WO2023056946A1 - Data caching method and apparatus, and electronic device - Google Patents

Abstract

Provided in the embodiments of the present description is a data caching method. The method comprises: constructing a cache model on the basis of a variable, and configuring, for the variable in the cache model, annotation information that has a matching rule; in response to a cache trigger event, calling the cache model to read the annotation information therein, acquiring a source data table, determining a target field name, which matches the matching rule, in the source data table, and assigning a value to the variable in the cache model on the basis of the target field name; and reading, by using the cache model subjected to value assignment, a field value corresponding to the target field name in the source data table, and generating key-value pair information and storing same in a cache space. Since a cache model can be independent of a data table, the cache model can be applied to different data tables, and a field name in a source data table and a corresponding field value can be automatically read and cached in advance, such that the low efficiency caused by temporarily reading data from a relational data table is avoided, and there is no need to individually develop a code for each data table, thereby improving the convenience.

Description

A data cache method, device and electronic equipment technical field

The present application relates to the computer field, in particular to a data caching method, device and electronic equipment.

Background technique

When a business system program needs to call data, it will access a relational database. A relational database refers to a database that uses a relational model to organize data, and stores data in the form of rows and columns. Key-value database: A key-value database is a non-relational database that stores data as a set of key-value pairs, and the key name is used as a unique identifier. Because a key-value database uses a simple key-value pair method to store data, its data storage capacity is relatively large. Poor, rarely used in databases.

After the amount of data access increases, system performance bottlenecks are often encountered, and generally the bottleneck at this time is accessing the relational database.

Therefore, it is necessary to provide a new method to improve data access speed.

Contents of the invention

The embodiments of this specification provide a data caching method, device and electronic equipment, so as to improve the convenience of data caching.

The embodiment of this specification provides a data caching method, including:

Constructing a cache model based on variables, and configuring annotation information with matching rules for the variables in the cache model;

Invoking the cache model to read the annotation information in response to the cache trigger event, obtaining the source data table, and determining the name of the target field in the source data table that matches the matching rule, based on the name of the target field Variable assignment in the cache model described above;

Using the assigned cache model to read the field value corresponding to the target field name in the source data table, generate key-value pair information and store it in the cache space.

Optionally, there is table structure information of the target field name in the matching rule;

The determining the name of the target field matching the matching rule in the source data table includes:

The field name query is performed on the source data table by using the table structure information in the matching rule, and the queried target field name is read.

Optionally, the table structure information in the matching rule is a table structure function with time as an independent variable;

The field name query of the source data table by using the table structure information in the matching rule includes:

Determining the time of the cache trigger event, calculating a table structure function value in combination with the time and the table structure function, and generating a current matching rule according to the table structure function value;

Execute the current matching rule to perform field name query on the source data table.

Optionally, the value of the table structure function is a row number or a column number.

Optionally, also include:

Configure data table monitoring rules for the cache model to monitor update events of the source data table, and if the source data table is detected, perform data synchronous reading to update the cache.

Optionally, the matching rules include preset field names and similarity calculation rules;

The determining the name of the target field matching the matching rule in the source data table includes:

Read the field name in the source data table, calculate its similarity with the preset field name according to the similarity calculation rule, and determine the matching target field name according to the similarity.

Optionally, the variable-based construction of the cache model includes:

Constructs a cache directive and replaces field names within it with variables.

Optionally, the matching rules also include source data table matching rules;

The acquisition source data table includes:

The source data table to be cached is determined and acquired from the database according to the source data table matching rule.

The embodiment of this specification also provides a data cache device, including:

The model construction module constructs a cache model based on variables, and configures annotation information with matching rules for the variables in the cache model;

The matching assignment module calls the cache model to read the annotation information in response to the cache trigger event, obtains the source data table, and determines the target field name in the source data table that matches the matching rule, based on the target The field name is the variable assignment in the cache model;

The cache execution module uses the assigned cache model to read the field value corresponding to the target field name in the source data table, and generates key-value pair information to store in the cache space.

The embodiment of this specification also provides an electronic device, wherein the electronic device includes:

Processor; and,

A memory storing a computer-executable program which, when executed, causes the processor to perform any of the methods described above.

