CN113641700A - Data processing method and device based on Spring boot frame - Google Patents

Abstract

The invention discloses a data processing method and device based on a Spring boot framework, and relates to the technical field of computers. A specific implementation of the method includes: obtaining a data query request; the data query request indicates the data identifier and data source information in the database to be queried; the data source information in the database to be queried is based on the starter in the Spring boot framework. A query statement is generated according to the data query request; and target data corresponding to the data identifier is acquired from a data source corresponding to the data source information according to the query statement. This embodiment simplifies the process of configuring data sources and realizes the isolation of different data sources, thereby avoiding the problem of data source conflict.

Description

A data processing method and device based on Spring boot framework

technical field

The invention relates to the field of computer technology, and in particular, to a data processing method and device based on a Spring boot framework.

Background technique

The display of data visualization is of great significance for business analysis and adjustment.

At present, the process of converting persistence layer data into report data is mainly realized by manually spelling code or using template to generate code.

In the process of realizing the present invention, the inventor found that there are at least the following problems in the prior art:

In the process of data visualization, when using manual spelling code or template-generated code to convert data from multiple data sources, it is necessary to switch data sources frequently, which may cause data incompatibility or data inconsistency, resulting in errors in data visualization.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention provide a data processing method and device based on the Spring boot framework, which can configure different types of data sources through the starter mechanism of Spring boot, simplifies the process of configuring data sources, and realizes different data sources. isolation, thus avoiding the problem of data source conflict.

Further, by generating query statements corresponding to different data source types through query annotations, and querying data from multiple data sources according to different query statements, the code reuse rate can be improved, the workload of spelling code can be reduced, and by The conversion annotation quickly converts the target data obtained by the query into the data in the report format, thereby improving the conversion efficiency from the persistence layer data to the report data.

In order to achieve the above purpose, according to the first aspect of the embodiments of the present invention, a data processing method based on the Spring boot framework is provided, including:

Obtain a data query request; the data query request indicates the data identifier and data source information in the database to be queried; the data source information in the database to be queried is configured according to the starter mechanism in the Spring boot framework;

generating a query statement according to the data query request;

The target data corresponding to the data identifier is acquired from the data source corresponding to the data source information according to the query statement.

Optionally, the method further includes:

The target data is transformed using a transformation annotation interpreter according to the format required for data visualization.

Optionally, according to the format required for data visualization, using a transformation annotation interpreter to transform the target data, including:

According to the conversion annotation interpreter, the target data is supplemented, so that the supplemented target data is continuous;

Based on the supplemented target data, the target data is combined into Json format report data.

Optionally, the method further includes:

Generate a configuration file according to the data source type and data source address information contained in the data source information in the database to be queried;

Load the configuration file through the starter, generate links corresponding to one or more data sources in the database to be queried, and put the links into the Spring container.

Optionally, generating a query statement according to the data query request includes:

By invoking the interface configured with the query annotation, the query annotation and parameter corresponding to the interface are obtained; the parameter includes a standard SQL statement corresponding to the data identifier;

According to the data source type contained in the data source information in the database to be queried, the standard SQL statement is converted into a query statement corresponding to the data source type by a query annotation interpreter.

Optionally, the query annotation and parameters corresponding to the interface are obtained by invoking an interface configured with query annotations, including:

Obtain the proxy class corresponding to the interface returned by the Spring container by calling the interface;

Obtain the query annotation and the parameter by calling the invoke method of the proxy class.

Optionally, obtaining the target data corresponding to the data identifier from the data source corresponding to the data source information according to the query statement includes:

By calling the connection class of the Spring container, the query statement is sent to the corresponding data source through the link in the Spring container;

Obtain target data from the data source according to the query statement.

According to a second aspect of the embodiments of the present invention, a data processing device based on the Spring boot framework is provided, including: a request acquisition module, a generation module and a data acquisition module; wherein,

The request obtaining module is used to obtain a data query request; the data query request indicates the data identifier and data source information in the database to be queried; the data source information in the database to be queried is configured according to the starter mechanism in the Springboot framework of;

The generating module is configured to generate a query statement according to the data query request;

The data acquisition module is configured to acquire target data corresponding to the data identifier from a data source corresponding to the data source information according to the query statement.

