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From "Andrew Wang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-6982) nntop: top­-like tool for name node users
Date Thu, 13 Nov 2014 01:12:50 GMT

    [ https://issues.apache.org/jira/browse/HDFS-6982?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14209024#comment-14209024
] 

Andrew Wang commented on HDFS-6982:
-----------------------------------

How would this behave to a sudden, large spike in operations? This is the situation we're
trying to detect. i.e. for something like:

{noformat}
0, 0, 0, 1000000, 0, 0, 0, ...
{noformat}

What I'd want to see is essentially a step function going 0 -> 1000000 -> 0, but an
EWMA would necessarily tail off exponentially.

I'm also happy to take a look at any references you have. I've done some reading on calculating
percentiles on rolling windows, and what we have now is pretty typical for that, i.e. a number
of buckets each representing a fixed time interval, aggregating buckets to calculate the metric,
old buckets being discarded as time passes.

> nntop: top­-like tool for name node users
> -----------------------------------------
>
>                 Key: HDFS-6982
>                 URL: https://issues.apache.org/jira/browse/HDFS-6982
>             Project: Hadoop HDFS
>          Issue Type: New Feature
>            Reporter: Maysam Yabandeh
>            Assignee: Maysam Yabandeh
>         Attachments: HDFS-6982.patch, HDFS-6982.v2.patch, HDFS-6982.v3.patch, HDFS-6982.v4.patch,
HDFS-6982.v5.patch, HDFS-6982.v6.patch, nntop-design-v1.pdf
>
>
> In this jira we motivate the need for nntop, a tool that, similarly to what top does
in Linux, gives the list of top users of the HDFS name node and gives insight about which
users are sending majority of each traffic type to the name node. This information turns out
to be the most critical when the name node is under pressure and the HDFS admin needs to know
which user is hammering the name node and with what kind of requests. Here we present the
design of nntop which has been in production at Twitter in the past 10 months. nntop proved
to have low cpu overhead (< 2% in a cluster of 4K nodes), low memory footprint (less than
a few MB), and quite efficient for the write path (only two hash lookup for updating a metric).



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