{'fraction_non_alphanumeric': 0.015360983102918587, 'fraction_numerical': 0.0, 'mean_word_length': 5.325242718446602, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Developing Method to Optimize Queries in Denormalized Databases

With the widespread implementation of information technologies in scientific, industrial, educational and other spheres of human activity, the task of effective processing of large amounts of data has become urgent. The rapid development of modern hardware has significantly increased the amount of memory for storing information, which in turn allows to use denormalized databases to increase the speed of query execution. The object under consideration is a database with materialized views. Materialized views are usually used in databases with a large volume (both in terms of the number of tables, records, and fields, and in terms of the total amount of information stored). Materialized views are an effective but narrow tool for increasing the speed of working with data. Since they actually speed up getting information for a single request. In this paper, we consider a method to construct alternative routes for query execution, which increase the possibility of using materialized views. It also describes a general query optimization scheme that is universal for optimizing query execution time in databases with materialized views. This schema can be applied to any database that has alternative routes for query execution.