According to a third aspect of the embodiments of the present invention, an electronic device is provided, including:

one or more processors;

storage means for storing one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the Spring boot framework-based data processing methods provided in the first aspect above. method described.

According to a fourth aspect of the embodiments of the present invention, there is provided a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, implements the Spring boot framework-based data provided in the above-mentioned first aspect The method described in any of the processing methods.

An embodiment of the above invention has the following advantages or beneficial effects: it can configure different types of data sources through the starter mechanism of Spring boot, simplifies the process of configuring data sources, and realizes the isolation of different data sources, thereby avoiding data sources. conflict issues.

Further, by generating query statements corresponding to different data source types through query annotations, and querying data from multiple data sources according to different query statements, the code reuse rate can be improved, the workload of spelling code can be reduced, and by The conversion annotation quickly converts the target data obtained by the query into the data in the report format, thereby improving the conversion efficiency from the persistence layer data to the report data.

Further effects of the above non-conventional alternatives will be described below in conjunction with specific embodiments.

Description of drawings

The accompanying drawings are used for better understanding of the present invention and do not constitute an improper limitation of the present invention. in:

1 is a schematic flowchart of a data processing method based on the Spring boot framework provided by an embodiment of the present invention;

2 is a schematic flowchart of data query and conversion provided by an embodiment of the present invention;

3 is a schematic diagram of the configuration flow of a Spring boot-based custom starter provided by an embodiment of the present invention;

4 is a schematic flowchart of a data query through query annotation provided by an embodiment of the present invention;

5 is a schematic structural diagram of a data processing device based on the Spring boot framework provided by an embodiment of the present invention;

FIG. 6 is an exemplary system architecture diagram to which an embodiment of the present invention may be applied;

FIG. 7 is a schematic structural diagram of a computer system suitable for implementing a terminal device or a server according to an embodiment of the present invention.

Detailed ways

Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

It should be pointed out that the embodiments of the present invention and the technical features in the embodiments may be combined with each other without conflict.

As shown in FIG. 1, an embodiment of the present invention provides a data processing method based on the Spring boot framework, and the method may include the following steps S101 to S103:

Step S101: Obtain a data query request; the data query request indicates the data identifier and data source information in the database to be queried; the data source information in the database to be queried is configured according to the starter mechanism in the Spring boot framework.

In the process of data visualization, the data of the persistence layer needs to be queried first and then converted. The data of the persistence layer is usually stored in different data sources. From the data query request, the data identifier and data source information to be queried can be determined.

It is understandable that the data source information indicated in the data query request provides specific access information about the data source, that is, the data source in the corresponding database can be connected and accessed to perform data query through the data source information. In the process of data visualization, the query statement of the database, the access address of the data source, the data source type, the access user and the access password of the data source can be directly written in the code. This simple way of integrating data sources is more efficient for one or a few data sources. However, in the case of many data sources, it is easy to make mistakes when integrating a large number of data sources in the code, and there will be more repetitive codes, which is intrusive to the system.

Therefore, in an embodiment of the present invention, the starter mechanism in the framework based on Spring boot is preferably used to configure the data source in the database, and the specific method is as follows: according to the data source type contained in the data source information in the database to be queried and data source address information, generate a configuration file; load the configuration file through the starter, generate a link corresponding to one or more data sources in the database to be queried, and put the link into the Spring container.

There may be many data sources in the database to be queried, and these data sources are usually relational databases, but the specific types of the databases may be different, such as SQL Server, Oracle, DB2, Mysql, and the like. And each data source has its address information, that is, the access information of the data source, including the url address of the data source, the user and password information when the data source is accessed, and so on.

In an embodiment of the present invention, a starter can be customized according to the principle of the Spring boot framework, and according to the configuration specification of the starter, the type of the data source and the address information of the data source are generated as the configuration file of the starter, and the configuration is loaded through the starter. After the file, generate different data source links for different data sources, and put the generated links into the Spring container. In an embodiment of the present invention, the process of automatically configuring the data source through a custom starter may be as shown in steps S301 to 304 in FIG. 3 .

It is understandable that when querying data, through the data source links configured by the starter, the query statement can be easily sent to different data sources through these links to obtain the target data, which makes the different data sources independent of each other, so that the It has the effect of isolating the data source.

Step S102: Generate a query statement according to the data query request.

It is understandable that, after the data query request is obtained, different query statements need to be determined according to different data source types, so as to use these query statements to query data in the corresponding data source.

