I have seen HortonWorks put the full Hadoop inside a docker that allows to install Hadoop in different environments. But how about the individual apps inside Hadoop that run on YARN? Especially in a multi-tenant environment, this would be useful.
Appreciate any thoughts on how to achieve this.
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We are searching a viable way for provisioning a Hadoop ecosystem cluster with OpenShift (based on Docker). We look to build up a cluster using the services of the Hadoop ecosystem, i.e. HDFS, YARN, Spark, Hive, HBase, ZooKeeper etc.
My team has been using Hortonworks HDP for on-premise hardware but will now switch into a OpenShift-based infrastructure. Hortonworks Cloudbreak seems not to be suitable for OpenShift-based infrastructures. I have found this article that describes the integration of YARN into OpenShift but it seems like there are no further information available.
What is the easiest way to provision a Hadoop ecosystem cluster on OpenShift? Manually adding all the services feels error-prone and hard to administer. I have stumbled upon the Docker images of these separate services, but it is not comparable to the automated provisioning you get with a platform like Hortonworks HDP. Any guidance is appreciated.
If you install Openstack within Openshift, Sahara allows provisioning of Openstack Hadoop clusters
Alternatively, Cloudbreak is Hortonwork's tool for provisioning container based cloud deployments
Both provides Ambari, allowing you the same interface for cluster administration as HDP.
FWIW, I personally don't find the reason for putting Hadoop in containers. Your datanodes are locked to specific disks. There's no improvement in running several smaller ResourceManagers on a single host. Plus, for YARN, you'd be running containers within containers. And for the namenode, you must have a replicated Fsimage + Editlog because the container could be placed on any system
I want to use Big Data Analytics for my work. I have already implemented all the docker stuff creating containers within containers. I am new to Big Data however and I have come to know that using Hadoop for HDFS and using Spark instead of MapReduce on Hadoop itself is the best way for websites and applications when speed matters (is it?). Will this work on my Docker containers? It'd be very helpful if someone could direct me somewhere to learn more.
You can try playing with Cloudera QuickStart Docker Image to get started. Please take a look at https://hub.docker.com/r/cloudera/quickstart/. This docker image supports single-node deployment of Cloudera's Hadoop platform, and Cloudera Manager. Also this docker image supports spark too.
We are looking for the possibility of an automation script which we can give how many master and data nodes we need and it would configure a cluster. Probably giving the credentials in a properties file.
Currently our approach is to login to the console and configure the Hadoop cluster. It would be great if there could be an automated way around it.
I've seen this done very nicely using Foreman, Chef, and Ambari Blueprints. Foreman was used to provision the VMs, Chef scripts were used to install Ambari, configure the Ambari blueprint, and to create the cluster using the Blueprint.
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.
i am new to Hadoop ,i likes to go in hadoop administration line so studied basics of hadoop and tried to install hadoop in pseudo distribution mode and installed successfully and run some basic examples also, now i need to improve me further,so i need to try a way to learn hadoop installation and configuration in real time so decided to go for Amazon micro instance ,can any one please tell how to install and configure hadoop in Amazon cloud.
Thanks in Advance.
I have tried this personally and you will not really be able to use hadoop on a single micro instance due to memory restrictions. IMHO you should atleast try a medium instance to run hadoop or better yet use their elastic-mapreduce api which is a modified version of hadoop. You can run a 3 node cluster for around 00.25 cents an hour. If you really want to learn big data this is the way I went.
You should check out their documentation here
http://aws.amazon.com/documentation/elasticmapreduce/