The embodiment of this specification also provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, any one of the above-mentioned methods can be implemented .

The various technical solutions provided by the embodiments of this specification construct a cache model based on variables, and configure annotation information with matching rules for the variables in the cache model, and call the cache model to read the annotation information in response to a cache trigger event , obtain the source data table, and determine the name of the target field in the source data table that matches the matching rule, assign the value of the variable in the cache model based on the name of the target field, and use the cache model after the assignment to read The field value corresponding to the target field name in the source data table generates key-value pair information and stores it in the cache space. The cache model can be independent of the data table, so it can be applied to different data tables, and can automatically read the field names and corresponding field values in the source data table, and cache them in advance to avoid temporarily reading data from relational data tables. The inefficiency of the data table is eliminated, and the convenience is improved by eliminating the need to develop code for each data table separately.

Description of drawings

The drawings described here are used to provide a further understanding of the application and constitute a part of the application. The schematic embodiments and descriptions of the application are used to explain the application and do not constitute an improper limitation to the application. In the attached picture:

FIG. 1 is a schematic diagram of the principle of a data caching method provided by an embodiment of this specification;

FIG. 2 is a schematic structural diagram of a data cache device provided by an embodiment of this specification;

FIG. 3 is a schematic structural diagram of an electronic device provided by an embodiment of this specification;

Fig. 4 is a schematic diagram of the principle of a computer-readable medium provided by the embodiment of this specification.

Detailed ways

Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. However, example embodiments may be embodied in many forms, and this invention should not be construed as limited to the embodiments set forth herein. On the contrary, providing these exemplary embodiments can make the present invention more comprehensive and complete, and facilitate the full transfer of the inventive concept to those skilled in the art. The same reference numerals denote the same or similar elements, components or parts in the drawings, and thus their repeated descriptions will be omitted.

On the premise of conforming to the technical concept of the present invention, the features, structures, characteristics or other details described in a specific embodiment do not exclude that they can be combined in one or more other embodiments in a suitable manner.

In the description of the specific embodiments, the features, structures, characteristics or other details described in the present invention are intended to enable those skilled in the art to fully understand the embodiments. However, it does not exclude that those skilled in the art can practice the technical solutions of the present invention without one or more of the specific features, structures, characteristics or other details.

The flow charts shown in the drawings are only exemplary illustrations, and do not necessarily include all contents and operations/steps, nor must they be performed in the order described. For example, some operations/steps can be decomposed, and some operations/steps can be combined or partly combined, so the actual order of execution may be changed according to the actual situation.

The block diagrams shown in the drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices entity.

The term "and/or" or "and/or" includes all combinations of any one or more of the associated listed items.

Figure 1 is a schematic diagram of the principle of a data caching method provided by an embodiment of this specification, the method may include:

S101: Construct a cache model based on variables, and configure annotation information with matching rules for the variables in the cache model.

The performance of memory in terms of reading and writing is generally several orders of magnitude higher than that of disk. In order to improve program performance and reduce access to the database, we can use the high performance of memory to cache database data, thereby improving program response speed and throughput.

Considering that the general business database uses a relational database, if you want to read the data in the database into the memory, you need to convert the storage structure.

Considering the need for data conversion when caching data, in order to avoid the disadvantages of cumbersome development process caused by separate business code development for each relational database table, we provide a processing method suitable for multiple data tables.

We make it possible to apply this method to multiple data tables through a caching model independent of data tables, rather than directly configuring caching instructions on data tables.

Then, considering the generality goal of this method, and the specificity constraints of cache instructions, we can construct the cache model as a general tool.

Specifically, we implement it with the following idea: in the stage of constructing the model, construct the cache model with variables, in the stage of using the cache model, determine how to assign values to the variables according to the source data table to be cached, and then use the cache model after assignment to realize cache.

In the embodiment of this specification, the variable-based construction of the cache model may include:

Constructs a cache directive and replaces field names within it with variables.

In this embodiment of the specification, attributes of variables, such as line numbers, can be configured in annotations.

