A Hierarchical Storage and Query Method Based on Key-Value Database

Abstract

The invention discloses a layering storage and inquiring method based on a key value database. The method includes the following implementation steps: constructing a layering key code naming rule and determining a comparison method between key codes; when executing a data storage request, determining the key code sequencing position of the data storage request according to the key code comparison method and inserting data into the key value database; when executing the data inquiring request, searching for a first greatest lower bound larger than or equal to all possible key codes under a target key code catalogue and utilizing the bound as a starting key code and returning all key values with the target key code as the beginning and results of sub catalogues as the data inquiring request from the starting key code. The method has high speed layering data storage and inquiring capability on the basis of traditional characteristics of the key value database, similar tree-shaped complex data can be effectively organized and stored, and the method can be used for storing data in the catalogue mode supporting massive files of a light distributive network file system.

Description

Technical field [0001] The invention relates to the technical field of key-value databases (Key-Value databases), in particular to a hierarchical storage and query method based on key-value databases. Background technique [0002] Compared with a typical SQL database, the key-value database (Key-Value database) is used to store unstructured key-value data, that is, the key code (ie Key) is used as an index to read, write, and write to the data record (ie Value) corresponding to the Key. Delete and other operations. Since the key-value database only cares about the process of indexing Value through the Key, and does not care about the structure and content of the specific data stored in the Value, compared to the SQL database, the key-value database has specific functions and high flat access data performance. , Distributed processing has the advantages of strong scalability. [0003] At present, the key-value database has a weak ability to express the structure of the data itself...

AI Technical Summary

Problems solved by technology

If you want to follow figure 1 As shown in the data organization, the score data of each classmate is stored hierarchically and classified, and the existing flat one-to-one storage mode of the key-value database is difficult to meet the storage requirements

[0005] 2. Existing key-value databases are difficult to query and iterate data at the same level

see figure 1 , if the key-value database stores the test scores of each person, the usual key-value pair description may be: , if we want to query which ones are in Class 1 When you are a student, although the key information in the above key-value database contains the answer to this question, the existing key-value database will be difficult to make queries

This is because the existing key-value database does not have a hierarchical storage structure, so it is only possible to query and extract information one by one by iterating all the keys in the entire database. The overall efficiency is relatively low and time-consuming

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