CN118210510A - Data processing method, system, computer device and medium - Google Patents
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Abstract
The present disclosure provides a data processing method, including: receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plugin according to a storage characteristic label corresponding to the application identifier, wherein the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label; and determining a target database corresponding to the storage plugin, and executing data processing operation corresponding to the first data processing request in the target database. The method and the device can improve flexibility, expansibility and intellectualization of the storage framework; the data service is isolated from the actual physical storage, so that decoupling of the application and the physical storage is realized, the best fit between the application and the database can be realized according to the storage requirement of the application, the best performance of the database is brought into full play, and the storage performance of the application in different service fields is ensured. The present disclosure also provides a data processing system, a computer device, and a readable medium.
Description
Technical Field
The present disclosure relates to the field of database technologies, and in particular, to a data processing method, a system, a computer device, and a medium.
Background
The low-code development is a development mode which is currently emerging, the application development efficiency can be greatly improved, the problem of insufficient development capacity in the application development field is solved, the low-code data storage is one of key subsystems of the low-code storage platform system, and the method has important significance for supporting the low-code storage platform to develop high-efficiency low-code application. The low-code development mode is mature gradually, the supported service field is expanded continuously, the data storage is more complex and variable, and the requirements on the platform storage subsystem are higher. How to efficiently support the requirements of various business field applications on data storage, simplify application development, and are important for constructing a good low-code storage platform.
The low-code development support field is continuously and rapidly developed, and is from simple light application to complex industry application, and single simple field is continuously expanded to various professional complex business fields. The method supports application development of different service fields, synchronously requires the platform to meet the storage requirements of applications in various service fields, and simultaneously, the platform itself keeps good expansion capacity to cope with the requirements of applications in potential service fields. The original simple and single storage design is insufficient to support the continuously complex storage requirement, and the current low code industry lacks systematic consideration on the change, so that the deficiency is continuously amplified and becomes a constraint and even a bottleneck affecting the development of the low code industry.
The current low-code storage platform system simply selects a single database for storage to finish the storage of low-code metadata or application service data, such as selecting a relational library longitudinal table mode to record metadata, or using a semi-structured database for storage, and the mode is simple to realize, and the characteristic of one database can be utilized for the early development of low codes to meet the service requirements of partial low-code application. However, with the continuous development of the low-code application field, supporting various different service fields has respective data processing requirements and storage requirements, and a single database or a simple storage design cannot meet the application scenes of various data, so that the storage efficiency of the overall application support of the platform cannot be ensured.
Disclosure of Invention
The present disclosure provides a data processing method, system, computer device and medium.
In a first aspect, an embodiment of the present disclosure provides a data processing method, including:
receiving a first data processing request of an application, and acquiring an application identifier carried in the first data processing request;
determining a storage plug-in according to the storage characteristic label corresponding to the application identifier; the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label, the storage requirement label represents the storage requirement of an application, and the storage characteristic label represents the characteristics of a database for storing application data;
determining a target database corresponding to the storage plugin;
And executing a data processing operation corresponding to the first data processing request in the target database.
In yet another aspect, an embodiment of the present disclosure provides a data processing system, including a data service layer, a data adaptation layer, and a storage layer, where the storage layer includes a database;
The data service layer is used for receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plug-in according to a storage characteristic label corresponding to the application identifier; the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label, the storage requirement label represents the storage requirement of an application, and the storage characteristic label represents the characteristics of a database for storing application data;
the data adaptation layer is used for determining a target database corresponding to the storage plugin, and executing data processing operation corresponding to the first data processing request in the target database.
In yet another aspect, the disclosed embodiments also provide a computer device, comprising: one or more processors; a storage device having one or more programs stored thereon; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data processing method as described above.
In yet another aspect, the disclosed embodiments also provide a computer readable medium having a computer program stored thereon, wherein the program when executed implements the data processing method as described above.
