The Distributed Cache uses the shared file system (which ever is specified).
The Distributed Cache can be loaded via the GenericOptionsParser / TooRunner
parameters. Those parameters (-files, -archives, -libjars) are seen on the
commandline and available in a MR driver class that implements the Tool
interface.
Those parameters as well as the methods in the Distributed Cache API load the
files into the shared filesystem used by the JT. From there the framework
manages the distribution to the DNs.
A couple of unique characteristics are:
1.The Distributed Cache will manage the deployment of the files into the cache
directory, where they can be used by all those jobs that need them. The TT
maintains a reference count to help ensure the file(s) aren't deleted
prematurely.
2.Archives are unarchived, with directory structures intact if needed. This is
an important requirement for my application. During the unarchive the directory
structure is created.
Most of this info is directly from HadoopDefGuide and various other sources on
the net.
I also look forward to comments and corrections from those with more
experience.John
Date: Tue, 9 Apr 2013 16:07:12 -0700
Subject: Re: Distributed cache: how big is too big?
From: bjorn...@gmail.com
To: user@hadoop.apache.org
I think the correct question is why would you use distributed cache for a large
file that is read during map/reduce instead of plain hdfs? It does not sound
wise to shuffle GB of data onto all nodes on each job submission and then just
remove it when the job is done. I would think about picking another "data
strategy" and just use hdfs for the file. Its no problem to make sure the file
is available on every node.
Anyway...maybe someone with more knowledge on this will chip in :)
On Tue, Apr 9, 2013 at 7:56 AM, Jay Vyas <jayunit...@gmail.com> wrote:
Hmmm.. maybe im missing something.. but (@bjorn) Why would you use hdfs as a
replacement for the distributed cache?
After all - the distributed cache is just a file with replication over the
whole cluster, which isn't in hdfs. Cant you Just make the cache size big and
store the file there?
What advantage is hdfs distribution of the file over all nodes ?
On Apr 9, 2013, at 6:49 AM, Bjorn Jonsson <bjorn...@gmail.com> wrote:
Put it once on hdfs with a replication factor equal to the number of DN. No
startup latency on job submission or max size and access it from anywhere with
fs since it sticks around untill you replace it? Just a thought.
On Apr 8, 2013 9:59 PM, "John Meza" <j_meza...@hotmail.com> wrote:
I am researching a Hadoop solution for an existing application that requires a
directory structure full of data for processing.
To make the Hadoop solution work I need to deploy the data directory to each DN
when the job is executed.
I know this isn't new and commonly done with a Distributed Cache.
Based on experience what are the common file sizes deployed in a Distributed
Cache? I know smaller is better, but how big is too big? the larger cache
deployed I have read there will be startup latency. I also assume there are
other factors that play into this.
I know that->Default local.cache.size=10Gb
-Range of desirable sizes for Distributed Cache= 10Kb - 1Gb??
-Distributed Cache is normally not used if larger than =____?
Another Option: Put the data directories on each DN and provide location to
TaskTracker?
thanks
John
