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MapReduce >> mail # user >> State of Art in Hadoop Log aggregation

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Re: State of Art in Hadoop Log aggregation

It sounds like you want a management console. We are using Cloudera
Manager, but for 200 nodes you would need to license it, it is only free up
to 50 nodes.

The FOSS version of this is Ambari, iirc.

Flume will provide a Hadoop-integrated pipeline for ingesting data. The
data will still need to be analyzed and visualized if you use Flume. Kafka
is a newer project for collecting and aggregating logs, but is a separate
project and will need a server of its own to manage.

We use Splunk also, since it is approved by our auditing compliance agency.

*Devin Suiter*
Jr. Data Solutions Software Engineer
100 Sandusky Street | 2nd Floor | Pittsburgh, PA 15212
Google Voice: 412-256-8556 | www.rdx.com
On Fri, Oct 11, 2013 at 9:54 AM, Alexander Alten-Lorenz <[EMAIL PROTECTED]
> wrote:

> Hi,
> http://flume.apache.org
> - Alex
> On Oct 11, 2013, at 7:36 AM, Sagar Mehta <[EMAIL PROTECTED]> wrote:
> Hi Guys,
> We have fairly decent sized Hadoop cluster of about 200 nodes and was
> wondering what is the state of art if I want to aggregate and visualize
> Hadoop ecosystem logs, particularly
>    1. Tasktracker logs
>    2. Datanode logs
>    3. Hbase RegionServer logs
> One way is to use something like a Flume on each node to aggregate the
> logs and then use something like Kibana -
> http://www.elasticsearch.org/overview/kibana/ to visualize the logs and
> make them searchable.
> However I don't want to write another ETL for the hadoop/hbase logs
>  themselves. We currently log in to each machine individually to 'tail -F
> logs' when there is an hadoop problem on a particular node.
> We want a better way to look at the hadoop logs themselves in a
> centralized way when there is an issue without having to login to 100
> different machines and was wondering what is the state of are in this
> regard.
> Suggestions/Pointers are very welcome!!
> Sagar
> --
> Alexander Alten-Lorenz
> http://mapredit.blogspot.com
> German Hadoop LinkedIn Group: http://goo.gl/N8pCF