For different database types, the SQL query statements are not exactly the same. For example, the database query statements of Mysql and SQL Server are similar, but there are also many differences. Therefore, in order to shield the specific details of the underlying query statement, extract a general query process, and reduce the amount of code duplication, in an embodiment of the present invention, it is preferable to use the annotation mechanism to achieve, the method is as follows: by calling the configuration with the query annotation interface, obtain the query annotations and parameters corresponding to the interface; the parameters include standard SQL statements corresponding to the data identifiers; according to the data source type contained in the data source information in the database to be queried, query annotations The interpreter converts the standard SQL statement into a query statement corresponding to the data source type.

Before querying, you can define a query annotation in advance, create a new interface, configure the query annotation on the interface, or configure the query annotation on the existing interface of the system. When configuring query annotations on the interface, you can add standard SQL statements to the parameters of the query annotations. The SQL statements are organized according to the data identifiers to be queried.

For example, the current data query request indicates that all data whose message_type is messageA needs to be queried from a data table, wherein the data identifier is messageA, the data table is stripe_log_table, and the standard SQL statement can be: Select*From Stripe_log_table where message_type= 'messageA'. If the newly created interface is Test() and the query annotation is @SelectSql(), you can use this standard SQL statement as a parameter of the query annotation @SelectSql, and add the parameter-added query annotation before the interface, as shown below:

@SelectSql("Select*From Stripe_log_table where message_type='messageA'")Test().

Of course, the query annotation can also contain other parameters. For example, in a standard SQL query statement, the data identifier to be queried is determined by passing parameters. For example, the value of message_type can be determined by the variable $messageType, which can be determined by calling Test( ) interface passed to the query annotation. For example, it can be written as follows:

@SelectSql("Select*From Stripe_log_table where message_type='$messageType'")Test(@SqlParam("messageType")String messageType). Among them, @SqlParam("messageType") is the annotation for passing parameters to @SelectSql.

Before calling the interface, you can also configure the Java package where the query annotation is located in the configuration of the starter, so that when the starter starts, the interface is automatically scanned in the Java package, and a dynamic proxy class is generated for the interface configured with the query annotation. The configuration process may be as shown in steps S305 to S308 in FIG. 3 .

When invoking the interface, one possible implementation of the present invention is: by invoking the interface, the proxy class corresponding to the interface returned by the Spring container is obtained; by invoking the invoke method of the proxy class, the query annotation and the parameters.

For example, when calling the Test() interface, the Spring container will return the dynamic proxy class P corresponding to the Test() interface generated based on the configuration of the starter, and obtain the Test() by calling the invoke() method in the dynamic proxy class P. The query annotation @SelectSql configured on the interface, and the parameters in the query annotation, that is, standard SQL statements.

After the standard SQL statement is obtained, an embodiment of the present invention is: according to the data source type contained in the data source information in the database to be queried, query the annotation interpreter to convert the standard SQL statement Converted into a query statement corresponding to the data source type.

Among them, the query annotation interpreter can convert the standard SQL statement contained in the query annotation parameter into the native query statement corresponding to the data source type according to the different data source types configured in the starter. For example, for a data source of Mysql type, it is converted into a query statement that conforms to the Mysql query syntax, and for a data source of SQL Server type, it is converted to a query statement that conforms to the SQL Server query syntax.

It is understandable that the general query process is extracted into query annotations, and the query annotation interpreter generates corresponding query statements for different data source types, which can reduce the amount of repetitive code. Moreover, the query annotation interpreter can be compatible with different types of data sources that are commonly used. Every time a new data query request is added, the query annotation interpreter can adapt to different data source types with less changes, saving data The time to modify the code depending on the source.

Step S103: Acquire target data corresponding to the data identifier from a data source corresponding to the data source information according to the query statement.

After the query language corresponding to the data source type is converted and generated by the query annotation interpreter, the query statement can be sent to the data source for query to obtain the target data. In an embodiment of the present invention, the following methods may be adopted: by invoking the connection class in the Spring container, the query statement is sent to the corresponding data source through the link in the Spring container; Get the target data from the source.

The connection class in the Spring container is loaded into the Spring container when the data source is configured through the starter. By calling this connection class, the generated query statements corresponding to different types of data sources can be sent to different types of data sources. Gives a data source of type SQLServer in the database. Therefore, the target data can be queried from different data sources through these query statements.