The data processing method provided by the embodiment of the disclosure comprises the following steps: receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plugin according to a storage characteristic label corresponding to the application identifier, wherein the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label; and determining a target database corresponding to the storage plugin, and executing data processing operation corresponding to the first data processing request in the target database. According to the embodiment of the disclosure, the application data is matched with the characteristics of the database by establishing the mapping relation between the storage requirement label and the storage characteristic label, the mapping relation can be flexibly defined, the storage requirement label and the storage characteristic label can be expanded, and the flexibility, expansibility and intellectualization of the storage framework are improved; the data service is isolated from the actual physical storage, and the decoupling of the application and the physical storage is realized, so that the application development does not need to pay attention to the selection of the bottom storage, the optimal fit between the application and the database can be realized according to the storage requirement of the application, the optimal performance of the database is brought into full play to the greatest extent, and the storage performance of the application in different service fields is ensured.
Drawings
FIG. 1 is a schematic flow chart of a data processing method according to an embodiment of the disclosure;
FIG. 2 is a flow chart of performing data processing operations in a target database according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a data processing flow provided in an embodiment of the disclosure;
FIG. 4 is a schematic flow chart of creating an application provided by an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a data processing system according to an embodiment of the present disclosure.
Detailed Description
Example embodiments will be described more fully hereinafter with reference to the accompanying drawings, but may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Embodiments described herein may be described with reference to plan and/or cross-sectional views with the aid of idealized schematic diagrams of the present disclosure. Accordingly, the example illustrations may be modified in accordance with manufacturing techniques and/or tolerances. Thus, the embodiments are not limited to the embodiments shown in the drawings, but include modifications of the configuration formed based on the manufacturing process. Thus, the regions illustrated in the figures have schematic properties and the shapes of the regions illustrated in the figures illustrate the particular shapes of the regions of the elements, but are not intended to be limiting.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The embodiment of the disclosure provides a data processing method, which is applied to a data processing system, as shown in fig. 5, and the data processing system is used for storing, modifying, deleting, reading and the like application data (such as business data) of various applications. Applications may include, but are not limited to, strong transaction applications, hybrid applications, high volume applications, and the like. In the embodiments of the present disclosure, a data processing system is illustrated as a low code storage platform system. As shown in fig. 5, the low-code storage platform system comprises a data service layer, a data adaptation layer and a storage layer, wherein the storage layer comprises a database, the data service layer stores access routes of various applications to the database; the data adaptation layer is used for storing the storage plug-ins of each database, realizing the matching of the application and the database, and calling the corresponding storage plug-ins in each database to realize data processing; the databases in the storage layer are physical databases storing application data of respective applications, including a relational database ((RDMBS) or a non-relational database (NoSQL), and exemplary databases may be a MYSQL database, mongodb database, orcale database, an elastic search database, and the like.
As shown in connection with fig. 1,3 and 5, the data processing method comprises the following steps:
step S11, a first data processing request of an application is received, and an application identifier carried in the first data processing request is obtained.
The data service layer of the data processing system receives a first data processing request for each application, the first data processing request including, but not limited to, requests for data storage, data querying, data modification (data addition/data deletion), and the like. And acquiring the application identifier carried in the first data processing request through analyzing the first data processing request so as to determine the application to be processed.
Step S12, determining a storage plug-in according to a storage characteristic label corresponding to the application identifier, wherein the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and the storage characteristic label.
The storage requirement label represents the storage requirement of an application, different applications support various different business fields and have respective data processing requirements and storage requirements, so that different applications correspond to different storage requirement labels. The storage characteristic tags represent characteristics of databases for storing application data, each database is configured with one storage characteristic tag, and the storage characteristic tags of different databases may be the same or different.
The data service layer stores a preset mapping relation between the storage requirement label and the storage characteristic label and a storage characteristic label corresponding to each application, the storage characteristic label corresponding to each application reflects routing information of data access, and the routing information is automatically generated and stored according to the mapping relation between the storage requirement label and the storage characteristic label when each application is established. In this step, the storage characteristic tag corresponding to the application identifier may be directly obtained from the data service layer, and the storage plugin may be determined according to the obtained storage characteristic tag.
Step S13, determining a target database corresponding to the storage plugin.
In this step, the data adaptation layer locates the target database according to the determined storage plugins. The method can determine the storage strategy of the application metadata and the business data, select one or more databases to complete data processing (such as data storage), and the application user does not need to directly pay attention to the storage scheme of the application, but only needs to describe the storage requirement of the application.
Step S14, a data processing operation corresponding to the first data processing request is performed in the target database.
The data adaptation layer performs operations such as data storage, data query, data modification (data addition/data deletion) and the like in the target database, and returns a data processing result.
The data processing method provided by the embodiment of the disclosure comprises the following steps: receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plugin according to a storage characteristic label corresponding to the application identifier, wherein the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label; and determining a target database corresponding to the storage plugin, and executing data processing operation corresponding to the first data processing request in the target database. According to the embodiment of the disclosure, the application data is matched with the characteristics of the database by establishing the mapping relation between the storage requirement label and the storage characteristic label, the mapping relation can be flexibly defined, the storage requirement label and the storage characteristic label can be expanded, and the flexibility, expansibility and intellectualization of the storage framework are improved; the data service is isolated from the actual physical storage, and the decoupling of the application and the physical storage is realized, so that the application development does not need to pay attention to the selection of the bottom storage, the optimal fit between the application and the database can be realized according to the storage requirement of the application, the optimal performance of the database is brought into full play to the greatest extent, and the storage performance of the application in different service fields is ensured.
In some embodiments, the language of the first data processing request is a preset database language, including but not limited to a standard SQL language.
Accordingly, as shown in fig. 2 and 3, the performing the data processing operation corresponding to the first data processing request in the target database (i.e. step S14) includes the following steps:
Step S141, converting the first data processing request in the preset database language into the second data processing request in the target database language.
In this step, the data adaptation layer performs a database language conversion on the data processing request. For example, if the target database is Mongodb databases and the preset database is an SQL database, converting the standard SQL query statement into Mongodb query statement through Mongo grammar; if the target database is an elastic search database and the preset database is an SQL database, converting the standard SQL query statement into an elastic search query statement through an ES grammar.
Step S142, a data processing operation corresponding to the second data processing request is performed in the target database.
In this step, operations such as data storage, data query, data modification (data addition/data deletion) and the like corresponding to the second data processing request of the target database language are performed in the target database.
In some embodiments, the storage plugin includes a storage instance through which the respective databases implement various data processing operations.
The step of converting the first data processing request in the preset database language into the second data processing request in the target database language (i.e. step S141) includes the steps of: and calling a storage instance of the storage plug-in, and converting the first data processing request in the preset database language into a second data processing request in the target database language by using the storage instance. That is, the data adaptation layer implements syntax conversion by calling the storage instance of the storage plug-in determined in step S12.
In some embodiments, as shown in FIG. 5, an application includes at least one storage requirement label, i.e., one or more storage requirement labels are configured for each application. At least one database corresponds to the same storage characteristic label and the same storage plug-in, namely, each database is provided with a storage characteristic label, and each database is provided with a storage plug-in. The different databases may have the same or different storage characteristic labels and the same or different storage plugins.
In some embodiments, at least two different types of databases correspond to the same storage characteristic tag and the same storage plugin. In the embodiment of the present disclosure, the types of databases include a relational database and a non-relational database, and one Relational Database (RDBMS) and one non-relational database (NoSQL) may correspond to the same storage characteristic tag and the same storage plugin, as shown in fig. 5, in which case data of one application may be stored in the two databases. The same storage characteristic is commonly supported by using multiple types of database combinations, so that the storage requirement of an application is matched with the storage characteristic of physical storage more adaptively and accurately, and various possibilities of future development can be dealt with.
In some embodiments, before receiving the first data processing request of the application (i.e. step S11), the data processing method may further comprise the steps of: and creating the applications and determining storage characteristic labels corresponding to the application identifiers of the applications.
As shown in fig. 4, the creating an application and determining a storage characteristic label corresponding to an application identifier of each application include the following steps:
Step 21, in the process of creating the application, the storage requirement label is configured for each application.
When an application is created in the low-code storage platform system, the storage requirement of the application is selected, and corresponding storage requirement labels are stored in the schema (object set) of the application, so that the configuration of the storage requirement labels is realized.
And step 22, determining a storage characteristic label corresponding to the application identifier of each application according to the storage requirement label and a preset mapping relation.
In the step, in the application creation stage, the storage requirement label of the application can be automatically queried according to the mapping relation. Because the mapping relation is stored by taking the application identifier of the application as an index, the storage characteristic labels corresponding to the applications can be stored in the data service layer by taking the application identifier of the application as an index so as to record the route information of data access, and when the data of the application is processed subsequently, the corresponding database is determined according to the route information.
