I don't have much control over the cluster configuration, but I will speak with 
those that do.  As far as the input splits are concerned, I will look into some 
custom CombinedInputFormat stuff.

Thank you both very much!

--  Adam


From: GOEKE, MATTHEW (AG/1000) [mailto:matthew.go...@monsanto.com]
Sent: Thursday, September 22, 2011 4:46 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

I don't think that this is hurting you in this particular instance but you are 
*most likely* oversubscribing your boxes with this configuration (a monitoring 
system like Ganglia will be able to confirm this). You will want at least 1 
dedicated physical core for the DN and TT daemons (some would argue 1 core per 
daemon) and with your current configuration you are mapping a slot per logical 
core (12 cores * 2 for HT = 24 logical cores vs 16 + 8 = 24 slots). This might 
not be that much of an impact based on your normal job loads but it definitely 
could bite you if you start swapping due to several heavy tasks at the same 
time.

Also Joey's follow up is still a valid point because you could consume more 
data per input split. You are not restricted to block size if you tune the 
right parameters/classes.

Matt

From: Adam Shook [mailto:ash...@clearedgeit.com]
Sent: Thursday, September 22, 2011 3:33 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

Each box has 3 (seems weird) quad core HT'ed CPUS for a total of 12 HT'ed cores 
per machine.  16 map tasks and 8 reduce tasks each.

-- Adam

From: GOEKE, MATTHEW (AG/1000) [mailto:matthew.go...@monsanto.com]
Sent: Thursday, September 22, 2011 4:26 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

Just to confirm your configuration, how many logical cores do these boxes 
actually have (I am assuming dual quad core HT'ed)? Do you not have any reduce 
slots allocated?

Matt

From: Adam Shook [mailto:ash...@clearedgeit.com]
Sent: Thursday, September 22, 2011 3:22 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

Okay, I put a Thread.sleep to test my theory and it will run all 128 at a time 
- they are just completing too quickly.  I guess there is no other way to get 
around it, unless someone knows how to make the scheduler schedule faster...

-- Adam

From: Adam Shook [mailto:ash...@clearedgeit.com]
Sent: Thursday, September 22, 2011 4:17 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

It's an 8 node cluster and all 8 task trackers are being used.  Each tracker 
has 16 max map tasks.  Each tracker seems to be running two at a time.  Map 
tasks take 10 seconds from start to finish.  Is it possible that they are just 
completing faster than they can be created and it just seems to stick around 16?

-- Adam

From: GOEKE, MATTHEW (AG/1000) [mailto:matthew.go...@monsanto.com]
Sent: Thursday, September 22, 2011 4:06 PM
To: mapreduce-user@hadoop.apache.org
Subject: RE: FairScheduler Local Task Restriction

If you dig into the job history on the web-ui can you confirm whether it is the 
same 16 tasktrackers slots that are getting the map tasks? Long shot but it 
could be that it is actually distributing across your cluster and there is some 
other issue that is springing up. Also, how long does each of your map tasks 
take?

Matt

From: Adam Shook [mailto:ash...@clearedgeit.com]
Sent: Thursday, September 22, 2011 2:41 PM
To: mapreduce-user@hadoop.apache.org
Subject: FairScheduler Local Task Restriction

Hello All,

I have recently switched my small Hadoop dev cluster (v0.20.1) to use the 
FairScheduler.  I have a max of 128 map tasks available and recently noticed 
that my jobs seem to use a maximum of 16 at any given time (the job I am 
looking at in particular runs for about 15 minutes) - they are also all data 
local map tasks.  I searched around a bit and discovered the 
mapred.fairscheduler.locality.delay may be to blame.  I set it to 0 in 
mapred-site.xml, copied the file around to my nodes and tried running another 
job.  It still has 16 tasks.

Does it require a cluster restart?  Is it something totally different?  Should 
I not set this value to zero?

Thanks!

-- Adam
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