After the target data is obtained, the target data can be stored in the memory for subsequent use by the transformation annotation.

It is understandable that, through the query annotation and the query annotation interpreter, when a data query request is added, the standard SQL statement in the existing query annotation can be modified into a standard SQL query statement with a new data identifier, or a new data query can be added. A query annotation and writing a standard SQL statement corresponding to the newly added data identifier in the parameter can complete the purpose of querying the newly added target data, which can greatly save the time of rewriting the code and improve the efficiency of data visualization.

After obtaining target data from multiple data sources, these target data need to be transformed to obtain the format required for data visualization, that is, converted into report data, so that specific report graphics can be generated according to the report data, such as generating line charts, Column charts, pie charts, etc.

When transforming the target data, an embodiment of the present invention preferably adopts an annotation mechanism to transform the data, and the method may be as follows: according to the format required for data visualization, the target data is transformed using a transformation annotation interpreter.

The conversion annotation interpreter can convert the data obtained by the conversion annotation to obtain report data. The conversion annotation interpreter is universal for data processing, compatible with a variety of report data formats, and suitable for data conversion of most common data sources. It is understandable that when a new data visualization request is added, the conversion annotation interpreter can convert the data into the required report data format without making too many changes, saving a lot of time for manual code spelling, and achieving rapid response and conversion. The purpose of report data, thereby improving the conversion efficiency of report data.

The specific way of using the transformation annotation interpreter to transform the target data may be provided in an embodiment of the present invention, including: supplementing the target data according to the transformation annotation interpreter, so that the complemented The target data is continuous; based on the supplemented target data, the target data is combined into Json format report data.

After the target data is stored in the memory, use the reflection mechanism to read the data from the target data stored in the memory through the transformation annotation, and then put the data into the corresponding collection through the transformation annotation interpreter to facilitate transformation. For example, put the data read by the transformation annotation @X into the set x, put the data read by the transformation annotation @Y into the set y, and put the data read by the transformation annotation @Data into the set z. In this way, the data set can be corresponding to the coordinate axis of the generated line chart. For example, the data of the X coordinate axis is in the x set, the data of the Y coordinate axis is in the y set, and the specific data of the point corresponding to the X-Y coordinate axis is in the set z.

In the set z, the key of the data is X'-Y', and the values of X' and Y' in the key may already be in the set x and y, or one of them may be in the existing set x or y. , and possibly neither in set x nor set y. That is to say, in combination with the data in the set z, there can be the following four situations: For the data Z1 in the set z, the corresponding key is (X'1-Y'1), and the X'1 in the key is in the set x. , Y'1 is in set y; for data Z2, its corresponding key is (X'2-Y'2), X'2 in key is in set x, and Y'2 is not in set y; for data Z3, The corresponding key is (X'3-Y'3), X'3 in the key is not in the set x, and Y'3 is in the set y; for the data Z4, the corresponding key is (X'4-Y' 4), X'4 in key is not in set x, and Y'4 is not in set y either.

Then in order to make the data of the X and Y coordinate axes correspond one-to-one with the data in the z set, the value of X' in the key of the z set data that is not in the set x can be added to the corresponding x set; the z set data can be added to the corresponding x set. The value of Y' in the key that is not in the set y is added to the corresponding y set.

For continuous coordinate axis data, the missing continuous values in the coordinate set can also be supplemented to make the coordinate axis data continuous. For example, the Y axis is the time axis, and the data in the current collection y are July 1, July 3, and July 5. At this time, the data that is not in the collection can be supplemented, for example, July 2, July 4 These two data of day, so that the time data of the coordinate axis Y is continuous.

According to the supplemented data sets x, y, and z, the data in the set is combined into Json format report data, so as to be used when generating a visual report graph.

According to an embodiment of the present invention, a data processing method based on the Spring boot framework is provided, which can configure different types of data sources through the starter mechanism of Spring boot, simplifies the process of configuring the data sources, and realizes the isolation of different data sources, thereby avoiding The problem of data source conflict is solved.

Further, by generating query statements corresponding to different data source types through query annotations, and querying data from multiple data sources according to different query statements, the code reuse rate can be improved, the workload of spelling code can be reduced, and by The conversion annotation quickly converts the target data obtained by the query into the data in the report format, thereby improving the conversion efficiency from the persistence layer data to the report data.

