache.spark.ml.regression.GeneralizedLinearRegression.train(GeneralizedLinearRegression.scala:275)
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.c
> 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: Improvement
> Components: ML, SparkR
> Affects Versions: 2.0.0
> Reporter: sai pavan kumar chitti
> Assignee: Sean Owen
> Priority: Minor
>
> 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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