I am reading blogs and tutorials and noticed that the node that is configured on the masters file is also included in the name node, why are they including the secondary name node on the slaves file as well? A technical or conceptual explanation is very much appreciated
It is possible to configure both master processes and slave processes on the same node in a cluster. But it is not recommended in production. In production, you will not see the overlap between masters and slaves. However on single node Hadoop set up as well as small clusters for development, it is common to have overlap between master and slave processes.
Master processes: namenode, secondary namenode, resource manager, jobhistory server etc.
Slave processes: datanode, nodemanager etc.
If you have node as part of masters and based up on the ip address in core-site.xml and yarn-site.xml it will start namenode and resourcemanager respectively.
For slaves configuration files typically have 0.0.0.0 as ip address, so it will start both datanode as well as nodemanager on all the nodes that are defined as slaves (unless you exclude it).
Related
I have a multinode hadoop cluster setup. 1 master server and 25 slave nodes. The size of the master node is 2T whereas the slaves are 18T each. So I don't want a datanode in my master server because it may cause storage issues in the future. How can I configure that? I tried removing Master from slaves file in conf but it didn't work.
If you are using Ambari to manage your cluster you can decommission the datanode on your master node. I'm also concerned you only have 1 master node. But that's a problem for another day.
I have updated the /conf/slaves file on the Hadoop master node with the hostnames of my slave nodes, but I'm not able to start the slaves from the master. I have to individually start the slaves, and then my 5-node cluster is up and running. How can I start the whole cluster with a single command from the master node?
Also, SecondaryNameNode is running on all the slaves. Is that a problem? If so, how can I remove them from the slaves? I think there should only be one SecondaryNameNode in a cluster with one NameNode, am I right?
Thank you!
In Apache Hadoop 3.0 use $HADOOP_HOME/etc/hadoop/workers file to add slave nodes one per line.
I'm trying to set up and use a 4-node Hadoop cluster.
Setting up seems to go fine, as everything is running in the master and slave nodes.
Master: DataNode, ResourceManager, SecondaryNameNode, NameNode, NodeManager
Slaves: NodeManager, DataNode
Also, the logs show no errors. When I try to run my code however, it takes roughly the same amount of time as when I run it on a single node. Also, there is no increased CPU activity on any of the slave nodes.
Slaves can ssh to the master node, master node is listening at the correct port, ...
Any help on how I can track down the problem?
Thanks!
OS: Ubuntu 14.04.2
Hadoop version: 2.6.0
I have seen related questions, but they were no help to me:
hadoop cluster is using only master node or all nodes
Hadoop use only master node for processing data
Basically you have only one datanode and two nodemangers. It not much great configuration compared to single node cluster. To check whats happen you can goto resource manager UI . By default its on port 8088.
I am setting up hadoop on a multinode cluster, and I have a few questions:
Will it be ok to have NameNode and ResourceManager on the same machine?
Which will be the best role for a master system, NameNode, ResourceManager Or DataNode/NodeManager?.
I have a master and 3 slave machines. The slaves file on the master machine has the following entries:
master
slave1
slave2
slave3
Do I have to place this same slaves file in all of the slave machines? Or should I remove the first line (master) and then place it in the slave machines?
Best Regards.
Yes, at least in small clusters those two should be running in the master node.
Check answer 1. Master node can have also for example SecondaryNamenode and JobHistoryServer
No, the slaves file is only on the master node. If you have the master node in the slaves file, it means that the master node acts also as a datanode. Especially in small clusters that's totally fine. The slaves file essentially tells which on nodes the datanode processes are started.
Slave nodes should only run DataNode and NodeManager. But this is all handled by Hadoop if the configurations are correct - you can just check which processes are running after starting the cluster from the master node. Master node basically takes care of everything and you "never" need to manually connect to the slaves for any configurations.
My answer is meant for small clusters, probably in bigger "real" clusters the server responsibilities are even more separated.
For fully understand the multinode cluster concept follow this link-- http://bradhedlund.com/2011/09/10/understanding-hadoop-clusters-and-the-network/
and for implemtation of multinode cluster step vise follow this link --
http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-multi-node-cluster/
May these links help you
I've setup a Hadoop 2.5 cluster with 1 master node(namenode and secondary namenode and datanode) and 2 slave nodes(datanode).All of the machines use Linux CentOS 7 - 64bit. When I run my MapReduce program (wordcount), I can only see that master node is using extra CPU and RAM. Slave nodes are not doing a thing.
I've checked the logs from all of the namenode and there is nothing wrong on slave nodes. Resource Manager is running and all of the slave nodes can see the Resource Manager.
Datanodes are working in terms of distributed data storing but I can't see any indication of distributed data processing. Do I have to configure the xml configuration files in some other way so all of the machines will process data while I'm running my MapReduce Job?
Thank you
Make sure you are mentioaning the IP's Addresses of the daanodes on the Masternode networking files. Also each node in the cluster is supposed to contain IP address of the other machines.
Besides that check the includes file if it contains the relevant datanodes entry onto it or not.