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From "Vinod Kumar Vavilapalli (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-2082) Support for alternative log aggregation mechanism
Date Fri, 23 May 2014 03:29:02 GMT

    [ https://issues.apache.org/jira/browse/YARN-2082?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14006753#comment-14006753

Vinod Kumar Vavilapalli commented on YARN-2082:

We should also consider some scalable solutions on HDFS itself - to post process the logs
automatically to reduce the file-count and may be NMs forming a tree of aggregation (with
network copy of logs) before hitting HDFS.

IAC, the pluggability is sort of a dup of the proposal at YARN-1440 (albeit for a different

> Support for alternative log aggregation mechanism
> -------------------------------------------------
>                 Key: YARN-2082
>                 URL: https://issues.apache.org/jira/browse/YARN-2082
>             Project: Hadoop YARN
>          Issue Type: New Feature
>            Reporter: Ming Ma
> I will post a more detailed design later. Here is the brief summary and would like to
get early feedback.
> Problem Statement:
> Current implementation of log aggregation create one HDFS file for each {application,
nodemanager }. These files are relative small, in the range of 1-2 MB. In a large cluster
with lots of application and many nodemanagers, it ends up creating lots of small files in
HDFS. This creates pressure on HDFS NN on the following ways.
> 1. It increases NN Memory size. It is mitigated by having history server deletes old
log files in HDFS.
> 2. Runtime RPC hit on HDFS. Each log aggregation file introduced several NN RPCs such
as create, getAdditionalBlock, complete, rename. When the cluster is busy, such RPC hit has
impact on NN performance.
> In addition, to support non-MR applications on YARN, we might need to support aggregation
for long running applications.
> Design choices:
> 1. Don't aggregate all the logs, as in YARN-221.
> 2. Create a dedicated HDFS namespace used only for log aggregation.
> 3. Write logs to some key-value store like HBase. HBase's RPC hit on NN will be much
> 4. Decentralize the application level log aggregation to NMs. All logs for a given application
are aggregated first by a dedicated NM before it is pushed to HDFS.
> 5. Have NM aggregate logs on a regular basis; each of these log files will have data
from different applications and there needs to be some index for quick lookup.
> Proposal:
> 1. Make yarn log aggregation pluggable for both read and write path. Note that Hadoop
FileSystem provides an abstraction and we could ask alternative log aggregator implement compatable
FileSystem, but that seems to an overkill.
> 2. Provide a log aggregation plugin that write to HBase. The scheme design needs to support
efficient read on a per application as well as per application+container basis; in addition,
it shouldn't create hotspot in a cluster where certain users might create more jobs than others.
For example, we can use hash($user+$applicationId} + containerid as the row key.

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