I am trying to set up a multi-node Hadoop cluster between 2 windows devices. I am using Hadoop 2.9.2.
how can I achieve that, please.
after a lot of trial and error the following did the job me.
do same configuration as previous answer by #AbsoluteBeginner.
disable windows firewall on all machines (i think you could keep it on and just mess around with the rules, but thats for you to find out)
hdfs namenode -format all nodes (master and slaves)
make sure that the datanode folder is empty in all 3 nodes (just shift+del)
in master node run start-all.cmd. all the following should appear.
50436 NameNode
54696 NodeManager
54744 DataNode
60028 Jps
7340 ResourceManager
in slave nodes run start-all.cmd. all the following should appear
6116 DataNode
2408 Jps
3208 NodeManager
note the reason that nameode and resource manager isn't appearing, is becuase they are running on master node and already occupy the port, and you only need the master resourcemanger and name node running
note if you saw multi-cluster tutorial of linux the master node also shows SeceondryNameNode when executing jps. not really sure why its not appearing in windows.
go to master:50070, and navigate to data nodes you should see something like this
go to master:8088, and navigate to Node you should see something like this
Install open-ssh server on both of your systems using this guide. Generating a new SSH public and private key pair on your local computer is the first step towards authenticating with a remote server without a password. Add the public key to the authorized_keys and add your hostname to list of known hosts. You can find guides on how to do this by searching the internet.
2.Add your hadoop master and slave ips to your hosts file. Open “C:\Windows\System32\drivers\etc\hosts”
and add
your-master-ip hadoopMaster
your-salve-ip hadoopSlave
you can use these names in your configuration files.
much like Linux systems, these are the steps you have to follow in order to run a Hadoop cluster on windows:
3. First you need to have Java installed on your system and JAVA_HOME must be added to your environment variables. You can download Java from Oracle website and install it.
Download Hadoop binary files from Apache website and extract it.
Note that you shouldn't have space in your folder names or you might encounter problems.
Next you have to add Java and Hadoop home and bin folders to your environment variables. just open start menu and type "environment variable" and open the edit environment variables window from control panel.
Add
HADOOP_HOME=”root of your hadoop extracted folder\hadoop-2.9.2″
HADOOP_BIN=”root of hadoop extracted folder\hadoop-2.9.2\bin”
JAVA_HOME=<Root of your JDK installation>”
Edit your "path" environment variable and add %JAVA_HOME%, %HADOOP_HOME%, %HADOOP_BIN%, %HADOOP_HOME%/sbin to your PATH one by one.
you can validate your additions by opening cmd and type in:
echo %HADOOP_HOME%
echo %HADOOP_BIN%
echo %PATH%
CONFIGURING HADOOP:
10. Open "your hadoop root\hadoop-2.9.2\etc\hadoop\hadoop-env.cmd" and add the following lines to the bottom of the file:
set HADOOP_PREFIX=%HADOOP_HOME%
set HADOOP_CONF_DIR=%HADOOP_PREFIX%\etc\hadoop
set YARN_CONF_DIR=%HADOOP_CONF_DIR%
set PATH=%PATH%;%HADOOP_PREFIX%\bin
11.Open "your-hadoop-root\hadoop-2.9.2\etc\hadoop\hdfs-site.xml" and add the below content:
<property>
<name>dfs.name.dir</name>
<value>your desired address</value>
</property>
<property>
<name>dfs.data.dir</name>
<value>your desired address</value>
</property>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
<property>
<name>dfs.datanode.use.datanode.hostname</name>
<value>false</value>
</property>
<property>
<name>dfs.namenode.datanode.registration.ip-hostname-check</name>
<value>false</value>
</property>
<property>
<name>dfs.namenode.http-address</name>
<value>hadoopMaster:50070</value>
<description>Your NameNode hostname for http access.</description>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>hadoopMaster:50090</value>
<description>Your Secondary NameNode hostname for http access.</description>
</property>
edit your core-site.xml and add:
<property>
<name>fs.default.name</name>
