Question

尝试将一些示例数据加载到PySpark for Spark 1.3.0的RandomForests的MLlib示例中，并得到以下错误。我是MLlib的新手，不确定如何进一步检查这个错误。

代码：https://spark.apache.org/docs/1.3.0/mllib-ensembles.html

错误：

data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt")
15/10/28 15:46:27 INFO storage.MemoryStore: ensureFreeSpace(100612) called with curMem=213451, maxMem=278302556
15/10/28 15:46:27 INFO storage.MemoryStore: Block broadcast_1 stored as values in memory (estimated size 98.3 KB, free 265.1 MB)
15/10/28 15:46:28 INFO storage.MemoryStore: ensureFreeSpace(22935) called with curMem=314063, maxMem=278302556
15/10/28 15:46:28 INFO storage.MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 22.4 KB, free 265.1 MB)
15/10/28 15:46:28 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on localhost:43188 (size: 22.4 KB, free: 265.4 MB)
15/10/28 15:46:28 INFO storage.BlockManagerMaster: Updated info of block broadcast_1_piece0
15/10/28 15:46:28 INFO spark.SparkContext: Created broadcast 1 from textFile at NativeMethodAccessorImpl.java:-2
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib/spark/python/pyspark/mllib/util.py", line 120, in loadLibSVMFile
    numFeatures = parsed.map(lambda x: -1 if x[1].size == 0 else x[1][-1]).reduce(max) + 1
  File "/usr/lib/spark/python/pyspark/rdd.py", line 740, in reduce
    vals = self.mapPartitions(func).collect()
  File "/usr/lib/spark/python/pyspark/rdd.py", line 701, in collect
    bytesInJava = self._jrdd.collect().iterator()
  File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
  File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o49.collect.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: hdfs://nameservice1/user/aowens/data/mllib/sample_libsvm_data.txt
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:56)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:56)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1511)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:813)
    at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:312)
    at org.apache.spark.api.java.JavaRDD.collect(JavaRDD.scala:32)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:207)
    at java.lang.Thread.run(Thread.java:745)

Answer 1

根据您的错误日志，您提供的输入路径例如hdfs://nameservice1/user/aowens/data/mllib/sample_libsvm_data.txt不存在。

您需要确保路径存在。

将mllib示例数据加载到PySpark时出错

1 个答案: