On 2 Aug 2017, at 10:34, Riccardo Ferrari <email@example.com> wrote:
I am working on a pyspark streaming job (ver 2.2.0) and I need to enable checkpointing. At high level my python script goes like this:
hadoopConfiguration().set('fs. s3a.access.key',....)sparkContext._jsc. hadoopConfiguration().set('fs. s3a.secret.key',....)
def doJob(self):ssc = StreamingContext.getOrCreate('
<S3-location>', <function to create ssc>)
and I run it:
myJob = StreamingJob(...)myJob.doJob()
The problem is that StreamingContext.getOrCreate is not able to have access to hadoop configuration configured in the constructor and fails to load from checkpoint with
AmazonClientException: Unable to load AWS credentials from any provider in the chain"
If I export AWS credentials to the system ENV before starting the script it works!
Spark magically copies the env vars over for you when you launch a job
I see the Scala version has an option to provide the hadoop configuration that is not available in python
I don't have the whole Hadoop, just Spark, so I don't really want to configure hadoop's xmls and such
when you set up the context, as in spark-defaults.conf
key=access keyspark.hadoop.fs.s3a.secret. key=secret key
Reminder: Do keep your secret key a secret, avoid checking it in to any form of revision control.