[
https://issues.apache.org/jira/browse/HDFS-5711?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sanjay Radia updated HDFS-5711:
-------------------------------
Description:
This jira is to track changes to be made to remove HDFS name-node memory
limitation to hold block - block location mappings.
It is a known fact that the single Name-node architecture of HDFS has
scalability limits. The HDFS federation project alleviates this problem by
using horizontal scaling. This helps increase the throughput of metadata
operation and also the amount of data that can be stored in a Hadoop cluster.
The Name-node stores all the filesystem metadata in memory (even in the
federated architecture), the
Name-node design can be enhanced by persisting part of the metadata onto
secondary storage and retaining
the popular or recently accessed metadata information in main memory. This
design can benefit a HDFS deployment
which doesn't use federation but needs to store a large number of files or
large number of blocks. Lin Xiao from Hortonworks attempted a similar
project [1] in the Summer of 2013. They used LevelDB to persist the Namespace
information (i.e file and directory inode information).
A patch with this change is yet to be submitted to code base. We also intend to
use LevelDB to persist metadata, and plan to
provide a complete solution, by not just persisting the Namespace information
but also the Blocks Map onto secondary storage.
We did implement the basic prototype which stores the block-block location
mapping metadata to the persistent key-value store i.e. levelDB. Prototype also
maintains the in-memory cache of the recently used block-block location
mappings metadata.
References:
[1] Lin Xiao, Hortonworks, Removing Name-node’s memory limitation, HDFS-5389,
http://www.slideshare.net/ydn/hadoop-meetup-hug-august-2013-removing-the-namenodes-memory-limitation.
was:
This jira is to track changes to be made to remove HDFS name-node memory
limitation to hold block - block location mappings.
It is a known fact that the single Name-node architecture of HDFS has
scalability limits. The HDFS federation project alleviates this problem by
using horizontal scaling. This helps increase the throughput of metadata
operation and also the amount of data that can be stored in a Hadoop cluster.
The Name-node stores all the filesystem metadata in memory (even in the
federated architecture), the
Name-node design can be enhanced by persisting part of the metadata onto
secondary storage and retaining
the popular or recently accessed metadata information in main memory. This
design can benefit a HDFS deployment
which doesn't use federation but needs to store a large number of files or
large number of blocks. Lin Xiao from Hortonworks attempted a similar
project [1] in the Summer of 2013. They used LevelDB to persist the Namespace
information (i.e file and directory inode information).
A patch with this change is yet to be submitted to code base. We also intend to
use LevelDB to persist metadata, and plan to
provide a complete solution, by not just persisting the Namespace information
but also the Blocks Map onto secondary storage.
We did implement the basic prototype which stores the block-block location
mapping metadata to the persistent key-value store i.e. levelDB. Prototype also
maintains the in-memory cache of the recently used block-block location
mappings metadata.
References:
[1] Lin Xiao, Hortonworks, Removing Name-node’s memory limitation,
http://www.slideshare.net/ydn/hadoop-meetup-hug-august-2013-removing-the-namenodes-memory-limitation
> Removing memory limitation of the Namenode by persisting Block - Block
> location mappings to disk.
> -------------------------------------------------------------------------------------------------
>
> Key: HDFS-5711
> URL: https://issues.apache.org/jira/browse/HDFS-5711
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: namenode
> Reporter: Rohan Pasalkar
>
> This jira is to track changes to be made to remove HDFS name-node memory
> limitation to hold block - block location mappings.
> It is a known fact that the single Name-node architecture of HDFS has
> scalability limits. The HDFS federation project alleviates this problem by
> using horizontal scaling. This helps increase the throughput of metadata
> operation and also the amount of data that can be stored in a Hadoop cluster.
> The Name-node stores all the filesystem metadata in memory (even in the
> federated architecture), the
> Name-node design can be enhanced by persisting part of the metadata onto
> secondary storage and retaining
> the popular or recently accessed metadata information in main memory. This
> design can benefit a HDFS deployment
> which doesn't use federation but needs to store a large number of files or
> large number of blocks. Lin Xiao from Hortonworks attempted a similar
> project [1] in the Summer of 2013. They used LevelDB to persist the Namespace
> information (i.e file and directory inode information).
> A patch with this change is yet to be submitted to code base. We also intend
> to use LevelDB to persist metadata, and plan to
> provide a complete solution, by not just persisting the Namespace
> information but also the Blocks Map onto secondary storage.
> We did implement the basic prototype which stores the block-block location
> mapping metadata to the persistent key-value store i.e. levelDB. Prototype
> also maintains the in-memory cache of the recently used block-block location
> mappings metadata.
> References:
> [1] Lin Xiao, Hortonworks, Removing Name-node’s memory limitation, HDFS-5389,
> http://www.slideshare.net/ydn/hadoop-meetup-hug-august-2013-removing-the-namenodes-memory-limitation.
>
--
This message was sent by Atlassian JIRA
(v6.1.5#6160)
