Can a Hadoop Yarn instance manage nodes from different places on Earth, networks? Can it manage nodes that use different platforms?
Every note about Yarn I found tells that Yarn manages clusters, but if the app I deploy is written in Java then it should probably work on the nodes regardless of the nodes' hardware.
Similarly, Yarn seems general enough to support more than just a LAN.
YARN is not platform aware. It is also not aware about how application processes on different hosts communicate with each other to perform the work.
In the same time for YARN application master should be run as a command line - and thereof any node on the cluster with enough resources should be able to run it.
If not every platform is capable to run specific app master- then YARN should be aware on it. Today it can not, but I can imegine platform to be special kind of resource - and then YARN will select appropriate node
Regarding LAN if you have application master which knows how to manage job over several LAN - it is should be fine with YARN.
Related
I know that the similar question was asked Applications not shown in yarn UI when running mapreduce hadoop job?
but the answers did not solve my problems.
I am running Hadoop streaming on Linux 17.01. I setup a cluster with 3 nodes and 1 master node.
When I start Hadoop, I can access localhost:50070 to see other nodes (all nodes are alive).
However, I see no information in "Application" of localhost:8088
as well as by command "yarn application -list -appStates ALL".
Here is my configuration.
My yarn-site.xml (for all nodes)
Here is all processes on master node
The problems may due to yarn services are running on ipv6. However, I followed I followed this thread
https://askubuntu.com/questions/440649/how-to-disable-ipv6-in-ubuntu-14-04
to change all Yarn services to ipv4. However, still there is no tasks displayed on Yarn UI, even I can see all nodes in my cluster marked as "active" on Yarn UI.
So, I do not know why this happened. Do you have any suggestion?
Thank you very much.
I haven't typically seen YARN being configured for IPv4, but this property is added into the hadoop-env.sh
export HADOOP_OPTS="-Djava.net.preferIPv4Stack=true"
I'm sure you also add a similar variable into the yarn-env.sh for YARN_OPTS, I think
However, it's not really clear from the your question when / if you've even submitted an application for anything to appear
I have cluster of 3 Mesos slaves, where I have two applications: “redis” and “memcached”. Where redis depends on memcached and the requirement is both of the applications/services should start on same node instead of different slave nodes.
So I have created the application group and added the dependency properly in the JSON file. After launching the JSON file via “v2/groups” REST API, I observe that sometime both application group will start on same node but sometimes it will start on different slaves which breaks our requirement.
So intent/requirement is; if any application fails to start on a slave both the application should failover to other slave node. Also can I configure the JSON file to tell Marathon to start the application group on slave-1 (specific slave first) if it is available else start it on other slave in a cluster. Due to some reason if this application group will start on other slave can Marathon relaunch the application group to slave-1 if it is available to serve the request.
Thanks in advance for help.
Edit/Update (2):
Mesos, Marathon, and DC/OS support for PODs is available now:
DC/OS: https://dcos.io/docs/1.9/usage/pods/using-pods/
Mesos: https://github.com/apache/mesos/blob/master/docs/nested-container-and-task-group.md
Marathon: https://github.com/mesosphere/marathon/blob/master/docs/docs/pods.md
I assume you are talking about marathon apps.
Marathon application groups don't have any semantics concerning co-location on the same node and the same is the case for dependencies.
You seem to be looking for a Kubernetes like Pod abstraction in marathon, which is on the roadmap but not yet available (see update above :-)).
Hope this helps!
I think this should be possible (as a workaround) if you specify the correct app contraints within the group's JSON.
Have a look at the example request at
https://mesosphere.github.io/marathon/docs/generated/api.html#v2_groups_post
and the constraints syntax at
https://mesosphere.github.io/marathon/docs/constraints.html
e.g.
"constraints": [["hostname", "CLUSTER", "slave-1"]]
should do. Downside is that there will be no automatic failover to another slave that way. Still, I'd be curious why both apps need to specifically run on the same slave node...
I like to study about Hadoop multinode setup and installation, by referring the above tutorial I understand that single node cluster environment can be used as node for the multinode cluster
http://bigdatahandler.com/hadoop-hdfs/hadoop-multi-node-cluster-setup/
Currently I am learning Hadoop using Horton sandbox, can we use a sandbox system as a single node environment?
If not what is the difference between sandbox and traditional Hadoop cluster installation
The sandbox images (from Hortonworks and Cloudera) provide the user with a pre-configured development environment with all the usual tools already available and installed (pig, hive etc.). Since the image is a single "system" it is set-up such that the hadoop cluster is single-node: i.e. everything - HDFS, Hadoop map-reduce etc. - is local to that image. That is a massive benefit, as anyone who has set up a hadoop cluster will tell you! It allows you to get up-and-running with very little operational overhead.
