Skip to main content

Why it is better not to use VirtualBox(VMWare etc..)

Cons

1. VirtualBox can not use full 100% resources of PC. Your hadoop will not be as fast as you expect.

2. You have to start virtual nodes whenever your reboot your PC (unless if you made some auto-start scripts)

3. Several virtual nodes in the same PC can cause mismanagement of resources. If RAM usage of VirtualBox nodes exceeds the maximum then your PC just crashes.


Though, VirtualBox is a good starting point to build experimental hadoop environment.

Pros

1. You can create several nodes in the same PC (if you lack PCs)
2. VirtualBox has Export /Import features that helps you to do "Do once - Copy many" 
3. Do experiments by changing hardware features (add CPUs, reduce RAM etc..)

For learning hadoop VirtualBox can be helpful to build hadoop environment.
However, for production purpose it is better to avoid Virtualbox and use PC itself as a single node.


Comments

Popular posts from this blog

Three essential things to do while building Hadoop environment

Last year I setup Hadoop environment by using Cloudera manager. (Basically I followed this video tutorial :  http://www.youtube.com/watch?v=CobVqNMiqww ) I used CDH4(cloudera hadoop)  that included HDFS, MapReduce, Hive, ZooKeeper HBase, Flume and other essential components. It also included YARN (MapReduce 2) but it was not stable so I used MapReduce instead. I installed CDH4 on 10 centos nodes, and I set the Flume to collect twitter data, and by using "crontab" I scheduled the indexing the twitter data in Hive. Anyways, I want to share some of my experiences  and challenges that I faced. First, let me give some problem solutions that everyone must had faced while using Hadoop. 1. vm.swappiness warning on hadoop nodes It is easy to get rid of this warning by just simply running this shell command on nodes: >sysctl -w vm.swappiness=0 More details are written on cloudera's site 2. Make sure to synchronize time on all nodes (otherwise it will give error on n

NLP for Uzbek language

    Natural language processing is an essential tool for text mining in data analysis field. In this post, I want to share my approach in developing stemmer for Uzbek language.      Uzbek language is spoken by 27 million people  around the world and there are a lot of textual materials in internet in uzbek language and it is growing. As I was doing my weekend project " FlipUz " (which is news aggregator for Uzbek news sites) I stumbled on a problem of automatic tagging news into different categories. As this requires a good NLP library, I was not able to find one for Uzbek language. That is how I got a motive to develop a stemmer for Uzbek language.       In short,  Stemming  is an algorithm to remove meaningless suffixes at the end, thus showing the core part of the word. For example: rabbits -> rabbit. As Uzbek language is similar to Turkish, I was curious if there is stemmer for Turkish. And I found this: Turkish Stemmer with Snowball.  Their key approach was to u

NAT Traversal or how to make P2P on Android

Many of us used BitTorrent(or uTorrent) to download files on internet in a short time. Their download speed is high due to Peer-to-peer technology. That means, rather than downloading file from server, we are getting the file from another computer. But how two computers that have a local IP and are behind NAT, how they can connect each other? For that, NAT Traversal methodologies come for help. Note that there are mainly 2 types of NAT: Symmetrical(complex NATs:carrier-grade NAT) and Full (home network or small enterprises). let us consider Full NATs first. Methodologies of NAT traversal are: UPnP - old and hardware oriented method NAT-PMP (later succeeded by PCP)- introduced by Apple, also hardware oriented(i.e: not all routers have it, and even if it had, it is turned off by default) UDP Punching  - this is done by STUN which uses public server to discover NAT public IP & port TCP Punching -  similar to UDP punching but more complicated Symmetrical NATs are a big is