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Posted to dev@spark.apache.org by "Chawla,Sumit " <su...@gmail.com> on 2017/01/31 17:08:22 UTC

Unique Partition Id per partition

Hi All

I have a rdd, which i partition based on some key, and then can sc.runJob
for each partition.
 Inside this function, i assign each partition a unique key using following:

"%s_%s" % (id(part), int(round(time.time()))

This is to make sure that, each partition produces separate bookeeping stuff,

which can be aggregated by external system. However, I sometimes i
notice multiple

partition results pointing to same partition_id. Is this some issue due to the

way above code is serialized by Pyspark. What's the best way to define
a unique id

for each partition. I undestand that its same executor getting
multiple partitions to process,

but i would expect the above code to produce a unique id for each partition.



Regards
Sumit Chawla

Re: Unique Partition Id per partition

Posted by Michael Allman <mi...@videoamp.com>.
Hi Sumit,

Can you use http://spark.apache.org/docs/latest/api/python/pyspark.html?highlight=rdd#pyspark.RDD.mapPartitionsWithIndex <http://spark.apache.org/docs/latest/api/python/pyspark.html?highlight=rdd#pyspark.RDD.mapPartitionsWithIndex> to solve your problem?

Michael

> On Jan 31, 2017, at 9:08 AM, Chawla,Sumit <su...@gmail.com> wrote:
> 
> Hi All
> 
> I have a rdd, which i partition based on some key, and then can sc.runJob for each partition. 
>  Inside this function, i assign each partition a unique key using following:
> 
> "%s_%s" % (id(part), int(round(time.time()))
> This is to make sure that, each partition produces separate bookeeping stuff, 
> which can be aggregated by external system. However, I sometimes i notice multiple 
> partition results pointing to same partition_id. Is this some issue due to the 
> way above code is serialized by Pyspark. What's the best way to define a unique id 
> for each partition. I undestand that its same executor getting multiple partitions to process,
> but i would expect the above code to produce a unique id for each partition.
> 
> 
> Regards
> Sumit Chawla
>