The embodiment of the disclosure further provides a data processing system, as shown in fig. 5, where the data processing system includes a data service layer, a data adaptation layer, and a storage layer, and the storage layer includes a database.
The data service layer is used for receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plug-in according to a storage characteristic label corresponding to the application identifier; the storage characteristic label is determined according to a preset mapping relation between the storage requirement label and the storage characteristic label, the storage requirement label represents the storage requirement of the application, and the storage characteristic label represents the characteristics of a database for storing application data;
The data adapting layer is used for determining a target database corresponding to the storage plug-in, and executing data processing operation corresponding to the first data processing request in the target database.
In some embodiments, the data processing system is a low code storage platform system.
The following describes in detail the data storage architecture creation process and the data processing process of the low-code storage platform system, taking the low-code storage platform system as an example, with reference to fig. 5 and 3.
Step 1, extract data services layer, this layer provides DDL (Data Definition Language ) and DML (Data Manipulation Language, data operation language) operations to upper layer applications, such as: basic service interfaces such as newly-built library table, newly-added data, modified data, deleted data, query data, paging query data and the like isolate upper-layer application from specific physical storage and unify service capacities of different physical storage pairs.
According to the application mode of metadata definition, the data storage north-oriented service interface and south-oriented adaptation interface of the abstract metadata are used for storing and designing the business data and the metadata in a separated mode, and meanwhile, the requirements of function requirements, performance, capacity, safety, multi-tenant, authority and management layer interfaces of the data plug-in are met.
The storage requirement label and the storage characteristic label of the management application are configured to be mapped.
And 2, defining a unified input/output interface in the data service layer, and carrying out standardization processing on parameters responded by the data request of the upper layer.
And 3, extracting the data adaptation layer, uniformly developing a protocol, and building and storing storage plug-ins of all databases without paying attention to protocol driving of all databases in the storage layer so as to realize data storage.
The southbound adaptation interface is realized to dock different databases in the storage layer, the conversion from the service interface to the storage layer is completed, the differentiation of the databases is shielded, and the storage characteristic labels of the databases are defined.
The combination of the actual database and the storage plug-in instance is deployed to support the south-oriented adaptation interface requirements.
The steps 1-3 are the creation process of the low-code storage platform system, and the following steps 4-5 are the data processing process of the low-code storage platform system.
And 4, after receiving a data processing request of DSL (Domain Specific Language ) sent by the upper layer application through a query interface of the data service layer, selecting a storage plug-in at the data service layer according to a storage characteristic label (namely a storage route) corresponding to the application identifier. When the application is created, the storage characteristic label is automatically determined according to a preset mapping relation between the storage requirement label and the storage characteristic label.
And 5, determining a target database corresponding to the storage plugin by the data adaptation layer, calling the corresponding storage plugin to perform database language conversion on the data processing request sent by the data service layer, converting the data processing request into the language of the target database, and executing corresponding data processing operation in the target database.
The embodiment of the disclosure is applied to a low-code storage platform system, and supports data storage differentiated appeal scenes in various application development fields and other scenes with similar requirements, such as a data lake design scene and the like.
According to the embodiment of the disclosure, the data service and the data physical storage are separated and converted, so that the flexibility and the expandability of the data storage are improved, the decoupling of the application data and the physical storage is realized, and the optimal route matching of the storage requirement of the application and the actual storage capacity of the database is realized through flexible configuration of the storage requirement of the application and the storage characteristic of the database.
Aiming at the problem that a single database or a simple collaborative data storage architecture cannot meet the data storage requirement continuously developed in the field of low-code development application, the embodiment of the disclosure provides a data storage architecture with layered design, application calling and physical storage are separated, and a mapping relation between a storage requirement label and a storage characteristic label is introduced by the data storage architecture, so that the best matching of the application and the storage is realized. And the storage requirements and the decoupling of the database are realized by analyzing the support of the application capacity of the low-code storage platform system and abstracting the storage requirements of the low-code storage platform system and the application data. The method comprises the steps of analyzing characteristics of different databases, defining storage characteristic labels, defining different storage requirement labels for storage requirements of different types of applications, configuring mapping relations between the storage requirement labels and the storage characteristic labels to form storage routes, automatically selecting different storage plugins and corresponding databases according to the storage routes to finish storage calling of application data, realizing optimal matching of the characteristics of the application and the databases, and fully playing own advantages of the databases. The mapping relation has enough flexibility, can be customized, the storage characteristic label and the storage requirement label can be expanded, and the types of the database can be increased; multiple types of database combinations can be used to jointly support storage characteristics, so that the storage requirements of an application are matched with the storage characteristics of the database more adaptively and accurately, and various future development possibilities can be dealt with.
