Spark read s3 using sc.textFile(“s3a://bucket/filePath”). java.lang.NoSuchMethodError: com.amazonaws.services.s3.transfer.TransferManager

9
votes

I have add blew jars to spark/jars path.

  • hadoop-aws-2.7.3.jar
  • aws-java-sdk-s3-1.11.126.jar
  • aws-java-sdk-core-1.11.126.jar
  • spark-2.1.0

In spark-shell

scala> sc.hadoopConfiguration.set("fs.s3a.access.key", "***")

scala> sc.hadoopConfiguration.set("fs.s3a.secret.key", "***")

scala> val f = sc.textFile("s3a://bucket/README.md")

scala> f.count

java.lang.NoSuchMethodError: com.amazonaws.services.s3.transfer.TransferManager.(Lcom/amazonaws/services/s3/AmazonS3;Ljava/util/concurrent/ThreadPoolExecutor;)V at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:287) at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669) at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94) at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703) at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373) at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295) at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:258) at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229) at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315) at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:202)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958) at org.apache.spark.rdd.RDD.count(RDD.scala:1157) ... 48 elided

  1. "java.lang.NoSuchMethodError: com.amazonaws.services.s3.transfer.TransferManager" is raised by mismatched jar? (hadoop-aws, aws-java-sdk)

  2. To access data stored in Amazon S3 from Spark applications should use Hadoop file APIs. So is hadoop-aws.jar contains the Hadoop file APIS or must run hadoop env ?

1
apache-sparkamazon-s3

1 Answers

23
votes

Mismatched JARs; the AWS SDK is pretty brittle across versions.

Hadoop S3A code is in hadoop-aws JAR; also needs hadoop-common. Hadoop 2.7 is built against AWS S3 SDK 1.10.6. (*updated: No, it's 1.7.4. The move to 1.10.6 went into Hadoop 2.8)HADOOP-12269

You must use that version. If you want to use The 1.11 JARs then you will need to check out the hadoop source tree and build branch-2 yourself. The good news: that uses the shaded AWS SDK so its versions of jackson and joda time don't break things. Oh, and if you check out spark master, and build with the -Phadoop-cloud profile, it pulls the right stuff in to set Spark's dependencies up right.

Update: Oct 1 2017: Hadoop 2.9.0-alpha and 3.0-beta-1 use 1.11.199; assume the shipping versions will be that or more recent.