Home | About | Sematext search-lucene.com search-hadoop.com
 Search Hadoop and all its subprojects:

Switch to Threaded View
Hadoop >> mail # user >> Huge disk IO on only one disk


Copy link to this message
-
RE: Huge disk IO on only one disk
Thanks Brahma,
That answers my question.

*------------------------*

Cheers !!!

Siddharth Tiwari

Have a refreshing day !!!
"Every duty is holy, and devotion to duty is the highest form of worship of God.”

"Maybe other people will try to limit me but I don't limit myself"
From: [EMAIL PROTECTED]
To: [EMAIL PROTECTED]
Subject: RE: Huge disk IO on only one disk
Date: Mon, 3 Mar 2014 06:51:30 +0000
 

 

What should be the standard around setting up the hadoop.tmp.dir parameter.

 
 

 

MapReduce:

 

mapreduce.cluster.local.dir
${hadoop.tmp.dir}/mapred/local
The local directory where MapReduce stores intermediate data files. May be a comma-separated list of directories on different devices in order to spread disk i/o. Directories that do not exist are ignored.

mapreduce.jobtracker.system.dir
${hadoop.tmp.dir}/mapred/system
The directory where MapReduce stores control files.
mapreduce.jobtracker.staging.root.dir
${hadoop.tmp.dir}/mapred/staging
The root of the staging area for users' job files In practice, this should be the directory where users' home directories are located (usually /user)

mapreduce.cluster.temp.dir
${hadoop.tmp.dir}/mapred/temp
A shared directory for temporary files.
 

Yarn :

 

yarn.nodemanager.local-dirs
${hadoop.tmp.dir}/nm-local-dir
List of directories to store localized files in. An application's localized file directory will be found in: ${yarn.nodemanager.local-dirs}/usercache/${user}/appcache/application_${appid}. Individual containers' work directories, called
 container_${contid}, will be subdirectories of this.

 

 

HDFS :

 

dfs.namenode.name.dir
file://${hadoop.tmp.dir}/dfs/name
Determines where on the local filesystem the DFS name node should store the name table(fsimage). If this is a comma-delimited list of directories then the name table is replicated in all of the directories, for redundancy.
 

dfs.datanode.data.dir
file://${hadoop.tmp.dir}/dfs/data
Determines where on the local filesystem an DFS data node should store its blocks. If this is a comma-delimited list of directories, then data will be stored in all named directories, typically on different devices. Directories that do not exist
 are ignored.

 

dfs.namenode.checkpoint.dir
file://${hadoop.tmp.dir}/dfs/namesecondary
Determines where on the local filesystem the DFS secondary name node should store the temporary images to merge. If this is a comma-delimited list of directories then the image is replicated in all of the directories for redundancy.

 

 

 

 

Thanks & Regards

 

Brahma Reddy Battula

 

From: Siddharth Tiwari [[EMAIL PROTECTED]]

Sent: Monday, March 03, 2014 11:20 AM

To: USers Hadoop

Subject: RE: Huge disk IO on only one disk
Hi Brahma,

No I havnt, I have put comma separated list of disks here dfs.datanode.data.dir . Have
 put disk5 for hadoop.tmp.dir. My Q is, should we set up hadoop.tmp.dir or not ? if yes what should be standards around.
*------------------------*

Cheers !!!

Siddharth
Tiwari

Have a refreshing day !!!

"Every duty is holy, and devotion to duty is the highest form of worship of God.”
"Maybe other people will try to limit me but I don't limit myself"

From: [EMAIL PROTECTED]

To: [EMAIL PROTECTED]

Subject: RE: Huge disk IO on only one disk

Date: Mon, 3 Mar 2014 05:14:34 +0000

 

Seems to be you had started cluster with default values for the following two properties and configured for only hadoop.tmp.dir .

 

dfs.datanode.data.dir --->  file://${hadoop.tmp.dir}/dfs/data (Default value)

 
 

yarn.nodemanager.local-dirs -->  ${hadoop.tmp.dir}/nm-local-dir (Default value)

 
 

 

Please configure above two values as muliple dir's..

 

 

Thanks & Regards

Brahma Reddy Battula

 

From: Siddharth Tiwari [[EMAIL PROTECTED]]

Sent: Monday, March 03, 2014 5:58 AM

To: USers Hadoop

Subject: Huge disk IO on only one disk
Hi Team,

I have 10 disks over which I am running my HDFS. Out of this on disk5 I have my hadoop.tmp.dir configured. I see that on this disk I have huge IO when I run my jobs compared to other disks. Can you guide my to the standards
 to follow so that this IO can be distributed across to other disks as well.
What should be the standard around setting up the hadoop.tmp.dir parameter.
Any help would be highly appreciated. below is IO while I am running a huge job.
Device:            tps   Blk_read/s   Blk_wrtn/s   Blk_read   Blk_wrtn

sda               2.11        37.65       226.20  313512628 1883809216

sdb               1.47        96.44       152.48  803144582 1269829840

sdc               1.45        93.03       153.10  774765734 1274979080

sdd               1.46        95.06       152.73  791690022 1271944848

sde               1.47        92.70       153.24  772025750 1276195288

sdf               1.55        95.77       153.06  797567654 1274657320

sdg              10.10       364.26      1951.79 3033537062 16254346480

sdi               1.46        94.82       152.98  789646630 1274014936

sdh               1.44        94.09       152.57  783547390 1270598232

sdj               1.44        91.94       153.37  765678470 1277220208

sdk               1.52        97.01       153.02  807928678 1274300360
*------------------------*

Cheers !!!

Siddharth Tiwari

Have a refreshing day !!!

"Every duty is holy, and devotion to duty is the highest form of worship of God.”
"Maybe other people will try to limit me but I don't limit myself"