I am trying to read data from S3 bucket using Pyspark on Jupyterhub using the code below
config = pyspark.SparkConf().setAll([("spark.executor.instances", "4")\
,('spark.executor.memory', '50g')\
, ('spark.executor.cores', '4')\
, ('spark.cores.max', '48')\
, ('spark.driver.memory','50g')\
, ("spark.driver.maxResultSize", "35g")
, ("spark.jars", "/home/aws_jars/hadoop-aws-2.7.3.jar,/home/aws_jars/aws-java-sdk-1.11.30.jar")])
spark = SparkSession.builder.config(conf=config).getOrCreate()
# connect to AWS with boto3
sess = boto3.Session(region_name='us-east-1')
credentials = sess.get_credentials()
credentials = credentials.get_frozen_credentials()
sc=spark.sparkContext
hadoop_conf=sc._jsc.hadoopConfiguration()
hadoop_conf.set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
hadoop_conf.set("fs.s3a.awsAccessKeyId", credentials.access_key)
hadoop_conf.set("fs.s3a.awsSecretAccessKey", credentials.secret_key)
df = spark.read.load('s3a://ml-bucket/spark-project/data/D2021117_BI_1982.txt',format ="csv",inferSchema="true")
df.show()
Here is the exception that I got.
Py4JJavaError: An error occurred while calling o63.load.
: java.lang.NoClassDefFoundError: com/amazonaws/AmazonServiceException
Here are the versions on the server
Hadoop 2.7.3
Python 3.6.12
Spark Version 3.1.2
openjdk version 1.8.0_312
I tried troubleshooting it with different hadoop-aws and aws-jdk versions. But, I am not able to make it work. I am also able to read it using Pandas but not with Pysaprk. Am I missing something here?
Update
Here is the complete error log after I replaced aws-java-sdk-1.11.30 with aws-java-sdk-bundle-1.11.901
Py4JJavaError: An error occurred while calling o59.load.
: java.lang.IllegalArgumentException
at java.util.concurrent.ThreadPoolExecutor.<init>(ThreadPoolExecutor.java:1314)
at java.util.concurrent.ThreadPoolExecutor.<init>(ThreadPoolExecutor.java:1237)
at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:280)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3303)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3352)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3320)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:479)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)
at org.apache.spark.sql.execution.streaming.FileStreamSink$.hasMetadata(FileStreamSink.scala:46)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:377)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:325)
at org.apache.spark.sql.DataFrameReader.$anonfun$load$3(DataFrameReader.scala:307)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:307)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:239)
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)