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Simple and Distributed Machine Learning
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[BUG] Unable to run LightGBMClassifier on large dataset #2105

Open dpdrmj opened 1 year ago

dpdrmj commented 1 year ago

SynapseML version

com.microsoft.azure:synapseml_2.12:0.11.3

System information

Describe the problem

while trying to use LightGBMClassifier, the program always crashes with connection refused error. Same code works completely fine if the data size is smaller. My train data has ~500million rows. And there is no way that this is happening because of memory issues are I'm using 7 executors and each one has 256GB memory. I tried changing some params as well, I tried without executionMode='streaming', tried using useBarrierExecutionMode=True as well but it doesn't work. Looks like this is a frequent issue which people face with large data size? I have not found any solution to this problem. Does the following give any hint on the problem? 

  model = model.fit(train_data)
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/ml/base.py", line 161, in fit
  File "~/.ivy2/jars/com.microsoft.azure_synapseml-lightgbm_2.12-0.11.3.jar/synapse/ml/lightgbm/LightGBMClassifier.py", line 2148, in _fit
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/ml/wrapper.py", line 336, in _fit_java
  File "PATH_TO_spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in deco
  File "PATH_TO_spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o38.fit.

Code to reproduce issue

    model = LightGBMClassifier(
        baggingFraction=0.8,
        executionMode='streaming',
        baggingFreq=5,
        boostingType='gbdt',
        categoricalSlotNames=categorical_features,
        featureFraction=0.8,
        featuresCol="features",
        featuresShapCol='',
        labelCol="has_install",
        lambdaL1=3.0,
        lambdaL2=100.0,
        learningRate=0.05,
        maxDepth=7,
        metric='binary_logloss,auc',
        minDataInLeaf=20,
        minSumHessianInLeaf=5.0,
        numIterations=200,
        numLeaves=63,
        objective='binary',
        parallelism='data_parallel',
        predictionCol='prediction',
        probabilityCol='probability',
        rawPredictionCol='rawPrediction',
        verbosity=2,
        weightCol=None,
    )

    model = model.fit(train_data)

