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From "Kai Mosebach (JIRA)" <j...@apache.org>
Subject [jira] Created: (HADOOP-3999) Need to add host capabilites / abilities
Date Fri, 22 Aug 2008 09:42:46 GMT
Need to add host capabilites / abilities
----------------------------------------

                 Key: HADOOP-3999
                 URL: https://issues.apache.org/jira/browse/HADOOP-3999
             Project: Hadoop Core
          Issue Type: Improvement
          Components: metrics
         Environment: Any
            Reporter: Kai Mosebach


The MapReduce paradigma is limited to run MapReduce jobs with the lowest common factor of
all nodes in the cluster.

On the one hand this is wanted (cloud computing, throw simple jobs in, nevermind who does
it)
On the other hand this is limiting the possibilities quite a lot, for instance if you had
data which could/needs to be fed to a 3rd party interface like Mathlab, R, BioConductor you
could solve a lot more jobs via hadoop.

Furthermore it could be interesting to know about the OS, the architecture, the performance
of the node in relation to the rest of the cluster. (Performance ranking)
i.e. if i'd know about a sub cluster of very computing performant nodes or a sub cluster of
very fast disk-io nodes, the task tracker could select these nodes regarding a so called job
profile (i.e. heavy computing job / heavy disk-io job), which can usually be estimated by
a developer before.

To achieve this, node capabilities could be introduced and stored in the DFS, giving you

a1.) basic information about each node (OS, ARCH)
a2.) more sophisticated infos (additional software, path to software, version). 
a3.) PKI collected about the node (disc-io, cpu power, memory)
a4.) network throughput to neighbor hosts, which might allow generating a network performance
map over the cluster

This would allow you to

b1.) generate jobs that have a profile (computing intensive)
b2.) generate jovs that have software dependencies (run on Linux only, run on nodes with MathLab
only)
b3.) generate a performance map of the cluster (sub clusters of fast disk nodes, sub clusters
of fast cpu nodes, network-speed-relation-map between nodes)

>From step b3) you could then even acquire statistical information which could again be
fed into the DFS Namenode to see if we could store data on fast disk subclusters only (that
might need to be a tool outside of hadoop core though)

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