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https://issues.apache.org/jira/browse/YARN-3448?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14531653#comment-14531653
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Zhijie Shen commented on YARN-3448:
-----------------------------------

bq. GenericObjectMapper is quite slow consuming 7-10% of the processing time on 
my example data. 

Thanks, Jonathan! It's useful information. We may want to exploit it in v2 
backend implementation too.

bq. Should I leave this new error in?

I'm fine with keeping it.

+1 for the last patch. I'll hold the patch until tomorrow for commit, giving 
other folks the chance to take a look again.

> Add Rolling Time To Lives Level DB Plugin Capabilities
> ------------------------------------------------------
>
>                 Key: YARN-3448
>                 URL: https://issues.apache.org/jira/browse/YARN-3448
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>          Components: timelineserver
>            Reporter: Jonathan Eagles
>            Assignee: Jonathan Eagles
>              Labels: BB2015-05-TBR
>         Attachments: YARN-3448.1.patch, YARN-3448.10.patch, 
> YARN-3448.12.patch, YARN-3448.13.patch, YARN-3448.14.patch, 
> YARN-3448.15.patch, YARN-3448.16.patch, YARN-3448.17.patch, 
> YARN-3448.2.patch, YARN-3448.3.patch, YARN-3448.4.patch, YARN-3448.5.patch, 
> YARN-3448.7.patch, YARN-3448.8.patch, YARN-3448.9.patch
>
>
> For large applications, the majority of the time in LeveldbTimelineStore is 
> spent deleting old entities record at a time. An exclusive write lock is held 
> during the entire deletion phase which in practice can be hours. If we are to 
> relax some of the consistency constraints, other performance enhancing 
> techniques can be employed to maximize the throughput and minimize locking 
> time.
> Split the 5 sections of the leveldb database (domain, owner, start time, 
> entity, index) into 5 separate databases. This allows each database to 
> maximize the read cache effectiveness based on the unique usage patterns of 
> each database. With 5 separate databases each lookup is much faster. This can 
> also help with I/O to have the entity and index databases on separate disks.
> Rolling DBs for entity and index DBs. 99.9% of the data are in these two 
> sections 4:1 ration (index to entity) at least for tez. We replace DB record 
> removal with file system removal if we create a rolling set of databases that 
> age out and can be efficiently removed. To do this we must place a constraint 
> to always place an entity's events into it's correct rolling db instance 
> based on start time. This allows us to stitching the data back together while 
> reading and artificial paging.
> Relax the synchronous writes constraints. If we are willing to accept losing 
> some records that we not flushed in the operating system during a crash, we 
> can use async writes that can be much faster.
> Prefer Sequential writes. sequential writes can be several times faster than 
> random writes. Spend some small effort arranging the writes in such a way 
> that will trend towards sequential write performance over random write 
> performance.



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