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From cs user <acldstk...@gmail.com>
Subject Re: Best way to migrate PB scale data between live cluster?
Date Tue, 12 Apr 2016 10:14:37 GMT
Hi there,

At some point in the near future we are also going to require exactly what
you describe. We had hope to use distcp.

You mentioned:

1. it do not handle data delete

distcp has a -delete flag which says -

"Delete the files existing in the dst but not in src"

Does this not help with handling deleted data?

I believe there is an issue if data is removed during a distcp run, so for
example at the start of the run it captures all the files it needs to sync.
If some files are deleted during the run, it may lead to errors. Is there a
way to ignore these errors and have distcp retry on the next run?

I'd be interested in how you manage to eventually accomplish the syncing
between the two clusters, because we also need to solve the very same
problem :-)

Perhaps others on the mailing list have experience with this?


Thanks!


On Tue, Apr 12, 2016 at 10:44 AM, raymond <rgbbones@163.com> wrote:

> Hi
>
>
> We have a hadoop cluster with several PB data. and we need to migrate it
> to a new cluster across datacenter for larger volume capability.
> We estimate that the data copy itself might took near a month to finish.
> So we are seeking for a sound solution. The requirement is as below:
> 1. we cannot bring down the old cluster for such a long time ( of course),
> and a couple of hours is acceptable.
> 2. we need to mirror the data, it means that we not only need to copy the
> new data, but also need to delete the deleted data happened during the
> migration period.
> 3. we don’t have much space left on the old cluster, say 30% room.
>
>
> regarding distcp, although it might be the easiest way , but
>
>
> 1. it do not handle data delete
> 2. it handle newly appended file by compare file size and overwrite it (
> well , it might waste a lot of bandwidth )
> 3. error handling base on file is triffle.
> 4 load control is difficult ( we still have heavy work load on old
> cluster) you can just try to split your work manually and make it small
> enough to achieve the flow control goal.
>
>
> In one word, for a long time mirror work. It won't do well by itself.
>
>
> The are some possible works might need to be done :
>
>
> We can:
>
>
>
>    1. Do  some wrap work around distcp to make it works better. ( say
>    error handling, check results. Extra code for sync deleted files etc. )
>    2. Utilize Snapshot mechanisms for better identify files need to be
>    copied and deleted. Or renamed.
>
>
> Or
>
>
>
>    1. Forget about distcp. Use FSIMAGE and editlog as a change history
>    source, and write our own code to replay the operation. Handle each file
>    one by one. ( better per file error handling could be achieved), but this
>    might need a lot of dev works.
>
>
>
>
> Btw. The closest thing I could found is facebook migration 30PB hive
> warehouse:
>
>
>
> https://www.facebook.com/notes/facebook-engineering/moving-an-elephant-large-scale-hadoop-data-migration-at-facebook/10150246275318920/
>
>
> They modifiy the distcp to do a initial bulk load (to better handling
> large files and very small files, for load balance I guess.) , and a
> replication system (not much detail on this part) to mirror the changes.
>
>
> But it is not clear that how they handle those shortcomings of distcp I
> mentioned above. And do they utilize snapshot mechanism.
>
>
> So , does anyone have experience on this kind of work? What do you think
> might be the best approaching for our case? Is there any ready works been
> done that we can utilize? Is there any works have been done around snapshot
> mechanism to easy data migration?
>

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