FIG. 2 is a schematic flowchart of a data query and transformation provided by an embodiment of the present invention. The specific steps are as follows:

Step S201: Obtain query annotations.

Obtain query annotations and parameters by calling the interface configured with query annotations.

Step S202: Generate a query statement through the query annotation interpreter.

Through the query annotation interpreter, the standard SQL statement contained in the query annotation is converted into a query statement corresponding to the data source type.

Step S203: Send the query statement to the data source.

Query statements are sent to different types of data sources through links in the Spring container configured by the starter.

Step S204: Obtain target data from a data source through a query statement.

After obtaining the target data, store the target data in the memory.

Step S205: Read the target data through the conversion annotation.

Use the reflection mechanism to obtain the data corresponding to the transformation annotation from the target data in the memory through the transformation annotation.

Step S206: Generate report data by converting the annotation interpreter.

Through the conversion annotation interpreter, the data obtained by the conversion annotation is supplemented, and the data is combined into Json format report data. Subsequently, the generated report data can be sent to the interface for generating report graphs to generate graphs.

As shown in FIG. 3 , an embodiment of the present invention provides a schematic flowchart of a custom starter configuration data source and a dynamic proxy configuration interface in a data processing method based on the Spring boot framework.

The specific steps of configuring the data source may be S301 to S304:

Step S301: Write the data source information into the configuration file corresponding to the custom bean.

The data source information includes the type of the data source, the url address of the data source, the access user and password information of the data source. .

Step S302: Determine whether the conditions for creating a bean are satisfied.

Step S303: Load the custom bean.

Step S304: Load the corresponding configuration file, generate different links according to the data source type, and put them into the Spring container.

Load the configuration file of the data source corresponding to the bean, generate links to different data sources according to the type of data source, and put these links into the Spring container.

The specific steps for configuring the dynamic proxy of the interface may be S305 to S308:

Step S305: Configure the Java package where the query annotation is located.

There can be multiple query annotations, and the path of the package where the query annotation is located is written into the configuration file of the starter.

Step S306: Import the query annotation scanner.

Step S307: Scan the interface according to the Java package where the annotation is located.

Use the scanner in step S306 to scan the interfaces in the Java package to obtain interfaces configured with query annotations.

Step S308: Generate a dynamic proxy class corresponding to the interface, and put the dynamic proxy class into the beanDefinition.

After configuring the interface dynamic proxy class of the query annotation, in the subsequent process of Spring, the bean can be instantiated according to the beanDefinition, and then during the interface invocation process, the corresponding dynamic proxy class is returned through the instantiated bean in the Spring container. Use the methods in the dynamic proxy class to obtain standard SQL statements in query annotation parameters, and generate query statements corresponding to different data source types through the query annotation interpreter to query data from different data sources. The specific process can be shown in Figure 4.

4 is a schematic flowchart of a data query in a data processing method based on the Spring boot framework provided by an embodiment of the present invention, and the specific steps may be as follows:

Step S401: At runtime, the interface configured with the query annotation is invoked.

Step S402: The Spring container returns the dynamic proxy class.

The Spring container returns the dynamic proxy class corresponding to the interface configured through the starter.

Step S403: call the invoke method in the dynamic proxy class.

Step S404: Obtain query annotations and parameters.

Through the invoke method and reflection mechanism, query annotations and parameters on the interface can be obtained.

Step S405: Generate different query statements according to the query annotation interpreter.

Convert standard SQL statements contained in query annotation parameters into native query statements corresponding to different data source types.

Step S406: Invoke the connection class in the Spring container.

The connection class in the Spring container is loaded into the Spring container when the starter configures the data source. Through the connection class, these native query statements can be sent to different data sources through the links in the Spring container, so as to query the target data from different data sources.

Step S407: Obtain the query result and return it.

Obtain the target data queried from different data sources, and return the result to the invoke method of the proxy class, thereby returning and storing the target data in memory.

As shown in FIG. 5, an embodiment of the present invention provides a data processing apparatus 500 based on the Spring boot framework, including: a request acquisition module 501, a generation module 502 and a data acquisition module 503; wherein,

The request obtaining module 501 is used to obtain a data query request; the data query request indicates the data identifier and data source information in the database to be queried; the data source information in the database to be queried is based on the starter mechanism in the Springboot framework configured;

The generating module 502 is configured to generate a query statement according to the data query request;

The data acquisition module 503 is configured to acquire target data corresponding to the data identifier from a data source corresponding to the data source information according to the query statement.

