Natural Language to Structured Query Language using Elasticsearch for descriptive columns


In the present day, data is captured in large amounts in the form of numbers, text, images etc. The data captured is either very simple to extract any useful information or it is very complex such that it takes a lot of time to generate information. In addition to this, data is being stored either in relational databases like MySQL, PostgreSQL or in document-oriented databases like MongoDB, Cassandra. The extraction of data from these databases requires some special knowledge of writing queries that are designed for that particular database. Hence there is a need for a system which extracts information from an input natural language query and convert it into a query which can be understood by the database in a fast and an efficient way. This paper proposes a way to create such a system by making use of Elasticsearch which is used for extracting data from descriptive columns. This paper is mainly focused on creating optimized SQL queries from natural language inputs using Elasticsearch where the extraction of data happens by means of searching through keywords present in input query throughout all the descriptive columns.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL