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Miao Wang commented on SPARK-20307: ----------------------------------- [~Monday0927!] "Have you also try to load the model trained in SparkR and call it in scala with pipeline.load? I currently has this problem" This might be a separate issue. The JIRA is about processing unseen labels in the test data. Actually, the underlying StringIndexer already has the logic. The right fix is that the RFormula class sets the logic in the StringIndexer. Your issue might be different or might be fixed if we set the handleInvalid logic when training the model in SparkR. Please refer to the PR. Thanks! Miao > SparkR: pass on setHandleInvalid to spark.mllib functions that use > StringIndexer > -------------------------------------------------------------------------------- > > Key: SPARK-20307 > URL: https://issues.apache.org/jira/browse/SPARK-20307 > Project: Spark > Issue Type: Improvement > Components: SparkR > Affects Versions: 2.1.0 > Reporter: Anne Rutten > Priority: Minor > > when training a model in SparkR with string variables (tested with > spark.randomForest, but i assume is valid for all spark.xx functions that > apply a StringIndexer under the hood), testing on a new dataset with factor > levels that are not in the training set will throw an "Unseen label" error. > I think this can be solved if there's a method to pass setHandleInvalid on to > the StringIndexers when calling spark.randomForest. > code snippet: > {code} > # (i've run this in Zeppelin which already has SparkR and the context loaded) > #library(SparkR) > #sparkR.session(master = "local[*]") > data = data.frame(clicked = base::sample(c(0,1),100,replace=TRUE), > someString = base::sample(c("this", "that"), > 100, replace=TRUE), stringsAsFactors=FALSE) > trainidxs = base::sample(nrow(data), nrow(data)*0.7) > traindf = as.DataFrame(data[trainidxs,]) > testdf = as.DataFrame(rbind(data[-trainidxs,],c(0,"the other"))) > rf = spark.randomForest(traindf, clicked~., type="classification", > maxDepth=10, > maxBins=41, > numTrees = 100) > predictions = predict(rf, testdf) > SparkR::collect(predictions) > {code} > stack trace: > {quote} > Error in handleErrors(returnStatus, conn): org.apache.spark.SparkException: > Job aborted due to stage failure: Task 0 in stage 607.0 failed 1 times, most > recent failure: Lost task 0.0 in stage 607.0 (TID 1581, localhost, executor > driver): org.apache.spark.SparkException: Failed to execute user defined > function($anonfun$4: (string) => double) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > 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: org.apache.spark.SparkException: Unseen label: the other. > at > org.apache.spark.ml.feature.StringIndexerModel$$anonfun$4.apply(StringIndexer.scala:170) > at > org.apache.spark.ml.feature.StringIndexerModel$$anonfun$4.apply(StringIndexer.scala:166) > ... 16 more > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958) > at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) > at org.apache.spark.rdd.RDD.collect(RDD.scala:934) > at > org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) > at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765) > at > org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2375) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2375) > at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2778) > at > org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2375) > at org.apache.spark.sql.Dataset.collect(Dataset.scala:2351) > at org.apache.spark.sql.api.r.SQLUtils$.dfToCols(SQLUtils.scala:208) > at org.apache.spark.sql.api.r.SQLUtils.dfToCols(SQLUtils.scala) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) > at > org.apache.spark.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:40) > at > io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) > at > io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) > at > io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) > at > io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) > at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) > at > io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) > at > io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) > at java > {quote} -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org