Question

我正在尝试将MlLib用于我的colloborative过滤。

当我在Apache Spark 1.0.0中运行时，我在Scala程序中遇到以下错误。

   14/07/15 16:16:31 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    14/07/15 16:16:31 WARN LoadSnappy: Snappy native library not loaded
    14/07/15 16:16:31 INFO FileInputFormat: Total input paths to process : 1
    14/07/15 16:16:38 WARN TaskSetManager: Lost TID 10 (task 80.0:0)
    14/07/15 16:16:38 WARN TaskSetManager: Loss was due to java.lang.UnsatisfiedLinkError
    java.lang.UnsatisfiedLinkError: org.jblas.NativeBlas.dposv(CII[DII[DII)I
        at org.jblas.NativeBlas.dposv(Native Method)
        at org.jblas.SimpleBlas.posv(SimpleBlas.java:369)
        at org.jblas.Solve.solvePositive(Solve.java:68)
        at org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateBlock$2.apply(ALS.scala:522)
        at org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateBlock$2.apply(ALS.scala:509)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
        at scala.collection.mutable.ArrayOps$ofInt.foreach(ArrayOps.scala:156)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
        at scala.collection.mutable.ArrayOps$ofInt.map(ArrayOps.scala:156)
        at org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$updateBlock(ALS.scala:509)
        at org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateFeatures$2.apply(ALS.scala:445)
        at org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateFeatures$2.apply(ALS.scala:444)
        at org.apache.spark.rdd.MappedValuesRDD$$anonfun$compute$1.apply(MappedValuesRDD.scala:31)
        at org.apache.spark.rdd.MappedValuesRDD$$anonfun$compute$1.apply(MappedValuesRDD.scala:31)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
        at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$4.apply(CoGroupedRDD.scala:156)
        at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$4.apply(CoGroupedRDD.scala:154)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:154)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.Task.run(Task.scala:51)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:744)
    14/07/15 16:16:38 ERROR TaskSchedulerImpl: Lost executor 0 on maroki.office.mkechinov.ru: Uncaught exception
    14/07/15 16:16:38 WARN TaskSetManager: Lost TID 12 (task 80.0:0)
    14/07/15 16:16:42 WARN TaskSetManager: Lost TID 18 (task 80.0:1)
    14/07/15 16:16:42 WARN TaskSetManager: Loss was due to fetch failure from null
    14/07/15 16:16:42 WARN TaskSetManager: Loss was due to fetch failure from null
    14/07/15 16:16:43 WARN TaskSetManager: Lost TID 25 (task 80.1:0)
    14/07/15 16:16:43 WARN TaskSetManager: Loss was due to java.lang.UnsatisfiedLinkError

如何解决此错误？

Answer 1

Spark documentation明确提到MLLib使用本地库，这些库需要存在于节点上。（也就是它没有安装火花）

MLlib使用jblas线性代数库，它本身依赖于本机Fortran例程。如果节点上尚不存在gfortran运行时库，则可能需要安装它。如果MLlib无法自动检测到这些库，则会抛出链接错误。

您必须确保所有节点上都存在 libgfortran 库。

用于debian / ubuntu： sudo apt-get install libgfortran3

用于使用： sudo yum install gcc-gfortran

Apache Spark - MlLib - 协作过滤

1 个答案: