Provenance method for application program interfaces of data services

Abstract

The application discloses a data service application interface tracing method. The method comprises the following steps: obtaining a target application interface corresponding to a target data service; obtaining a first result table corresponding to the target application interface in a preset type database through a meta warehouse data table of a data center; combing a data link relationship between the first result table and a second result table corresponding to an analysis layer of the data center, and obtaining a corresponding relationship between the second result table and a shared layer business detail table; and integrating a full link relationship from a database to the shared layer of the target data service according to at least the corresponding relationship and the data link relationship. The application solves the technical problem that the use of data services cannot be determined due to the lack of effective data service combing methods in related technologies, resulting in a large number of scattered data analysis applications and low practical value.

Description

Technical Field

[0001] This application relates to the field of data processing, and more specifically, to a method for tracing the source of an application programming interface (API) for a data service. Background Technology

[0002] With the digitalization and intelligentization of core power grid operations, the number of professional data analysis services is constantly increasing. These services are characterized by diversity, inconsistent standards, and low sharing. In related technologies, the lack of effective methods for analyzing data links means that the company's data platform cannot directly obtain information on whether data service APIs are being used, their complexity, and activity levels. This makes it difficult for data managers to effectively grasp data usage and destination, leaving them unclear about "where the data is used, how it is used, and for whom it is used." Furthermore, the lack of unified management and results sharing at the company level results in numerous but scattered data analysis applications with low practical value.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a method for tracing the application programming interface (API) of a data service, which at least solves the technical problem that the lack of an effective data service sorting method in related technologies makes it impossible to determine the usage of data services, resulting in a large number of scattered data analysis applications with low practical value.

[0005] According to one aspect of the embodiments of this application, a method for tracing the application interface of a data service is provided, comprising: obtaining a target application interface corresponding to a target data service; obtaining a first result table corresponding to the target application interface in a preset type database through the metadata table of the data middle platform; sorting out the data link relationship between the first result table and a second result table corresponding to the analysis layer of the data middle platform, and obtaining the correspondence between the second result table and the business detail table of the shared layer; and integrating the entire link relationship of the target data service from the database to the shared layer based at least on the correspondence relationship and the data link relationship.

[0006] Optionally, the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, including: extracting preset type fields from the original data table, parsing the fields to obtain the preset type data corresponding to the fields, and filtering the preset type data to obtain the data link relationship.

[0007] Optionally, the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, and the correspondence between the second result table and the shared layer business detail table is obtained. This includes: iteratively extracting all lineage links from the second result table corresponding to the data platform analysis layer to the shared layer business detail table, obtaining all shared layer data tables corresponding to the second result table of each analysis layer, and storing them in the form of a data list.

[0008] Optionally, after integrating the full-link relationship of the target data service from the database to the shared layer based at least on the correspondence and data link relationship, the method further includes: obtaining the number of business detail tables used by the target data service in the shared layer; comparing the number with preset data, and marking the service complexity of the target data service.

[0009] Optionally, after obtaining the target application interface corresponding to the target data service, the method further includes: obtaining the access frequency of the target data service within the target time period and the last access time through the data warehouse data table of the data platform.

[0010] Optionally, after obtaining the access frequency of the target data service within the target time period and the last access time through the data warehouse data table of the data platform, the method further includes: determining whether the target data service is available based on the last access time; and if the target data service is determined to be available, determining the activity level of the target data service based on the number of accesses within the target time period.

[0011] Optionally, determining whether the target data service is available based on the last access time includes: obtaining the real-time time corresponding to the current moment, determining the difference between the last access time and the real-time time; if the difference is greater than a preset duration, determining that the target data service is unavailable and taking the target data service offline.

[0012] Optionally, the default database type includes: RDS database.

[0013] According to another aspect of the embodiments of this application, a tracing device for an application programming interface (API) of a data service is also provided, comprising: a first acquisition module, configured to acquire a target API corresponding to a target data service; a second acquisition module, configured to acquire a first result table corresponding to the target API in a preset type database through a data middleware data table; a sorting module, configured to sort out the data link relationship between the first result table and a second result table corresponding to the analysis layer of the data middleware, and acquire the correspondence between the second result table and a shared layer business detail table; and an integration module, configured to integrate the entire link relationship of the target data service from the database to the shared layer based at least on the correspondence relationship and the data link relationship.

[0014] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the storage medium including a stored program, wherein a tracing method is provided for controlling the device where the storage medium is located to execute any kind of data service application programming interface during program execution.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement a tracing method for an application programming interface of any data service.

