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https://issues.apache.org/jira/browse/HADOOP-15016?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16238075#comment-16238075
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Xiaoyu Yao commented on HADOOP-15016:
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[~ywskycn], Thanks for the heads up. This looks like an interesting proposal.
bq. However, this has some limitations when a cluster is shared among both
end-users and some service jobs, like some ETL jobs which run under a service
account and need to issue lots of RPC calls.
Have you looking into RPC CallerID (HDFS-9184) that is designed to trace
callers under different services (Yarn/Spark/Hive/Tez). You could extend a
IdentifyProvider to leverage that and thus avoid punishing all the RPC calls
from the same service user.
bq. One idea here is to introduce reservation support to RPC resources.
Can you elaborate on how to quantify the cost of RPC calls, which are not equal
in terms of the cost on NN? Same RPC call with different parameter may have
significant difference in cost as well. Can you post more details of the
proposal for discussion.
> Add reservation support to RPC FairCallQueue
> --------------------------------------------
>
> Key: HADOOP-15016
> URL: https://issues.apache.org/jira/browse/HADOOP-15016
> Project: Hadoop Common
> Issue Type: Improvement
> Reporter: Wei Yan
> Assignee: Wei Yan
> Priority: Normal
>
> FairCallQueue is introduced to provide RPC resource fairness among different
> users. In current implementation, each user is weighted equally, and the
> processing priority for different RPC calls are based on how many requests
> that user sent before. This works well when the cluster is shared among
> several end-users.
> However, this has some limitations when a cluster is shared among both
> end-users and some service jobs, like some ETL jobs which run under a service
> account and need to issue lots of RPC calls. When NameNode becomes quite
> busy, this set of jobs can be easily backoffed and low-prioritied. We cannot
> simply treat this type jobs as "bad" user who randomly issues too many calls,
> as their calls are normal calls. Also, it is unfair to weight a end-user and
> a heavy service user equally when allocating RPC resources.
> One idea here is to introduce reservation support to RPC resources. That is,
> for some services, we reserve some RPC resources for their calls. This idea
> is very similar to how YARN manages CPU/memory resources among different
> resource queues. A little more details here: Along with existing
> FairCallQueue setup (like using 4 queues with different priorities), we would
> add some additional special queues, one for each special service user. For
> each special service user, we provide a guarantee RPC share (like 10% which
> can be aligned with its YARN resource share), and this percentage can be
> converted to a weight used in WeightedRoundRobinMultiplexer. A quick example,
> we have 4 default queues with default weights (8, 4, 2, 1), and two special
> service users (user1 with 10% share, and user2 with 15% share). So finally
> we'll have 6 queues, 4 default queues (with weights 8, 4, 2, 1) and 2 special
> queues (user1Queue weighted 15*10%/75%=2, and user2Queue weighted
> 15*15%/75%=3).
> For new coming RPC calls from special service users, they will be put
> directly to the corresponding reserved queue; for other calls, just follow
> current implementation.
> By default, there is no special user and all RPC requests follow existing
> FairCallQueue implementation.
> Would like to hear more comments on this approach; also want to know any
> other better solutions? Will put a detailed design once get some early
> comments.
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