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Windows local mode support #4

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hanfernandes opened this issue Jan 30, 2019 · 5 comments
Open

Windows local mode support #4

hanfernandes opened this issue Jan 30, 2019 · 5 comments

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@hanfernandes
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I run the code

library(sparkxgb)
library(sparklyr)
library(dplyr)

sc <- spark_connect(master = "local")
iris_tbl <- sdf_copy_to(sc, iris)

xgb_model <- xgboost_classifier(
  iris_tbl, 
  Species ~ .,
  objective = "multi:softprob",
  num_class = 3,
  num_round = 50, 
  max_depth = 4
)

and the following error appeared

Console Error ml.dmlc.xgboost4j.java.XGBoostError: XGBoostModel training failed at ml.dmlc.xgboost4j.scala.spark.XGBoost$.ml$dmlc$xgboost4j$scala$spark$XGBoost$$postTrackerReturnProcessing(XGBoost.scala:364) at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4.apply(XGBoost.scala:294) at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4.apply(XGBoost.scala:256) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.immutable.List.foreach(List.scala:381) at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) at scala.collection.immutable.List.map(List.scala:285) at ml.dmlc.xgboost4j.scala.spark.XGBoost$.trainDistributed(XGBoost.scala:255) at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:200) at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:48) at org.apache.spark.ml.Predictor.fit(Predictor.scala:118) at org.apache.spark.ml.Predictor.fit(Predictor.scala:82) at org.apache.spark.ml.Pipeline$$anonfun$fit$2.apply(Pipeline.scala:153) at org.apache.spark.ml.Pipeline$$anonfun$fit$2.apply(Pipeline.scala:149) 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.scala:44) at scala.collection.SeqViewLike$AbstractTransformed.foreach(SeqViewLike.scala:37) at org.apache.spark.ml.Pipeline.fit(Pipeline.scala:149) at org.apache.spark.ml.Pipeline.fit(Pipeline.scala:96) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source) at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source) at java.lang.reflect.Method.invoke(Unknown Source) at sparklyr.Invoke.invoke(invoke.scala:139) at sparklyr.StreamHandler.handleMethodCall(stream.scala:123) at sparklyr.StreamHandler.read(stream.scala:66) at sparklyr.BackendHandler.channelRead0(handler.scala:51) at sparklyr.BackendHandler.channelRead0(handler.scala:4) at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340) at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340) at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:310) at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:284) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348) at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:340) at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1359) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:348) at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:935) at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:138) at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:645) at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:580) at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:497) at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:459) at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858) at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138) at java.lang.Thread.run(Unknown Source)
Spark_log(sc) at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337) at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335) at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1092) at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1083) at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1018) at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1083) at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:809) at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335) at org.apache.spark.rdd.RDD.iterator(RDD.scala:286) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:109) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) at java.lang.Thread.run(Unknown Source) Driver stacktrace: 19/01/30 11:12:37 INFO DAGScheduler: Job 10 failed: foreachPartition at XGBoost.scala:287, took 0,026189 s 19/01/30 11:12:37 ERROR RabitTracker: Uncaught exception thrown by worker: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, most recent failure: Lost task 0.0 in stage 15.0 (TID 15, localhost, executor driver): java.lang.NoClassDefFoundError: Could not initialize class ml.dmlc.xgboost4j.java.XGBoostJNI at ml.dmlc.xgboost4j.java.DMatrix.(DMatrix.java:53) at ml.dmlc.xgboost4j.scala.DMatrix.(DMatrix.scala:42) at ml.dmlc.xgboost4j.scala.spark.Watches$.buildWatches(XGBoost.scala:436) at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4$$anonfun$12.apply(XGBoost.scala:276) at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4$$anonfun$12.apply(XGBoost.scala:275) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337) at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335) at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1092) at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1083) at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1018) at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1083) at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:809) at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335) at org.apache.spark.rdd.RDD.iterator(RDD.scala:286) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:109) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source) at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source) at java.lang.Thread.run(Unknown Source)

