CN116340354A

CN116340354A - Data query method, device, computer equipment and computer readable storage medium

Info

Publication number: CN116340354A
Application number: CN202310239759.4A
Authority: CN
Inventors: 张黎明; 符勇; 黄志洪; 吴海鹏
Original assignee: Kingdee Software China Co Ltd
Current assignee: Kingdee Software China Co Ltd
Priority date: 2023-03-06
Filing date: 2023-03-06
Publication date: 2023-06-27
Also published as: WO2024183311A1

Abstract

The application relates to a data query method, a data query device, computer equipment and a computer readable storage medium. Comprising the following steps: responding to a starting instruction to acquire current node information, a target node father category identifier and a node association list, wherein the current node category identifier comprises a current father category identifier and a current sub-category identifier, and the node association list is generated by traversing each node path and node category identifiers of each node in a data map corresponding to the current node information; determining adjacent node information corresponding to the current node information according to the association relation; generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification; and inquiring the node association list based on the inquiry instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information. By adopting the method, the data query efficiency can be effectively improved.

Description

Data query method, device, computer equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a data query method, a data query device, a computer device, and a computer readable storage medium.

Background

With the development of computer technology, the data storage scale of computer equipment is larger and larger, so how to quickly and efficiently complete data query operation is important when data query is performed on a database with a larger data storage scale.

In the prior art, the data in the database is traversed through the whole database according to the paths of all data nodes in sequence, so that the associated paths corresponding to all paths are stored, but the target data to be queried cannot be subjected to area positioning when the data query is performed, and the data query efficiency is low.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a data query method, apparatus, computer device, and computer readable storage medium, which can effectively improve the data query efficiency.

In a first aspect, the present application provides a data query method, including:

responding to a starting instruction to acquire current node information, a target node father category identifier and a node association list, wherein the current node information comprises a current node category identifier and association relations with other nodes, the current node category identifier comprises the current father category identifier and the current sub-category identifier, and the node association list is generated by traversing each node path and each node category identifier in a data map corresponding to the current node information;

Determining adjacent node information corresponding to the current node information according to the association relation, wherein the adjacent node information and the current node information are in a direct association relation;

generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification;

and inquiring the node association list based on the inquiry instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information.

In one embodiment, determining the neighboring node information corresponding to the current node information according to the association relationship includes:

determining an association path between the current node corresponding to the current node information and each association node in the data map according to the association relation;

when no other nodes exist on the associated path, determining the associated node as the adjacent node corresponding to the current node information, and acquiring the adjacent node information corresponding to the adjacent node.

In one embodiment, generating a query instruction according to the current parent category identifier, the current sub-category identifier, the neighboring node sub-category identifier corresponding to the neighboring node information, and the target node parent category identifier includes:

When the number of the target node father category identifications is at least two, generating batch inquiry instructions according to the current father category identifications, the current subcategory identifications, the adjacent node subcategory identifications corresponding to the adjacent node information and the father category identifications of all the target nodes;

inquiring the node association list based on the inquiry command to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information, wherein the method comprises the following steps:

carrying out batch inquiry on the node association list according to the batch inquiry instruction to obtain corresponding target node information, and determining target data according to the target node information;

and ordering and outputting the target data based on the association relation of the parent class identification of the target nodes.

In one embodiment, the query instruction is used for querying the node association list to obtain target node information corresponding to the target node father category identifier, and determining and outputting target data according to the target node information, including:

determining a first query range in a node association list according to the current parent category identification and the current sub-category identification;

determining a second query scope in the first query scope according to the adjacent node sub-category identification;

And determining corresponding target node information in a second query range according to the target node father category identification, and determining and outputting target data according to the target node information.

In a second aspect, the present application provides a data list generating method, including:

acquiring a data map corresponding to target data, and determining target data nodes according to the data map, wherein the data map at least comprises two data nodes with different data categories and association relations among the data nodes;

determining corresponding list column dimension based on total number of data categories of each data node in the data map;

traversing each node path of the data map based on the association relation among the data nodes, wherein the node path is determined by taking a target data node as a starting point and a corresponding data node as an ending point;

storing the data nodes on each node path into a list position matched with the data category corresponding to the list column dimension based on the corresponding data category, wherein each node path corresponds to the same row;

and generating a target data list corresponding to the data map until the storage of each node path in the data map is completed.

