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From 조주일 <tjst...@kgrid.co.kr>
Subject Re: rolling upgrade(2.4.1 to 2.6.0) problem
Date Fri, 24 Apr 2015 08:15:36 GMT
ulimit -a
core file size          (blocks, -c) 0
data seg size           (kbytes, -d) unlimited
scheduling priority             (-e) 0
file size               (blocks, -f) unlimited
pending signals                 (-i) 62580
max locked memory       (kbytes, -l) 64
max memory size         (kbytes, -m) unlimited
open files                      (-n) 102400
pipe size            (512 bytes, -p) 8
POSIX message queues     (bytes, -q) 819200
real-time priority              (-r) 0
stack size              (kbytes, -s) 10240
cpu time               (seconds, -t) unlimited
max user processes              (-u) 10240
virtual memory          (kbytes, -v) unlimited
file locks                      (-x) unlimited
 
------------------------------------------------------
Hadoop cluster was operating normally in the 2.4.1 version. 
Hadoop cluster is a problem in version 2.6. 
 
E.g
 
Slow BlockReceiver logs are often seen 
"org.apache.hadoop.hdfs.server.datanode.DataNode: Slow BlockReceiver write data to disk cost"

 
If the data node failure and under-block occurs,  
another many nodes heartbeat check is fails. 
So, I stop all nodes and I start all nodes. 
The cluster is then normalized. 
 
In this regard, Hadoop Is there a difference between version 2.4 and 2.6? 
 
 
ulimit -a
core file size          (blocks, -c) 0
data seg size           (kbytes, -d) unlimited
scheduling priority             (-e) 0
file size               (blocks, -f) unlimited
pending signals                 (-i) 62580
max locked memory       (kbytes, -l) 64
max memory size         (kbytes, -m) unlimited
open files                      (-n) 102400
pipe size            (512 bytes, -p) 8
POSIX message queues     (bytes, -q) 819200
real-time priority              (-r) 0
stack size              (kbytes, -s) 10240
cpu time               (seconds, -t) unlimited
max user processes              (-u) 10240
virtual memory          (kbytes, -v) unlimited
file locks                      (-x) unlimited
 
 
-----Original Message-----
From: "Drake민영근"&lt;drake.min@nexr.com&gt; 
To: "user"&lt;user@hadoop.apache.org&gt;; "조주일"&lt;tjstory@kgrid.co.kr&gt;;

Cc: 
Sent: 2015-04-24 (금) 16:58:46
Subject: Re: rolling upgrade(2.4.1 to 2.6.0) problem
 
HI,  How about the ulimit setting of the user for hdfs datanode ?Drake 민영근 Ph.Dkt NexR

On Wed, Apr 22, 2015 at 6:25 PM, 조주일 &lt;tjstory@kgrid.co.kr&gt; wrote:
 
I allocated 5G. 
I think OOM is not the cause of essentially 
 
-----Original Message-----
From: "Han-Cheol Cho"&lt;hancheol.cho@nhn-playart.com&gt; 
To: &lt;user@hadoop.apache.org&gt;; 
Cc:  
Sent: 2015-04-22 (수) 15:32:35
Subject: RE: rolling upgrade(2.4.1 to 2.6.0) problem
 Hi,
 
The first warning shows out-of-memory error of JVM.
Did you give enough max heap memory for DataNode daemons?
DN daemons, by default, uses max heap size 1GB. So if your DN requires more 
than that, it will be in a trouble.
 You can check the memory consumption of you DN dameons (e.g., top command) 
and the memory allocated to them by -Xmx option (e.g., jps -lmv).
If the max heap size is too small, you can use HADOOP_DATANODE_OPTS variable
(e.g., HADOOP_DATANODE_OPTS="-Xmx4g") to override it.
 
Best wishes,
Han-Cheol
 
 
 
 
 
-----Original Message-----
From: "조주일"&lt;tjstory@kgrid.co.kr&gt; 
To: &lt;user@hadoop.apache.org&gt;; 
Cc: 
Sent: 2015-04-22 (수) 14:54:16
Subject: rolling upgrade(2.4.1 to 2.6.0) problem
 
 
My Cluster is..
hadoop 2.4.1
Capacity : 1.24PB
Used 1.1PB
16 Datanodes 
Each node is a capacity of 65TB, 96TB, 80TB, Etc..
 
I had to proceed with the rolling upgrade 2.4.1 to 2.6.0. 
A data node upgraded takes about 40 minutes. 
Occurs during the upgrade is in progress under-block. 
 
10 nodes completed upgrade 2.6.0.  
Had a problem at some point during a rolling upgrade of the remaining nodes.
 
Heartbeat of the many nodes(2.6.0 only) has failed. 
 
