Adaptive indexing method and device

Abstract

The invention discloses an adaptive indexing method and an adaptive indexing device, and belongs to the database technology field. The adaptive indexing method includes: receiving an query request which carries range query conditions; obtaining at least one first result data block corresponding to the query request according to the range query conditions; sorting data in the at least one first result data block corresponding to the range query conditions, which is disordered and meets a preset price condition; updating a result data block set according to the result data blocks which are sorted and the other result data blocks which are not sorted, and updating an index of the result data block set. By using the adaptive indexing method and the adaptive indexing device, convergence rate of a database is improved on the premise that resource consumption is reduced during the early query process of the database.

Description

technical field [0001] The invention relates to the technical field of databases, in particular to a method and device for self-adaptive indexing. Background technique [0002] With the continuous development of database technology, adaptive index technology has been widely used. The self-adaptive indexing technology is a technology that builds an index through the query process in the database, and continuously updates and improves the index through the continuous query process to improve query efficiency. The types of queries in the database can include range data queries, fuzzy data queries, etc. Generally, in adaptive index technology, the index is established and improved during the range data query process. [0003] The HCC (Hyper Crack Crack, fast split) algorithm proposed in the article Merging What’s Cracked, Cracking What’s Merged: adaptive indexing in main memory column-stores, VLDB, 2011 is an adaptive indexing technology. Based on the HCC algorithm, at the ini...

AI Technical Summary

Problems solved by technology

[0007] The database using the HCC algorithm continuously updates the result data block set through range data query, and continuously updates the index of the result data block set to gradually improve the query efficiency of the database. However, although the data of each result data block recorded in the index range, which can improve the efficiency of locating the result data block. However, after the result data block is located through the index, the query efficiency is still relatively low when further data query is performed in the block, which leads to the slow convergence speed of the database using the HCC algorithm. , often cannot meet the needs of the application

In addition, although the database using the HCS algorithm has a fast convergence speed, in the early query process of the database, because the result data blocks need to be sorted, the query processing resources (such as time, processing resources, etc.) are seriously consumed.

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