In one embodiment, storing data nodes on each node path in a list location matching a data category corresponding to a list column dimension based on the corresponding data category includes:

Inquiring the data category corresponding to each data node on each node path in sequence;

when the data category of the current data node is not matched with the data category corresponding to the list column dimension, adding the corresponding target data category in the target list column dimension according to the data category of the current data node, and storing the current data node in a list position corresponding to the target data category.

In a third aspect, the present application provides a data query apparatus, including:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for responding to a starting instruction to acquire current node information, target node father category identifiers and node association lists, the current node information comprises current node category identifiers and association relations with other nodes, the current node category identifiers comprise the current father category identifiers and the current sub category identifiers, and the node association lists are generated by traversing all node paths and node category identifiers of all nodes in a data map corresponding to the current node information;

the query instruction generation module is used for determining adjacent node information corresponding to the current node information according to the association relation, wherein the adjacent node information and the current node information are in a direct association relation; generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification;

And the query module is used for querying the node association list based on the query instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information.

In a fourth aspect, the present application provides a data list generating apparatus, including:

the data acquisition module is used for acquiring a data map corresponding to the target data and determining target data nodes according to the data map, wherein the data map at least comprises two data nodes with different data categories and association relations among the data nodes;

the data traversing module is used for determining corresponding list orientation dimensions based on the total number of data categories of each data node in the data map; traversing each node path of the data map based on the association relation among the data nodes, wherein the node path is determined by taking a target data node as a starting point and a corresponding data node as an ending point;

the list generation module is used for storing the data nodes on each node path into a list position matched with the data category corresponding to the dimension of the list column based on the corresponding data category, and each node path corresponds to the same row; and generating a target data list corresponding to the data map until the storage of each node path in the data map is completed.

In a fifth aspect, the present application provides a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program:

In a sixth aspect, the present application provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

In a seventh aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

In an eighth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

According to the data query method, the device, the computer equipment and the computer readable storage medium, the current node information, the target node father type identification and the node association list are obtained by responding to the starting instruction, the adjacent node information corresponding to the current node information is determined according to the association relation between the current node information and other node information in the data map, and then the query instruction is generated based on the current node type identification of the current node information, the adjacent node subcategory identification of the adjacent node and the target node father type identification, so that the query range of the target node subcategory identification in the node association list can be effectively reduced according to the query instruction, further the target data can be rapidly queried, and the data query efficiency is effectively improved.

Drawings

FIG. 1 is an application environment diagram of a data polling method in one embodiment;

FIG. 2 is a flow diagram of a method of data polling in one embodiment;

FIG. 3 is a flow diagram of determining neighbor node information for current node information in one embodiment;

FIG. 4 is a flow diagram of a batch query of multiple target data in one embodiment;

FIG. 5 is a flow chart illustrating steps according to querying target data in one embodiment;

FIG. 6 is a flow diagram of a method of data list generation in one embodiment;

FIG. 7 is a flow diagram of traversing a node path in one embodiment;

FIG. 8 is a block diagram of a data polling device in one embodiment;

FIG. 9 is a block diagram showing the structure of a data list generating apparatus in one embodiment;

FIG. 10 is a flow diagram of a method of generating a data list in one embodiment;

FIG. 11 is a schematic diagram of a data list generated in one embodiment;

fig. 12 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The data query method provided by the application can be applied to an application environment shown in fig. 1. As shown in fig. 1, the computer device 102 obtains, in response to a startup instruction, current node information, a target node parent category identifier, and a node association list, where the current node information includes a current node category identifier and an association relationship with other nodes, the current node category identifier includes a current parent category identifier and a current child category identifier, and the node association list is generated by traversing each node path and each node category identifier in a data map corresponding to the current node information; determining adjacent node information corresponding to the current node information according to the association relation, wherein the adjacent node information and the current node information are in a direct association relation; generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification; and inquiring the node association list based on the inquiry instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information. The computer device 102 may be, but not limited to, various personal computers, servers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like.

