pyspark on emr with boto3, copy of s3 object result with Futures timed out after [100000 milliseconds] - pyspark

Question

I have a pyspark application that will transform csv to parquet and before this happen I'm copying some S3 object from a bucket to another.
pyspark with spark 2.4, emr 5.27, maximizeResourceAllocation set to true
I have various csv files size, from 80kb to 500mb.
Nonetheless, my EMR cluster (it doesn't fail on local with spark-submit) fails at 70% completion on a file that is 166mb (a previous at 480mb succeeded).
The job is simple:
def organise_adwords_csv():
s3 = boto3.resource('s3')
bucket = s3.Bucket(S3_ORIGIN_RAW_BUCKET)
for obj in bucket.objects.filter(Prefix=S3_ORIGIN_ADWORDS_RAW + "/"):
key = obj.key
copy_source = {
'Bucket': S3_ORIGIN_RAW_BUCKET,
'Key': key
}
key_tab = obj.key.split("/")
if len(key_tab) < 5:
print("continuing from length", obj)
continue
file_name = ''.join(key_tab[len(key_tab)-1:len(key_tab)])
if file_name == '':
print("continuing", obj)
continue
table = file_name.split("_")[1].replace("-", "_")
new_path = "{0}/{1}/{2}".format(S3_DESTINATION_ORDERED_ADWORDS_RAW_PATH, table, file_name)
print("new_path", new_path) <- the last print will end here
try:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
print("copy done")
except Exception as e:
print(e)
print("an exception occured while copying")
if __name__=='__main__':
organise_adwords_csv()
print("copy Final done") <- never printed
spark = SparkSession.builder.appName("adwords_transform") \
...
but, in the stdout, no errors / exception are showing.
In stderr logs:
19/10/09 16:16:57 INFO ApplicationMaster: Waiting for spark context initialization...
19/10/09 16:18:37 ERROR ApplicationMaster: Uncaught exception:
java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
19/10/09 16:18:37 INFO ApplicationMaster: Final app status: FAILED, exitCode: 13, (reason: Uncaught exception: java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
)
19/10/09 16:18:37 INFO ShutdownHookManager: Shutdown hook called
I'm completely blind, I don't understand what is failing / why.
How can I figure that out? On local it works like a charm (but super slow of course)
Edit:
After many tries I can confirm that the function:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
make the EMR cluster timeout, even tho it processed 80% of the files already.
Does anyone have a recommendation about this?

Answer 1

s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
This will fail for any source object larger than 5 GB. please use multipart upload in AWS. See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#multipartupload