YottaByte Me

Hadoop is nothing but a source of software framework that is generally used in the processing immense and bulk data simultaneously across many servers. In the recent years, it has turned out to be one of most viable option for enterprises, which has the never-ending requirement to save and manage all the data. Web based businesses such as Facebook, Amazon, eBay, and Yahoo have used high-end Hadoop applications to manage their large data sets. It is believed that Hadoop is still relevant to both small organizations as well as big time businesses.

Hadoop is able to process a huge chunk of data in a lesser time which enabled the companies to analyze that this was not possible before within that stipulated time. Another important advantage of the Hadoop applications is the cost effectiveness, which cannot be availed in any other technologies. One can avoid the high cost involved in the software licenses and the fees that has to be upgraded periodically when using anything apart from Hadoop. It is highly recommended for businesses, which have to work with huge amount of data, to go for Hadoop applications as it helps in fixing any issues.

Actually, Hadoop applications are made up of two parts; one is the HDFS, which means the Hadoop Distributed File System while the other is the Hadoop mapreduce that helps in the processing of data and scheduling of job depending upon the priority, which is a technique that initially originated in Google search engine. Along with these two primary components, there are nine other parts, which are decided as per the distribution one uses along with other complementary tools. There are three most common functions of Hadoop applications. The first function is the storage and analysis of all the data, which does not require the loading of the relational database management system. Secondly, it is used in the conversion of huge repository of semi-structured and unstructured data, for example a log file in the form of a structured data. Such complicated data are hard to understand in SQL tools like analyzing the graph and data mining.

Hadoop applications are mostly used in the web-related businesses wherein one has to work with big log files and data from the social network sites. When it comes to media or the advertising world, enterprises use Hadoop, which enables the best performance of ad offer analysis and help understand online reviews. Before using any Hadoop tool, it is advisable to read through the Hadoop map tutorials available online.

An Overview of MapReduce and Its Impact on Distributed Data Processing

Organizations collect many types of data about the processes they support: marketing, operational, activity logging, etc. For example, “click stream” and log data provide a record of the end user’s activity during past visits to a web site. Shopping cart data provides information on what items a customer intends purchase, and checkout data records the items eventually purchased. Companies like Amazon.com and Netflix provide examples of how information is used by organizations to enhanc

Price:

Find More MapReduce Products

Hadoop applications are software frameworks that enable distributed manipulation of large amount of data. Using this framework for data distribution is a reliable, efficient and scalable way. Hadoop system is reliable proves from the fact that it maintains several copies of working data to ensure that processing can be redistributed around failed nodes and work can be performed without any difficulty. As far as efficiency of the system is concerned, it works on the principle of parallelization that allows data to process in parallel to increase the processing speed. Furthermore, it is confirmed that Hadoop applications are scalable. Due to this reason it permits operations on petabytes of data. Now you must be thinking that this system is offering so many benefits, it would be costly. But you would be surprised to know that this application is inexpensive and is available for use by anyone.

If you want to understand the system and it functions more closely, it is important that you understand the Hadoop architecture. In simple language, it is a framework which works in combination with several elements. To start with, the first element is the Hadoop distributed file system (HDFS). As the name suggest it is a file system, so its function is the storage of various files across storage nodes in a Hadoop cluster. This file system lies at the bottom, above which Map reduce engine resides. Now in the Map reduce engine there are two main components – Job Trackers and Task Trackers. For the external client, HDFS appears to be a traditional hierarchical file system, which comprises of Meta data (also called NameNode) and several data nodes. Here files can be created, deleted, moved, renamed and so on.

In the Hadoop architecture, files are stored in HDFS which are divided into blocks and these blocks are replicated to multiple data nodes (computers). In comparison to the traditional RAID architectures, there is a huge difference in HDFS. Here all the operations are controlled by the NameNode. The protocol used for all the communications within HDFS is TCP/IP protocol. If you are interested in knowing about the major use of Hadoop applications then you must be thrilled to know that this technology is used primarily for web search. One of the most interesting aspects of this application is the Map and Reduce process, which is inspired by Google’s development. Using this system, the user can easily identify the data from the defined search parameters.

On the whole, it seems to be a very useful application which is meant for everyone.