我已经升级到Apache Spark 1.5.1,但我不确定是否会导致它。我在spark-submit中有我的访问键,它一直有用。
Exception in thread "main" java.lang.NoSuchMethodError: org.jets3t.service.impl.rest.httpclient.RestS3Service.<init>(Lorg/jets3t/service/security/AWSCredentials;)V
SQLContext sqlContext = new SQLContext(sc);
DataFrame df = sqlContext.read()
.format("com.databricks.spark.csv")
.option("inferSchema", "true")
.load("s3n://ossem-replication/gdelt_data/event_data/" + args[0]);
df.write()
.format("com.databricks.spark.csv")
.save("/user/spark/ossem_data/gdelt/" + args[0]);
以下更多错误。有一个类不包含该方法,因此意味着依赖项不匹配。似乎jets3t不包含RestS3Service方法。(Lorg / jets3t / service / security / AWSCredentials;)V有人可以向我解释一下吗?
Exception in thread "main" java.lang.NoSuchMethodError: org.jets3t.service.impl.rest.httpclient.RestS3Service.<init>(Lorg/jets3t/service/security/AWSCredentials;)V
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.initialize(Jets3tNativeFileSystemStore.java:60)
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:497)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at org.apache.hadoop.fs.s3native.$Proxy24.initialize(Unknown Source)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.initialize(NativeS3FileSystem.java:272)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2596)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:256)
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:207)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1277)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)
at org.apache.spark.rdd.RDD.take(RDD.scala:1272)
at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1312)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)
at org.apache.spark.rdd.RDD.first(RDD.scala:1311)
at com.databricks.spark.csv.CsvRelation.firstLine$lzycompute(CsvRelation.scala:101)
at com.databricks.spark.csv.CsvRelation.firstLine(CsvRelation.scala:99)
at com.databricks.spark.csv.CsvRelation.inferSchema(CsvRelation.scala:82)
at com.databricks.spark.csv.CsvRelation.<init>(CsvRelation.scala:42)
at com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:74)
at com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:39)
at com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:27)
at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:125)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:114)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:104)
at com.bah.ossem.spark.GdeltSpark.main(GdeltSpark.java:20)
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:497)
答案 0 :(得分:6)
我有同样的问题,但使用Spark 1.6,我使用的是Scala而不是Java。出现此错误的原因是Spark Core具有Hadoop Client 2.2版,而我使用的Spark集群安装版本为1.6。我必须进行以下更改才能使其正常工作。
将hadoop客户端依赖项更改为2.6(我正在使用的Hadoop版本)
"org.apache.hadoop" % "hadoop-client" % "2.6.0",
在我的Spark胖jar中包含hadoop-aws库,因为1.6中的Hadoop库不再包含此依赖项
"org.apache.hadoop" % "hadoop-aws" % "2.6.0",
将AWS密钥和密钥导出为环境变量。
在SparkConf中指定以下Hadoop配置
val sparkContext = new SparkContext(sparkConf)
val hadoopConf = sparkContext.hadoopConfiguration
hadoopConf.set("fs.s3.impl", "org.apache.hadoop.fs.s3native.NativeS3FileSystem")
hadoopConf.set("fs.s3.awsAccessKeyId", sys.env.getOrElse("AWS_ACCESS_KEY_ID", ""))
hadoopConf.set("fs.s3.awsSecretAccessKey", sys.env.getOrElse("AWS_SECRET_ACCESS_KEY", ""))