Big Data Retrieval using HDFS with LZO Compression

Any type of organization depends on accurate data analytics to make better decisions. Users of these organizations request access from different resources like processes or executors. When processing this request of users, the data retrieval speed is low and also data is inaccurate for some conditions. To solve this issue, a system may be proposed having Hadoop Distributed File system (HDFS) with Lempel-Ziv-Oberhumer(LZO). The first step in the proposed technique is to retrieve and mine the data from respective database. The next step is to cluster the extracted data and optimize it using HDFS and LZO compression method. In the last step, if the compressed data is found similar to user requested data, the final data has to be visualized to the user. The proposed retrieving process in big data gives better performance and reduced execution time.