[0016] In this embodiment, the following methods are employed: 1) Obtain the target application interface corresponding to the target data service; 2) Obtain the first result table corresponding to the target application interface in a preset type database through the data repository data table of the data platform; 3) Organize the data link relationship between the first result table and the second result table corresponding to the analysis layer of the data platform, and obtain the correspondence between the second result table and the business detail table of the shared layer; 4) Integrate the entire link relationship of the target data service from the database to the shared layer based on at least the correspondence and data link relationship, thereby achieving automated data link organization, understanding the actual use of data, data usage, data destination, and other technical effects. This solves the technical problem that the lack of effective data service organization methods in related technologies leads to the inability to determine the usage of data services, resulting in a large number of scattered data analysis applications with low practical value. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a flowchart illustrating the tracing method of the application programming interface of a data service according to an embodiment of this application;

[0019] Figure 2 This is a flowchart illustrating the specific implementation process of the data service application interface tracing method in one embodiment of this application;

[0020] Figure 3 This is a schematic diagram of the structure of a data service application interface tracing device according to an embodiment of this application;

[0021] Figure 4 A schematic block diagram of an electronic device 400 according to an embodiment of this application. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] To facilitate a better understanding of the relevant embodiments of this application by those skilled in the art, the technical terms or nouns that may be involved in this application are explained as follows:

[0025] Data platform: refers to a big data architecture that integrates the collection, governance, modeling, analysis, and application of multi-source heterogeneous data from within and outside an enterprise.

[0026] Data Service API: Application Programming Interface, a network service that provides an interface-level call entry point to the outside world. Its characteristic is that it returns the analytical data required by the business requester.

[0027] RDS (Relational Database Service): RDS is short for Relational Database Service, a ready-to-use, stable, reliable, and elastically scalable online database service. It features multiple security measures and a comprehensive performance monitoring system, and provides professional database backup, recovery, and optimization solutions, allowing you to focus on application development and business growth.

[0028] The shared layer is the standard model layer in the data platform architecture. It stores detailed enterprise-level business standard data that has undergone model mapping transformation, unified encoding, and data normalization. All data sharing services with upper-layer applications are completed within the shared layer.

[0029] Analysis Layer: This is the public data layer in the data platform architecture, including public dimension tables, public detail (fact) tables, and public summary tables. It is processed from the data in the shared layer and mainly completes data processing and integration, establishes consistent dimensions, constructs reusable detailed fact tables for analysis and statistics, and summarizes public granularity indicators.

[0030] MaxCompute, Alibaba's distributed big data computing service, provides petabyte-scale data warehouse solutions. It employs a distributed architecture, allowing for parallel scaling as needed, and features automatic fault tolerance mechanisms to ensure high data reliability. It supports multiple programming models, including SQL, MapReduce, and Graph, and supports multi-tenancy, enabling multiple users to collaboratively analyze data.

[0031] Dataworks: Alibaba's professional, efficient, secure and reliable one-stop big data intelligent R&D platform, which can meet users' needs for data access, data governance, data development and quality management. From data development to algorithm development, the closed loop covers the entire data business process, giving users one-stop data development capabilities.

[0032] Data Integration (DI): Alibaba's reliable, secure, low-cost, and elastically scalable data synchronization platform that can synchronize data across heterogeneous data storage systems, providing full / incremental data input / output channels for various data sources under different network environments.

[0033] According to an embodiment of this application, an embodiment of a method for tracing the application interface of a data service is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] Figure 1 This is a method for tracing the application programming interface of a data service according to embodiments of this application, such as... Figure 1 As shown, the method includes the following steps:

[0035] Step S102: Obtain the target application interface corresponding to the target data service;

[0036] Step S104: Obtain the first result table corresponding to the target application interface in the preset type database through the data warehouse data table of the data platform;

[0037] Step S106: Analyze the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer, and obtain the correspondence between the second result table and the shared layer business detail table;

[0038] Step S108: Integrate the entire link relationship of the target data service from the database to the shared layer based at least on the corresponding relationship and data link relationship.

[0039] The method for tracing the application interface of this data service involves obtaining the target application interface corresponding to the target data service; obtaining the first result table corresponding to the target application interface in a preset type database through the data warehouse data table of the data platform; sorting out the data link relationship between the first result table and the second result table corresponding to the analysis layer of the data platform, and obtaining the correspondence between the second result table and the business detail table of the shared layer; and integrating the entire link relationship of the target data service from the database to the shared layer based on at least the correspondence and data link relationship. This achieves automated sorting of the data link, grasps the actual use of data, and understands the usage and destination of data. This solves the technical problem that the lack of effective data service sorting methods in related technologies leads to the inability to determine the usage of data services, resulting in a large number of scattered data analysis applications with low practical value.

[0040] In some embodiments of this application, the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, including: extracting preset type fields from the original data table, parsing the fields to obtain the preset type data corresponding to the fields, and filtering the preset type data to obtain the data link relationship.

[0041] Optionally, the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, and the correspondence between the second result table and the shared layer business detail table is obtained. This includes: iteratively extracting all lineage links from the second result table corresponding to the data platform analysis layer to the shared layer business detail table, obtaining all shared layer data tables corresponding to the second result table of each analysis layer, and storing them in the form of a data list.

[0042] Optionally, after integrating the full-link relationship of the target data service from the database to the shared layer based at least on the correspondence and data link relationship, the method further includes: obtaining the number of business detail tables used by the target data service in the shared layer; comparing the number with preset data, and marking the service complexity of the target data service.

[0043] Optionally, after obtaining the target application interface corresponding to the target data service, the method further includes: obtaining the access frequency of the target data service within the target time period and the last access time through the data warehouse data table of the data platform.

[0044] In some embodiments of this application, after obtaining the access frequency of the target data service within a target time period and the last access time through the data warehouse data table of the data platform, the method further includes: determining whether the target data service is available based on the last access time; and if the target data service is determined to be available, determining the activity level of the target data service based on the number of accesses within the target time period.

[0045] As an optional implementation, determining whether a target data service is available based on the last access time can be achieved in the following way: Specifically, the real-time time corresponding to the current moment can be obtained, and the difference between the last access time and the real-time time can be determined; if the difference is greater than a preset duration, the target data service is determined to be unavailable and the target data service is taken offline.

[0046] It should be noted that the above-mentioned preset database types include: RDS databases.

[0047] To facilitate understanding of the above technical solutions, the following is a combination of... Figure 2 The above embodiments will be described in detail. Figure 2 This is a specific implementation process of the tracing method for the application programming interface of the data service in one embodiment of this application, such as... Figure 2 As shown:

[0048] The main technical concept of this application is to rely on the data in the data middle platform's metadata repository to sort out the corresponding result tables in the RDS database for data service APIs. Based on the synchronization link between the RDS result table data and the data in the data middle platform's analysis layer, the corresponding analysis layer result tables for the APIs are obtained. On this basis, according to the data table lineage in the data middle platform, the entire link from RDS to the corresponding business detail data in the data middle platform is sorted out for the data service APIs. Based on the sorting results, the data service APIs are tagged with multiple dimensions such as complexity, whether it is recommended to take them offline, and activity level.

[0049] Based on the above analysis results, a platform for monitoring the entire API lineage and activity was developed using the self-developed analysis tool FineBI. This platform monitors relevant indicator information and creates a unified data service API resource catalog. The specific steps are as follows:

[0050] (1) Organize the RDS result table corresponding to the API, the last access time of the API, and the data access frequency in the past year.

[0051] The RDS data corresponding to the data service API is obtained from the YuanCang data table un9001_01_meta1_dwdataservice_api_datasource_version. The access frequency and last access time of the data service API in the past year are obtained from the YuanCang data table un9001_01_meta1_sls_api_apigateway_log_bjdc_1.

[0052] (2) Analyze the data link between the data platform analysis layer result table and the RDS result table.

[0053] By writing a pyoodps script, the data table un9001_01_ in the source repository is extracted.

[0054] The `content(json string)` field in `meta1_dwide_file` is further parsed into JSON data, filtering the data link from MaxCompute to MySQL, thereby obtaining the data link relationship between the data middleware analysis layer result table and the RDS result table.

[0055] (3) Organize the shared layer detail tables corresponding to the data platform analysis layer result tables.

[0056] Based on the single-link primary lineage relationships in the Yuancang data table un9001_01_meta1_dpbizmeta_base_meta_temp_table_relation, a pyodps script was written to iteratively extract all lineage links from the analysis layer result table to the shared layer detail table. This yielded all shared layer data tables corresponding to each analysis layer result table, which were then stored in the form of a data list.

[0057] (4) Integrate the entire data service API into the sharing layer

[0058] Based on the above three data relationships: the relationship between the data service API and the RDS result table, the relationship between the RDS data table and the data middle platform analysis layer result table, and the relationship between the data middle platform analysis layer data table and the shared layer detail table, a wide data result table from the data service to the data middle platform shared layer is constructed by associating the data table names.

[0059] (5) Setting multi-dimensional tags for API complexity, API usage status, and API access activity.

[0060] Based on the number of business detail data tables in the shared layer of the data platform used by the data service API, label the data service API as simple API, general API, and complex API; based on the last access time of the data service API, label the data service API as whether it is in use. For APIs with no access records in the past year, data administrators can take them offline to save data platform resources; based on the data access frequency in the past year, label the data service API as active, general, and inactive.

