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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/04/22 15:51:13 UTC
[jira] [Assigned] (SPARK-14843) Error while encoding:
java.lang.ClassCastException with LibSVMRelation
[ https://issues.apache.org/jira/browse/SPARK-14843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-14843:
------------------------------------
Assignee: (was: Apache Spark)
> Error while encoding: java.lang.ClassCastException with LibSVMRelation
> ----------------------------------------------------------------------
>
> Key: SPARK-14843
> URL: https://issues.apache.org/jira/browse/SPARK-14843
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib, SQL
> Reporter: Nick Pentreath
>
> While trying to run some example ML linear regression code, I came across the following. In fact this error occurs when doing {{./bin/run-example ml.LinearRegressionWithElasticNetExample}}.
> {code}
> scala> import org.apache.spark.ml.regression.LinearRegression
> import org.apache.spark.ml.regression.LinearRegression
> scala> import org.apache.spark.mllib.linalg.Vector
> import org.apache.spark.mllib.linalg.Vector
> scala> import org.apache.spark.sql.Row
> import org.apache.spark.sql.Row
> scala> val data = sqlContext.read.format("libsvm").load("data/mllib/sample_linear_regression_data.txt")
> data: org.apache.spark.sql.DataFrame = [label: double, features: vector]
> scala> val model = lr.fit(data)
> {code}
> Stack trace:
> {code}
> Driver stacktrace:
> ...
> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1276)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:357)
> at org.apache.spark.rdd.RDD.take(RDD.scala:1250)
> at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1290)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:357)
> at org.apache.spark.rdd.RDD.first(RDD.scala:1289)
> at org.apache.spark.ml.regression.LinearRegression.train(LinearRegression.scala:165)
> at org.apache.spark.ml.regression.LinearRegression.train(LinearRegression.scala:69)
> at org.apache.spark.ml.Predictor.fit(Predictor.scala:90)
> ... 48 elided
> Caused by: java.lang.RuntimeException: Error while encoding: java.lang.ClassCastException: java.lang.Double cannot be cast to org.apache.spark.mllib.linalg.Vector
> if (input[0, org.apache.spark.sql.Row].isNullAt) null else newInstance(class org.apache.spark.mllib.linalg.VectorUDT).serialize
> :- input[0, org.apache.spark.sql.Row].isNullAt
> : :- input[0, org.apache.spark.sql.Row]
> : +- 0
> :- null
> +- newInstance(class org.apache.spark.mllib.linalg.VectorUDT).serialize
> :- newInstance(class org.apache.spark.mllib.linalg.VectorUDT)
> +- input[0, org.apache.spark.sql.Row].get
> :- input[0, org.apache.spark.sql.Row]
> +- 0
> at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:230)
> at org.apache.spark.ml.source.libsvm.DefaultSource$$anonfun$buildReader$1$$anonfun$8.apply(LibSVMRelation.scala:209)
> at org.apache.spark.ml.source.libsvm.DefaultSource$$anonfun$buildReader$1$$anonfun$8.apply(LibSVMRelation.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:90)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegen$$anonfun$7$$anon$1.hasNext(WholeStageCodegen.scala:362)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:254)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.ClassCastException: java.lang.Double cannot be cast to org.apache.spark.mllib.linalg.Vector
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:227)
> ... 17 more
> {code}
> The error is triggered by L163 of {{LinearRegression}}:
> {code}
> val numFeatures = dataset.select(col($(featuresCol))).limit(1).rdd.map {
> case Row(features: Vector) => features.size
> }.first()
> {code}
> Using the above example, the following works:
> {code}
> scala> data.select("label").rdd.map { case Row(d: Double) => d }.first
> res49: Double = -9.490009878824548
> {code}
> But this triggers the exception:
> {code}
> scala> data.select("features").rdd.map { case Row(d: Vector) => d }.first
> 16/04/22 11:25:20 ERROR Executor: Exception in task 0.0 in stage 87.0 (TID 98)
> java.lang.RuntimeException: Error while encoding: java.lang.ClassCastException: java.lang.Double cannot be cast to org.apache.spark.mllib.linalg.Vector
> ...
> {code}
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