On Wed, Nov 29, 2017 at 8:52 AM Aristeu Gil Alves Jr <aristeu.jr@xxxxxxxxx> wrote:
> Does s3 or swifta (for hadoop or spark) have integrated data-layout APIs for
> local processing data as have cephfs hadoop plugin?
>
With s3 and swift you won't have data locality as it was designed for
public cloud.
We recommend disable locality based scheduling in Hadoop when running
with those connectors.
There is on going work on to optimize those connectors to work with
object storage.
Hadoop community works on the s3a connector.
There is also https://github.com/SparkTC/stocator which is a swift
based connector IBM wrote for their cloud.Assuming this cases, how would be a mapreduce process without data locality?How the processors get the data? Still there's the need to split the data, no?Doesn't it severely impact the performance of big files (not just the network)?
Given that you already have your data in CephFS (and have been using it successfully for two years!), I'd try using its Hadoop plugin and seeing if it suits your needs. Trying a less-supported plugin is a lot easier than rolling out a new storage stack! :)
-Greg
_______________________________________________ ceph-users mailing list ceph-users@xxxxxxxxxxxxxx http://lists.ceph.com/listinfo.cgi/ceph-users-ceph.com
