我们正在使用 Spark CSV 阅读器读取要转换为 DataFrame 的 csv 文件,并且我们正在运行该作业yarn-client
,它在本地模式下工作正常。
我们正在提交 spark 作业edge node
。
但是当我们将文件放在本地文件路径而不是 HDFS 中时,我们会收到文件未找到异常。
代码:
sqlContext.read.format("com.databricks.spark.csv")
.option("header", "true").option("inferSchema", "true")
.load("file:/filepath/file.csv")
我们也尝试过file:///
,但仍然遇到同样的错误。
错误日志:
2016-12-24 16:05:40,044 WARN [task-result-getter-0] scheduler.TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, hklvadcnc06.hk.standardchartered.com): java.io.FileNotFoundException: File file:/shared/sample1.csv does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:609)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:822)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:599)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSInputChecker.<init>(ChecksumFileSystem.java:140)
at org.apache.hadoop.fs.ChecksumFileSystem.open(ChecksumFileSystem.java:341)
at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:767)
at org.apache.hadoop.mapred.LineRecordReader.<init>(LineRecordReader.java:109)
at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:241)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:212)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:101)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)