Hi,
I tried to read a csv file from amazon s3, but I get the following
exception which I have no clue how to solve this. I tried both spark 1.3.1
and 1.2.1, but no success. Any idea how to solve this is appreciated.
best,
/Shahab
the code:
val hadoopConf=sc.hadoopConfiguration;
hadoopConf.set("fs.s3.impl",
"org.apache.hadoop.fs.s3native.NativeS3FileSystem")
hadoopConf.set("fs.s3.awsAccessKeyId", aws_access_key_id)
hadoopConf.set("fs.s3.awsSecretAccessKey", aws_secret_access_key)
val csv = sc.textFile(""s3n://mybucket/info.csv") // original file
val data = csv.map(line => line.split(",").map(elem => elem.trim)) //lines
in rows
Here is the exception I faced:
Exception in thread "main" java.lang.NoClassDefFoundError:
org/jets3t/service/ServiceException
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.createDefaultStore(
NativeS3FileSystem.java:280)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.initialize(
NativeS3FileSystem.java:270)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2397)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:89)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2431)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2413)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:368)
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:304)
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.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.SparkContext.runJob(SparkContext.scala:1512)
at org.apache.spark.rdd.RDD.count(RDD.scala:1006)