<value>hdfs://hadoopMaster:9000</value>
</property>
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>your-temp-directory</value>
<description>A base for other temporary directories.</description>
</property>
Open "root to hadoop\hadoop-2.9.2\etc\hadoop\mapred-site.xml" and add below content within tags. If you don’t see mapred-site.xml then open mapred-site.xml.template file and rename it to mapred-site.xml
<property>
<name>mapred.job.tracker</name>
<value>hadoopMaster:9001</value>
</property>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
14.Edit your yarn-site.xml and add:
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce.shuffle</value>
<description>Long running service which executes on Node Manager(s) and provides MapReduce Sort and Shuffle functionality.</description>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
<description>Enable log aggregation so application logs are moved onto hdfs and are viewable via web ui after the application completed. The default location on hdfs is '/log' and can be changed via yarn.nodemanager.remote-app-log-dir property</description>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>hadoopMaster:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>hadoopMaster:8031</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>hadoopMaster:8032</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>hadoopMaster:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>hadoopMaster:8088</value>
</property>
In your slaves file in "root-hadoop-directory/hadoop/bin" add
hadoopSlave
Do these steps on your slave nodes too.
open cmd and cd to your sbin folder in hadoop directory.
18.format your nameNode
hadoop namenode -format
19.run the following command:
start-dfs.sh
then run:
start-yarn.sh
I've integrated my hadoop2 and hbase0.98 with phoenix and by typing command sqlline.py localhost phoenix shell starts, but when I try to run apache phoenix example by this command : psql.py /usr/local/phoenix/examples/WEB_STAT.sql /usr/local/phoenix/examples/WEB_STAT.csv /usr/local/phoenix/examples/WEB_STAT_QUERIES.sql I faced this error ERROR client.HConnectionManager$HConnectionImplementation: The node /hbase is not in ZooKeeper. It should have been written by the master. Check the value configured in 'zookeeper.znode.parent'. There could be a mismatch with the one configured in the master.
I use hadoop 2.6 in single mode and hbase 0.98 in psudo distributed mod, in addition I didn't explicitly install zookeeper, is it required to install zookeeper explicitly?
my HBASE_HOME/conf/hbase-site.xml file contains :
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://localhost:54310/hbase</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
<property>
<name>hbase.zookeeper.quorum</name>
<value>localhost</value>
</property>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>hbase.zookeeper.property.clientPort</name>
<value>2181</value>
</property>
<property>
<name>hbase.zookeeper.property.dataDir</name>
<value>/home/hduser/hbase/zookeeper</value>
</property>
<property>
<name>zookeeper.znode.parent</name>
<value>/hbase</value>
</property>
<property>
<name>hbase.master</name>
<value>hadoop-master:60000</value>
</property>
</configuration>
and my running java process are
7415 DataNode
7262 NameNode
9119 Jps
7605 SecondaryNameNode
7893 NodeManager
8704 HRegionServer
8544 HMaster
8475 HQuorumPeer
7763 ResourceManager
Simply you should add the address of your server here localhost to your command. Pay attention to command you've already run, sqlline.py localhost that you gave the server address.
Are you using the HDP distribution? iirc they use /hbase-unsecure or for un-Kerberized clusters. I don't remember how it interacted with your config setting for /hbase
start the ZooKeeper cli
zkCli.sh or perhaps some variant of zookeepershell
query the existing root nodes
ls /
the HBase root node is probably named hbase-unsecure
I tried to run simple word count as MapReduce job. Everything works fine when run locally (all work done on Name Node). But, when I try to run it on a cluster using YARN (adding mapreduce.framework.name=yarn to mapred-site.conf) job hangs.
