A STRUCTURE FOR HADOOP-COMPATIBLE PRIVATE DATA EVALUATION AND USE OF A BROAD ARRAY OF CLOUD IMAGE PROCESSORS FROM HADOOP ENVIRONMENT

New centuries of devices, images and personal information have strong energy and space but are behind in aspects of Big Data Storage and Cloud Processing software systems. Hadoop offers shared memory and computing capacities on commodity hardware cluster, a scalable platform. Most people use the internet to express their views and data on Facebook and Twitter. This huge and complex amount of information is called' big data,' because classical techniques cannot be processed. There are several spatial analysis tools in Hadoop, such as Pig, HBase, etc. But unstructured news is included in Internet data and social networking websites. The information on the image covers the entire range of press papers. The most significant problem is the processing of light-speed images, rather than the preservation of images. Every day approximately 350 million images are posted on the social network. So far, over 200 billion images have been published on Facebook alone. The average number of images per client is Approximately 200. This quantitude can be divided into 3 sixes-structured, semi-structured and unstructured-all produces around the world. The evaluation shows that the application addresses all the limitations of handling large amounts of information in motive clusters. Therefore, our scheme is an optional solution for increasing portable cloud processing requirements, but various cloud-based technologies, such as Google,