CN110554958A - Graph database testing method, system, device and storage medium - Google Patents

Abstract

The present application discloses a graph database testing method, system, device and storage medium, wherein the method includes: generating graph data satisfying the target business scenario according to the requirements of the target business scenario; determining the test type for the graph database to be tested; and the graph data that meets the target business scenario, generate test data suitable for the test type; test the to-be-tested graph database according to the test data suitable for the test type. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios. The test function can cover the complex relationship of many scenarios, realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system.

Description

Graph database testing method, system, device and storage medium

technical field

The present application relates to the technical field of database testing, and in particular, to a graph database testing method, system, device, and computer-readable storage medium.

Background technique

Currently, graph databases are the fastest growing category of all data management systems. Through the graph format storage of nodes, attributes and edges, the graph database overcomes the large and complex data problems that other databases cannot solve, and has obvious advantages in dealing with complex problems. Its advantages are mainly reflected in: better and faster query and analysis; simpler and more natural data modeling; support for both real-time updates and queries; more flexible data structures. Therefore, more and more graph database-based products and analysis systems have emerged on the market.

For traditional databases, there are already some relatively mature functions and performance automation testing solutions and systems. Compared with traditional databases, graph databases have different scenarios for data modeling, storage, and expression applications, and the test solutions of traditional databases cannot be applied to the testing of graph databases. In addition, since the graph database belongs to the emerging database form that has become popular in recent years, there is no systematic testing method for this type of data.

Therefore, how to implement graph database testing has become an urgent problem to be solved.

SUMMARY OF THE INVENTION

The purpose of this application is to solve one of the technical problems in the related art at least to a certain extent.

Therefore, the first purpose of the present application is to propose a graph database testing method, which can solve the difficult problem of graph data testing, so as to realize the function of testing graph databases.

The second purpose of this application is to propose a graph database testing system.

The third purpose of this application is to propose a device based on the graph database testing method.

A fourth object of the present application is to propose a computer-readable storage medium.

In order to achieve the above purpose, an embodiment of the first aspect of the present application proposes a method for testing a graph database, including: generating graph data satisfying the target business scenario according to the requirements of a target business scenario; determining a test type for the graph database to be tested; Generate test data suitable for the test type according to the test type and the graph data that meets the target business scenario; test.

The graph database testing method of the embodiment of the present application generates graph data that meets the target business scenario according to the requirements of the target business scenario, determines the test type for the graph database to be tested, and generates graph data suitable for the target business scenario according to the test type and graph data that meets the target business scenario. Test data for the test type, and test the database to be tested according to the test data for the test type. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. .

In order to achieve the above purpose, a second aspect embodiment of the present application proposes a graph database testing system, including: a graph data generating module for generating graph data satisfying the target business scenario according to the requirements of the target business scenario; graph database testing The module is used to determine the test type for the graph database to be tested, and generate test data suitable for the test type according to the test type and the graph data that meets the target business scenario, and The test data of the test type is used to test the to-be-tested graph database.

The graph database testing system of the embodiment of the present application generates graph data satisfying the target business scenario according to the requirements of the target business scenario; determines the test type for the graph database to be tested; The graph data of the scene is generated to generate test data suitable for the test type; according to the test data suitable for the test type, the to-be-tested graph database is tested. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. .

In order to achieve the above purpose, an embodiment of the third aspect of the present application proposes a device based on a graph database testing method, including: a memory, a processor, and a computer program stored on the memory and running on the processor, When the processor executes the computer program, the graph database testing method described in the embodiments of the first aspect of the present application is implemented.

To achieve the above purpose, the fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the first aspect of the present application is implemented. The described graph database testing method.

Additional aspects and advantages of the present application will be set forth, in part, in the following description, and in part will be apparent from the following description, or learned by practice of the present application.

Description of drawings

The above and/or additional aspects and advantages of the present application will become apparent and readily understood from the following description of embodiments taken in conjunction with the accompanying drawings, wherein:

1 is a schematic flowchart of a graph database testing method according to a first embodiment of the present application;

2 is a schematic flowchart of a graph database testing method according to a second embodiment of the present application;

3 is a schematic flowchart of a graph database testing method according to a third embodiment of the present application;

4 is a schematic flowchart of a graph database testing method according to a fourth embodiment of the present application;

5 is a schematic structural diagram of a graph database testing system according to the first embodiment of the present application;

6 is a schematic structural diagram of a graph database testing system according to a second embodiment of the present application;

7 is a schematic structural diagram of a graph database testing system according to a third embodiment of the present application;

8 is a schematic structural diagram of a graph database testing system according to a fourth embodiment of the present application;

9 is a schematic structural diagram of a graph database testing system according to a fifth embodiment of the present application;

10 is a schematic structural diagram of a graph database testing system according to a sixth embodiment of the present application;

FIG. 11 shows a block diagram of a device suitable for implementing the graph database-based testing method of the embodiments of the present application.

Detailed ways

The following describes in detail the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary, and are intended to be used to explain the present application, but should not be construed as a limitation to the present application.

The graph database testing method, system, device, and computer-readable storage medium of the embodiments of the present application are described below with reference to the accompanying drawings. The graph database testing method of the embodiment of the present application can be applied to the graph database testing system of the embodiment of the present application, so that the graph database testing system can execute the graph database testing method. Wherein, the graph database testing system of the embodiment of the present application can be applied to any business scenarios relying on the graph database, for example, financial transaction scenarios, e-commerce transaction scenarios, network management scenarios, and the like.

FIG. 1 is a schematic flowchart of a graph database testing method according to an embodiment of the present application.

As shown in Figure 1, the graph database testing method includes the following steps:

Step 101 , according to the requirements of the target business scenario, generate graph data that meets the target business scenario.

It can be understood that the graph database testing system of the embodiment of the present application can be applied to any business scenarios relying on the graph database, for example, financial transaction scenarios, e-commerce transaction scenarios, network management scenarios, and the like. Therefore, the target business scenario is the business scenario that relies on the graph database for the application of the graph database test system.

In the embodiment of the present application, in order to facilitate the generation of the test data of the graph database, first, according to the requirements of the target business scenario, graph data satisfying the target business scenario can be generated. The graph data format that meets the target business scenario may include, but is not limited to, a CSV (Comma-Separated Values, comma-separated value) file format, a JSON (JavaScript ObjectNotation, JavaScript Object Notation) file format, and the like.

Optionally, as shown in FIG. 2 , according to the requirements of the target business scenario, the specific steps for generating graph data satisfying the target business scenario are as follows:

Step 201, according to the requirements of the target business scenario, obtain the configuration information required for generating the graph data; wherein, the configuration information includes the entity data schema definition information in the graph data, the scale definition information of each type of entity, the definition information of the story scenario template and Relationship density setting information.

In this embodiment of the present application, in order to facilitate the generation of graph data that meets the target business scenario, first, configuration information required for generating graph data may be obtained according to the requirements of the target business scenario; wherein the configuration information may include entity data patterns in the graph data Definition information, scale definition information for each type of entity, definition information for story scenario templates, and relationship density setting information. It can be understood that the configuration information can be pre-configured by those skilled in the art.

For example, the entity data schema definition information in the graph data in the configuration information may be customer information, account information, device information, etc.; the corresponding scale definition information for each type of entity may be that the scale of customer information is 500,000, and the size of account information is 500,000. The scale is 1 million, and the scale of device information is 100,000; the definition information of the story scenario template can be obtained based on the story scenario template, wherein the story scenario template can include simple story scenario templates and complex story scenario templates, such as simple story The scenario template is: customer A has account C, and the definition information of the corresponding story scenario template is: customer A--(owned)--account C; the complex story scenario template is: account C uses device D to transfer account M, the corresponding story The definition information of the scenario template is: account C--(use)--device D--((transfer))--account M.

In addition, in order to facilitate the generation of the relationship between each type of entities in the graph data, the relationship density setting information can be set according to the proportion of entities with different out-degrees in the configuration information. For example, the out-degree can be set to 0-10. 50%, 30% for the 10-100 range, and 20% for the 100-10000 range. Among them, the out-degree represents the number of edges from an entity to connect other entities.

Step 202: Generate entity data information according to the entity data schema definition information and the scale definition information of each type of entity in the configuration information.

Further, after obtaining the configuration information required for generating the graph data, entity data information can be generated according to the entity data schema definition information and the scale definition information of each type of entity in the configuration information.

For example, take the transfer scenario as an example: the entity data mode in the configuration information defines the information as customer information, account information, and device information, and the scale definition information for each type of entity is that the scale of customer information is 500,000, and the scale of account information is 500,000. 1 million, and the scale of device information is 100,000, so based on the entity data schema definition information and the scale definition information of each type of entity in the configuration information, the generated entity data information is 500,000 customer information, 1 million account information, 100,000 ATM device information.

Step 203 , according to the definition information, relationship density setting information and entity data information of the story scenario template, instantiate the corresponding story scenario template into multiple pieces of story scenario data.

Specifically, according to the definition information of the story scene template, the relationship density setting information and the generated entity data information in the configuration information, the corresponding instance of the story scene template can be instantiated into a plurality of pieces of story scene data.

For example, assume that the generated entity data information is "500,000 customer information, 1 million account information", assume that the definition information of the story scenario template in the configuration information is "customer A--(owned)--account C", the relationship density is set If the information is "Set the out-degree to 0-10, 50%, 10-100 to 30%, and 100-10000 to 20%", you can configure the configuration based on this information. The story scenario template is instantiated into multiple pieces of completed story scenario data. Among them, the multiple pieces of story scenario data meet the following conditions: the multiple pieces of story scenario data include 500,000 customer entities and 1 million account entities, and the customer entities and account entities meet the following story scenarios: a customer entity -- (owned) --An account entity; among the 500,000 customer entities and 1 million account entities, the number of entities with an out-degree range of 0-10 accounts for 50% of the total number of entities, and the number of entities with an out-degree range of 10-100 accounts for 50% of the total number of entities. The proportion of the total number of entities is 30%, and the proportion of the number of entities in the range of 100-10000 is 20% of the total number of entities.

Step 204: Determine the relationships included in the story scenario template, and parse multiple pieces of story scenario data into corresponding relationship data according to the relationships included in the story scenario template to obtain graph data satisfying the target business scenario.

It is understandable that the story scenario template contains the correspondence between entities in the configuration information. Therefore, after obtaining multiple pieces of story scenario data, the multiple story scenario data can be parsed into For the corresponding relational data, the corresponding relational data obtained by analysis is used as graph data satisfying the target business scenario, thereby obtaining graph data satisfying the target business scenario.

For example, taking the story scenario template as: Account C--(Use)--Device D--((Transfer))--Account M as an example, we can first analyze the story scenario template according to the story scenario template and find out that the story scenario template contains There are two types of relationships, namely: the account uses the device, and the account is transferred to the account. Afterwards, according to the relationship contained in the story scenario template, the multiple pieces of story scenario data obtained after the instantiation can be parsed into specific relationship data, so as to obtain graph data satisfying the target business scenario.

In addition, it should also be noted that, in the embodiment of the present application, the data format generated in steps 201-204 is CSV. If the user needs the generated data to be in JSON format, the data in CSV format is converted into corresponding JSON format. In addition, since the data in CSV format has no header attribute value, if the user needs the generated data to be CSV, the corresponding entity attribute information needs to be initialized, so that the generated relational data can be supplemented with the attribute value of each entity correspondingly.

Step 102: Determine the test type for the graph database to be tested.

In the embodiment of the present application, in order to further build a complete test system for graph data products, after generating graph data that meets the target business scenario, it is necessary to judge the test type of the graph database to be tested, and determine the test for the graph database to be tested. type. For example, the test type for the to-be-tested graph database can be determined according to the test requirements of the to-be-tested graph database. For example: when the test requirement of the graph database to be tested is: whether the graph database to be tested meets the specified storage target, the test type for the graph database to be tested can be determined as the storage test type according to the requirement; when the test requirement of the graph database to be tested To be: when the graph database to be tested has a query analysis function, it can be determined that the test type for the graph database to be tested is the query analysis test type. Among them, it should be noted that the test types may include but are not limited to storage test types and query analysis test types. Among them, storage test types may include but are not limited to batch offline data loading tests, streaming data writing tests, etc.; query analysis test types may include but are not limited to basic query function tests, path analysis tests, centrality analysis tests, and group analysis tests. Wait. Step 103 , according to the test type and graph data satisfying the target business scenario, generate test data suitable for the test type.

Further, after generating graph data satisfying the target business scenario and determining the test type for the graph database to be tested, test data suitable for the test type can be generated according to the test type and graph data satisfying the target business scenario.