In an embodiment of the present invention, the request obtaining module 501 is configured to generate a configuration file according to the data source type and data source address information contained in the data source information in the database to be queried; load the configuration file through a starter, Links corresponding to one or more data sources in the database to be queried are generated, and the links are put into the Spring container.

In an embodiment of the present invention, the generating module 502 is configured to obtain query annotations and parameters corresponding to the interface by calling an interface configured with query annotations; the parameters include standard SQL statements corresponding to the data identifiers ; According to the data source type contained in the data source information in the database to be queried, the standard SQL statement is converted into a query statement corresponding to the data source type through a query annotation interpreter.

In an embodiment of the present invention, the generating module 502 is configured to obtain the proxy class corresponding to the interface returned by the Spring container by calling the interface; and obtain the query annotation by calling the invoke method of the proxy class and the parameters.

In an embodiment of the present invention, the data acquisition module 503 is configured to send the query statement to the corresponding data source through the link in the Spring container by invoking the connection class in the Spring container; Obtain the target data from the data source described above.

In an embodiment of the present invention, the data acquisition module 503 is configured to transform the target data by using a transformation annotation interpreter according to a format required for data visualization.

In an embodiment of the present invention, the data acquisition module 503 is configured to supplement the target data according to the conversion annotation interpreter, so that the supplemented target data is continuous; The target data is combined into report data in Json format.

According to an embodiment of the present invention, a data processing device based on the Spring boot framework is provided, which can configure different types of data sources through the starter mechanism of Spring boot, simplifies the process of configuring data sources, and realizes the isolation of different data sources, thereby avoiding The problem of data source conflict is solved.

Further, by generating query statements corresponding to different data source types through query annotations, and querying data from multiple data sources according to different query statements, the code reuse rate can be improved, the workload of spelling code can be reduced, and by The conversion annotation quickly converts the target data obtained by the query into the data in the report format, thereby improving the conversion efficiency from the persistence layer data to the report data.

FIG. 6 shows an exemplary system architecture 600 of a data processing method and apparatus based on the Spring boot framework to which embodiments of the present invention can be applied

As shown in FIG. 6 , the system architecture 600 may include terminal devices 601 , 602 , and 603 , a network 604 and a server 605 . The network 604 is a medium used to provide a communication link between the terminal devices 601 , 602 , 603 and the server 605 . Network 604 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user can use the terminal devices 601, 602, 603 to interact with the server 605 through the network 604 to receive or send messages and the like.

The terminal devices 601, 602, 603 may be various electronic devices having a display screen and supporting information browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

The server 605 may be a server that provides various services, such as a background management server that provides support for data query requests made by users using the terminal devices 601 , 602 , and 603 . The background management server can analyze and process the received data query request and other data, and feed back the processing result to the terminal device.

It should be noted that the data processing method based on the Spring boot framework provided by the embodiment of the present invention is generally executed by the server 605 , and accordingly, the data processing apparatus based on the Spring boot framework is generally set in the server 605 .

It should be understood that the numbers of terminal devices, networks and servers in FIG. 6 are merely illustrative. There can be any number of terminal devices, networks and servers according to implementation needs.

Referring next to FIG. 7 , it shows a schematic structural diagram of a computer system 700 suitable for implementing a terminal device according to an embodiment of the present invention. The terminal device shown in FIG. 7 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present invention.

As shown in FIG. 7, a computer system 700 includes a central processing unit (CPU) 701, which can be processed according to a program stored in a read only memory (ROM) 702 or a program loaded from a storage section 708 into a random access memory (RAM) 703 Various appropriate actions and processes are performed. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701 , the ROM 702 , and the RAM 703 are connected to each other through a bus 704 . An input/output (I/O) interface 705 is also connected to bus 704 .

The following components are connected to the I/O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc. ; and a communication section 709 including a network interface card such as a LAN card, a modem, and the like. The communication section 709 performs communication processing via a network such as the Internet. Drive Z10 is also connected to I/O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 710 as needed so that a computer program read therefrom is installed into the storage section 708 as needed.