Other info / logs

2023-10-23 13:31:41,655 ERROR scheduler.TaskSetManager: Task 2 in stage 3.0 failed 4 times; aborting job
2023-10-23 13:31:41,705 ERROR lightgbm.LightGBMClassifier: {"protocolVersion":"0.0.1","method":"fit","libraryName":"SynapseML","errorMessage":"org.apache.spark.SparkException","errorType":"org.apache.spark.SparkException","className":"class com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier","libraryVersion":"0.11.3","modelUid":"LightGBMClassifier_9f52737c29e2"}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 3.0 failed 4 times, most recent failure: Lost task 2.3 in stage 3.0 (TID 13) (IP.xx.x.xx executor 1): java.net.ConnectException: Connection refused (Connection refused)
    at java.net.PlainSocketImpl.socketConnect(Native Method)
    at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
    at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
    at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
    at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
    at java.net.Socket.connect(Socket.java:607)
    at java.net.Socket.connect(Socket.java:556)
    at java.net.Socket.<init>(Socket.java:452)
    at java.net.Socket.<init>(Socket.java:229)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
    at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
    at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:201)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:131)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:750)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2289)
    at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:1029)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:410)
    at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
    at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2971)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704)
    at org.apache.spark.sql.Dataset.collect(Dataset.scala:2971)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executePartitionTasks(LightGBMBase.scala:623)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executeTraining(LightGBMBase.scala:598)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.trainOneDataBatch(LightGBMBase.scala:446)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$train$2(LightGBMBase.scala:62)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb(SynapseMLLogging.scala:147)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb$(SynapseMLLogging.scala:144)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logVerb(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit(SynapseMLLogging.scala:137)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit$(SynapseMLLogging.scala:136)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logFit(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train(LightGBMBase.scala:64)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train$(LightGBMBase.scala:36)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
    at org.apache.spark.ml.Predictor.fit(Predictor.scala:151)
    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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.lang.Thread.run(Thread.java:750)
Caused by: java.net.ConnectException: Connection refused (Connection refused)
    at java.net.PlainSocketImpl.socketConnect(Native Method)
    at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
    at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
    at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
    at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
    at java.net.Socket.connect(Socket.java:607)
    at java.net.Socket.connect(Socket.java:556)
    at java.net.Socket.<init>(Socket.java:452)
    at java.net.Socket.<init>(Socket.java:229)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
    at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
    at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:201)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:131)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more
Traceback (most recent call last):
  File "runner.py", line 393, in <module>
    main()
  File "runner.py", line 389, in main
    run_train_full(args, train_timestamp)
  File "runner.py", line 333, in run_train_full
    model = model.fit(train_data)
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/ml/base.py", line 161, in fit
  File "~/.ivy2/jars/com.microsoft.azure_synapseml-lightgbm_2.12-0.11.3.jar/synapse/ml/lightgbm/LightGBMClassifier.py", line 2148, in _fit
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/ml/wrapper.py", line 336, in _fit_java
  File "PATH_TO_spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
  File "PATH_TO_spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in deco
  File "PATH_TO_spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o38.fit.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 3.0 failed 4 times, most recent failure: Lost task 2.3 in stage 3.0 (TID 13) (IP.xx.xx.xx executor 1): java.net.ConnectException: Connection refused (Connection refused)
    at java.net.PlainSocketImpl.socketConnect(Native Method)
    at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
    at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
    at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
    at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
    at java.net.Socket.connect(Socket.java:607)
    at java.net.Socket.connect(Socket.java:556)
    at java.net.Socket.<init>(Socket.java:452)
    at java.net.Socket.<init>(Socket.java:229)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
    at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
    at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:201)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:131)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:750)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2450)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2399)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2398)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2398)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1156)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1156)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1156)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2638)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2580)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2569)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2224)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2245)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2264)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2289)
    at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:1029)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:410)
    at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715)
    at org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2971)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
    at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704)
    at org.apache.spark.sql.Dataset.collect(Dataset.scala:2971)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executePartitionTasks(LightGBMBase.scala:623)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.executeTraining(LightGBMBase.scala:598)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.trainOneDataBatch(LightGBMBase.scala:446)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$train$2(LightGBMBase.scala:62)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb(SynapseMLLogging.scala:147)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logVerb$(SynapseMLLogging.scala:144)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logVerb(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit(SynapseMLLogging.scala:137)
    at com.microsoft.azure.synapse.ml.logging.SynapseMLLogging.logFit$(SynapseMLLogging.scala:136)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.logFit(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train(LightGBMBase.scala:64)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.train$(LightGBMBase.scala:36)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier.train(LightGBMClassifier.scala:27)
    at org.apache.spark.ml.Predictor.fit(Predictor.scala:151)
    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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.lang.Thread.run(Thread.java:750)
Caused by: java.net.ConnectException: Connection refused (Connection refused)
    at java.net.PlainSocketImpl.socketConnect(Native Method)
    at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
    at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
    at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
    at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
    at java.net.Socket.connect(Socket.java:607)
    at java.net.Socket.connect(Socket.java:556)
    at java.net.Socket.<init>(Socket.java:452)
    at java.net.Socket.<init>(Socket.java:229)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getNetworkTopologyInfoFromDriver(NetworkManager.scala:133)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$2(NetworkManager.scala:120)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:24)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.core.utils.FaultToleranceUtils$.retryWithTimeout(FaultToleranceUtils.scala:29)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.$anonfun$getGlobalNetworkInfo$1(NetworkManager.scala:115)
    at com.microsoft.azure.synapse.ml.core.env.StreamUtilities$.using(StreamUtilities.scala:28)
    at com.microsoft.azure.synapse.ml.lightgbm.NetworkManager$.getGlobalNetworkInfo(NetworkManager.scala:111)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.initialize(BasePartitionTask.scala:197)
    at com.microsoft.azure.synapse.ml.lightgbm.BasePartitionTask.mapPartitionTask(BasePartitionTask.scala:132)
    at com.microsoft.azure.synapse.ml.lightgbm.LightGBMBase.$anonfun$executePartitionTasks$1(LightGBMBase.scala:615)
    at org.apache.spark.sql.execution.MapPartitionsExec.$anonfun$doExecute$3(objects.scala:201)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:131)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

10/23/2023 01:31:41 PM Closing down clientserver connection

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github-actions[bot] commented 1 year ago

Hey @dpdrmj :wave:! Thank you so much for reporting the issue/feature request :rotating_light:. Someone from SynapseML Team will be looking to triage this issue soon. We appreciate your patience.

dpdrmj commented 1 year ago

Hello everyone! Can someone please help here? Does anyone know what could've caused this?

hmoster commented 12 months ago

Hello everyone! Can someone please help here? Does anyone know what could've caused this?

val (trainingData, validationData) =
  if (get(validationIndicatorCol).isDefined && dataset.columns.contains(getValidationIndicatorCol))
    (df.filter(x => !x.getBoolean(x.fieldIndex(getValidationIndicatorCol))),
      Some(sc.broadcast(preprocessData(df.filter(x =>
        x.getBoolean(x.fieldIndex(getValidationIndicatorCol)))).collect())))

if the validationData is large, the "collect" use many memory. you need to set driver.memory and executor.memory very large.

hmoster commented 12 months ago

Hello everyone! Can someone please help here? Does anyone know what could've caused this?

val (trainingData, validationData) =
  if (get(validationIndicatorCol).isDefined && dataset.columns.contains(getValidationIndicatorCol))
    (df.filter(x => !x.getBoolean(x.fieldIndex(getValidationIndicatorCol))),
      Some(sc.broadcast(preprocessData(df.filter(x =>
        x.getBoolean(x.fieldIndex(getValidationIndicatorCol)))).collect())))

if the validationData is large, the "collect" use many memory. you need to set driver.memory and executor.memory very large.

set driver.memory and executor.memory very large can fix it, but it is slow, consume many resource, hope hynapseML team find a new way to rewrite the code, hope to replace the "collect".