In one embodiment, as shown in fig. 2, a data query method is provided, and the method is applied to the computer device 102 in fig. 1 for illustration, and includes the following steps:

step S202, current node information, a target node father category identification and a node association list are obtained in response to the starting instruction.

The current node information comprises a current node category identifier and association relations with other nodes, the current node category identifier comprises current node position information, a current father category identifier and a current sub-category identifier, the node association list is generated by traversing each node path and each node category identifier in a data map corresponding to the current node information, each node in the data map has corresponding node information, and the node information comprises the position information and the node category identifier of the corresponding node.

Specifically, after receiving a starting instruction, the computer equipment acquires current node information corresponding to a current node corresponding to a current data query operation of a user, a target node father category identifier corresponding to the current node information and a node association list, wherein the target node is a data node to be queried.

Step S204, determining adjacent node information corresponding to the current node information according to the association relationship, wherein the adjacent node information and the current node information are in a direct association relationship.

The direct association relationship is that at least one direct association path is included between two node information, and the direct association path is that no other node is included in the association path between two nodes, for example, only the association path a-b-c exists to generate association, and therefore, the association path between the node a and the node c includes other node b, so that the node a and the node c are not in direct association relationship, and the node a and the node b, and the node b and the node c are all in direct association relationship.

Specifically, according to the current node information obtained in the previous step, the computer equipment determines the association path information of the current node information and other node information corresponding to the current node information in the data map, determines the node information which is in a direct association relationship with the current node information in the whole data map, and determines the node information which is in the direct association relationship with the current node information as adjacent node information corresponding to the current node information.

Step S206, generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification.

The query instruction is used for querying the sub-category identification of the target node in the node association list according to the current node information and the parent category identification of the target node.

Specifically, the computer equipment generates a first sub-segment corresponding to the query instruction according to the current parent category identification and the current sub-category identification, generates a second sub-segment corresponding to the query instruction according to the first sub-segment and the adjacent node information, and finally fuses the first sub-segment, the second sub-segment and the target node parent category identification to generate the query instruction.

Step S208, inquiring the node association list based on the inquiry instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information.

Specifically, the computer device determines a first query range corresponding to the current node information in the node association list according to a first sub-segment of the query instruction, then continues to determine a second query range corresponding to the current node information in the first query range according to a second sub-segment of the query instruction, finally queries corresponding target node information in the second query range according to the target node father category identification, and determines storage position information of corresponding target data according to the target node information and outputs the storage position information.

In this embodiment, the current node information, the target node parent class identifier and the node association list are obtained in response to the start instruction, the adjacent node information corresponding to the current node information is determined according to the association relationship between the current node information and other node information in the data map, and then the query instruction is generated based on the current node class identifier of the current node information, the adjacent node sub-class identifier of the adjacent node and the target node parent class identifier, so that the query range of the target node sub-class identifier in the node association list can be effectively narrowed according to the query instruction, and further the target data can be quickly queried, thereby effectively improving the data query efficiency.

In one embodiment, as shown in fig. 3, determining, according to the association relationship, neighboring node information corresponding to the current node information includes:

step S302, determining the association path between the current node corresponding to the current node information and each association node in the data map according to the association relation.

Specifically, the computer equipment reads the corresponding association relation in the current node information, and obtains the association path of the current node corresponding to the current node information and each association node in the data map according to the association relation between the current node information and other node information.

Step S304, when no other nodes exist on the associated path, determining that the associated node is the adjacent node corresponding to the current node information, and acquiring the adjacent node information corresponding to the adjacent node.

Specifically, the computer device traverses each association path corresponding to the current node determined in the previous step in turn, when no other node exists on the association path (i.e. only the current node and the corresponding termination point are included on a certain association path), determines the association path without other nodes as a direct association path, determines the corresponding nodes except the current node on the direct association path as neighboring nodes corresponding to the current node, and acquires neighboring node information corresponding to the neighboring nodes.

