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Data query method and device, electronic equipment and storage medium

A data query and metadata technology, applied in the field of big data management, can solve the problems of increasing database management and maintenance costs, poor metadata flexibility, and poor scalability

Pending Publication Date: 2020-10-23
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The above-mentioned solution for querying data in the database by the business end has the following disadvantages: database tables need to be established in advance for each business requirement / scenario. Fixed relationship, poor scalability, and greatly increased database management and maintenance costs; when different business requirements / scenarios overlap, it is necessary to repeatedly create database tables for the intersection data, resulting in poor flexibility of metadata

Method used

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  • Data query method and device, electronic equipment and storage medium
  • Data query method and device, electronic equipment and storage medium
  • Data query method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0031] figure 1 It is a flowchart of a data query method provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of querying the target data requested by the business end in massive database resources. This method can be executed by a data query device, so The data query device is generally integrated in a terminal, and typically, the terminal can be a server. see figure 1 As shown, the data query method specifically includes the following steps:

[0032] Step 110: Receive a user analysis request sent by the service end, the user analysis request includes dimension data and at least one item of index data; each of the index data includes a field to be queried, and the dimension data includes a primary key field.

[0033] Specifically, see figure 2 A schematic diagram of the format of a user analysis request shown in FIG. figure 2 In the example, the dimension data includes two primary key fields, and the two primary key fields ar...

Embodiment 2

[0041] image 3 It is a flow chart of a data query method provided by Embodiment 2 of the present invention. On the basis of the above embodiments, this embodiment performs the step "determine from at least one physical table bound to the logical metadata that is related to the Dimension data matching physical table" has been optimized. The benefit of optimization is that it can accurately match the target physical table, thereby realizing fast query of the target data. see image 3 As shown, the data query method specifically includes the following steps:

[0042] Step 310: Receive a user analysis request sent by the service end, the user analysis request includes dimension data and at least one item of index data; each of the index data includes a field to be queried, and the dimension data includes a primary key field.

[0043] Step 320, for each of the index data, respectively determine whether there is logical metadata consistent with the current index data in at least ...

Embodiment 3

[0052] Image 6 It is a flow chart of a data query method provided by Embodiment 3 of the present invention. On the basis of the above embodiments, this embodiment performs the step "determine from at least one physical table bound to the logical metadata that is related to the Dimension Data Matching Physical Table" continued to be optimized, see Image 6 As shown, the data query method specifically includes the following steps:

[0053] Step 610: Receive a user analysis request sent by the service end, the user analysis request includes dimension data and at least one item of index data; each of the index data includes a field to be queried, and the dimension data includes a primary key field.

[0054] Step 620, for each of the index data, respectively determine whether there is logical metadata consistent with the current index data in at least one preset logical metadata, and if so, proceed to step 630, wherein each of the logical metadata is a field contained in at leas...

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Abstract

The invention discloses a data query method and device, electronic equipment and a storage medium. The method comprises the steps of receiving a user analysis request sent by a service end, wherein the user analysis request comprises dimension data and at least one item of index data, wherein each piece of index data comprises a to-be-queried field, and the dimension data comprises a primary key field; for each piece of index data, determining whether logic metadata consistent with the current index data exists in at least one piece of preset logic metadata or not; if yes, determining a physical table matched with the dimension data from at least one physical table bound with the logic metadata, and querying data from the determined physical table based on the current index data and the dimension data, wherein each logic metadata is a field contained in at least one existing physical table; and splicing the queried data and returning the spliced data to the service end. Through the technical scheme, the data management efficiency in the database is improved.

Description

technical field [0001] Embodiments of the present invention relate to big data management technologies, and in particular to a data query method, device, electronic equipment, and storage medium. Background technique [0002] With the rapid development of information technology, more and more data needs to be managed in big data platform products, and the increasing amount of data makes the management and use of these data more difficult. [0003] Currently, database technology is commonly used to store and manage data. The business side can query the data in the database. For different business requirements / scenarios (each business requirement / scenario corresponds to a business model, which is used to represent the data requested for query), different database tables need to be established in advance (this database table is called corresponding to the business model The physical model is used to represent the data source table where the requested query data resides and it...

Claims

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Application Information

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IPC IPC(8): G06F16/2455G06F16/248G06F16/22
CPCY02D10/00
Inventor 李毅星王哲文
Owner BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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