Hadoop MapReduce is one of the popular framework for BigData analytics. MapReduce cluster is shared among multiple users with heterogeneous workloads. When jobs are concurrently submitted to the cluster, resources are shared among them so system performance might be degrades. The issue here is that schedule the tasks and provide the fairness of resources to all jobs. Hadoop supports different s...

Hadoop is a software framework that supports data intensive distributed application. Hadoop creates clusters of machine and coordinates the work among them. It include two major component, HDFS (Hadoop Distributed File System) and MapReduce. HDFS is designed to store large amount of data reliably and provide high availability of data to user application running at client. It creates multiple da...

Received Oct 10 th , 2012 Accepted Oct 31 th , 2012 Today, we‟re surrounded by data like oxygen. The exponential growth of data first presented challenges to cutting-edge businesses such as Google, Yahoo, Amazon, Microsoft, Facebook, Twitter etc. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for processing and...

Hadoop is one of open source software technology that is used for processing large amount of data across clusters of commodity servers in distributed manner. Mainly it is designed to provide high fault tolerance and scale up a single server to thousands numbers of machines. Hadoop uses Hadoop distributed file system (HDFS) which is open source implementation of Google File System (GFS) for data...

MapReduce is an implementation for processing large scale data parallelly. Actual benefits of MapReduce occur when this framework is implemented in large scale, shared nothing cluster. MapReduce framework abstracts the complexity of running distributed data processing across multiple nodes in cluster. Hadoop is open source implementation of MapReduce framework, which processes the vast amount o...

Apache Pig allows users to describe dataflows to be executed in Apache Hadoop. The distributed nature of Hadoop, as well as its execution paradigms, provide many execution opportunities as well as impose constraints on the system. Given these opportunities and constraints Pig must make decisions about how to optimize the execution of user scripts. This paper covers some of those optimization ch...

In order to obtain a real-time situational awareness about the specific behavior of target-of-interests out of huge-scale sensory data-set, this proposed work presents a generic sensor-oriented information system based on Hadoop cluster (SOIS-Hadoop). NoSQL database is used to store and manage the heterogeneous sensory data; Hadoop/MapReduce programming paradigm is employed to optimize the para...

The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economica...