> On 20 Jun 2017, at 07:49, sririshindra wrote:
>
> Is there anything similar to s3 connector for Google cloud storage?
> Since Google cloud Storage is also an object store rather than a file
> system, I imagine the same problem that the s3 connector is trying to solve
> arises with google cloud
On 19 Jun 2017, at 16:55, Ryan Blue
mailto:rb...@netflix.com.INVALID>> wrote:
I agree, the problem is that Spark is trying to be safe and avoid the direct
committer. We also modify Spark to avoid its logic. We added a property that
causes Spark to always use the output committer if the destina
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hrc file.
>
> Please add anything that I might have missed.
>
> Also please look at ryan's talk at spark summit a few days ago
> ( Imporoving Apache spark with s3 by ryan blue
> <https://www.youtube.com/watch?v=BgHrff5yAQo> )
>
>
>
>
>
>
>
;s talk at spark summit a few days ago
( Imporoving Apache spark with s3 by ryan blue
<https://www.youtube.com/watch?v=BgHrff5yAQo> )
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make spark call the PartitionedOutputCommiter even when the file already
> exists in s3?
>
>
>
>
>
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it$.org$apache$spark$
> deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
> >at
> > org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
> >at
> > org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
> >at org.apac
ation.getClass(Configuration.java:2221)
>... 28 more
>
> can you please point out my mistake.
>
> If possible can you give a working example of saving a dataframe as a
> parquet file in s3.
>
>
>
>
>
>
on.getClass(Configuration.java:2221)
... 28 more
can you please point out my mistake.
If possible can you give a working example of saving a dataframe as a
parquet file in s3.
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afety. Even
if there were, I couldn't use it, because I'm stuck on Spark 1.5 and there
doesn't seem to be a way to force the use of a given output committer.
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d. I will be
> interested in following and possibly contributing to S3Guard in the future.
>
>
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On Tue, Feb 21, 2017 at 6:15 AM, Steve Loughran wrote:
> On 21 Feb 2017, at 01:00, Ryan Blue wrote:
> > You'd have to encode the task ID in the output file name to identify files
> > to roll back in the event you need to revert a task, but if you have
> > partitioned output, you have to do a lo
ead. I will be
interested in following and possibly contributing to S3Guard in the future.
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On 21 Feb 2017, at 14:15, Steve Loughran
mailto:ste...@hortonworks.com>> wrote:
What your patch has made me realise is that I could also do a delayed-commit
copy by reading in a file, doing a multipart put to its final destination, and
again, postponing the final commit. this is something whic
any feedback on my proposed "safe" append
strategy, and 2) is there any way to circumvent the restriction on append
committers without editing and recompiling Spark? Discussion of solutions
in Spark 2.1 is also welcome.
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1 is also welcome.
>
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f solutions
in Spark 2.1 is also welcome.
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