Spark + s3 - error - java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem not found

Question

I have a spark ec2 cluster where I am submitting a pyspark program from a Zeppelin notebook. I have loaded the hadoop-aws-2.7.3.jar and aws-java-sdk-1.11.179.jar and place them in the /opt/spark/jars directory of the spark instances. I get a java.lang.NoClassDefFoundError: com/amazonaws/AmazonServiceException

Why is spark not seeing the jars? Do I have to have to jars in all the slaves and specify a spark-defaults.conf for the master and slaves? Is there something that needs to be configured in zeppelin to recognize the new jar files?

I have placed jar files /opt/spark/jars on the spark master. I have created a spark-defaults.conf and added the lines

spark.hadoop.fs.s3a.access.key     [ACCESS KEY]
spark.hadoop.fs.s3a.secret.key     [SECRET KEY]
spark.hadoop.fs.s3a.impl           org.apache.hadoop.fs.s3a.S3AFileSystem
spark.driver.extraClassPath        /opt/spark/jars/hadoop-aws-2.7.3.jar:/opt/spark/jars/aws-java-sdk-1.11.179.jar

I have zeppelin interpreter sending a spark submit to the spark master.

I have also placed the jars in the /opt/spark/jars in the slaves too but did not create a spark-deafults.conf.

%spark.pyspark

#importing necessary libaries
from pyspark import SparkContext
from pyspark.sql import SparkSession
from pyspark.sql.functions import *
from pyspark.sql.types import StringType
from pyspark import SQLContext
from itertools import islice
from pyspark.sql.functions import col

# add aws credentials
sc._jsc.hadoopConfiguration().set("fs.s3n.awsAccessKeyId", "[ACCESS KEY]")
sc._jsc.hadoopConfiguration().set("fs.s3n.awsSecretAccessKey", "[SECRET KEY]")
sc._jsc.hadoopConfiguration().set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")

#creating the context
sqlContext = SQLContext(sc)

#reading the first csv file and store it in an RDD
rdd1= sc.textFile("s3a://filepath/baby-names.csv").map(lambda line: line.split(","))

#removing the first row as it contains the header
rdd1 = rdd1.mapPartitionsWithIndex(
lambda idx, it: islice(it, 1, None) if idx == 0 else it
)

#converting the RDD into a dataframe
df1 = rdd1.toDF(['year','name', 'percent', 'sex'])

#print the dataframe
df1.show()

Error thrown:

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 7, 10.11.93.90, executor 1): java.lang.NoClassDefFoundError: com/amazonaws/AmazonServiceException
    at java.lang.Class.forName0(Native Method)
    at java.lang.Class.forName(Class.java:348)
    at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:2134)
    at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2099)
    at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2193)
    at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2654)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2667)
    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.LineRecordReader.<init>(LineRecordReader.java:108)
    at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
    at org.apache.spark.rdd.HadoopRDD$$anon$1.liftedTree1$1(HadoopRDD.scala:267)
    at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:266)
    at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:224)
    at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:95)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ClassNotFoundException: com.amazonaws.AmazonServiceException
    at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    ... 34 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
    at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:153)
    at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
    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:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoClassDefFoundError: com/amazonaws/AmazonServiceException
    at java.lang.Class.forName0(Native Method)
    at java.lang.Class.forName(Class.java:348)
    at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:2134)
    at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2099)
    at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2193)
    at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2654)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2667)
    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.LineRecordReader.<init>(LineRecordReader.java:108)
    at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
    at org.apache.spark.rdd.HadoopRDD$$anon$1.liftedTree1$1(HadoopRDD.scala:267)
    at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:266)
    at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:224)
    at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:95)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more
Caused by: java.lang.ClassNotFoundException: com.amazonaws.AmazonServiceException
    at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    ... 34 more

Answer 1

I was able to address the above to make sure I had the correct versions of the hadoop aws jar per the version of spark hadoop that I was running, downloading the correct version of aws-java-sdk, and lastly downloading the dependency jets3t library

