REVIEW ON PERFORMANCE IMPROVEMENT OF HETEROGENEOUS HADOOP CLUSTER USING RANKING ALGORITHM

Enhancing technologies increases the use and growth of information technology. As we can see the growth of data which is increasing rapidly in every single minute. This exponential growth in data is one of the reason for the generation of rapid data. Stored data is processed to extract worth from inaccurate data to form a way for the parallel and distributed processing for Hadoop. All the nodes in Hadoop are assumed to be in homogeneous nature but it is not same as it looks like, in cloud different configuration systems are used which represents it logically. So data placement policy is used to distribute data on the basis of power of node. Dynamic block placement strategy is used in Hadoop, this strategy work as the distributing input data blocks to the nodes on the basis of its computing capacity. The proposed approach balance and reorganize the input data dynamically in accordance with each node capability in an heterogeneous nature. Data transfer time is reduced in the proposed approach with the improvement in performance. Block placement strategy, page ranking algorithm and sampling algorithm strategies are used in the proposed approach. The data placement strategy used works as decreasing the execution time and improving the performance of the clusters which are of heterogeneous nature. Big data are handled using Hadoop. Small files are handled using applications on Hadoop so that the issue of performance can be reduced on the Hadoop platform. Better performance improvement is shown in the proposed work.