In particular, the processes described above with reference to the flowcharts may be implemented as computer software programs in accordance with the disclosed embodiments of the present invention. For example, embodiments disclosed herein include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 709 and/or installed from the removable medium 711 . When the computer program is executed by the central processing unit (CPU) 701, the above-described functions defined in the system of the present invention are executed.

It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples of computer readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code therein. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device . Program code embodied on a computer readable medium may be transmitted using any suitable medium including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented in special purpose hardware-based systems that perform the specified functions or operations, or can be implemented using A combination of dedicated hardware and computer instructions is implemented.

The modules involved in the embodiments of the present invention may be implemented in a software manner, and may also be implemented in a hardware manner. The described modules can also be set in the processor, for example, it can be described as: a processor includes an acquisition module, a generation module, and a determination module. Wherein, the names of these modules do not constitute a limitation of the module itself under certain circumstances, for example, the acquisition module may also be described as "the module that acquires the request".

As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or may exist alone without being assembled into the device. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by a device, the device includes: obtaining a data query request; the data query request indicates the data in the database to be queried Identification and data source information; the data source information in the database to be queried is configured according to the starter mechanism in the Spring boot framework; according to the data query request, a query statement is generated; according to the query statement, from and the data source information The target data corresponding to the data identifier is obtained from the corresponding data source.

According to the technical solution of the embodiment of the present invention, different types of data sources can be configured through the starter mechanism of Spring boot, which simplifies the process of configuring data sources, and realizes the isolation of different data sources, thereby avoiding the problem of data source conflicts.

Further, by generating query statements corresponding to different data source types through query annotations, and querying data from multiple data sources according to different query statements, the code reuse rate can be improved, the workload of spelling code can be reduced, and by The conversion annotation quickly converts the target data obtained by the query into the data in the report format, thereby improving the conversion efficiency from the persistence layer data to the report data.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. A data processing method based on a Spring boot frame is characterized by comprising the following steps:

acquiring a data query request; the data query request indicates data identification and data source information in a database to be queried; the data source information in the database to be inquired is configured according to a starter mechanism in a Spring boot frame;

generating a query statement according to the data query request;

and acquiring target data corresponding to the data identification from a data source corresponding to the data source information according to the query statement.

2. The method of claim 1, further comprising:

and converting the target data by using a conversion annotation interpreter according to a format required by data visualization.

3. The method of claim 2, wherein translating the target data with a translation annotation interpreter according to a format required for data visualization comprises:

supplementing the target data according to the conversion annotation interpreter, so that the supplemented target data are continuous;

and combining the target data into report data in a Json format based on the supplemented target data.

4. The method of claim 1, further comprising:

generating a configuration file according to the data source type and the data source address information contained in the data source information in the database to be queried;

and loading the configuration file through a starter, generating links corresponding to one or more data sources in the database to be queried respectively, and putting the links into a Spring container.

5. The method of claim 1, wherein generating a query statement from the data query request comprises:

acquiring query annotations and parameters corresponding to an interface by calling the interface configured with the query annotations; the parameter comprises a standard SQL statement corresponding to the data identifier;

and converting the standard SQL statement into a query statement corresponding to the data source type through a query annotation interpreter according to the data source type contained in the data source information in the database to be queried.

6. The method according to claim 5, wherein the obtaining of the query annotation and the parameter corresponding to the interface by calling the interface configured with the query annotation comprises:

acquiring an agent class corresponding to the interface returned by the Spring container by calling the interface;

and acquiring the query annotation and the parameter by calling an invoke method of the proxy class.

7. The method of claim 4, wherein the obtaining target data corresponding to the data identifier from the data source corresponding to the data source information according to the query statement comprises:

sending the query statement to a corresponding data source through a link in a Spring container by calling a connection class in the Spring container;

and acquiring target data from the data source according to the query statement.

8. A Spring boot frame-based data processing apparatus, comprising: the device comprises a request acquisition module, a generation module and a data acquisition module; wherein,

the request acquisition module is used for acquiring a data query request; the data query request indicates data identification and data source information in a database to be queried; the data source information in the database to be inquired is configured according to a starter mechanism in a Spring boot frame;

the generating module is used for generating a query statement according to the data query request;

and the data acquisition module is used for acquiring target data corresponding to the data identifier from a data source corresponding to the data source information according to the query statement.

9. An electronic device, comprising:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.

10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.

Images