I try to run HBase on Hadoop in fully distributed mode with two nodes. To start HBase I execute the script start-hbase.sh. The daemons on the master-node, where I execute the script run fine. But on the other node the startup fails:
node2.example.com: ksh: cd: /disk/node1/hbase-0.98.4-hadoop2 - No such file or directory
node2.example.com: ksh: /disk/node1/hbase-0.98.4-hadoop2/bin/hbase-daemon.sh: not found
Obviously this is because HBase thinks that the $HBASE_HOME-Path is the same on both machines. But this ist not the case (as you can see in the error-message) and I don't have the option to change that.
So here ist my question: Is it possible to say HBase that the $HBASE_HOME-directories are different for each machine?
I am using Hadoop 2.4.1 and HBase 0.98.4 on two FreeBSD machines.
As there where no answers for my question until now, I solved the problem by writing my own start-hbase.sh with the correct paths hardcoded in it. I found this solution and adapted it to hbase which config is very similar to hadoop. Its a bit of work for ten machines but works for my purpose.
Related
I am new to Hadoop and am trying to execute the WordCount Problem.
Things I did so far -
Setting up the Hadoop Single Node cluster referring the below link.
http://www.bogotobogo.com/Hadoop/BigData_hadoop_Install_on_ubuntu_single_node_cluster.php
Write the word count problem referring the below link
https://kishorer.in/2014/10/22/running-a-wordcount-mapreduce-example-in-hadoop-2-4-1-single-node-cluster-in-ubuntu-14-04-64-bit/
Problem is when I execute the last line to run the program -
hadoop jar wordcount.jar /usr/local/hadoop/input /usr/local/hadoop/output
Following is the error I get -
The directory seems to be present
The file is also present in the directory with contents
Finally, on a side note I also tried the following directory sturcture in the jar command.
No avail! :/
I would really appreciate if someone could guide me here!
Regards,
Paul Alwin
Your first image is using input from the local Hadoop installation directory, /usr
If you want to use that data on your local filesystem, you can specify file:///usr/...
Otherwise, if you're running pseudo distributed mode, HDFS has been setup, and /usr does not exist in HDFS unless you explicitly created it there.
Based on the stacktrace, I believe the error comes from the /app/hadoop/ staging directory path not existing, or the permissions for it are not allowing your current user to run commands against that path
Suggestion: Hortonworks and Cloudera offer pre-built VirtualBox images and lots of tutorial resources. Most companies will have Hadoop from one of those vendors, so it's better to get familiar with that rather than mess around with having to install Hadoop yourself from scratch, in my opinion
This question already has answers here:
How to use start-all.sh to start standalone Worker that uses different SPARK_HOME (than Master)?
(3 answers)
Closed 4 months ago.
I'm setting up a [somewhat ad-hoc] cluster of Spark workers: namely, a couple of lab machines that I have sitting around. However, I've run into a problem when I attempt to start the cluster with start-all.sh: namely, Spark is installed in different directories on the various workers. But the master invokes $SPARK_HOME/sbin/start-all.sh on each one using the master's definition of $SPARK_HOME, even though the path is different for each worker.
Assuming I can't install Spark on identical paths on each worker to the master, how can I get the master to recognize the different worker paths?
EDIT #1 Hmm, found this thread in the Spark mailing list, strongly suggesting that this is the current implementation--assuming $SPARK_HOME is the same for all workers.
I'm playing around with Spark on Windows (my laptop) and have two worker nodes running by starting them manually using a script that contains the following
set SPARK_HOME=C:\dev\programs\spark-1.2.0-worker1
set SPARK_MASTER_IP=master.brad.com
spark-class org.apache.spark.deploy.worker.Worker spark://master.brad.com:7077
I then create a copy of this script with a different SPARK_HOME defined to run my second worker from. When I kick off a spark-submit I see this on Worker_1
15/02/13 16:42:10 INFO ExecutorRunner: Launch command: ...C:\dev\programs\spark-1.2.0-worker1\bin...
and this on Worker_2
15/02/13 16:42:10 INFO ExecutorRunner: Launch command: ...C:\dev\programs\spark-1.2.0-worker2\bin...
So it works, and in my case I duplicated the spark installation directory, but you may be able to get around this
You might want to consider assign the name by changing SPARK_WORKER_DIR line in the spark-env.sh file.
A similar question was asked here
The solution I used was to create a symbolic link mimicking the master node's installation path on each worker node so when the start-all.sh executing on the master node does its SSH into the worker node, it will see identical pathing to run the worker scripts.
Example in my case, I had 2 Macs and 1 Linux machine. Both Macs had spark installed under /Users/<user>/spark however the Linux machine had it under /home/<user>/spark. One of the Macs was the master node so running the start-all.sh it would error each time on the Linux machine due to pathing (error: /Users/<user>/spark does not exist)).
The simple solution was to mimic the Mac's pathing on the Linux machine using a symbolic link:
open terminal
cd / <-- go to the root of the drive
sudo ln -s home Users <-- create a sym link "Users" pointing to the actual "home" directory.
Hi I am new to Hadoop.
