Access trend prediction based time series database cache management method

Abstract

The invention provides an access trend prediction based time series database cache management method. The method comprises: on the basis of providing a data access cache by a conventional database, establishing a time series database dual-cache mechanism; and in addition to a conventional cache, adding a prediction data cache for predicting pre-loading of access data to load the access data into a memory before data access so as to increase the query speed. The method is used for effectively managing the time series database data cache to improve the efficiency of data cache hitting and system data query. A system analyzes recent access data and predicts a data access trend, and the prediction data is loaded to increase the data access speed. The method is suitable for time series database data cache management and is used for improving the efficiency of time series database data query.

Description

technical field [0001] The invention relates to the field of time series databases, in particular to a time series database data cache management method based on access trend prediction. Background technique [0002] The time-series database is the basis of the Wide Area Measurement System (WAMS), and it can also be used in multiple systems such as substation monitoring, dispatching, DC, and stability control to meet its needs for storing massive and high-frequency data. In practical applications, time series databases store millisecond-level data, and the frequency of data access is high, and the amount of data accessed is large. To ensure access efficiency, an access cache is set in the database system to improve access efficiency. [0003] For data retrieval of time series database, it has the following characteristics: [0004] 1 Burst access to a large amount of data in a short period of time, and query a large amount of data at a certain measuring point in a certain p...

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Problems solved by technology

[0005] 2 Data access often has a continuous trend, such as querying the data of a certain measuring point for a period of time each time, and continuous access

[0008] However, this method is based on the data that has been used or retrieved at present, but the data access of the time series database often has obvious trends. For example, when querying the historical curve of a certain measuring point, it will be continuously retrieved for a period of time in a short period of time. The retrieved data is often not accessed repeatedly, and the data in adjacent time periods may be read continuously. Conventional caching methods often do not achieve good results.

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