Data querying method, device and system

Abstract

The invention discloses a data querying method, device and system, which are used for satisfying requirements on users for data range and querying frequency while querying data. The method comprises the following steps: a data querying server obtains a data querying condition provided by the user, and determining corresponding information according to the data querying condition; the data querying server determines a data querying policy according to the determined data information and sample data sampled from data managed by each region server of a data management system in advance based on a pre-set sampling rule, wherein the pre-set sampling rule is achieved as follows: data managed by all servers are sampled by correspondingly using pre-set sampling rates which are in ascending order according to descending order of time difference between the time when sampling the managed data and the time when generating the managed data; and the data querying server queries the data corresponding to the data information according to the determined data querying policy.

Description

technical field [0001] The invention relates to the technical field of computers and communications, in particular to a data query method, device and system. Background technique [0002] At present, in many industries, the amount of data to be managed and analyzed is extremely large, even reaching hundreds of terabytes or petabytes, such as bill data in the communication industry, network traffic data, etc. For such data, distributed files can be used system, or distributed semi-structured storage system and other data management systems (such as Hive, Pig, CloudBase, etc.) The only master node allocates the data managed by each node. Unlike traditional relational databases, the advantage of this type of system is that through the unique three-tier index architecture, it can realize high-speed data processing based on primary key operations. For example, for a certain A row of data corresponding to the primary key is added, deleted, modified, and a piece of data within the...

AI Technical Summary

Problems solved by technology

[0004] At present, the data query schemes based on sampling data provided in the prior art often only sample data within a certain period of time, for example, only sample recently generated data, or only sample historical data, and the existing The data query scheme provided by the technology does not take into account that users have different query frequencies for data generated in different periods when sampling data, so the data query scheme provided by the existing technology is difficult to meet the user's requirements when querying data. Data range and query frequency requirements

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