Light-weight combination method based on log combination tree structure

Abstract

The invention discloses a light-weight combination method based on a log combination tree structure. The method disclosed by the invention is characterized in that sequenced key value pair tables with dynamic size changes are used in the log combination tree structure, and metadata of the lower-layer sequenced key value pair table is stored in an upper-layer sequenced key value pair table with an overlaid key value scope; according to the balance degree of each sequenced key value pair table layer in the log combination tree, corresponding sequenced key value pair tables are taken as cooperation objects; the metadata in the selected sequenced key value pair tables is combined, and the combined metadata and corresponding key value pair data are written into the lower-layer sequenced key value pair table with the overlaid key value scope through supplementation; key value scopes of the sequenced key value pair tables are adjusted, so loads of the sequenced key value pair tables on the same level could be balanced; and a subsection dichotomy search manner is used to conduct rapid and efficiency search of the key value pair data. The method has the advantages that the combination operation cost of the log combination tree can be reduced; write amplification can be reduced; and performance of the log combination tree structure can be enhanced.

Description

technical field [0001] The invention belongs to the technical field of information storage, and more specifically relates to a lightweight merging method based on a log merging tree structure. Background technique [0002] With the rapid development of information technology and the popularization of the Internet, the amount of data has increased by leaps and bounds, and the data storage scale and data access volume of application services have also increased. The availability requirements and performance requirements for database storage systems have also further increased. improve. Due to the clear requirements for the stored data structure, the traditional relational database cannot meet the high concurrent reading and writing requirements of the current service application, the high-efficiency storage and access requirements for massive data, and the high scalability and scalability of the database. High availability requirements. In order to solve such problems, non-r...

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Problems solved by technology

[0004] In the existing technology, although the log merge tree can provide good write performance, in order to maintain good read performance, it is necessary to continuously perform merge operations in the background to make the data orderly, which also makes the merge overhead of the log merge tree become The performance bottleneck in the key-value storage system based on log merge tree algorithm

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