I know it is a duplicate question but since the other questions did not have answers with it, I am reposting it. I have recently installed hadoop cluster using 2 VMs on my laptop. I could go and checkout port 50070 and under datanodes tab I can see only one data node, but I have 2 data nodes, one on master node and other on slave node. What could be the reasons?
Sorry, feels like it's been a time. But still I'd like to share my answer: the root cause is from hadoop/etc/hadoop/hdfs-site.xml: the xml file has a property named dfs.datanode.data.dir. If you set all the datanodes with the same name, then hadoop is assuming the cluster has only one datanode. So the proper way of doing it is naming every datanode with a unique name:
Regards, YUN HANXUAN
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I want to delete datanode from my hadoop cluster, but don't want to lose my data. Is there any technique so that data which are there on the node which I am going to delete may get replicated to the reaming datanodes?
What is the replication factor of your hadoop cluster?
If it is default which is generally 3, you can delete the datanode directly since the data automatically gets replicated. this process is generally controlled by name node.
If you changed the replication factor of the cluster to 1, then if you delete the node, the data in it will be lost. You cannot replicate it further.
Check all the current data nodes are healthy, for these you can go to the Hadoop master admin console under the Data nodes tab, the address is normally something link http://server-hadoop-master:50070
Add the server you want to delete to the files /opt/hadoop/etc/hadoop/dfs.exclude using the full domain name in the Hadoop master and all the current datanodes (your config directory installation can be different, please double check this)
Refresh the cluster nodes configuration running the command hdfs dfsadmin -refreshNodes from the Hadoop name node master
Check the Hadoop master admin home page to check the state of the server to remove at the "Decommissioning" section, this may take from couple of minutes to several hours and even days depending of the volume of data you have.
Once the server is shown as decommissioned complete, you may delete the server.
NOTE: if you have other services like Yarn running on the same server, the process is relative similar but with the file /opt/hadoop/etc/hadoop/yarn.exclude and then running yarn rmadmin -refreshNodes from the Yarn master node
I have installed a hadoop cluster with total 3 machines, with 2 nodes acting as datanodes and 1 node acting as Namenode and as well as a Datanode.
I wanted to clear certain doubts regarding hadoop cluster installation and architecture.
Here is a list of questions I am looking answers for----
I uploaded a data file around 500mb size in the cluster and then checked the hdfs report.
I noticed that the namenode I made is also occupying 500mb size in the hdfs, along with datanodes with a replication factor of 2.
The problem here is that I want the namenode not to store any data on it, in short i dont want it to work as a datanode as it is also storing the file I am uploading. So what is the way of making it only act as a Master Node and not like a datanode?
I tried running the command hadoop -daemon.sh stop on the Namenode to stop the datanode services on it but it wasnt of any help.
How much metadata does a Namenode generate for a filesize typically of 1 GB? Any approximations?
Go to conf directory inside your $HADOOP_HOME directory on your master. Edit the file named slaves and remove the entry corresponding to your name node from it. This way you are only asking the other two nodes to act as slaves and name node as only the master.
I have a Hadoop cluster with 1 Master and 5 slaves. Is there any way of submitting jobs to specific set of slaves? Basically what i am trying to do is benchmark my application with many possibilities. So after testing with 5 slaves, I would like to run my application with 4 slaves and then 3 slaves and so on.
Currently the only way I know of is decommissioning a slave and removing from the hadoop cluster. But that seems to be a tedious task. I was wondering if there is an easier approach so as to avoid removing a node from the cluster.
Thanks.
In hadoop/conf there is a file called 'slaves' here you can simply add or remove nodes, and then restart your dfs and mapred.
There is a setting that points to a file with a list of excluded hosts you can set in the mapred-site-xml. Though also a bit cumbersome, changing a single configuration value might be preferable physically decommissioning and recommissioning multiple nodes. You could prepare multiple host exclusion files in advance, change the setting and restart the mapreduce service. Restarting the mapreduce service is pretty quick.