It is not difficult to understand that different test types are used in different ways to generate test data suitable for the test type. For example, when the test type is storage test type, data preprocessing can be performed on the graph data that meets the target business scenario according to the data input format supported by the graph database to be tested to generate corresponding test data; when the test type is query analysis When testing the type, the corresponding graph retrieval syntax can be generated according to the preset test requirements, and then the specific request content corresponding to the graph retrieval syntax can be generated to generate corresponding test data. For the specific implementation, reference may be made to the descriptions of the subsequent embodiments.

Step 104: Test the database to be tested according to the test data applicable to the test type.

Further, after the test data suitable for the test type is generated, the database to be tested is tested according to the test data suitable for the test type.

In order to be compatible with and support the testing of multiple graph databases, shield the internal differences between different database systems, and improve the reusability of the graph database testing system, optionally, in an embodiment of the present application, the test method is suitable for testing For the type of test data, the specific process of testing the database to be tested may include the following steps: determine an adaptive application program interface for the database to be tested; database for testing.

That is to say, the adaptation development is performed according to the application program interface type of the graph database to be tested, and then, the test graph database to be tested is tested through the adaptation application program interface according to the test data suitable for the test type. For example, the application program interface of the graph database can be divided into three categories, such as: service acquisition application program interface, data loading application program interface, and query application program interface. After the three types of application program interfaces are correspondingly supported, different graph database systems can be accessed by unifying the above application program interfaces, thereby supporting the testing of various graph databases and shielding the internal differences between different database systems.

In order to better improve the efficiency and quality of the test, the indicator data generated by each test can be analyzed. Therefore, when the test of the database to be tested is completed, the indicator data generated by this test can be collected. It should be noted that the indicator data generated by the test is different depending on the test type. When the test type is the storage test type, the indicator data generated by the test may include but are not limited to: data loading success rate, throughput, post-loading Occupation of disk and memory space, etc. When the test type is the query analysis test type, the indicator data generated by the test may include but are not limited to: query analysis success rate, time-consuming, concurrent performance, etc.

In addition, it should be noted that, in order to further improve the efficiency of the test, it is necessary to know the environmental data information of the server in the process of testing the database to be tested. Therefore, in the process of testing the database to be tested, it is necessary to collect the Environment data information of the server where the test graph database is located. For example: monitor the health status of the service during the test, whether the service exists, whether there are core files, memory usage, disk usage, CPU usage, and the consumption of system resources in different test scenarios.

In this embodiment of the present application, in order to enhance the readability of the test results, after collecting the indicator data and environment data generated by this test, optionally, according to the collected indicator data and environment data generated by this test Data information, generate test results against the graph database to be tested, and output the test results.

That is to say, after collecting the index data and environmental data generated by this test, the test results can be integrated according to the collected index data and environmental data information generated by this test, and the integrated test results can be used as The test results of the test chart database are treated to make the test results highly readable.

The graph database testing method of the embodiment of the present application generates graph data that meets the target business scenario according to the requirements of the target business scenario; determines the test type for the graph database to be tested; Test data of the test type; according to the test data applicable to the test type, the test graph database is to be tested. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. . In addition, in the embodiments of the present application, it is proposed to generate graph data based on the story scenario mode, which solves the problem of generating complex relational data in a graph database in various business scenarios. Finally, the present application effectively complies with the testing of various graph database products through the adaptation of the application program interface of the graph database, which greatly expands the applicable scenarios of the test scheme and improves the system reuse.

It should be noted that, with different test types, the manners used to generate test data suitable for the test types are also different. Two different implementation manners will be given below with reference to FIG. 3 and FIG. 4 .

FIG. 3 is a flowchart of a graph database testing method according to an embodiment of the present application. It should be noted that the graph database testing method in the embodiment of the present application is described in the case that the test type is the storage test type. As shown in FIG. 3 , the graph database testing method may include:

Step 301 , according to the requirements of the target business scenario, generate graph data that meets the target business scenario.

Step 302, determining that the test type of the graph database to be tested is the storage test type.

Step 303 , determine the data input format supported by the database to be tested.

Step 304 , according to the data input format supported by the graph database to be tested, perform data preprocessing on graph data that meets the target business scenario, and generate test data suitable for storing the test type.

