A Rapid Data Retrieval in Big Data Environment using HummingBird Algorithm

Abstract A Range Aggregate Query (RAQ) is a mechanism where the range servers are tenacious aggregate queries inquest information in numerous servers i.e. splitting the queries and inquest the information. Disparate data are cluster into single page. Data records are temperate and uploaded by the admin where the uploaded files are unstructured files; admin alone can recast the content and update it. Data records are stored in Hadoop Distributed File System (HDFS) which act as database. Balance Partitioning is done in numerous queries. If any queries are not found, redirection process takes place. Queries process in the format of m:n i.e. m aggregate columns and n index columns in a same record. Hummingbird algorithm is used to retrieve the queries accurately and efficiently. Irrelevant features are ejected from the database and elite inquest are appeared to the end user.