In this embodiment, the association path between the current node corresponding to the current node information and each associated node in the data map is determined according to the association relationship, then it is determined that the associated node is an adjacent node corresponding to the current node information when no other node exists on the association path, and the adjacent node information corresponding to the adjacent node is obtained, so that the adjacent node information corresponding to the current node information can be quickly determined according to the association relationship corresponding to each node information, and the efficiency of determining the adjacent node information is effectively improved.

In one embodiment, as shown in fig. 4, generating a query instruction according to the current parent category identifier, the current sub-category identifier, the neighboring node sub-category identifier corresponding to the neighboring node information, and the target node parent category identifier includes:

step S402, when the number of the target node father category identifications is at least two, generating batch inquiry instructions according to the current father category identifications, the adjacent node subcategory identifications corresponding to the current subcategory identifications, the adjacent node information and the father category identifications of each target node.

Specifically, when the computer equipment obtains the father category identifiers of a plurality of target nodes (at least two in number) at a time, a first sub-segment corresponding to the batch query instruction is generated according to the current father category identifier and the current sub-category identifier, a second sub-segment corresponding to the batch query instruction is generated according to the adjacent node sub-category identifier corresponding to the adjacent node information of the first sub-segment, and finally the first sub-segment, the second sub-segment and the father category identifier of the target nodes are fused to generate the batch query instruction.

And step S404, carrying out batch inquiry on the node association list according to the batch inquiry instruction to obtain each corresponding target node information, and determining each target data according to each target node information.

The batch inquiry instruction is used for batch inquiring target data corresponding to a plurality of target node information associated with the current node information in the node association list according to the current node information.

Specifically, the computer device may determine a first search range corresponding to the current node information in the node association list according to a first sub-segment corresponding to the batch of query instructions, determine a second search range in the first search range according to a second sub-segment corresponding to the batch of query instructions, and further determine target data corresponding to each target node information in the second search range according to each target node father category identifier.

Step S406, sorting and outputting the target data based on the association relation of the parent class identification of the target nodes.

The association relation of the father category identifiers of all the target nodes comprises the front-back relation of push-up and push-down of the target nodes and other nodes on the father category identifiers.

Specifically, the computer device performs batch query on the target data corresponding to the parent class identifier of each target node according to the batch query instruction determined in the previous step, sorts and outputs the queried target data according to the association relationship (push-up and push-down) corresponding to the parent class identifier of each target node.

In this embodiment, when the number of target node parent class identifiers is at least two, a batch query instruction is generated according to the current parent class identifier, the adjacent node child class identifiers corresponding to the current child class identifier and the adjacent node information, and each target node parent class identifier, a batch query is performed on the node association list according to the batch query instruction, so as to obtain each corresponding target node information, each target data is determined according to each target node information, and each target data is ordered and output based on the association relation of each target node parent class identifier, so that batch query on a plurality of target data according to the current node information can be realized, and the data query efficiency is effectively improved.

In one embodiment, as shown in fig. 5, the query instruction is used to query the node association list to obtain the target node information corresponding to the target node parent category identifier, and determine and output the target data according to the target node information, including:

step S502, determining a first query scope in the node association list according to the current parent category identification and the current sub-category identification.

Specifically, the computer device determines a corresponding column in which the current node information is located in the node association list according to a current parent category identifier corresponding to the current node information, determines a row in which the current node information is located in the corresponding column according to the current sub-category identifier, and determines a first query range according to the corresponding column and the row in which the current node information is located.

Step S504, determining a second query scope within the first query scope according to the adjacent node sub-category identification.

Wherein the second query scope is a subset of the first query scope.

Specifically, the computer device determines the first query scope according to the steps, and then determines the second query scope in the first query scope according to the adjacent node sub-category identification.

Step S506, corresponding target node information is determined in the second query range according to the target node father category identification, and target data is determined and output according to the target node information.

In this embodiment, a first query range is determined in the node association list according to the current parent category identifier and the current sub-category identifier, a second query range is determined in the first query range according to the adjacent node sub-category identifier, corresponding target node information is determined in the second query range according to the target node parent category identifier, and target data is determined and output according to the target node information, so that rapid query on the target node information according to the current node information and the target node parent category identifier is realized, the corresponding target data is further queried, the query range is effectively reduced, the targeted regional query effect is realized, and the data query efficiency is effectively improved.

