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From "Amir Langer (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HDFS-7244) Reduce Namenode memory using Flyweight pattern
Date Tue, 14 Oct 2014 11:30:34 GMT
Amir Langer created HDFS-7244:

             Summary: 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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