Quick data retrieval method and quick data retrieval system by novel Hash value table

Abstract

The invention discloses a quick data retrieval method and a quick data retrieval system by a novel Hash value table. In the method, a mapping table and a dynamic array are created; elements of the dynamic array include data and subscripts, and the mapping table is used for storing position indexes of the elements in the dynamic array; through the subscripts, the mapping relation between the mapping table and the dynamic array can be built, and operations such as adding, inquiring and deleting of the elements in the dynamic array can be realized. The system comprises a creating module and a retrieving module, and the retrieving module comprises an adding unit, an inquiring unit and a deleting unit. By the quick data retrieval method and the quick data retrieval system, frequent traversal and inquiry in linked-list operations are avoided, and time is effectively saved; particularly, for access operations on mass data, through the subscripts, Hash value conflict can be avoided, and operation objectives can be achieved quickly and accurately.

Description

technical field [0001] The invention relates to the field of data retrieval, in particular to a method and system for realizing fast data retrieval through a novel hash value table. Background technique [0002] The hash table is a fast element access and read array, mainly used in the field of fast data retrieval, because it is characterized by array positioning and access based on the hash value of the element, and its efficiency is very high. However, when the hash values ​​of multiple elements are the same, there will be a hash value conflict, that is, the corresponding array position can only store one element. The traditional method is to resolve the conflict through a linked list, but this method When adding, querying, and deleting, it is necessary to traverse the linked list, especially when the amount of data is huge, hash collisions will cause the length of the linked list to increase continuously. However, the traversal and query process of the linked list is ver...

AI Technical Summary

Problems solved by technology

However, when the hash values ​​of multiple elements are the same, there will be a hash value conflict, that is, the corresponding array position can only store one element. The traditional method is to resolve the conflict through a linked list, but this method When adding, querying and deleting, it is necessary to traverse the linked list, especially when the amount of data is huge, the hash collision will cause the length of the linked list to increase continuously

However, the traversal and query process of the linked list is very slow, so the traditional linked list method cannot efficiently solve the conflict of the hash table, and the efficiency is even lower when a large amount of data is accessed.

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