Statistical query method

Abstract

The embodiment discloses a statistical query method, which comprises: obtaining a statistical query request; analyzing a unit mode in the statistical query request, and dividing the unit mode into pre-calculation logic, aggregate calculation and post-calculation logic; carrying out calculation for data received during statistical query and calculation threads separately allocated to the pre-calculation logic, and producing an aggregate result set for the calculation threads separately allocated to the pre-calculation logic; and producing statistical query results through the post-calculation logic according to the aggregate result set after completion of aggregate calculation. In the embodiment, all data processing operations are completed on the background, and only the submission of statistical query requests and display of final results needs to be completed on the foreground. Therefore, data interaction between the foreground and the background is reduced, data processing operations on the foreground are also reduced, and thus the overall efficiency of the statistical inquiry is increased.

Description

technical field [0001] The invention relates to the field of databases, more specifically, to a statistical query method. Background technique [0002] When performing statistical query through a distributed database, the general operation mode is that the client sends the query request to each server, and the service process on each server returns the statistical data that meets the conditions and has been initially gathered to the client; the client After receiving the data transmitted by each server, the terminal performs further aggregation, dynamic column transposition, information expansion and other processing, and then generates and displays the data required by the user. [0003] In a distributed environment, the data is scattered in multiple servers, so the statistical query through the distributed database usually needs to summarize the stored data, transpose the rows and columns, translate the values, or merge the rows before generating the report. Wherein, when...

AI Technical Summary

Problems solved by technology

In this way, the server needs to transmit a large amount of data to the client, so that the client with limited resources undertakes a large amount of data interaction calculation work, which makes the operation efficiency and performance of the statistical query task low

[0004] In the existing technology, in order to solve the problem of low operating efficiency and performance of statistical query tasks, there is a way to use database interconnection SQL technology, but this method is more suitable for simple queries, complex statistical queries require multi-step Moreover, the SQL language cannot implement inter-row merging and row-column transposition processing, which requires complex program logic to complete, so efficient statistical queries cannot be performed

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