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From "Amir Langer (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-7244) Reduce Namenode memory using Flyweight pattern
Date Tue, 14 Oct 2014 11:35:34 GMT

    [ https://issues.apache.org/jira/browse/HDFS-7244?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14170801#comment-14170801
] 

Amir Langer commented on HDFS-7244:
-----------------------------------

Although not focusing on off-heap specifically  this JIRA could be the mechanism to have off-heap
data structures in the Namenode.
Ultimately, the goal of this JIRA and HDFS-6709 is the same.


> Reduce Namenode memory using Flyweight pattern
> ----------------------------------------------
>
>                 Key: HDFS-7244
>                 URL: https://issues.apache.org/jira/browse/HDFS-7244
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: namenode
>            Reporter: Amir Langer
>
> Using the flyweight pattern can dramatically reduce memory usage in the Namenode. The
pattern also abstracts the actual storage type and allows the decision of whether it is off-heap
or not and what is the serialisation mechanism to be configured per deployment. 
> The idea is to move all BlockInfo data (as a first step) to this storage using the Flyweight
pattern. The cost to doing it will be in higher latency when accessing/modifying a block.
The idea is that this will be offset with a reduction in memory and in the case of off-heap,
a dramatic reduction in memory (effectively, memory used for BlockInfo would reduce to a very
small constant value).
> This reduction will also have an huge impact on the latency as GC pauses will be reduced
considerably and may even end up with better latency results than the original code.
> I wrote a stand-alone project as a proof of concept, to show the pattern, the data structure
we can use and what will be the performance costs of this approach.
> see [Slab|https://github.com/langera/slab]
> and [Slab performance results|https://github.com/langera/slab/wiki/Performance-Results].
> Slab abstracts the storage, gives several storage implementations and implements the
flyweight pattern for the application (Namenode in our case).
> The stages to incorporate Slab into the Namenode is outlined in the sub-tasks JIRAs.



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