【问题标题】:Exception when training data in Predictionio在 Predictionio 中训练数据时出现异常
【发布时间】:2016-07-28 11:34:18
【问题描述】:

我正在尝试部署 quick start guide 中提到的推荐引擎。 我完成了构建引擎的步骤。现在我想训练推荐引擎。我按照快速入门指南中的说明做了。 (执行pio train)。然后我得到了冗长的错误日志,我无法在此处粘贴所有内容。所以我把错误的前几行放在上面。

[INFO] [Console$] Using existing engine manifest JSON at /home/PredictionIO/PredictionIO-0.9.6/bin/MyRecommendation/manifest.json
[INFO] [Runner$] Submission command: /home/PredictionIO/PredictionIO-0.9.6/vendors/spark-1.5.1-bin-hadoop2.6/bin/spark-submit --class io.prediction.workflow.CreateWorkflow --jar/PredictionIO/PredictionIO-0.9.6/bin/MyRecommendation/target/scala-2.10/template-scala-parallel-recommendation_2.10-0.1-SNAPSHOT.jar,file:/home/PredictionIO/PredictionIO-0.9.6/bndation/target/scala-2.10/template-scala-parallel-recommendation-assembly-0.1-SNAPSHOT-deps.jar --files file:/home/PredictionIO/PredictionIO-0.9.6/conf/log4j.properties --driver/home/PredictionIO/PredictionIO-0.9.6/conf:/home/PredictionIO/PredictionIO-0.9.6/lib/postgresql-9.4-1204.jdbc41.jar:/home/PredictionIO/PredictionIO-0.9.6/lib/mysql-connector-jav file:/home/PredictionIO/PredictionIO-0.9.6/lib/pio-assembly-0.9.6.jar --engine-id qokYFr4rwibijNjabXeVSQKKFrACyrYZ --engine-version ed29b3e2074149d483aa85b6b1ea35a52dbbdb9a --et file:/home/PredictionIO/PredictionIO-0.9.6/bin/MyRecommendation/engine.json --verbosity 0 --json-extractor Both --env PIO_ENV_LOADED=1,PIO_STORAGE_REPOSITORIES_METADATA_NAME=pFS_BASEDIR=/root/.pio_store,PIO_HOME=/home/PredictionIO/PredictionIO-0.9.6,PIO_FS_ENGINESDIR=/root/.pio_store/engines,PIO_STORAGE_SOURCES_PGSQL_URL=jdbc:postgresql://localhost/pGE_REPOSITORIES_METADATA_SOURCE=PGSQL,PIO_STORAGE_REPOSITORIES_MODELDATA_SOURCE=PGSQL,PIO_STORAGE_REPOSITORIES_EVENTDATA_NAME=pio_event,PIO_STORAGE_SOURCES_PGSQL_PASSWORD=pio,PIURCES_PGSQL_TYPE=jdbc,PIO_FS_TMPDIR=/root/.pio_store/tmp,PIO_STORAGE_SOURCES_PGSQL_USERNAME=pio,PIO_STORAGE_REPOSITORIES_MODELDATA_NAME=pio_model,PIO_STORAGE_REPOSITORIES_EVENTDGSQL,PIO_CONF_DIR=/home/PredictionIO/PredictionIO-0.9.6/conf
[INFO] [Engine] Extracting datasource params...
[INFO] [WorkflowUtils$] No 'name' is found. Default empty String will be used.
[INFO] [Engine] Datasource params: (,DataSourceParams(MyApp3,None))
[INFO] [Engine] Extracting preparator params...
[INFO] [Engine] Preparator params: (,Empty)
[INFO] [Engine] Extracting serving params...
[INFO] [Engine] Serving params: (,Empty)
[WARN] [Utils] Your hostname, test-digin resolves to a loopback address: 127.0.1.1; using 192.168.2.191 instead (on interface p5p1)
[WARN] [Utils] Set SPARK_LOCAL_IP if you need to bind to another address
[INFO] [Remoting] Starting remoting
[INFO] [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@192.168.2.191:56574]
[WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id is not set.
[INFO] [Engine$] EngineWorkflow.train
[INFO] [Engine$] DataSource: duo.DataSource@6088451e
[INFO] [Engine$] Preparator: duo.Preparator@1642eeae
[INFO] [Engine$] AlgorithmList: List(duo.ALSAlgorithm@a09303)
[INFO] [Engine$] Data sanity check is on.
[INFO] [Engine$] duo.TrainingData does not support data sanity check. Skipping check.
[INFO] [Engine$] duo.PreparedData does not support data sanity check. Skipping check.
[WARN] [BLAS] Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS
[WARN] [BLAS] Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS
[WARN] [LAPACK] Failed to load implementation from: com.github.fommil.netlib.NativeSystemLAPACK
[WARN] [LAPACK] Failed to load implementation from: com.github.fommil.netlib.NativeRefLAPACK
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task serialization failed: java.lang.StackOverflowError
java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
scala.collection.immutable.$colon$colon.writeObject(List.scala:379)
sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
java.lang.reflect.Method.invoke(Method.java:498)
java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)

我可以做些什么来克服这个问题?

【问题讨论】:

  • 似乎是内存问题。您是否尝试过增加驱动程序内存限制?
  • 我使用 4 核、6GB RAM 和 Ubuntu 14.04 服务器。我在训练模型时监控服务器的性能,但它没有使用交换内存,甚至没有占用全部 6GB。所以我认为例外是别的。
  • 但是从你上面贴的异常来看确实是内存相关的。尝试使用标志 --driver-memory--executor-memory 运行 4G 或更高版本,看看是否有帮助
  • 我试过pio train -- --master spark://127.0.1.1:7077 --driver-memory 4G --executor-memory 5G 然后我得到以下错误。 [Remoting] Remoting started; listening on addresses :[akka.tcp://sparkDriver@192.168.2.191:59748] [WARN] [MetricsSystem] Using default name DAGScheduler for source because spark.app.id is not set. [ERROR] [SparkUncaughtExceptionHandler] Uncaught exception in thread Thread[appclient-registration-retry-thread,5,main]
  • 要训练的数据集有多大?您只是使用默认的火车数据吗?尝试不使用 --executor-memory 标志

标签: python apache-spark recommendation-engine data-science predictionio


【解决方案1】:

你的错误是java.lang.StackOverflowError,因为你可以减少engine.json文件中的numIterations parameter。参考this

【讨论】:

    【解决方案2】:

    我在 8GB MacOS 机器上遇到了类似的问题。将 /MyRecommendation/engine.json 中的 numIterations 参数更改为 10(以前默认为 20)为我解决了这个问题。使用 --driver-memory 和 --executor-memory 和 pio train 没有。

    【讨论】:

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