I did changes the following attributes but I did not fix the problem,  
dfs.datanode.handler.count = 100 ---&gt; 300, 400, 500  
dfs.datanode.max.transfer.threads = 4096 ---&gt; 8000, 10000 
 
I think, 
1. Something that causes a delay in processing threads. I think it may be because the block
replication between different versions.
2. Whereby the many handlers and xceiver became necessary. 
3. Whereby the out of memory, an error occurs. Or the problem arises on a datanode.
4. Heartbeat fails, and datanode dies.
 I found a datanode error log for the following: 
However, it is impossible to determine the cause. 
 
I think, therefore I am. Called because it blocks the replication between different versions

 
Give me someone help me !! 
 
DATANODE LOG
--------------------------------------------------------------------------
### I had to check a few thousand close_wait connection from the datanode.
 
org.apache.hadoop.hdfs.server.datanode.DataNode: Slow BlockReceiver write packet to mirror
took 1207ms (threshold=300ms)
 
2015-04-21 22:46:01,772 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: DataNode is
out of memory. Will retry in 30 seconds.
java.lang.OutOfMemoryError: unable to create new native thread
        at java.lang.Thread.start0(Native Method)
        at java.lang.Thread.start(Thread.java:640)
        at org.apache.hadoop.hdfs.server.datanode.DataXceiverServer.run(DataXceiverServer.java:145)
        at java.lang.Thread.run(Thread.java:662)
2015-04-21 22:49:45,378 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: datanode-192.168.1.207:40010:DataXceiverServer:java.io.IOException:
Xceiver count 8193 exceeds the limit of concurrent xcievers: 8192
        at org.apache.hadoop.hdfs.server.datanode.DataXceiverServer.run(DataXceiverServer.java:140)
        at java.lang.Thread.run(Thread.java:662)		
2015-04-22 01:01:25,632 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: datanode-192.168.1.207:40010:DataXceiverServer:java.io.IOException:
Xceiver count 8193 exceeds the limit of concurrent xcievers: 8192
        at org.apache.hadoop.hdfs.server.datanode.DataXceiverServer.run(DataXceiverServer.java:140)
        at java.lang.Thread.run(Thread.java:662)
2015-04-22 03:49:44,125 ERROR org.apache.hadoop.hdfs.server.datanode.DataNode: datanode-192.168.1.204:40010:DataXceiver
error processing READ_BLOCK operation  src: /192.168.2.174:45606 dst: /192.168.1.204:40010
java.io.IOException: cannot find BPOfferService for bpid=BP-1770955034-0.0.0.0-1401163460236
        at org.apache.hadoop.hdfs.server.datanode.DataNode.getDNRegistrationForBP(DataNode.java:1387)
        at org.apache.hadoop.hdfs.server.datanode.DataXceiver.readBlock(DataXceiver.java:470)
        at org.apache.hadoop.hdfs.protocol.datatransfer.Receiver.opReadBlock(Receiver.java:116)
        at org.apache.hadoop.hdfs.protocol.datatransfer.Receiver.processOp(Receiver.java:71)
        at org.apache.hadoop.hdfs.server.datanode.DataXceiver.run(DataXceiver.java:235)
        at java.lang.Thread.run(Thread.java:662)
2015-04-22 05:30:28,947 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: DatanodeRegistration(192.168.1.203,
datanodeUuid=654f22ef-84b3-4ecb-a959-2ea46d817c19, infoPort=40075, ipcPort=40020, storageInfo=lv=-56;cid=CID-CLUSTER;nsid=239138164;c=1404883838982):Failed
to transfer BP-1770955034-0.0.0.0-1401163460236:blk_1075354042_1613403 to 192.168.2.156:40010
got
java.net.SocketException: Original Exception : java.io.IOException: Connection reset by peer
        at sun.nio.ch.FileChannelImpl.transferTo0(Native Method)
        at sun.nio.ch.FileChannelImpl.transferToDirectly(FileChannelImpl.java:405)
        at sun.nio.ch.FileChannelImpl.transferTo(FileChannelImpl.java:506)
        at org.apache.hadoop.net.SocketOutputStream.transferToFully(SocketOutputStream.java:223)
        at org.apache.hadoop.hdfs.server.datanode.BlockSender.sendPacket(BlockSender.java:559)
        at org.apache.hadoop.hdfs.server.datanode.BlockSender.sendBlock(BlockSender.java:728)
        at org.apache.hadoop.hdfs.server.datanode.DataNode$DataTransfer.run(DataNode.java:2017)
        at java.lang.Thread.run(Thread.java:662)
Caused by: java.io.IOException: Connection reset by peer
        ... 8 more
 
 








 


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