File data management method based on relational database and K-D tree indexes

Abstract

The invention discloses a file data management method based on a relational database and K-D tree indexes. The file data management method comprises the following steps that distribution storage is conducted on files with a consistent Hash algorithm, MD5 values of the files are regarded as Hash values of the files, a mapping relation between the Hash values and servers in a cluster is established, and thus the files with the different Hash values are distributed to the different servers; the relational database is established at a meta data management server side, and the structure of a file meta database table is designed; a multi-dimensional retrieval tree is established according to the number of fields of the file meta database table; corresponding inquiring is conducted according to types of inquiring requests received by the server side, and inquiring results are fed back. According to the file data management method based on the relational database and the K-D tree indexes, the relational database and the file indexes in an internal storage device are used, the usability of fuzzy retrieval is ensured, the high efficiency of range retrieval is also ensured, and the file data management method has important practical application value in the field of massive file data management.

Description

technical field [0001] The invention relates to a management method for massive file data, in particular to a file data management method based on a relational database and a K-D tree index. Background technique [0002] There are massive business data in large-scale enterprise applications that need to be managed. Among these document data, document data (including scanned documents, policies and regulations, etc.) account for the vast majority. How to design a reasonable and efficient document storage and management mechanism according to business characteristics is a very meaningful problem. [0003] Each business system that needs to be integrated has left a large amount of documents, and its management will encounter the following problems: (1) The amount of document data is large. Taking a district-level unit as an example, all the documents involved The total size has exceeded 5T, and the data volume is increasing by 2T per year. (2) There is no backup mechanism for...

AI Technical Summary

Problems solved by technology

[0003] Each business system that needs to be integrated has left a large amount of documents, and its management will encounter the following problems: (1) The amount of document data is large. Taking a district-level unit as an example, all the documents involved The total size has exceeded 5T, and the data volume is increasing by 2T per year

(2) There is no backup mechanism for files, and any security incident will result in the loss of files

(3) Documents are stored in the form of "file name + file path", which lacks an effective query mechanism, making it difficult to consult

(4) The storage efficiency of files and data is low. Some business systems store image files directly in the database, and the reading and writing of files must go through the SQL engine, so the storage efficiency is low

The business attributes of the file are entrusted to the upper application database management, resulting in a strong coupling between the file system and the application system

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