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Cloud has been a computationaland storage solution for many data centric organizations . The problem today those organizations are facing from the cloud is in data searching in an efficient manner. A framework is required to distribute the work of searching and fetching from thousands of computers. The data in HDFS is scattered and needs lots of time to retrieve. The major idea is to design a web server in the map phase using the jetty web server which will give a fast and efficientway of searching data in MapReduce paradigm . For real time processing on Hadoop, a sear chable mechanism is implemented in HDFS by creatinga multilevel index in web server with multi-level index keys and indexing in DataNode. The web server uses to handle traffic throughput. By web clustering technology we can improve the application performance. To keep the work down, the load balancer should automatically be able to distribute load to the newly added nodes in the server.

Design an Efficient Big Data Analytic Architecture for Retrieval of Data Based on Web Server in Cloud Environment