In one embodiment, as shown in fig. 6, a data list generating method is provided, and the method is applied to the computer device 102 in fig. 1 for illustration, and includes the following steps:

step S602, a data map corresponding to the target data is obtained, and target data nodes are determined according to the data map, wherein the data map at least comprises two data nodes with different data categories and association relations among the data nodes.

The target data are source data corresponding to a data list to be generated, the data map comprises all data nodes corresponding to the target data and association relations and topological structures among the data nodes, and the data map at least comprises two data nodes with different data categories.

Specifically, after the computer device acquires a data map corresponding to the target data, one data node is arbitrarily determined in the data map and is used as the target data node.

In step S604, a corresponding list column dimension is determined based on the total number of data categories for each data node in the data graph.

The data category of each data node in the data map includes a corresponding parent category identifier and a sub-category identifier, where the parent category identifier is used to characterize attribute characteristics of target data of the corresponding data node, for example, the parent category identifier may be "sales order," "shipping notification," "sales delivery notification," "receipt-receivable," etc., and the sub-category identifier is used to identify specific target data location information under the parent category identifier. .

Specifically, the computer device determines the number of columns (column dimension) of the data list to be generated according to the data types of each data node in the data map, wherein the number of the data types is equal to the number of the column dimension of the list.

Step S606, traversing each node path of the data map based on the association relation among the data nodes, wherein the node path is determined by taking the target data node as a starting point and the corresponding data node as an ending point.

The node information corresponding to each data node comprises adjacent node information associated with the data node.

Specifically, the computer device determines each node path between each data node according to the association relationship between each data node in the data map.

Step S608, storing the data nodes on each node path in the list position matched with the data category corresponding to the dimension of the list column based on the corresponding data category, wherein each node path corresponds to the same row.

Step S610, until the storage of each node path in the data map is completed, generating a target data list corresponding to the data map.

In this embodiment, a data map corresponding to target data is obtained, a target data node is determined according to the data map, a corresponding list orientation dimension is determined based on the total number of data categories of each data node in the data map, each node path of the data map is traversed based on an association relationship between each data node, the data node on each node path is stored in a list position matched with the data category corresponding to the list orientation dimension based on the corresponding data category, node information on each node path corresponds to the same row of the data list until each node path in the data map is stored, and a target data list corresponding to the data map is generated, so that each data node corresponding to the target data is generated according to the association relationship (node path) between the data nodes and the data node type, and a data list in a corresponding format is generated.

In one embodiment, as shown in fig. 7, storing the data nodes on each node path into a list location matching the data category corresponding to the list column dimension based on the corresponding data category, includes:

step S702, query is performed on the data category corresponding to each data node on each node path in turn.

Specifically, the computer equipment traverses each data node on each node path in the data map in turn, and queries the data category of each node in turn according to the front-back order from the target data node as a starting point and the corresponding data node as an ending point.

Step S704, when the data category of the current data node is not matched with the data category corresponding to the dimension in the list direction, adding the corresponding target data category in the dimension in the target list direction according to the data category of the current data node, and storing the current data node in the list position corresponding to the target data category.

Specifically, the computer equipment inquires the data category of the current data node on the current traversing node path, when the data category of the current data node is not matched with the data category corresponding to the list direction dimension, the corresponding target data category is added in the target list direction dimension according to the data category of the current data node, and the current data node is stored in the list position corresponding to the target data category; when the data category of the current data node is matched with the data category corresponding to the column dimension of the list, the current data node is stored in the row and column positions corresponding to the column dimension of the list.

In this embodiment, by sequentially querying the data category corresponding to each data node on each node path, when the data category of the current data node is not matched with the data category corresponding to the column dimension of the list, adding the corresponding target data category in the column dimension of the target list according to the data category of the current data node, and storing the current data node in the column position corresponding to the target data category, in order to sequentially generate each column dimension of the data list and store the corresponding data node in the column position corresponding to the corresponding data list in the process of traversing each node path, thereby quickly generating the data list in the corresponding storage format and effectively improving the generation efficiency of the data list.

