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Posted to common-issues@hadoop.apache.org by "Wei-Chiu Chuang (JIRA)" <ji...@apache.org> on 2019/05/01 16:17:00 UTC
[jira] [Commented] (HADOOP-16284) KMS Cache Miss Storm
[ https://issues.apache.org/jira/browse/HADOOP-16284?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16831100#comment-16831100 ]
Wei-Chiu Chuang commented on HADOOP-16284:
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[~zsombor] I think you'd be interested in this bug, for similar scalability bugs could exist in Ranger KMS.
> KMS Cache Miss Storm
> --------------------
>
> Key: HADOOP-16284
> URL: https://issues.apache.org/jira/browse/HADOOP-16284
> Project: Hadoop Common
> Issue Type: Bug
> Components: kms
> Affects Versions: 2.6.0
> Environment: CDH 5.13.1, Kerberized, Cloudera Keytrustee Server
> Reporter: Wei-Chiu Chuang
> Priority: Major
>
> We recently stumble upon a performance issue with KMS, where occasionally it exhibited "No content to map" error (this cluster ran an old version that doesn't have HADOOP-14841) and jobs crashed. *We bumped the number of KMSes from 2 to 4, and situation went even worse.*
> Later, we realized this cluster had a few hundred encryption zones and a few hundred encryption keys. This is pretty unusual because most of the deployments known to us has at most a dozen keys. So in terms of number of keys, this cluster is 1-2 order of magnitude higher than any one else.
> The high number of encryption keys in creases the likelihood of key cache miss in KMS. In Cloudera's setup, each cache miss forces KMS to sync with its backend, the Cloudera Keytrustee Server. Plus the high number of KMSes amplifies the latency, effectively causing a [cache miss storm|https://en.wikipedia.org/wiki/Cache_stampede].
> We were able to reproduce this issue with KMS-o-meter (HDFS-14312) - I will come up with a better name later surely - and discovered a scalability bug in CKTS. The fix was verified again with the tool.
> Filing this bug so the community is aware of this issue. I don't have a solution for now in KMS. But we want to address this scalability problem in the near future because we are seeing use cases that requires thousands of encryption keys.
> ----
> On a side note, 4 KMS doesn't work well without HADOOP-14445 (and subsequent fixes). A MapReduce job acquires at most 3 KMS delegation tokens, and so for cases, such as distcp, it wouldn fail to reach the 4th KMS on the remote cluster. I imagine similar issues exist for other execution engines, but I didn't test.
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