It can be understood that the data of the graph data satisfying the target business scenario may be, but not limited to, offline graph data, and the offline graph data format may include, but is not limited to, CSV, JSON format, and the like. Therefore, when testing the graph database to be tested that stores the test type, it is necessary to determine the data input format supported by the graph database to be tested. Graph data undergoes data preprocessing to generate test data suitable for storage test types.

Step 305: Test the database to be tested according to the test data suitable for the test type.

Specifically, according to the test data applicable to the test type, the corresponding test data can be executed to test the to-be-tested graph database. Wherein, executing the corresponding test data may include, but is not limited to, batch data loading, streaming data writing, and the like.

According to the graph database testing method of the embodiment of the present application, according to the requirements of the target business scenario, graph data satisfying the target business scenario is generated; the test type of the graph database to be tested is determined as the storage test type; the data input format supported by the graph database to be tested is determined ;According to the data input format supported by the graph database to be tested, perform data preprocessing on graph data that meets the target business scenario, and generate test data suitable for storing test types; test. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. .

FIG. 4 is a flowchart of a graph database testing method according to another specific embodiment of the present application. It should be noted that the graph database testing method in the embodiment of the present application is described with the test type being the query analysis testing type. As shown in FIG. 4 , the graph database testing method may include:

Step 401 , according to the requirements of the target business scenario, generate graph data that meets the target business scenario.

Step 402: Determine the test type of the graph database to be tested as the query analysis test type.

Step 403: Generate a corresponding graph retrieval grammar according to preset test requirements.

Step 404: Generate specific request content corresponding to the graph retrieval syntax according to the graph data satisfying the target business scenario, and use the specific request content corresponding to the graph retrieval syntax as test data suitable for the query analysis test type.

In the embodiment of the present application, when testing the graph database to be tested of the query analysis test type, a corresponding graph retrieval grammar, such as the out grammar of neighbor query, can be generated according to preset test requirements. Afterwards, according to the graph data and graph retrieval syntax that satisfy the target business scenario, specific request content corresponding to the retrieval syntax is generated, for example, a list of entity IDs for which neighbor query needs to be performed specifically. Next, the specific request content corresponding to the graph retrieval syntax is used as the test data suitable for the query analysis test type. Wherein, the preset test requirement may be, but not limited to, the user's test requirement.

Step 405: Test the database to be tested according to the test data applicable to the test type.

Specifically, according to the test data applicable to the test type, the corresponding test data can be executed to test the to-be-tested graph database. After that, in order to further confirm the correctness of the test results, after the graph database test is completed, the test results and the baseline results can be tested for interface difference (Diff for short), that is, to compare the returned content of the same interface in different versions or different environments. Whether it meets the expectations, so that the correctness of the results can be verified.

According to the graph database testing method of the embodiment of the present application, graph data satisfying the target business scenario is generated according to the requirements of the target business scenario; the test type of the graph database to be tested is determined as the query analysis test type; and the corresponding test requirements are generated according to the preset test requirements. Graph retrieval syntax; according to the graph data satisfying the target business scenario, generate the specific request content corresponding to the graph retrieval syntax, and use the specific request content corresponding to the graph retrieval syntax as the test data suitable for the query analysis test type; Test data, to be tested against the test graph database. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. .

Corresponding to the graph database testing methods provided by the above-mentioned embodiments, an embodiment of the present application further provides a graph database testing system. The graph database testing method corresponds to the graph database testing method, so the foregoing embodiments of the graph database testing method are also applicable to the graph database testing system provided in this embodiment, which will not be described in detail in this embodiment. FIG. 5 is a schematic structural diagram of a graph database testing system according to an embodiment of the present application. As shown in FIG. 5 , the graph database testing system includes: a graph data generating module 510 and a graph database testing module 520 .

Wherein, the graph data generation module 510 is configured to generate graph data satisfying the target business scenario according to the requirements of the target business scenario;

The graph database testing module 520 is configured to determine the test type for the graph database to be tested, and generate test data suitable for the test type according to the test type and the graph data satisfying the target business scenario, and according to the test data suitable for the test type, Test against a database of test graphs.

As a possible implementation manner of the embodiment of the present application, the graph data generation module 510 is specifically configured to: obtain configuration information required for generating graph data according to the requirements of the target business scenario; wherein the configuration information includes entity data in the graph data Schema definition information, scale definition information for each type of entity, story scenario template definition information, and relationship density setting information; according to the entity data schema definition information in the configuration information and the scale definition information for each type of entity, the entity data information is generated; according to the story The definition information, relationship density setting information and the entity data information of the scenario template, instantiate the corresponding story scenario template into multiple pieces of story scenario data; determine the relationship included in the story scenario template, and according to the relationship included in the story scenario template, Parse multiple story scenario data into corresponding relational data to obtain graph data that satisfies the target business scenario.