The application scenario also provides an application scenario, wherein the application scenario applies the data query method, and the method is applied to the scenario of querying the business document of the enterprise. Specifically, the application of the data query method in the application scene is as follows:

(1) Creating a document association list

The method comprises the steps that a computer device reads a data map corresponding to target source data, a target data node is determined in the data map, the target data node is used as a root node of the data map, a parent class identifier of the root node is used as a class attribute of a first column of a document association list to be generated, a termination point of a certain corresponding node is determined in the data map, the target data node is used as a starting point, each node path from the starting point to the termination point is traversed, then data classes (parent class identifiers) corresponding to the nodes on each path are sequentially queried, whether the parent class identifier of the current node can be matched with each column attribute in the document association list is judged, when the parent class identifier of the current node is matched with each column attribute in the document association list, current node information corresponding to the current node is stored in the position of the corresponding column of the document association list, and each node belonging to each node on each node path is guaranteed to be stored in the same row, when the parent class identifier of the current node is not matched with each column attribute of the document association list, corresponding column attribute of the current node is created in the association list, the current node is stored in the corresponding column attribute of the current node is stored in the corresponding node position, and the corresponding document path is further traversed to the data map 10, and the corresponding document path is further generated according to the specific document map is generated.

For example, assume that there is a node path: bill a, bill B, and bill C, in order to record their relationships, the information identifying the bill needs to be considered as a node, and each node stores a line of data. If node a's data is now known, node C needs to be found, node B needs to be found first, and then node C can be found based on node B's data. If there is a long roadmap or if there are different routes to reach node C and there is also uncertainty in the position of node C, then the complete route needs to be traversed one pass. The column dimension number output from the line to the column is fixed, and the node C is directly found according to the node A. Examples are as follows:

example 1, assume that there is a node path in the original node association list of the target source data: node a→node b→node C, as shown in table 1 below:

TABLE 1

Node A	Node A data
		Node B	Node B data
Node C	Node C data

The method of data storage is converted into a document association list stored in columns as shown in the following table 2:

TABLE 2

Node A	NodeB	Node C
			Node A data	Node B data	Node C data

Example 2, assume that there is a node path in the original node association list of the target source data: node a→node B1 and node B2→node C, as shown in table 3 below:

TABLE 3 Table 3

Node A	Node A data
		Node B	Node B1 data
Node B	Node B2 data
		Node C	Node C data

The method of data storage is converted into a document association list stored in columns as shown in the following table 4:

TABLE 4 Table 4

Node A	Node B	Node C
			Node A data	Node B1 data	Node C data
Node A data	Node B2 data	Node C data

(2) Querying business documents of enterprises:

the method comprises the steps that a computer device receives a starting instruction of data query, a bill association list corresponding to all business bills is obtained, current node information corresponding to the current business bills in a database is obtained according to bill information corresponding to the current known business bills, adjacent node information which is in direct association with the current node information is obtained according to the current node information, a first query range is locked in the bill association list according to a current father category identification and a subcategory identification in the current node information, a second query range is determined according to the subcategory identification in the adjacent node information, the second query range is contained in the first query range, finally, target node information is locked in the second query range according to a target node father category identification of target node information corresponding to the target business bills to be queried, further, target business is determined according to the guiding of the target node information, the target business bills are output and displayed, query operation of the whole business is completed, when the fatategory category identification of the current node is a sales order, the target node category identification shown in fig. 11 is queried and output according to a first column of sales order, and the target node category identification shown in fig. 11 is a shipping order.

In this embodiment, the current node information, the target node parent category identifier and the bill association list are obtained in response to the start instruction, the adjacent node information corresponding to the current node information is determined according to the association relationship between the current node information and other node information in the data map, and then the query instruction is generated based on the current node category identifier of the current node information, the adjacent node sub-category identifier of the adjacent node and the target node parent category identifier, so that the query range of the target node sub-category identifier in the bill association list can be effectively narrowed according to the query instruction, and further the target data can be quickly queried, thereby effectively improving the data query efficiency.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