The embodiment of the disclosure adopts isolation of data service and physical storage, realizes separation of low-code data service and an actual database, and increases expansibility, flexibility and intellectualization of a storage framework by associating the storage requirement of an application with the storage characteristic of the database. The low-code application development does not need to pay attention to selection of bottom storage, the optimal fit between the application and the database can be realized according to the storage requirement of the application, the optimal performance of the database is exerted to the greatest extent, and the storage performance of the low-code application in different service fields is ensured.
The disclosed embodiments also provide a computer device comprising: one or more processors and a storage device; wherein the storage device stores one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the data processing method provided in the foregoing embodiments.
The disclosed embodiments also provide a computer readable medium having a computer program stored thereon, wherein the computer program, when executed, implements the data processing method as provided by the foregoing embodiments.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, functional modules/units in the apparatus disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted in a generic and descriptive sense only and not for purpose of limitation. In some instances, it will be apparent to one skilled in the art that features, characteristics, and/or elements described in connection with a particular embodiment may be used alone or in combination with other embodiments unless explicitly stated otherwise. It will therefore be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the scope of the present invention as set forth in the following claims.
Claims (10)
1. A method of data processing, comprising:
receiving a first data processing request of an application, and acquiring an application identifier carried in the first data processing request;
determining a storage plug-in according to the storage characteristic label corresponding to the application identifier; the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label, the storage requirement label represents the storage requirement of an application, and the storage characteristic label represents the characteristics of a database for storing application data;
determining a target database corresponding to the storage plugin;
And executing a data processing operation corresponding to the first data processing request in the target database.
2. The method of claim 1, wherein the language of the first data processing request is a preset database language, and the performing, in the target database, a data processing operation corresponding to the first data processing request comprises:
converting the first data processing request of the preset database language into a second data processing request of the target database language;
and executing a data processing operation corresponding to the second data processing request in the target database.
3. The method of claim 2, wherein the storage plug-in includes a storage instance, the converting the first data processing request in the preset database language to the second data processing request in the target database language, comprising:
and calling a storage instance of the storage plug-in, and converting the first data processing request of the preset database language into a second data processing request of the target database language by using the storage instance.
4. The method of claim 1, wherein prior to receiving the first data processing request of the application, the method further comprises: creating applications and determining storage characteristic labels corresponding to application identifiers of the applications;
the creating the application and determining the storage characteristic label corresponding to the application identifier of each application comprises the following steps:
in the process of creating the applications, configuring storage requirement labels for the applications;
and determining a storage characteristic label corresponding to the application identifier of each application according to the storage requirement label and the preset mapping relation.
5. The method of claim 1, wherein an application includes at least one storage requirement label, at least one of the databases corresponding to the same storage characteristic label and the same storage plug-in.
6. The method of claim 5, wherein at least two different types of the databases correspond to the same storage characteristic tag and the same storage plugin.
7. The method of any of claims 1-6, wherein the method is applied to a low code storage platform system.
8. A data processing system comprising a data service layer, a data adaptation layer and a storage layer, the storage layer comprising a database;
The data service layer is used for receiving a first data processing request of an application, acquiring an application identifier carried in the first data processing request, and determining a storage plug-in according to a storage characteristic label corresponding to the application identifier; the storage characteristic label is determined according to a mapping relation between a preset storage requirement label and a storage characteristic label, the storage requirement label represents the storage requirement of an application, and the storage characteristic label represents the characteristics of a database for storing application data;
the data adaptation layer is used for determining a target database corresponding to the storage plugin, and executing data processing operation corresponding to the first data processing request in the target database.
9. A computer device, comprising:
one or more processors;
A storage device having one or more programs stored thereon;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data processing method of any of claims 1-7.
10. A computer readable medium having stored thereon a computer program, wherein the program when executed implements the data processing method according to any of claims 1-7.
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