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:929)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:927)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4$$anon$1.run(XGBoost.scala:287)
Caused by: java.lang.NoClassDefFoundError: Could not initialize class ml.dmlc.xgboost4j.java.XGBoostJNI
at ml.dmlc.xgboost4j.java.DMatrix.(DMatrix.java:53)
at ml.dmlc.xgboost4j.scala.DMatrix.(DMatrix.scala:42)
at ml.dmlc.xgboost4j.scala.spark.Watches$.buildWatches(XGBoost.scala:436)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4$$anonfun$12.apply(XGBoost.scala:276)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4$$anonfun$12.apply(XGBoost.scala:275)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:800)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1092)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1083)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1018)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1083)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:809)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
19/01/30 11:12:42 INFO RabitTracker$TrackerProcessLogger: Tracker Process ends with exit code 1
19/01/30 11:12:42 INFO RabitTracker: Tracker Process ends with exit code 1
19/01/30 11:12:42 INFO XGBoostSpark: Rabit returns with exit code 1

Anybody know?
@kevinykuo
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What's your setup? I've seen that but have trouble getting a consistent reprex.

@hanfernandes
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R version 3.5.2 (2018-12-20)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

Matrix products: default

locale:
[1] LC_COLLATE=Portuguese_Brazil.1252 LC_CTYPE=Portuguese_Brazil.1252 LC_MONETARY=Portuguese_Brazil.1252 LC_NUMERIC=C
[5] LC_TIME=Portuguese_Brazil.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] sparklyr_0.9.9000 sparkxgb_0.1.0 tidyr_0.8.2 bindrcpp_0.2.2 data.table_1.11.8 dplyr_0.7.8 Neuropack_0.1.0

loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 dbplyr_1.2.2 later_0.7.5 pillar_1.3.1 compiler_3.5.2 bindr_0.1.1 r2d3_0.2.3 base64enc_0.1-3 tools_3.5.2
[10] digest_0.6.18 bit_1.1-14 jsonlite_1.6 tibble_1.4.2 pkgconfig_2.0.2 rlang_0.3.0.1 shiny_1.2.0 cli_1.0.1 DBI_1.0.0
[19] rstudioapi_0.8 parallel_3.5.2 yaml_2.2.0 withr_2.1.2 httr_1.4.0 rappdirs_0.3.1 generics_0.0.2 htmlwidgets_1.3 rprojroot_1.3-2
[28] bit64_0.9-7 tidyselect_0.2.5 glue_1.3.0 forge_0.1.9002 R6_2.3.0 fansi_0.4.0 purrr_0.2.5 magrittr_1.5 promises_1.0.1
[37] backports_1.1.3 htmltools_0.3.6 assertthat_0.2.0 xtable_1.8-3 mime_0.6 httpuv_1.4.5.1 config_0.3 utf8_1.1.4 openssl_1.1
[46] lazyeval_0.2.1 crayon_1.3.4

@kevinykuo
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Possibly related: dmlc/xgboost#2780

@The-Dub The-Dub mentioned this issue Feb 22, 2019
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@kevinykuo
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kevinykuo commented Feb 25, 2019 •
edited

Turns out the published jars don't support windows, so we'd have to work around it. See the note at https://xgboost.readthedocs.io/en/latest/jvm/#access-snapshot-version. We could try to download from criteo-forks/xgboost-jars on the fly.

@kevinykuo kevinykuo changed the title XGBoostModel training failed Windows local mode support Feb 25, 2019
@CooperChen453
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Turns out the published jars don't support windows, so we'd have to work around it. See the note at https://xgboost.readthedocs.io/en/latest/jvm/#access-snapshot-version. We could try to download from criteo-forks/xgboost-jars on the fly.

So it means that we can not run xgboost with sparklyr on windows?

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@kevinykuo @hanfernandes @CooperChen453