I came across a similar problem here:
MapReduce jobs get stuck in Accepted state
Output from job:
*** START ***
15/12/25 17:52:50 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
15/12/25 17:52:51 WARN mapreduce.JobResourceUploader: Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
15/12/25 17:52:51 INFO input.FileInputFormat: Total input paths to process : 5
15/12/25 17:52:52 INFO mapreduce.JobSubmitter: number of splits:5
15/12/25 17:52:52 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1451083949804_0001
15/12/25 17:52:53 INFO impl.YarnClientImpl: Submitted application application_1451083949804_0001
15/12/25 17:52:53 INFO mapreduce.Job: The url to track the job: http://hadoop-droplet:8088/proxy/application_1451083949804_0001/
15/12/25 17:52:53 INFO mapreduce.Job: Running job: job_1451083949804_0001
mapred-site.xml:
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.job.tracker</name>
<value>localhost:54311</value>
</property>
<!--
<property>
<name>mapreduce.job.tracker.reserved.physicalmemory.mb</name>
<value></value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>1024</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>3000</value>
<source>mapred-site.xml</source>
</property> -->
</configuration>
yarn-site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<!--
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>3000</value>
<source>yarn-site.xml</source>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>500</value>
</property>
<property>
<name>yarn.scheduler.capacity.maximum-am-resource-percent</name>
<value>3000</value>
</property>
-->
</configuration>
//I the left commented options - they were not solving the problem
YarnApplicationState: ACCEPTED: waiting for AM container to be allocated, launched and register with RM.
What can be the problem?
EDIT:
I tried this configuration (commented) on machines: NameNode(8GB RAM) + 2x DataNode (4GB RAM). I get the same effect: Job hangs on ACCEPTED state.
EDIT2:
changed configuration (thanks #Manjunath Ballur) to:
yarn-site.xml:
<configuration>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>hadoop-droplet</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>hadoop-droplet:8031</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>hadoop-droplet:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>hadoop-droplet:8030</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>hadoop-droplet:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>hadoop-droplet:8088</value>
</property>
<property>
<description>Classpath for typical applications.</description>
<name>yarn.application.classpath</name>
<value>
$HADOOP_CONF_DIR,
$HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,
$HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,
$HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,
$YARN_HOME/*,$YARN_HOME/lib/*
</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce.shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/data/1/yarn/local,/data/2/yarn/local,/data/3/yarn/local</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/data/1/yarn/logs,/data/2/yarn/logs,/data/3/yarn/logs</value>
</property>
<property>
<description>Where to aggregate logs</description>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/var/log/hadoop-yarn/apps</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>50</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>390</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>390</value>
</property>
</configuration>
mapred-site.xml:
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>50</value>
</property>
<property>
<name>yarn.app.mapreduce.am.command-opts</name>
<value>-Xmx40m</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>50</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>50</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx40m</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx40m</value>
</property>
</configuration>
Still not working.
Additional info: I can see no nodes on cluster preview (similar problem here: Slave nodes not in Yarn ResourceManager )
You should check the status of Node managers in your cluster. If the NM nodes are short on disk space then RM will mark them "unhealthy" and those NMs can't allocate new containers.
1) Check the Unhealthy nodes: http://<active_RM>:8088/cluster/nodes/unhealthy
If the "health report" tab says "local-dirs are bad" then it means you need to cleanup some disk space from these nodes.
2) Check the DFS dfs.data.dir property in hdfs-site.xml. It points the location on local file system where hdfs data is stored.
3) Login to those machines and use df -h & hadoop fs - du -h commands to measure the space occupied.
4) Verify hadoop trash and delete it if it's blocking you.
hadoop fs -du -h /user/user_name/.Trash and hadoop fs -rm -r /user/user_name/.Trash/*
I feel, you are getting your memory settings wrong.
To understand the tuning of YARN configuration, I found this to be a very good source: http://www.cloudera.com/content/www/en-us/documentation/enterprise/latest/topics/cdh_ig_yarn_tuning.html
I followed the instructions given in this blog and was able to get my jobs running. You should alter your settings proportional to the physical memory you have on your nodes.
