[jira] Commented: (HADOOP-1839) Link-ify the Pending/Running/Complete/Killed tasks/task-attempts on jobdetails.jsp

["Hadoop QA (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HADOOP-1839?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12528715 ] 

Hadoop QA commented on HADOOP-1839:
-----------------------------------

-1 overall.  Here are the results of testing the latest attachment 
http://issues.apache.org/jira/secure/attachment/12366153/HADOOP-1839.patch
against trunk revision r577171.

    @author +1.  The patch does not contain any @author tags.

    javadoc -1.  The javadoc tool appears to have generated  messages.

    javac +1.  The applied patch does not generate any new compiler warnings.

    findbugs +1.  The patch does not introduce any new Findbugs warnings.

    core tests +1.  The patch passed core unit tests.

    contrib tests +1.  The patch passed contrib unit tests.

Test results: http://lucene.zones.apache.org:8080/hudson/job/Hadoop-Patch/790/testReport/
Findbugs warnings: http://lucene.zones.apache.org:8080/hudson/job/Hadoop-Patch/790/artifact/trunk/build/test/findbugs/newPatchFindbugsWarnings.html
Checkstyle results: http://lucene.zones.apache.org:8080/hudson/job/Hadoop-Patch/790/artifact/trunk/build/test/checkstyle-errors.html
Console output: http://lucene.zones.apache.org:8080/hudson/job/Hadoop-Patch/790/console

This message is automatically generated.

> Link-ify the Pending/Running/Complete/Killed tasks/task-attempts on jobdetails.jsp
> ----------------------------------------------------------------------------------
>
>                 Key: HADOOP-1839
>                 URL: https://issues.apache.org/jira/browse/HADOOP-1839
>             Project: Hadoop
>          Issue Type: Improvement
>          Components: mapred
>    Affects Versions: 0.15.0
>            Reporter: Arun C Murthy
>            Assignee: Amar Kamat
>             Fix For: 0.15.0
>
>         Attachments: HADOOP-1839.patch
>
>
> Ensuring that we can quickly view the Pending/Running/Complete/Killed tasks and task-attempts from jobdetails.jsp helps to narrow down and hence makes it easier to debug.

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.

TCO and human hours for large deployments

[Lance Reed <lr...@boomerang.com>]

I am working out the Total Cost for a large (er, scalable...) hdfs 
deployment to use for persistent storage.  We already use a hdfs / 
hadoop setup for computational purposes. The numbers for hardware are 
relatively easy depending on design.  However, like all opensource 
initiatives, calculating the time / resources for administration by 
humans is tricky until you do it for awhile.  Our company has plenty of 
experience using OpenSource tools for the majority of our needs, with 
the proprietary solution thrown in where applicable.  So I was wondering 
if anyone who is attempting to setup a hdfs storage setup, or who is 
using one now could shed some light on the subject.  I figured 
initially, on a new deployment, about 60% of a single Administrators 
time would be taken up to maintain a large hdfs cluster.  I figure 
design and implementation would take much more than that (maybe 2 or 3 
people to save time).  I am comparing this to a couple proprietary 
solutions we have been looking at that are known to scale well into 
multi TB or even PB setup that are basically Scalable NAS solutions that 
use a "brick" mentality.  The theory being that you pay upfront for 
stability or support if needed.  But I am wondering if say 60% for the 
first year of learning how to maintain and grow a production hdfs is 
close or not.  Too high / low?

Any thoughts or real work data would be great.

Thanks all!!