Hadoop Version (2.2.0)
Goals:
Setup Hadoop standalone - Ubuntu 12 (Completed)
Setup Hadoop standalone - Windows 7 (cygwin being used for only sshd) (Completed)
Setup cluster with Ubuntu Master and Windows 7 slave (This is mostly for learning purposes and setting up a env for development) (Stuck)
Setup in relationship with the questions below:
Master running on Ubuntu with hadoop 2.2.0
Slaves running on Windows 7 with a self compiled version from hadoop 2.2.0 source. I am using cygwin only for the sshd
password less login setup and i am able to login both ways using ssh
from outside hadoop. Since my Ubuntu and Windows machine have
different usernames I have set up a config file in the .ssh folder
which maps Hosts with users
Questions:
In a cluster does the username in the master need to be same as in the slave. The reason I am asking this is that post configuration of the cluster when I try to use start-dfs.sh the logs say that they are able to ssh into the slave nodes but were not able to find the location "/home/xxx/hadoop/bin/hadoop-daemon.sh" in the slave. The "xxx" is my master username and not the slaveone. Also since my slave in pure Windows version the install is under C:/hadoop/... Does the master look at the env variable $HADOOP_HOME to check where the install is in the slave? Is there any other env variables that I need to set?
My goal was to use the Windows hadoop build on slave since hadoop is officially supporting windows now. But is it better to run the Linux build under cygwin to accomplish this. The question comes since I am seeing that the start-dfs.sh is trying to execute hadoop-daemon.sh and not some *.cmd.
If this setup works out in future, a possible question that I have is whether Pig, Mahout etc will run in this kind of a setup as I have not seen a build of Pig, Mahout for Windows. Does these components need to be present only on the master node or do they need to be in the slave nodes too. I saw 2 ways of running mahout when experimenting with standalone mode first using the mahout script which I was able to use in linux and second using the yarn jar command where I passed in the mahout jar while using the windows version. In the case Mahout/ Pig (when using the provided sh script) will assume that the slaves already have the jars in place then the Ubuntu + Windows combo does not seem to work. Please advice.
As I mentioned this is more as an experiment rather than an implementation plan. Our final env will be completely on linux. Thank you for your suggestions.
You may have more success going with more standard ways of deploying hadoop. Try out using ubuntu vm's for master and slaves.
You can also try to do a pseudo-distributed deployment in which all of the processes run on a single VM and thus avoid the need to even consider multiple os's.
I have only worked with the same username. In general SSH allows to login with a different login name with the -l command. But this might get tricky. You have to list your slaves in the slaves file.
At least at the manual https://hadoop.apache.org/docs/r0.19.1/cluster_setup.html#Slaves I did not find anything to add usernames. it might be worth trying to add -l login_name to the slavenode in the slave conf file and see if it works.
I am a student, interested in Hadoop and started to explore it recently.
I tried adding an additional DataNode in the pseudo-distributed mode but failed.
I am following the Yahoo developer tutorial and so the version of Hadoop I am using is hadoop-0.18.0
I tried to start up using 2 methods I found online:
Method 1 (link)
I have a problem with this line
bin/hadoop-daemon.sh --script bin/hdfs $1 datanode $DN_CONF_OPTS
--script bin/hdfs doesn't seem to be valid in the version I am using. I changed it to --config $HADOOP_HOME/conf2 with all the configuration files in that directory, but when the script is ran it gave the error:
Usage: Java DataNode [-rollback]
Any idea what does the error mean? The log files are created but DataNode did not start.
Method 2 (link)
Basically I duplicated conf folder to conf2 folder, making necessary changes documented on the website to hadoop-site.xml and hadoop-env.sh. then I ran the command
./hadoop-daemon.sh --config ..../conf2 start datanode
it gives the error:
datanode running as process 4190. stop it first.
So I guess this is the 1st DataNode that was started, and the command failed to start another DataNode.
Is there anything I can do to start additional DataNode in the Yahoo VM Hadoop environment? Any help/advice would be greatly appreciated.
Hadoop start/stop scripts use /tmp as a default directory for storing PIDs of already started daemons. In your situation, when you start second datanode, startup script finds /tmp/hadoop-someuser-datanode.pid file from the first datanode and assumes that the datanode daemon is already started.
The plain solution is to set HADOOP_PID_DIR env variable to something else (but not /tmp). Also do not forget to update all network port numbers in conf2.
The smart solution is start a second VM with hadoop environment and join them in a single cluster. It's the way hadoop is intended to use.
I am executing a simple Hadoop MapReduce program with HBase as an input and output.
I am getting the error:
java.lang.RuntimeException: org.apache.hadoop.hbase.client.NoServerForRegionException: Unable to find region for OutPut,,99999999999999 after 10 tries.
This exception appeared to us when there was difference in hbase version.
Our code was built with and running with 0.94.X version of hbase jars. Whereas the hbase server was running on 0.90.3.
When we changed our pom file with right version (0.90.3) of hbase jars it started working fine.
Query bin/hbase hbck and find in which machine Region server is running.
Make sure that all your Region server is up and running.
Use start regionserver for starting Region server
Even if Regionserver at the machine is started it may fail because of time sync.
Make sure you have NTP installed on all Regionserver nodes and HbaseMaster node.
As Hbase works on a key-value pair where it uses the Timestamp as the Index, So it allows a time skew less than 3 seconds.
Deleting (or move to /tmp) the WAL logs helped in our case:
hdfs dfs -mv /apps/hbase/data/MasterProcWALs/state-*.log /tmp