[jira] [Created] (SPARK-9072) Parquet : Writing data to S3 very slowly

["Murtaza Kanchwala (JIRA)" <ji...@apache.org>]

Murtaza Kanchwala created SPARK-9072:
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             Summary: Parquet : Writing data to S3 very slowly
                 Key: SPARK-9072
                 URL: https://issues.apache.org/jira/browse/SPARK-9072
             Project: Spark
          Issue Type: Sub-task
          Components: SQL
            Reporter: Murtaza Kanchwala
            Priority: Critical
             Fix For: 1.5.0


I've created spark programs through which I am converting the normal textfile to parquet and csv to S3.

There is around 8 TB of data and I need to compress it into lower for further processing on Amazon EMR

Results : 

1) Text -> CSV took 1.2 hrs to transform 8 TB of data without any problems successfully to S3.

2) Text -> Parquet Job completed in the same time (i.e. 1.2 hrs) but still after the Job completion it is spilling/writing the data separately to S3 which is making it slower and in starvation.

Input : s3n://<SameBucket>/input
Output : s3n://<SameBucket>/output/parquet

Lets say If I have around 10K files then it is taking 1000 files / 20 min to write back in S3.

Note : 
Also I found that program is creating temp folder on S3 output location, And in Logs I've seen S3ReadDelays.

Can anyone tell me what am I doing wrong? or is there anything I need to add so that the Spark App cant create temp folder on S3 and do write ups fast from EMR to S3 just like saveAsTextFile. Thanks






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