In the /opt/spark/jars

sudo wget https://repo1.maven.org/maven2/com/amazonaws/aws-java-sdk/1.11.30/aws-java-sdk-1.11.30.jar
sudo wget https://repo1.maven.org/maven2/org/apache/hadoop/hadoop-aws/2.7.3/hadoop-aws-2.7.3.jar
sudo wget https://repo1.maven.org/maven2/net/java/dev/jets3t/jets3t/0.9.4/jets3t-0.9.4.jar

Testing it out

scala> sc.hadoopConfiguration.set("fs.s3n.awsAccessKeyId", [ACCESS KEY ID])
scala> sc.hadoopConfiguration.set("fs.s3n.awsSecretAccessKey", [SECRET ACCESS KEY] )
scala> val myRDD = sc.textFile("s3n://adp-px/baby-names.csv")
scala> myRDD.count()
res2: Long = 49

Answer 2

If S3 access is by assume_role from local cluster then below worked for me.

import boto3
import pyspark as pyspark
from pyspark import SparkContext

session = boto3.session.Session(profile_name='profile_name')
sts_connection = session.client('sts')
response = sts_connection.assume_role(RoleArn='arn:aws:iam:::role/role_name', RoleSessionName='role_name',DurationSeconds=3600)
credentials = response['Credentials']

conf = pyspark.SparkConf()

conf.set('spark.jars.packages', 'org.apache.hadoop:hadoop-aws:3.2.0')  //crosscheck the version. 

sc = SparkContext(conf=conf)
sc._jsc.hadoopConfiguration().set('fs.s3a.aws.credentials.provider', 'org.apache.hadoop.fs.s3a.TemporaryAWSCredentialsProvider')
sc._jsc.hadoopConfiguration().set('fs.s3a.access.key', credentials['AccessKeyId'])
sc._jsc.hadoopConfiguration().set('fs.s3a.secret.key', credentials['SecretAccessKey'])
sc._jsc.hadoopConfiguration().set('fs.s3a.session.token', credentials['SessionToken'])
url = str('s3a://data.csv')

l1 = sc.textFile(url).collect()
for each in l1:
    print(str(each))
    break

keep below proper version of class files also in $SPARK_HOME/jars

1. jets3t
2. aws-java-sdk
3. hadoop-aws

I prefer to delete unwanted jars from ~/.ivy2/jars

Answer 3

Add the following to this file hadoop/etc/hadoop/core-site.xml

<property>
  <name>fs.s3.awsAccessKeyId</name>
  <value>***</value>
</property>
<property>
  <name>fs.s3.awsSecretAccessKey</name>
  <value>***</value>
</property>

Inside the Hadoop installation directory, find aws jars, for MAC installation directory is /usr/local/Cellar/hadoop/

find . -type f -name "*aws*"

sudo cp hadoop/share/hadoop/tools/lib/aws-java-sdk-1.7.4.jar hadoop/share/hadoop/common/lib/
sudo cp hadoop/share/hadoop/tools/lib/hadoop-aws-2.7.5.jar hadoop/share/hadoop/common/lib/

Credit

Answer 4

Following worked for me

My system config:

Ubuntu 16.04.6 LTS python3.7.7 openjdk version 1.8.0_252 spark-2.4.5-bin-hadoop2.7

1. Configure PYSPARK_PYTHON path: add following line in $spark_home/conf/spark-env.sh

   export PYSPARK_PYTHON= python_env_path/bin/python

2. Start pyspark

   pyspark --packages com.amazonaws:aws-java-sdk-pom:1.11.760,org.apache.hadoop:hadoop-aws:2.7.0 --conf spark.hadoop.fs.s3a.endpoint=s3.us-west-2.amazonaws.com

   com.amazonaws:aws-java-sdk-pom:1.11.760 : depends on jdk version hadoop:hadoop-aws:2.7.0: depends on your hadoop version s3.us-west-2.amazonaws.com: depends on your s3 location

3.Read data from s3

df2=spark.read.parquet("s3a://s3location_file_path")

Credits

Answer 5

If nothing works in the above then do a cat and grep for the missing class. High possibility that the Jar is corrupted. For example, if you get class AmazonServiceException not found, then do a grep where the jar is already present as shown below.

grep "AmazonServiceException" *.jar