In one embodiment, as shown in fig. 8, a data query device is provided, which may employ a software module or a hardware module, or a combination of both, as part of a computer apparatus, and specifically includes: an acquisition module 802, a query instruction generation module 804, and a query module 806, wherein:

an obtaining module 802, configured to obtain, in response to a startup instruction, current node information, a target node parent category identifier, and a node association list, where the current node information includes a current node category identifier and an association relationship with other nodes, the current node category identifier includes a current parent category identifier and a current sub-category identifier, and the node association list is generated by traversing each node path and each node category identifier in a data map corresponding to the current node information;

a query instruction generating module 804, configured to determine, according to the association relationship, neighboring node information corresponding to the current node information, where the neighboring node information and the current node information are in a direct association relationship; generating a query instruction according to the current parent category identification, the current sub-category identification, the adjacent node sub-category identification corresponding to the adjacent node information and the target node parent category identification;

The query module 806 is configured to query the node association list based on the query instruction, obtain target node information corresponding to the target node parent category identifier, and determine and output target data according to the target node information.

In one embodiment, the query instruction generating module 804 is further configured to determine, according to the association relationship, an association path between the current node corresponding to the current node information and each associated node in the data map; when no other nodes exist on the associated path, determining the associated node as the adjacent node corresponding to the current node information, and acquiring the adjacent node information corresponding to the adjacent node.

In one embodiment, the query instruction generating module 804 is further configured to generate, when the number of target node parent category identifiers is at least two, a batch query instruction according to the current parent category identifier, the current sub-category identifier, the neighboring node sub-category identifier corresponding to the neighboring node information, and each target node parent category identifier; carrying out batch inquiry on the node association list according to the batch inquiry instruction to obtain corresponding target node information, and determining target data according to the target node information; and ordering and outputting the target data based on the association relation of the parent class identification of the target nodes.

In one embodiment, the query module 806 is further configured to determine a first query scope in the node association list according to the current parent category identification, the current child category identification; determining a second query scope in the first query scope according to the adjacent node sub-category identification; and determining corresponding target node information in a second query range according to the target node father category identification, and determining and outputting target data according to the target node information.

According to the data query device, the current node information, the target node father category identification and the node association list are obtained in response to the starting instruction, the adjacent node information corresponding to the current node information is determined according to the association relation between the current node information and other node information in the data map, and then the query instruction is generated based on the current node category identification of the current node information, the adjacent node subcategory identification of the adjacent node and the target node father category identification, so that the query range of the target node subcategory identification in the node association list can be effectively reduced according to the query instruction, further the target data can be rapidly queried, and the data query efficiency is effectively improved.

For specific limitations of the data query device, reference may be made to the above limitation of the data query method, and no further description is given here. The various modules in the data querying device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, as shown in fig. 9, a data list generating apparatus is provided, which may use a software module or a hardware module, or a combination of both, as a part of a computer device, and the apparatus specifically includes: a data acquisition module 902, a data traversal module 904, a list generation module 906, wherein:

the data acquisition module 902 is configured to acquire a data map corresponding to the target data, and determine a target data node according to the data map, where the data map at least includes two data nodes with different data categories and an association relationship between the data nodes;

a data traversal module 904 configured to determine a corresponding list column dimension based on a total number of data categories for each data node in the data graph; traversing each node path of the data map based on the association relation among the data nodes, wherein the node path is determined by taking a target data node as a starting point and a corresponding data node as an ending point;

a list generating module 906, configured to store the data nodes on each node path, based on the corresponding data categories, in a list position matched with the data categories corresponding to the dimensions of the list column, where each node path corresponds to the same row; and generating a target data list corresponding to the data map until the storage of each node path in the data map is completed.

In one embodiment, the list generating module 906 is further configured to query the data class corresponding to each data node on each node path in turn; when the data category of the current data node is not matched with the data category corresponding to the list column dimension, adding the corresponding target data category in the target list column dimension according to the data category of the current data node, and storing the current data node in a list position corresponding to the target data category.