In 0.23 this setting is named mapreduce.jobtracker.hosts.exclude.filename. This is a feature introduced in 0.21, though I believe the setting was named mapred.hosts.exclude then. Check what this setting is called for the version of Hadoop you are using.
For those who encounter this problem, comments from Alex and stackoverflow question will help in successfully decommissioning a node from hadoop cluster.
EDIT : Just editing files hdfs-site.xml and mapred-site.xml and executing hadoop dfsadmin -refreshNodes might put your datanode into decommissioning node status for a long time. So it is also necessary to change dfs.replication to an appropriate value.
I'm curious if you could essentially separate the HDFS filesystem from the MapReduce framework. I know that the main point of Hadoop is to run the maps and reduces on the machines with the data in question, but I was wondering if you could just change the *.xml files to change the configuration of what machine the jobtracker, namenode and datanodes are running on.
Currently, my configuration is a 2 VMs setup: one (the master) with Namenode, Datanode, JobTracker, Tasktracker (and the SecondaryNameNode), the other (the slave) with DataNode, Tasktraker. Essentially, what I want to change is have the master with NameNode DataNode(s), JobTracker, and have the slave with only the TaskTracker to perform the computations (and later on, have more slaves with only TaskTrackers on them; one on each). The bottleneck will be the data transfer between the two VMs for the computations of maps and reduces, but since the data at this stage is so small I'm not primarily concerned with it. I would just like to know if this configuration is possible, and how to do it. Any tips?
Thanks!
You don't specify this kind of options in the configuration files.
What you have to do is to take care of what kind of deamons you start on each machine(you call them VMs but I think you mean machines).
I suppose you usually start everything using the start-all.sh script which you can find in the bin directory under the hadoop installation dir.
If you take a look at this script you will see that what it does is to call a number of sub-scripts corresponding to starting the datanodes, tasktrackers and namenode, jobtracker.
In order to achive what you've said, I would do like this:
Modify the masters and slaves files as this:
Master file should contain the name of machine1
Slaves should contain the name of machine2
Run start-mapred.sh
Modify the masters and slaves files as this:
Master file should contain the machine1
Slaves file should contain machine1
Run start-dfs.sh
I have to tell you that I've never tried such a configuration so I'm not sure this is going to work but you can give it a try. Anyway the solution is in this direction!
Essentially, what I want to change is have the master with NameNode DataNode(s), JobTracker, and have the slave with only the TaskTracker to perform the computations (and later on, have more slaves with only TaskTrackers on them; one on each).
First, I am not sure why to separate the computation from the storage. The whole purpose of MR locality is lost, thought you might be able to run the job successfully.
Use the dfs.hosts, dfs.hosts.exclude parameters to control which datanodes can connect to the namenode and the mapreduce.jobtracker.hosts.filename, mapreduce.jobtracker.hosts.exclude.filename parameters to control which tasktrackers can connect to the jobtracker. One disadvantage of this approach is that the datanodes and tasktrackers are started on the nodes which are excluded and aren't part of the Hadoop cluster.
Another approach is to modify the code to have a separate slave file for the tasktracker and the datanode. Currently, this is not supported in Hadoop and would require a code change.
Please explain what's dfs.include file purpose and how to define it.
I've added a new node to the Hadoop cluster but it's not identified by the namenode. In one of the posts I found that dfs.include can resolve this issue.
Thank you in advance,
Vladi
Just including the node name in the dfs.include and mapred.include is not sufficient. The slave file has to be updated on the namenode/jobtracker. The tasktracker and the datanode have to be started on the new node and the refreshNodes command has to be run on the NameNode and the JobTracker to make them aware of the new node.
Here are the instructions on how to do this.
According to the 'Hadoop : The Definitive Guide'
The file (or files) specified by the dfs.hosts and mapred.hosts properties is different from the slaves file. The former is used by the namenode and jobtracker to determine which worker nodes may connect. The slaves file is used by the Hadoop control scripts to perform cluster-wide operations, such as cluster restarts. It is never used by the Hadoop
daemons.