Big Data Query Processing Approach UsingMongoDB

Abstract

The “Big Data” phrase describes to the management of a wide range of organized and unstructured data with increasing speed and quantity. These datasets are conventional, large, and difficult to maintain. However, these datasets are used within a number of companies to perform various tasks on them as well as for organizational purposes and to provide a summary of the data currently being used. More precise and accurate business judgments can be make as a result of the growing volume of big data, which is now more affordable and available. The objective of this research paper is to demonstrate how to identify and use only the most significant and important data to be used in a follow-up investigation, help other researchers perform additional analysis, take into account only a limited number of data, ensuring that the study will always provide the best results. Although there are other methods and tools to extract data with certain filters. MongoDB uses the NoSQL model as the basis for query processing. To obtain data from a large data collection, query processing is used and it will continue to play an important role in future research and strategies for this work. The behaviour of extraction of data from Big Data and query processing on the bases input parameters that are going to use in Machine Learning. This process also termed as Data Mining which will show the behaviour of mining data from large amount of combine data. This paper show the behaviour implementation of Mongo DB on required parameter and will produce the efficient result.