According to the data list generation device, the data map corresponding to the target data is obtained, the target data nodes are determined according to the data map, the corresponding list column direction dimension is determined based on the total number of data categories of all the data nodes in the data map, each node path of the data map is traversed based on the association relation among all the data nodes, the data nodes on each node path are stored in the list position matched with the data category corresponding to the list column direction dimension based on the corresponding data category, the node information on each node path corresponds to the same row of the data list until all the node paths in the data map are stored, and the target data list corresponding to the data map is generated, so that the data list in a corresponding format is generated according to the association relation (node path) among the data nodes and the data node types of all the data nodes, the data query operation based on the data list is simpler and more convenient, and the rationality of the data storage is effectively improved.

The specific limitation regarding the data list generating apparatus may be referred to the limitation regarding the data list generating method hereinabove, and will not be described herein. The respective modules in the above-described data list generating apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 12. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a data query method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, storing a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-described method embodiments.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A method of querying data, the method comprising:

responding to a starting instruction to acquire current node information, a target node father category identifier and a node association list, wherein the current node information comprises a current node category identifier and association relations with other nodes, the current node category identifier comprises a current father category identifier and a current sub-category identifier, and the node association list is generated by traversing each node path and each node category identifier in a data map corresponding to the current node information;

2. The method according to claim 1, wherein the determining the neighboring node information corresponding to the current node information according to the association relation includes:

determining an association path between the current node corresponding to the current node information and each association node in the data map according to the association relationship;

when no other nodes exist on the association path, determining that the association node is an adjacent node corresponding to the current node information, and acquiring the adjacent node information corresponding to the adjacent node.

3. The method of claim 1, wherein generating the query instruction based on the current parent category identification, the neighboring node child category identification corresponding to the current child category identification, the neighboring node information, and the target node parent category identification comprises:

inquiring the node association list based on the inquiry instruction to obtain target node information corresponding to the target node father category identification, and determining and outputting target data according to the target node information, wherein the method comprises the following steps:

performing batch inquiry on the node association list according to the batch inquiry instruction to obtain each corresponding target node information, and determining each target data according to each target node information;

and ordering and outputting the target data based on the association relation of the father class identification of the target nodes.

4. The method according to claim 1, wherein the querying the node association list based on the query instruction obtains target node information corresponding to the target node parent category identifier, and determines and outputs target data according to the target node information, including:

Determining a first query range in the node association list according to the current parent category identification and the current sub-category identification;

determining a second query range within the first query range according to the adjacent node subcategory identification;

and determining corresponding target node information in the second query range according to the target node father category identification, and determining and outputting target data according to the target node information.

5. A method of generating a data list, the method comprising:

traversing each node path of the data map based on the association relation among the data nodes, wherein the node paths are determined by taking the target data node as a starting point and the corresponding data node as an ending point;

6. The method of claim 5, wherein storing the data nodes on each node path in a list location matching the data category corresponding to the list column dimension based on the corresponding data category, comprises:

querying the data category corresponding to each data node on each node path in turn;

when the data category of the current data node is not matched with the data category corresponding to the dimension in the list direction, adding a corresponding target data category in the dimension in the target list direction according to the data category of the current data node, and storing the current data node in a list position corresponding to the target data category.

7. A data querying device, the device comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for responding to a starting instruction to acquire current node information, target node father category identifiers and node association lists, the current node information comprises current node category identifiers and association relations with other nodes, the current node category identifiers comprise current father category identifiers and current subcategory identifiers, and the node association lists are generated by traversing all node paths and node category identifiers of all nodes in a data map corresponding to the current node information;

8. A data list generation apparatus, the apparatus comprising:

the data acquisition module is used for acquiring a data map corresponding to target data and determining target data nodes according to the data map, wherein the data map at least comprises two data nodes with different data categories and association relations among the data nodes;

the data traversing module is used for determining corresponding list column dimension based on the total number of data categories of each data node in the data map; traversing each node path of the data map based on the association relation among the data nodes, wherein the node paths are determined by taking the target data node as a starting point and the corresponding data node as an ending point;

The list generation module is used for storing the data nodes on each node path into a list position matched with the data category corresponding to the list column dimension based on the corresponding data category, and each node path corresponds to the same row; and generating a target data list corresponding to the data map until the storage of each node path in the data map is completed.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 4 or 5 to 6 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 4 or 5 to 6.