As a possible implementation manner of the embodiment of the present application, the test type includes a storage test type and a query analysis test type.

As a possible implementation of the embodiment of the present application, as shown in FIG. 6 , on the basis of FIG. 5 , the graph database testing module 520 includes: a graph storage testing unit 521 and a graph query analysis testing unit 522 .

Among them, the graph storage testing unit 521 is used to determine the data input format supported by the graph database to be tested, and according to the data input format supported by the graph database to be tested, perform data preprocessing on graph data that meets the target business scenario, and generate data suitable for Store test data for the test type and test against the test chart database against the test data suitable for storing the test type. The graph query analysis and testing unit 522 is configured to generate the corresponding graph retrieval grammar according to the preset test requirements, and generate the specific request content corresponding to the graph retrieval grammar according to the graph data that meets the target business scenario, and generate the specific request content corresponding to the graph retrieval grammar. The content of the request is the test data suitable for the query analysis test type, and the test graph database is tested according to the test data suitable for the query analysis test type.

As a possible implementation manner of the embodiment of the present application, as shown in FIG. 7 , on the basis of that shown in FIG. 6 , the graph database testing system further includes: an indicator data collection module 530 .

Specifically, the indicator data collection module 530 is configured to collect the indicator data generated in this test when the test of the database to be tested is completed.

As a possible implementation manner of the embodiment of the present application, as shown in FIG. 8 , on the basis of that shown in FIG. 7 , the graph database testing system further includes: an environmental data information monitoring module 540 .

Specifically, the environmental data information monitoring module 540 is configured to collect environmental data information of the server where the to-be-tested graph database is located in the process of testing the to-be-tested graph database.

As a possible implementation manner of the embodiment of the present application, as shown in FIG. 9 , on the basis of that shown in FIG. 8 , the graph database testing system further includes: a test result generating module 550 .

Specifically, the test result generation module 550 is configured to generate a test result for the graph database to be tested according to the collected index data and environmental data information generated by this test, and output the test result.

As a possible implementation manner of the embodiment of the present application, as shown in FIG. 10 , on the basis of FIG. 5 , the graph database testing system further includes: a graph database system access module 560 .

Specifically, the graph database system access module 560 has a variety of adaptation application program interfaces for graph databases; wherein, the graph database testing module 520 is specifically used for: determining the adaptation application program interface for the graph database to be tested, and according to the application program interface suitable for the graph database to be tested The test data of the test type is tested against the test graph database by adapting the application program interface.

According to the graph database testing system of the embodiment of the present application, graph data satisfying the target business scenario is generated according to the requirements of the target business scenario; the test type of the graph database to be tested is determined as the query analysis test type; and the corresponding test requirements are generated according to the preset test requirements. Graph retrieval syntax; according to the graph data satisfying the target business scenario, generate the specific request content corresponding to the graph retrieval syntax, and use the specific request content corresponding to the graph retrieval syntax as the test data suitable for the query analysis test type; Test data, to be tested against the test graph database. That is, the graph data that meets different business scenarios is dynamically generated through the requirements of different business scenarios, and the graph database to be tested is tested based on the graph data that meets different business scenarios, which solves the problem of graph data testing in the prior art and realizes the graph database. The test function can cover the complex relationship of many scenarios, and can realize the performance difference of the graph database system in different scenarios, greatly expand the applicable scenarios of the test solution of the embodiment of the present application, and improve the reusability of the test system. .

In order to realize the above-mentioned embodiment, the embodiment of the present application further proposes a device based on the graph database test method, and FIG. 11 is a schematic structural diagram of the device based on the graph database test method provided by the embodiment of the present application. The apparatus based on the graph database testing method includes: a memory 1001 , a processor 1002 and a computer program stored in the memory 1001 and running on the processor 1002 .

When the processor 1002 executes the program, the graph database testing method provided in the above embodiment is implemented.

Further, the equipment based on the graph database testing method also includes:

The communication interface 1003 is used for communication between the memory 1001 and the processor 1002 .

