You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Amy Koh (JIRA)" <ji...@apache.org> on 2018/12/31 16:09:00 UTC
[jira] [Created] (SPARK-26511) java.lang.ClassCastException error
when loading Spark MLlib model from parquet file
Amy Koh created SPARK-26511:
-------------------------------
Summary: java.lang.ClassCastException error when loading Spark MLlib model from parquet file
Key: SPARK-26511
URL: https://issues.apache.org/jira/browse/SPARK-26511
Project: Spark
Issue Type: Bug
Components: MLlib
Affects Versions: 2.4.0
Reporter: Amy Koh
When I tried to load a decision tree model from a parquet file, the following error is thrown.
{code:bash}
Py4JJavaError: An error occurred while calling z:org.apache.spark.mllib.tree.model.DecisionTreeModel.load. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, localhost, executor driver): java.lang.ClassCastException: class java.lang.Double cannot be cast to class java.lang.Integer (java.lang.Double and java.lang.Integer are in module java.base of loader 'bootstrap') at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:101) at org.apache.spark.sql.Row$class.getInt(Row.scala:223) at org.apache.spark.sql.catalyst.expressions.GenericRow.getInt(rows.scala:165) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$SplitData$.apply(DecisionTreeModel.scala:171) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$NodeData$.apply(DecisionTreeModel.scala:195) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$$anonfun$9.apply(DecisionTreeModel.scala:247) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$$anonfun$9.apply(DecisionTreeModel.scala:247) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.Task.run(Task.scala:108) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) at java.base/java.lang.Thread.run(Thread.java:834) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2087) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936) 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:362) at org.apache.spark.rdd.RDD.collect(RDD.scala:935) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$.constructTrees(DecisionTreeModel.scala:262) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$.load(DecisionTreeModel.scala:249) at org.apache.spark.mllib.tree.model.DecisionTreeModel$.load(DecisionTreeModel.scala:326) at org.apache.spark.mllib.tree.model.DecisionTreeModel.load(DecisionTreeModel.scala) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.base/java.lang.reflect.Method.invoke(Method.java:566) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:280) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:214) at java.base/java.lang.Thread.run(Thread.java:834) Caused by: java.lang.ClassCastException: class java.lang.Double cannot be cast to class java.lang.Integer (java.lang.Double and java.lang.Integer are in module java.base of loader 'bootstrap') at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:101) at org.apache.spark.sql.Row$class.getInt(Row.scala:223) at org.apache.spark.sql.catalyst.expressions.GenericRow.getInt(rows.scala:165) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$SplitData$.apply(DecisionTreeModel.scala:171) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$NodeData$.apply(DecisionTreeModel.scala:195) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$$anonfun$9.apply(DecisionTreeModel.scala:247) at org.apache.spark.mllib.tree.model.DecisionTreeModel$SaveLoadV1_0$$anonfun$9.apply(DecisionTreeModel.scala:247) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.Task.run(Task.scala:108) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) ... 1 more
{code}
Reproduction steps as follow with reproduction files attached:
{code:python}
from pyspark.mllib.tree import DecisionTree, DecisionTreeModel
from pyspark.mllib.util import MLUtils
from pyspark import SparkContext
sc = SparkContext()
model = DecisionTreeModel.load(spark, <modelFilePath>)
{code}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org