Key things to remember is:
Values of mapreduce.map.memory.mb and mapreduce.reduce.memory.mb should be at least yarn.scheduler.minimum-allocation-mb
Values of mapreduce.map.java.opts and mapreduce.reduce.java.opts should be around "0.8 times the value of" corresponding mapreduce.map.memory.mb and mapreduce.reduce.memory.mb configurations. (In my case it is 983 MB ~ (0.8 * 1228 MB))
Similarly, value of yarn.app.mapreduce.am.command-opts should be "0.8 times the value of" yarn.app.mapreduce.am.resource.mb
Following are the settings I use and they work perfectly for me:
yarn-site.xml:
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1228</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>9830</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>9830</value>
</property>
mapred-site.xml
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>1228</value>
</property>
<property>
<name>yarn.app.mapreduce.am.command-opts</name>
<value>-Xmx983m</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>1228</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>1228</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx983m</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx983m</value>
</property>
You can also refer to the answer here: Yarn container understanding and tuning
You can add vCore settings, if you want your container allocation to take into account CPU also. But, for this to work, you need to use CapacityScheduler with DominantResourceCalculator. See the discussion about this here: How are containers created based on vcores and memory in MapReduce2?
This has solved my case for this error:
<property>
<name>yarn.scheduler.capacity.maximum-am-resource-percent</name>
<value>100</value>
</property>
Check your hosts file on master and slave nodes. I had exactly this problem. My hosts file looked like this on master node for example
127.0.0.0 localhost
127.0.1.1 master-virtualbox
192.168.15.101 master
I changed it like below
192.168.15.101 master master-virtualbox localhost
So it worked.
These lines
<property>
<name>yarn.nodemanager.disk-health-checker.max-disk-utilization-per-disk-percentage</name>
<value>100</value>
</property>
in the yarn-site.xml solved my problem since the node will be marked as unhealthy when disk usage is >=95%. Solution mainly suitable for pseudodistributed mode.
You have 512 MB RAM on each of the instance and all your memory configurations in yarn-site.xml and mapred-site.xml are 500 MB to 3 GB. You will not be able to run any thing on the cluster. Change every thing to ~256 MB.
Also your mapred-site.xml is using framework to by yarn and you have job tracker address which is not correct. You need to have resource manager related parameters in yarn-site.xml on a multinode cluster (including resourcemanager web address). With out that, the cluster does not know where your cluster is.
You need to revisit both your xml files.
anyway that's work for me .thank you a lot! #KaP
that's my yarn-site.xml
<property>
<name>yarn.resourcemanager.hostname</name>
<value>MacdeMacBook-Pro.local</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>${yarn.resourcemanager.hostname}:8088</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>4096</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>2.1</value>
that's my mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
The first thing is to check yarn resource manager logs. I had searched the Internet about this problem for a very long time, but nobody told me how to find out what is really happening. It's so straightforward and simple to check yarn resource manager logs. I am confused why people ignore logs.
For me, there was a error in log
Caused by: org.apache.hadoop.net.ConnectTimeoutException: 20000 millis timeout while waiting for channel to be ready for connect. ch : java.nio.channels.SocketChannel[connection-pending remote=172.16.0.167/172.16.0.167:55622]
That's because I switched wifi network in my work place, so my computer IP changed.
Old question, but I got on the same issue recently and in my case it was due to manually setting the master to local in the code.
Please, search for conf.setMaster("local[*]") and remove it.
Hope it helps.
