{'fraction_non_alphanumeric': 0.013777267508610792, 'fraction_numerical': 0.0, 'mean_word_length': 5.0979020979020975, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Survey on Implementation of Word-Count with Map Reduce Programming Oriented Model Using Hadoop Framework

In today’s era, data generation has been increasing continuously due to development of various technologies as well as increasing social networks online and cloud computing, it has been a big task for storing, processing, and analysing a huge amount of data. Hadoop and HDFS which was given by Apache is commonly used for the purpose of Big Data storage and management. Processing these large volume of data on the distributed networks consisting of hardware clusters forming Clouds system requires a model that provide computation such as Hadoop Map Reduce. In this paper, we explain the concept of big data and Map Reduce programming model along with its function and implementation of word-count with Map Reduce in distributed computing using Hadoop Framework.