An Approach in Big Data Analytics to Improve the Velocity of Unstructured Data Using MapReduce

Big Data Analytics is an innovative approach for extracting the data from a huge volume of warehouse systems. It reveals method to compress high into clusters by MapReduce and HDFS. However, processing has taken more time extract store in Hadoop clusters. The proposed system deals with challenges delay shuffle phase map-reduce due scheduling sequencing. For improving speed big data, this work using Compressed Elastic Search Index (CESI) MapReduce-Based Next Generation Sequencing Approach (MRBNGSA). This helps increase retrieval HDFS because way it stored that. only metadata which takes less memory during runtime compare reduces CPU utilization allocation resource manager Framework imroves speed, such that be reduced minimum latency.