The memory 1001 is used to store computer programs that can be executed on the processor 1002 .

The memory 1001 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

The processor 1002 is configured to implement the graph database testing method described in the foregoing embodiment when executing the program.

If the memory 1001, the processor 1002 and the communication interface 1003 are independently implemented, the communication interface 1003, the memory 1001 and the processor 1002 can be connected to each other through a bus and complete communication with each other. The bus may be an Industry Standard Architecture (referred to as ISA) bus, a Peripheral Component (referred to as PCI) bus, or an Extended Industry Standard Architecture (referred to as EISA) bus, etc. . The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, only one thick line is used in FIG. 11, but it does not mean that there is only one bus or one type of bus.

Optionally, in terms of specific implementation, if the memory 1001, the processor 1002 and the communication interface 1003 are integrated on one chip, the memory 1001, the processor 1002 and the communication interface 1003 can communicate with each other through an internal interface.

The processor 1002 may be a central processing unit (Central Processing Unit, referred to as CPU), or a specific integrated circuit (Application Specific Integrated Circuit, referred to as ASIC), or is configured to implement one or more of the embodiments of the present application integrated circuit.

In order to implement the above embodiments, the present application further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the graph database testing method described in the embodiments of the present application.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and combine the different embodiments or examples described in this specification, as well as the features of the different embodiments or examples, without conflicting each other.

In addition, the terms "first" and "second" are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature delimited with "first", "second" may expressly or implicitly include at least one of that feature. In the description of the present application, "plurality" means at least two, such as two, three, etc., unless expressly and specifically defined otherwise.

Any process or method description in the flowcharts or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing custom logical functions or steps of the process , and the scope of the preferred embodiments of the present application includes alternative implementations in which the functions may be performed out of the order shown or discussed, including performing the functions substantially concurrently or in the reverse order depending upon the functions involved, which should It is understood by those skilled in the art to which the embodiments of the present application belong.

The logic and/or steps represented in flowcharts or otherwise described herein, for example, may be considered an ordered listing of executable instructions for implementing the logical functions, may be embodied in any computer-readable medium, For use with, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from and execute instructions from an instruction execution system, apparatus, or apparatus) or equipment. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus. More specific examples (non-exhaustive list) of computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory.

It should be understood that various parts of this application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented by any one of the following techniques known in the art, or a combination thereof: discrete with logic gates for implementing logic functions on data signals Logic circuits, application specific integrated circuits with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.

Those skilled in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, and the program can be stored in a computer-readable storage medium. When executed, one or a combination of the steps of the method embodiment is included.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, and the like. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limitations to the present application. Embodiments are subject to variations, modifications, substitutions and variations.

Claims (19)