I am using the latest hadoop version 3.0.0 build from source code. I have my timeline service up and running and have configured hadoop to use that for job history also. But when I click on history in the resoucemanager UI I get the below error:-
HTTP ERROR 404
Problem accessing /jobhistory/job/job_1444395439959_0001. Reason:
NOT_FOUND
Can someone please point out what I am missing here. Following is my yarn-site.xml:-
<configuration>
<!-- Site specific YARN configuration properties -->
<property>
<description>The hostname of the Timeline service web application.</description>
<name>yarn.timeline-service.hostname</name>
<value>0.0.0.0</value>
</property>
<property>
<description>Address for the Timeline server to start the RPC server.</description>
<name>yarn.timeline-service.address</name>
<value>${yarn.timeline-service.hostname}:10200</value>
</property>
<property>
<description>The http address of the Timeline service web application.</description>
<name>yarn.timeline-service.webapp.address</name>
<value>${yarn.timeline-service.hostname}:8188</value>
</property>
<property>
<description>The https address of the Timeline service web application.</description>
<name>yarn.timeline-service.webapp.https.address</name>
<value>${yarn.timeline-service.hostname}:8190</value>
</property>
<property>
<description>Handler thread count to serve the client RPC requests.</description>
<name>yarn.timeline-service.handler-thread-count</name>
<value>10</value>
</property>
<property>
<description>Indicate to ResourceManager as well as clients whether
history-service is enabled or not. If enabled, ResourceManager starts
recording historical data that Timelien service can consume. Similarly,
clients can redirect to the history service when applications
finish if this is enabled.</description>
<name>yarn.timeline-service.generic-application-history.enabled</name>
<value>true</value>
</property>
<property>
<description>Store class name for history store, defaulting to file system
store</description>
<name>yarn.timeline-service.generic-application-history.store-class</name>
<value>org.apache.hadoop.yarn.server.applicationhistoryservice.FileSystemApplicationHistoryStore</value>
</property>
<property>
<description>URI pointing to the location of the FileSystem path where the history will be persisted.</description>
<name>yarn.timeline-service.generic-application-history.fs-history-store.uri</name>
<value>/tmp/yarn/system/history</value>
</property>
<property>
<description>T-file compression types used to compress history data.</description>
<name>yarn.timeline-service.generic-application-history.fs-history-store.compression-type</name>
<value>none</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
</configuration>
and my mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>localhost:10200</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>localhost:8188</value>
</property>
<property>
<name>mapreduce.job.emit-timeline-data</name>
<value>true</value>
</property>
</configuration>
JPS output:
6022 NameNode
27976 NodeManager
27859 ResourceManager
6139 DataNode
6310 SecondaryNameNode
28482 ApplicationHistoryServer
29230 Jps
If you want to see the logs through YARN RM web UI, then you need to enable the log aggregation. For that, you need to set the following parameters, in yarn-site.xml:
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/app-logs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir-suffix</name>
<value>logs</value>
</property>
If you do not enable log aggregation, then NMs will store the logs locally. With the above settings, the logs are aggregated in HDFS at "/app-logs/{username}/logs/". Under this folder, you can find logs for all the applications run so far. Again the log retention is determined by the configuration parameter "yarn.log-aggregation.retain-seconds" (how long to retain the aggregated logs).
When the MapReduce applications are running, then you can access the logs from the YARN's web UI. Once the application is completed, the logs are served through Job History Server.
Also, set following configuration parameter in yarn-site.xml:
<property>
<name>yarn.log.server.url</name>
<value>http://{job-history-hostname}:8188/jobhistory/logs</value>
</property>
I run hbase in a distributed mode. Hbase starts region servers java processes on all nodes, but web ui doesn' show them
http://s1.ipicture.ru/uploads/20120517/16DXTnsU.png
here is hbase-site.xml
<configuration>
<property>
<name>hbase.zookeeper.quorum</name>
<value>10.3.6.44</value>
</property>
<property>
<name>hbase.zookeeper.property.dataDir</name>
<value>/home/hadoop/hdfs/zookeeper</value>
</property>
<property>
<name>hbase.rootdir</name>
<value>hdfs://10.3.6.44:9000/hbase</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
btw hadoop cluster is running normally and sees all the datanodes
thanks very much for your help.
problem was with dns and hosts file.
Add this property to your hbase-site.xml file and see if it works for you
name - hbase.zookeeper.property.clientPort
value - 2181