I'm new to hadoop and trying to monitor the working of a multi node cluster using ganglia, The setup of gmond is done on all nodes and ganglia monitor only on the master.However,there are hadoop metrics graphs only for the master node and just system metrics for slaves. Do these hadoop metrics on the master include the slave metrics as well?Or is there any mistake in configuration files? Any help would be appreciated.
I think you should read this in order to understand how metrics flow between master and slave.
However, I would like to brief that, in genral, hadoop based or hbase based metrics are directly emitted/ sent to the master server (By master server, I mean the server on which gmetad is installed). All other OS related metrics are first collected by gmond installed on the corresponding slave and then redirected to the gmond installed on the master server.
So, if you are not getting any OS related metrics of slave servers then there is some misconfiguration in your gmond.conf. To know more about how to configure ganglia, please read this. This has helped me and could help you for sure, if you go through carefully.
There is a mistake in your configuration files.
More precisely, in transmitting / collecting the data, whichever approach you use.
Related
I just installed new version of hadoop2, I wish to know if I config a hadoop cluster and it's brought up, how can I know if data transmission is failed, and there's a need for failover?
Do I have to install other components like zookeeper to track/enable any HA events?
Thanks!
High Availability is not enabled by default. I would highly encourage you to read the Hadoop documentation from Apache. (http://hadoop.apache.org/) It will give an overview of the architecture and services that run on a Hadoop cluster.
Zookeeper is required for many Hadoop services to coordinate their actions across the entire Hadoop cluster, regardless of the cluster being HA or not. More information can be found in the Apache Zookeeper documentation (http://zookeeper.apache.org/).
I made a spark application that analyze file data. Since input file data size could be big, It's not enough to run my application as standalone. With one more physical machine, how should I make architecture for it?
I'm considering using mesos for cluster manager but pretty noobie at hdfs. Is there any way to make it without hdfs (for sharing file data)?
Spark maintain couple cluster modes. Yarn, Mesos and Standalone. You may start with the Standalone mode which means you work on your cluster file-system.
If you are running on Amazon EC2, you may refer to the following article in order to use Spark built-in scripts that loads Spark cluster automatically.
If you are running on an on-prem environment, the way to run in Standalone mode is as follows:
-Start a standalone master
./sbin/start-master.sh
-The master will print out a spark://HOST:PORT URL for itself. For each worker (machine) on your cluster use the URL in the following command:
./sbin/start-slave.sh <master-spark-URL>
-In order to validate that the worker was added to the cluster, you may refer to the following URL: http://localhost:8080 on your master machine and get Spark UI that shows more info about the cluster and its workers.
There are many more parameters to play with. For more info, please refer to this documentation
Hope I have managed to help! :)
This time, we build a storm cluster and don't have a tool like cloudera manager to monitor the status of cluster except the storm ui, and send alert notice when the cluster is in bad status.
Please write linux scripts with some basic storm commands and zookeeper commands to ensure the health of your cluster.
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.
I am new to cloudera, I installed cloudera in my system successfully I have two doubts,
Consider a machine with some nodes already using hadoop with some data, Can we install Cloudera to use the existing Hadoop without made any changes or modifaction on data stored existing hadooop.
I installed Cloudera in my machine, I have another three machines to add those as clusters, I want to know, Am i want install cloudera in those three machines before add those machines as clusters ?, or Can we add a node as clusters without installing cloudera on that purticular nodes?.
Thanks in advance can anyone, please give some information about the above questions.
Answer to questions -
1. If you want to migrate to CDH from existing Apache Distribution, you can follow this link
Excerpt:
Overview
The migration process does require a moderate understanding of Linux
system administration. You should make a plan before you start. You
will be restarting some critical services such as the name node and
job tracker, so some downtime is necessary. Given the value of the
data on your cluster, you’ll also want to be careful to take recent
back ups of any mission-critical data sets as well as the name node
meta-data.
Backing up your data is most important if you’re upgrading from a
version of Hadoop based on an Apache Software Foundation release
earlier than 0.20.
2.CDH binary needs be installed and configured in all the nodes to have a CDH based cluster up and running.
From the Cloudera Manual
You can migrate the data from a CDH3 (or any Apache Hadoop) cluster to a CDH4 cluster by
using a tool that copies out data in parallel, such as the DistCp tool
offered in CDH4.
Other sources
Regarding your second question,
Again from the manual page
Important:
Before proceeding, you need to decide:
As a general rule:
The NameNode and JobTracker run on the the same "master" host unless
the cluster is large (more than a few tens of nodes), and the master
host (or hosts) should not
run the Secondary NameNode (if used), DataNode or TaskTracker
services. In a large cluster, it is especially important that the
Secondary NameNode (if used) runs on a separate machine from the
NameNode. Each node in the cluster except the master host(s) should
run the DataNode and TaskTracker services.
Additionally, if you use Cloudera Manager it will automatically do all the setup necessary i.e install the necessary selected components on the nodes in the cluster.
Off-topic: I had a bad habit of not referrring the manual properly. Have a clear look at it, it answers all our questions
Answer to your second question,
you can add directly, with installation few pre requisites like openssh-clients and firewalls and java.
these machines( existing node, new three nodes) should accept same username and password (or) you should set passwordless ssh to these hosts..
you should connect to the internet while adding the nodes.
I hope it will help you:)