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From JG Perrin <jper...@lumeris.com>
Subject RE: CSV write to S3 failing silently with partial completion
Date Thu, 07 Sep 2017 09:59:07 GMT
Are you assuming that all partitions are of equal size? Did you try with more partitions (like
repartitioning)? Does the error always happen with the last (or smaller) file? If you are
sending to redshift, why not use the JDBC driver?

-----Original Message-----
From: abbim [mailto:abbim@amazon.com] 
Sent: Thursday, September 07, 2017 1:02 AM
To: user@spark.apache.org
Subject: CSV write to S3 failing silently with partial completion

Hi all,
My team has been experiencing a recurring unpredictable bug where only a partial write to
CSV in S3 on one partition of our Dataset is performed. For example, in a Dataset of 10 partitions
written to CSV in S3, we might see 9 of the partitions as 2.8 GB in size, but one of them
as 1.6 GB. However, the job does not exit with an error code.

This becomes problematic in the following ways:
1. When we copy the data to Redshift, we get a bad decrypt error on the partial file, suggesting
that the failure occurred at a weird byte in the file. 
2. We lose data - sometimes as much as 10%.

We don't see this problem with parquet format, which we also use, but moving all of our data
to parquet is not currently feasible. We're using the Java API with Spark 2.2 and Amazon EMR
5.8, code is a simple as this:
df.write().csv("s3://some-bucket/some_location"). We're experiencing the issue 1-3x/week on
a daily job and are unable to reliably reproduce the problem. 

Any thoughts on why we might be seeing this and how to resolve?
Thanks in advance.



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