Benefits of Hadoop API

Hadoop or Apache Hadoop is an open-source software platform designed to deal with data intensive computations between dispersed computer nodes and applications. It employs commodity computing –where you use a myriad of available simple nodes to undertake parallel processing of a task, thereby reducing the latency period between task querying and response by the main node. Hadoop is composed of two component application systems:

First, The Hadoop Distributed File System (HDFS): is a form of parallel-clustered file system where a file system is concurrently mounted on a multiplicity of servers, which allows simultaneous data processing, faster computation performance and backup of data.

Second, MapReduce: is computational framework that divides a task into smaller work fragments to be executed by distributed computational processers. The principle at action here is that a mammoth task divided into several smaller tasks, each of which is assigned to a different computer –termed worker node, can be accurately processed faster. The answer provided by the worker nodes is then compiled into a finished task by the main node. The first part of the process where the application is divided and spread is termed the Map function. While the second part where finished smaller tasks are recombined into one finished the job by the central node is termed the Reduce function.

The benefits of Hadoop API are as follows:

· Reduced computational processing times by providing a much faster way of handling data processing in large data volume scenarios. The HDFS and MapReduce applications allow the processing of large data sets in much faster time. This benefit is seen in response times for internet search engines and the websites of large online traders where a query is computed in a short time.

· It provides redundancies for data and applications. By spreading an application and the associated file systems it creates an environment where data and application services are backed up. This prevents entire system failure in case of an error in any one of the various nodes that make up the system.

· It provides a basis for engineering data analytics especially on social media where the data content created is enormous. Data analytics is a subject that specializes in the analysis of generated data to provide user trends and information specifically for business purposes.

· It provides a formal structure for the organization, processing and manipulation of large databases generated in any environment in an efficient manner.