The cache model corresponds to the table structure in the relational database, or corresponds to the data object that needs to be cached.

For example, the customer table contains the following fields: customer number, name, gender, ID number, and the business primary key can be: customer number, ID number.

In the embodiment of this specification, the configuration cache model may include:

Configure the cache model according to the structure information of the data table to be cached.

Specifically, the data table structure information includes field attributes corresponding to the data to be cached.

We can replace the data table parameter information and table structure parameter information in the originally developed code with variable forms to form variable expressions, and at the same time configure annotations for variable expressions to form a cache model to be assigned. In this way, when executing the cache model When reading the annotations and assigning values to the variable expressions, the field names and corresponding field values in the target relational data table can be read.

Specifically, it is possible to: configure annotations for data table parameter variables according to the target relational data table, and configure annotations for data table structure variables according to data table structure characteristics.

The structural feature of the data table may be the number of rows and columns where the target field is located.

In this way, instead of directly configuring data table names in the cache code, instead of directly configuring specific row and column names in the cache code, the cache model can be adapted to multiple data tables.

During specific implementation, the relational database can use mysql, oracle. Redis, memecache, etc. can be used in non-relational databases. In terms of caching, redis is usually used.

The embodiment of this specification can implement caching based on redis.

Considering that the API in the redis client may be difficult to meet more complex requirements, for example, when implementing some specific functions, it is likely to require multiple commands or interactions of multiple data types to complete, then such multiple network requests It has a relatively large impact on performance, so we can provide a mechanism to write some commands with business logic in order to reduce network requests. Specifically, support for the Lua environment is embedded in Redis, allowing developers to use Lua language to write scripts and transmit them to Redis for execution. Redis clients can use Lua scripts to directly execute multiple Redis commands atomically on the server side.

In this way, by configuring annotations and spring EL expressions on java methods in the embodiment of this specification, the caching technology can be conveniently used without modifying the logic of the business code.

Take adding the customer table as a cache as an example. The customer table contains the following fields: customer number, name, gender, and ID number. The operations on the customer table can include: query (such as query by customer number, or query by ID number) , Add (add a new customer), modify (modify the customer's name through the customer number, modify the customer's ID number through the customer number), delete (delete a customer through the customer number).

In this embodiment of the specification, the cache model is the CustEntity entity model, and the configuring the cache model may further include: configuring and initializing the cache of the CustEntity entity model based on xml.

Specifically, it can include: the system name for initializing the CustEntity entity model, the model type, the main cache switch, the maximum number of default caches, the default cache time, and the dynamic configuration environment information (based on the hot cache configuration implemented by the apollo configuration center: the maximum number of caches, the cache time wait).

Then configure the object fields to be cached: Based on the annotation configuration, initialize the field information cached in CustEntity and the key prefix cached in redis.

Specific code implementation:

S102: Call the cache model to read the annotation information in response to the cache trigger event, obtain the source data table, and determine the target field name in the source data table that matches the matching rule, based on the target field name Assign values to variables in the cached model.

Wherein, the caching trigger event may be that a data table to be cached in the database is updated, or a data table is newly created.

When considering practical applications, we can make the cache model applicable to all data tables of a certain database, or to a certain type of data table. For the latter, it is necessary to identify the data to be cached as the cache target when caching surface.

Therefore, in the embodiment of this specification, the matching rules also include source data table matching rules;

The acquisition source data table may include:

The source data table to be cached is determined and acquired from the database according to the source data table matching rule.

When reading the data in the data table, it may be read according to the structure of the data table. Therefore, when matching the field name, it can be matched according to the structure of the data table.

Therefore, in the embodiment of this specification, the table structure information of the target field name is included in the matching rule;

The determining the name of the target field matching the matching rule in the source data table may include:

The field name query is performed on the source data table by using the table structure information in the matching rule, and the queried target field name is read.

In the embodiment of this specification, the table structure information in the matching rule is a table structure function with time as an argument;

The field name query of the source data table by using the table structure information in the matching rule includes:

Determining the time of the cache trigger event, calculating a table structure function value in combination with the time and the table structure function, and generating a current matching rule according to the table structure function value;

Execute the current matching rule to perform field name query on the source data table.

In this embodiment of the specification, the value of the table structure function is a row number or a column number.

In the embodiment of this specification, the matching rules have preset field names and similarity calculation rules;

The determining the name of the target field matching the matching rule in the source data table includes:

Read the field name in the source data table, calculate its similarity with the preset field name according to the similarity calculation rule, and determine the matching target field name according to the similarity.

The similarity may be semantic similarity.

The semantics here can be equivalent semantics, or upper and lower semantics.

For example, if the default field in the matching rule is "Subject Score", then the matched field name can be: "Chinese Score", "Mathematics Score" or "English Score".

In the actual implementation, "a" can be constructed as a variable in the cache instruction, and its attribute "column number" and the matching rule for matching the column number of a can be added to the annotation. After obtaining the source data table, the field is matched according to the matching rule If the name is "mathematics score", assign "mathematics score" to a, and the cache model is called the code that can perform the cache function, and then read the data for caching.

S103: Use the assigned cache model to read the field value corresponding to the target field name in the source data table, generate key-value pair information and store it in the cache space.

Construct a cache model based on variables, configure annotation information with matching rules for the variables in the cache model, call the cache model to read the annotation information in response to a cache trigger event, obtain a source data table, and determine the source The target field name in the data table that matches the matching rule is based on the variable assignment in the cache model of the target field name, and the value corresponding to the target field name in the source data table is read using the cache model after the assignment. Field value, generate key-value pair information and store it in the cache space. The cache model can be independent of the data table, so it can be applied to different data tables, and can automatically read the field names and corresponding field values in the source data table, and cache them in advance to avoid temporarily reading data from relational data tables. The inefficiency of the data table is eliminated, and the convenience is improved by eliminating the need to develop code for each data table separately.

When reading data, the cache model finds the column "mathematics score", reads the field value under it, that is, the specific score value (such as 90), constructs a key-value pair "mathematics score: 90", and stores it in the memory middle.

In the embodiment of this specification, the method may also include:

Configure data table monitoring rules for the cache model to monitor update events of the source data table, and if the source data table is detected, perform data synchronous reading to update the cache.

When using a cached model, the following steps can be implemented:

When the application starts, the apolloDefaultEnv environment configuration is initialized, and the configuration can be loaded from Apollo in real time;

Initialize the CacheConfig.Builder configuration to obtain the cache configuration of the CustEntity model;

Read the cache specific field information of CustEntity. Store meta information in the application cache for execution (for example: key: com.qihoo.finance.cis.modules.cust.entity.CustEntity (cache object Key), value: com.qihoo.finance.hackit.cache. config.CacheConfig (cache object configuration metadata);

When the Dao method CustDao is executed, it enters the AOP interceptor.

An AOP interceptor can perform the following steps:

Step 1. When executing the method (selectCustByCustNo), it will first obtain the annotation on the method header, which is @CacheByFirstKeyAnnotation, then obtain the LUA expression, and obtain the value of the method input parameter custNo through the EL expression. Then use this value to execute the specific LUA script.

Among them, the execution of specific LUA scripts specifically includes:

Query the value REDIS_VALUE in Redis according to custNo;

If REDIS_VALUE is not empty, and the specified string "LOCK" is not specified, then use this value to return directly (optional: before returning, the convert method will be executed for data conversion and filling), and the database will not be queried;

If REDIS_VALUE is empty, it means that the custNo is not cached, and query the database again

If REDIS_VALUE is the specified string "LOCK", it means that the value is locked, and query the database again;

Query the database and get the data: DB_VALUE;

If DB_VALUE is empty, return directly;

If DB_VALUE is not empty, the object will be stored in Redis.

Step 2. When the getCustByIdNo method is executed, the annotation on the method header will be obtained first. This annotation is @CacheBySecondKeyAnnotation, the LUA expression is obtained, and the value of the method input parameter idNo is obtained through the EL expression. Then use this value to execute the specific LUA script.

Execute specific LUA scripts, including:

Query the customer number custNo in Redis according to idNo;

If custNo is empty, query the database directly;

Query the value REDIS_VALUE in Redis according to custNo;

Subsequent steps are the same as selectCustByCustNo and will not be described in detail.

Step 3. When the updateCustNameByCustNo method is executed, the EvictCacheByFirstKeyAnnotation annotation on the method header will be obtained first, the LUA expression will be obtained, and the value of the method input parameter custNo will be obtained through the EL expression. Execute specific LUA scripts, including:

Write locked data into Redis;

Fix REDIS_VALUE to "LOCK", and the default timeout is 60s;

Perform an update operation on the database.

Fig. 2 is a schematic structural diagram of a data caching device provided by an embodiment of this specification, and the device may include:

The model construction module 201 constructs a cache model based on variables, and configures annotation information with matching rules for the variables in the cache model;

The matching assignment module 202 calls the cache model to read the annotation information in response to the cache trigger event, obtains the source data table, and determines the name of the target field in the source data table that matches the matching rule, based on the The target field name is the variable assignment in the cache model;

The cache execution module 203 uses the assigned cache model to read the field value corresponding to the target field name in the source data table, and generates key-value pair information to store in the cache space.

The device constructs a cache model based on variables, configures annotation information with matching rules for the variables in the cache model, calls the cache model to read the annotation information in response to a cache trigger event, obtains a source data table, and determines the The target field name matching the matching rule in the source data table, based on the variable assignment in the cache model of the target field name, use the cache model after the assignment to read the target field name in the source data table Corresponding field values, generate key-value pair information and store them in the cache space. The cache model can be independent of the data table, so it can be applied to different data tables, and can automatically read the field names and corresponding field values in the source data table, and cache them in advance to avoid temporarily reading data from relational data tables. The inefficiency of the data table is eliminated, and the convenience is improved by eliminating the need to develop code for each data table separately.

Based on the same inventive concept, the embodiment of this specification also provides an electronic device.

An electronic device embodiment of the present invention will be described below, and the electronic device can be regarded as a specific physical implementation of the above-mentioned method and device embodiments of the present invention. The details described in the electronic device embodiments of the present invention should be regarded as supplements to the above method or device embodiments; details not disclosed in the electronic device embodiments of the present invention can be implemented by referring to the above method or device embodiments.

FIG. 3 is a schematic structural diagram of an electronic device provided by an embodiment of this specification. An electronic device 300 according to this embodiment of the present invention is described below with reference to FIG. 3 . The electronic device 300 shown in FIG. 3 is only an example, and should not limit the functions and application scope of this embodiment of the present invention.

As shown in FIG. 3, electronic device 300 takes the form of a general-purpose computing device. Components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including the storage unit 320 and the processing unit 310), a display unit 340, and the like.

Wherein, the storage unit stores program codes, and the program codes can be executed by the processing unit 310, so that the processing unit 310 executes the processing methods according to various exemplary embodiments of the present invention described in the above processing method section of this specification. step. For example, the processing unit 310 may execute the steps shown in FIG. 1 .

The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 3201 and/or a cache storage unit 3202 , and may further include a read-only storage unit (ROM) 3203 .

The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include the implementation of the network environment.

Bus 330 may represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local area using any of a variety of bus structures. bus.

The electronic device 300 can also communicate with one or more external devices 400 (such as keyboards, pointing devices, Bluetooth devices, etc.), and can also communicate with one or more devices that enable the user to interact with the electronic device 300, and/or communicate with Any device (eg, router, modem, etc.) that enables the electronic device 300 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interface 350 . Moreover, the electronic device 300 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and/or a public network such as the Internet) through the network adapter 360. The network adapter 360 can communicate with other modules of the electronic device 300 through the bus 330 . It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape Drives and data backup storage systems, etc.

Through the above description of the implementation manners, those skilled in the art can easily understand that the exemplary embodiments described in the present invention can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, and the software product can be stored in a computer-readable storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.) or on a network , including several instructions to make a computing device (which may be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. When the computer program is executed by a data processing device, the computer-readable medium can realize the above-mentioned method of the present invention, that is, the method as shown in FIG. 1 .

Fig. 4 is a schematic diagram of the principle of a computer-readable medium provided by the embodiment of this specification.

The computer program implementing the method shown in Figure 1 can be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: electrical connection with one or more conductors, portable disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

The computer readable storage medium may include a data signal carrying readable program code in baseband or as part of a carrier wave traveling as a data signal. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium other than a readable storage medium that can send, propagate or transport a program for use by or in conjunction with an instruction execution system, apparatus or device. Program code contained on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, cable, optical cable, RF, etc., or any suitable combination of the above.

Program code for carrying out the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural programming languages. Programming language - such as "C" or a similar programming language. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server to execute. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider). business to connect via the Internet).

To sum up, the present invention can be realized by hardware, or by software modules running on one or more processors, or by a combination thereof. Those skilled in the art should understand that general data processing devices such as microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all functions of some or all components in the embodiments of the present invention. The present invention can also be implemented as an apparatus or an apparatus program (for example, a computer program and a computer program product) for performing a part or all of the methods described herein. Such a program for realizing the present invention may be stored on a computer-readable medium, or may be in the form of one or more signals. Such a signal may be downloaded from an Internet site, or provided on a carrier signal, or provided in any other form.

The specific embodiments described above have further described the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the present invention is not inherently related to any specific computer, virtual device or electronic device, and various general devices are also The present invention can be realized. The above descriptions are only specific embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

Each embodiment in this specification is described in a progressive manner, the same and similar parts of each embodiment can be referred to each other, and each embodiment focuses on the differences from other embodiments.

The above descriptions are only examples of the present application, and are not intended to limit the present application. For those skilled in the art, various modifications and changes may occur in this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims (11)

A data caching method, characterized in that, comprising: Constructing a cache model based on variables, and configuring annotation information with matching rules for the variables in the cache model; Invoking the cache model to read the annotation information in response to the cache trigger event, obtaining the source data table, and determining the name of the target field in the source data table that matches the matching rule, based on the name of the target field Variable assignment in the cache model described above; Using the assigned cache model to read the field value corresponding to the target field name in the source data table, generate key-value pair information and store it in the cache space. The method according to claim 1, wherein the matching rule has table structure information of a target field name; The determining the name of the target field matching the matching rule in the source data table includes: The field name query is performed on the source data table by using the table structure information in the matching rule, and the queried target field name is read. The method according to claim 2, wherein the table structure information in the matching rule is a table structure function with time as an independent variable; The field name query of the source data table by using the table structure information in the matching rule includes: Determining the time of the cache trigger event, calculating a table structure function value in combination with the time and the table structure function, and generating a current matching rule according to the table structure function value; Execute the current matching rule to perform field name query on the source data table. The method according to claim 3, wherein the value of the table structure function is a row number or a column number. The method according to claim 1, further comprising: Configure data table monitoring rules for the cache model to monitor update events of the source data table, and if the source data table is detected, perform data synchronous reading to update the cache. The method according to claim 1, characterized in that, there are preset field names and similarity calculation rules in the matching rules; The determining the name of the target field matching the matching rule in the source data table includes: Read the field name in the source data table, calculate its similarity with the preset field name according to the similarity calculation rule, and determine the matching target field name according to the similarity. The method according to claim 1, wherein said constructing a cache model based on variables comprises: Constructs a cache directive and replaces field names within it with variables. The method according to claim 1, wherein the matching rule also has a source data table matching rule; The acquisition source data table includes: The source data table to be cached is determined and acquired from the database according to the source data table matching rule. A data cache device, characterized in that it comprises: The model construction module constructs a cache model based on variables, and configures annotation information with matching rules for the variables in the cache model; The matching assignment module calls the cache model to read the annotation information in response to the cache trigger event, obtains the source data table, and determines the target field name in the source data table that matches the matching rule, based on the target The field name is the variable assignment in the cache model; The cache execution module uses the assigned cache model to read the field value corresponding to the target field name in the source data table, and generates key-value pair information to store in the cache space. An electronic device, wherein the electronic device includes: Processor; and, A memory storing computer-executable instructions which, when executed, cause the processor to perform the method of any one of claims 1-8. A computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the implementation of any one of claims 1-8 Methods.

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