1. a graph database testing method, is characterized in that, comprises: According to the requirements of the target business scenario, graph data satisfying the target business scenario is generated; Determine the test type for the graph database to be tested; generating test data suitable for the test type according to the test type and the graph data satisfying the target business scenario; According to the test data suitable for the test type, test the to-be-tested graph database. 2. The graph database testing method according to claim 1, wherein generating graph data satisfying the target business scenario according to the requirements of the target business scenario, comprising: According to the requirements of the target business scenario, the configuration information required for generating the graph data is obtained; wherein, the configuration information includes entity data schema definition information in the graph data, scale definition information of each type of entity, and story scenarios Template definition information and relationship density setting information; generating entity data information according to the entity data schema definition information and the scale definition information of each type of entity in the configuration information; According to the definition information of the story scenario template, the relationship density setting information and the entity data information, the corresponding instantiation of the story scenario template into multiple pieces of story scenario data; Determine the relationship contained in the story scenario template, and parse the multiple pieces of story scenario data into corresponding relationship data according to the relationship contained in the story scenario template, and obtain the graph data that satisfies the target business scenario . 3 . The graph database testing method according to claim 1 , wherein the test types include storage test types and query analysis test types. 4 . 4. The graph database testing method according to claim 3, wherein when the test type is a storage test type, the graph data that satisfies the target business scenario is generated according to the test type and the graph data. Test data applicable to the described test types, including: Determine the data input format supported by the to-be-tested graph database; According to the data input format supported by the to-be-tested graph database, data preprocessing is performed on the graph data satisfying the target business scenario to generate test data suitable for the storage test type. 5. The graph database testing method according to claim 3, wherein when the test type is a query analysis test type, the graph data satisfying the target business scenario according to the test type, Generate test data suitable for the described test types, including: Generate the corresponding graph retrieval grammar according to the preset test requirements; According to the graph data satisfying the target business scenario, specific request content corresponding to the graph retrieval syntax is generated, and the specific request content corresponding to the graph retrieval syntax is used as test data suitable for the query analysis test type. 6. The graph database testing method according to any one of claims 1 to 5, characterized in that, further comprising: When the test of the graph database to be tested is completed, the indicator data generated by this test is collected. 7. graph database testing method according to claim 6, is characterized in that, also comprises: During the process of testing the graph database to be tested, the environment data information of the server where the graph database to be tested is located is collected. 8. graph database testing method according to claim 7, is characterized in that, also comprises: According to the collected indicator data and the environmental data information generated by the current test, a test result for the to-be-tested graph database is generated, and the test result is output. 9. The graph database testing method according to claim 1, wherein the testing the graph database to be tested according to the test data applicable to the test type, comprising: determining an adaptation API for the graph database to be tested; According to the test data suitable for the test type, test the graph database to be tested through the adaptation application program interface. 10. A graph database testing system, comprising: A graph data generation module, configured to generate graph data satisfying the target business scenario according to the requirements of the target business scenario; The graph database testing module is used to determine the test type for the graph database to be tested, and generate test data suitable for the test type according to the test type and the graph data that meets the target business scenario, and The test data applicable to the test type described above is used to test the to-be-tested graph database. 11. The graph database testing system according to claim 10, wherein the graph data generation module is specifically used for: According to the requirements of the target business scenario, the configuration information required for generating the graph data is obtained; wherein, the configuration information includes entity data schema definition information in the graph data, scale definition information of each type of entity, and story scenarios Template definition information and relationship density setting information; generating entity data information according to the entity data schema definition information and the scale definition information of each type of entity in the configuration information; According to the definition information of the story scenario template, the relationship density setting information and the entity data information, the corresponding instantiation of the story scenario template into multiple pieces of story scenario data; Determine the relationship contained in the story scenario template, and parse the multiple pieces of story scenario data into corresponding relationship data according to the relationship contained in the story scenario template, and obtain the graph data that satisfies the target business scenario . 12 . The graph database testing system according to claim 10 , wherein the test types include storage test types and query analysis test types. 13 . 13. The graph database testing system according to claim 12, wherein the graph database testing module comprises: The graph storage testing unit is used to determine the data input format supported by the graph database to be tested, and perform data analysis on the graph data that meets the target business scenario according to the data input format supported by the graph database to be tested. preprocessing, generating test data suitable for the storage test type, and testing the graph database to be tested according to the test data suitable for the storage test type; The graph query analysis and testing unit is used to generate the corresponding graph retrieval syntax according to the preset test requirements, and generate the specific request content corresponding to the graph retrieval syntax according to the graph data satisfying the target business scenario, and use the The specific request content corresponding to the graph retrieval syntax is used as the test data suitable for the query analysis test type, and the graph database to be tested is tested according to the test data suitable for the query analysis test type. 14. The graph database testing system according to any one of claims 10 to 13, characterized in that, further comprising: The index data collection module is configured to collect the index data generated by this test when the test of the graph database to be tested is completed. 15. The graph database testing system according to claim 14, further comprising: The environmental data information monitoring module is used for collecting environmental data information of the server where the to-be-tested graph database is located in the process of testing the to-be-tested graph database. 16. The graph database testing system according to claim 15, further comprising: The test result generation module is configured to generate a test result for the to-be-tested graph database according to the collected index data and the environment data information generated by the current test, and output the test result. 17. The graph database testing system according to claim 10, further comprising: a graph database system access module; the graph database system access module has an adaptation application program interface for multiple graph databases; Wherein, the graph database testing module is specifically used for: determining an adaptation application program interface for the graph database to be tested, and, according to the test data applicable to the test type, through the adaptation application program interface The to-be-tested graph database is tested. 18. A device based on a graph database testing method, characterized in that it comprises: a memory, a processor, and a computer program stored on the memory and running on the processor, the processor executing the computer When the program is executed, the graph database testing method according to any one of claims 1 to 9 is realized. 19. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the graph database testing method according to any one of claims 1 to 9 is implemented.