What these sandboxes do not provide, however, is realistic cluster behaviour as you have only one node. But there other possibilities - tools such as Vagrant and Docker - that would allow you to do this (I have not tried it myself).
The big data handler link you shared seems to be about combining several of these standalone, inherently single-node "clusters" so that you have something more realistic. But I would guess setting this up so that YARN, Zookeeper and other services are not duplicated comes with a not insignificant challenge.
Hi i have a small doubt , I have started to use in my curiosity but now i have the following problem
My scenario is like this - i have 10 machines connected in LAN and i need to create Name Node in one system and Data Nodes in remaining 9 machines . So do i need to install Hadoop on all the 10 machines ?
For example i have ( 1.. 10 ) machines , where machine1 is Server and from machine(2..9) are slaves[Data Nodes] so do i need to install hadoop on all 10 machines ?
And i have searched a lot On Hadoop cluster network on commodity machine but i dint get any thing related to Installation [ that is configuration]. Some of them given like how to config and install Hadoop on own system but not on the clustered environment
Can any one help me ? and give me the detailed idea or article suggested links to do the above process
Thanks
Yes, you need Hadoop installed in every node and each node should have the services started as for appropriate for its role. Also the configuration files, present on each node, have to coherently describe the topology of the cluster, including location/name/port for various common used resources (eg. namenode). Doing this manually, from scratch, is error prone, specially if you never did this before and you don't know exactly what you're trying to do. Also would be good to decide on a specific distribution of Hadoop (HortonWorks, Cloudera, HDInsight, Intel, etc)
I would recommend use one of the many deployment solutions out there. My favorite is Puppet, but I'm sure Chef will do too.
A different (perhaps better?) alternative is to use Ambari, which is a Hadoop specialized deployment and administering solution. See Deploying and Managing Hadoop Clusters with AMBARI.
Some Puppet resources to get you started: Using Vagrant, Puppet, Testing & Hadoop
Please verify below tutorial
http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-multi-node-cluster/
Hope it helps
Yes hadoop needs to be there on all the computers
For clustered Environment please go through the video
I'm trying to get set up on the Amazon Cloud to run some hadoop MapReduce jobs but I'm struggling to successfully create a cluster. I have downloaded the ec2 files, have my certificates and keypair file, but I believe it's the AMIs that are causing me trouble. If I'm trying to run a cluster with a master node and n slave nodes, I start n+1 instances using standard compatible AMIs and then run the code "hadoop-ec2 launch-cluster name n" in the terminal. The master node is successful, but I get an error when the slave nodes start to launch, saying "missing parameter -h (AMI missing)" and I'm not entirely sure how to progress.
Also, some of my jobs will require an alteration in hadoops parameter settings (specifically the mapred-site.xml config file), is it possible to alter this file, and if so, how do I gain access to it? Is hadoop already installed on amazon machines, with this file accessible and alterable?
Thanks
Have you tried Amazon Elastic MapReduce? This is a simple API that brings up Hadoop clusters of a specified size on demand.
That's easier then to create own cluster manually.
But once the jobflow is finished by default it shuts the cluster down, leaving you with outputs on S3. If what you need is simply to do some crunching, this may be the way to go.
In case you need HDFS contents stored permanently (e.g. if you are running HBase on top of Hadoop) you may actually need own cluster on EC2. In this case you may find Cloudera's distribution of Hadoop for Amazon EC2 useful.
Altering Hadoop configuration on nodes it will start is possible using EC2 Bootstrap Actions:
Q: How do I configure Hadoop settings for my job flow?
The Elastic MapReduce default Hadoop configuration is appropriate for most workloads. However, based on your job flow’s specific memory and processing requirements, it may be appropriate to tune these settings. For example, if your job flow tasks are memory-intensive, you may choose to use fewer tasks per core and reduce your job tracker heap size. For this situation, a pre-defined Bootstrap Action is available to configure your job flow on startup. See the Configure Memory Intensive Bootstrap Action in the Developer’s Guide for configuration details and usage instructions. An additional predefined bootstrap action is available that allows you to customize your cluster settings to any value of your choice. See the Configure Hadoop Bootstrap Action in the Developer’s Guide for usage instructions.
About the way you are starting the cluster, please clarify:
If I'm trying to run a cluster with a master node and n slave nodes, I start n+1 instances using standard compatible AMIs and then run the code "hadoop-ec2 launch-cluster name n" in the terminal. The master node is successful, but I get an error when the slave nodes start to launch, saying "missing parameter -h (AMI missing)" and I'm not entirely sure how to progress.
How exactly you are trying start it? What exactly AMIs are you using?