[0061] Understandably, the above methods can automate the process of identifying the link relationships and related dimensional information between data service APIs and various levels of the data platform. Secondly, data management personnel and relevant business personnel can use the API end-to-end lineage and activity monitoring platform to effectively understand the actual situation of "who uses, where, and for whom" data services. Furthermore, the API's activity level, complexity, and usage status provide strong support for data management in the data platform, while also offering a new approach to analyzing the call frequency of data detail tables in the data platform's shared layer. Simultaneously, a preliminary company-level API data resource sharing catalog can be constructed, addressing collaborative data sharing security control issues and enabling the accumulation of common data analysis service assets within the company.

[0062] Figure 3 This is a tracing device for an application programming interface (API) of a data service according to an embodiment of this application, such as... Figure 3 As shown, the device includes:

[0063] The first acquisition module 30 is used to acquire the target application interface corresponding to the target data service;

[0064] The second acquisition module 32 is used to acquire the first result table corresponding to the target application interface in a preset type database through the data warehouse data table of the data platform;

[0065] The sorting module 34 is used to sort out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer, and to obtain the correspondence between the second result table and the business detail table of the shared layer.

[0066] Integration module 36 is used to integrate the entire link relationship of the target data service from the database to the shared layer, based at least on the correspondence and data link relationship.

[0067] In this traceability device, the first acquisition module 30 is used to acquire the target application interface corresponding to the target data service; the second acquisition module 32 is used to acquire the first result table corresponding to the target application interface in a preset type database through the data warehouse data table of the data platform; the sorting module 34 is used to sort out the data link relationship between the first result table and the second result table corresponding to the analysis layer of the data platform, and acquire the correspondence between the second result table and the business detail table of the shared layer; the integration module 36 is used to integrate the entire link relationship of the target data service from the database to the shared layer based at least on the correspondence and data link relationship, thereby realizing the automated sorting of the data link, grasping the actual use of data, as well as the data usage and data destination, etc., and thus solving the technical problem that the lack of effective data service sorting methods in related technologies leads to the inability to determine the usage of data services, resulting in a large number of scattered data analysis applications with low practical value.

[0068] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the storage medium including a stored program, wherein a tracing method is provided for controlling the device where the storage medium is located to execute any kind of data service application programming interface during program execution.

[0069] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement a tracing method for an application programming interface of any data service.

[0070] Specifically, the aforementioned storage medium is used to store program instructions for the following functions, thereby implementing the following functions:

[0071] Obtain the target application interface corresponding to the target data service; obtain the first result table corresponding to the target application interface in the preset type database through the data warehouse data table of the data platform; sort out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer, and obtain the correspondence between the second result table and the business detail table of the shared layer; integrate the entire link relationship of the target data service from the database to the shared layer based on at least the correspondence relationship and the data link relationship.

[0072] Optionally, in this embodiment, the storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specific examples of the storage medium include electrical connections based on 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), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0073] In an exemplary embodiment of this application, a computer program product is also provided, including a computer program and a method for tracing the source of the application programming interface that implements the data service described above when the computer program is executed by a processor.

[0074] Optionally, when executed by a processor, the computer program may perform the following steps:

[0075] Obtain the target application interface corresponding to the target data service; obtain the first result table corresponding to the target application interface in the preset type database through the data warehouse data table of the data platform; sort out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer, and obtain the correspondence between the second result table and the business detail table of the shared layer; integrate the entire link relationship of the target data service from the database to the shared layer based on at least the correspondence relationship and the data link relationship.

[0076] An electronic device is provided according to an embodiment of this application. The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a tracing method for an application programming interface of any of the above-mentioned data services.

[0077] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0078] Figure 4A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0079] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 402 or a computer program loaded from storage unit 408 into random access memory (RAM) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0080] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0081] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the sourcing method for the application programming interface (API) of a data service. For example, in some embodiments, the sourcing method for the API of a data service may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the sourcing method for the API of a data service described above may be performed. Alternatively, in other embodiments, computing unit 401 may be configured by any other suitable means (e.g., by means of firmware) to perform a tracing method of the application programming interface for data services.

[0082] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0083] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0084] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on 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), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0085] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0086] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0087] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0088] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0089] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0093] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0094] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of tracing an application program interface of a data service, characterized in that, include: Obtain the target application interface corresponding to the target data service; The first result table corresponding to the target application interface in the preset type database is obtained through the original data table of the data middle platform; The data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, and the correspondence between the second result table and the shared layer business detail table is obtained. At least the entire link relationship of the target data service from the database to the shared layer is integrated based on the correspondence and the data link relationship; The process of sorting out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer includes: extracting preset type fields from the original data table, parsing the fields to obtain the preset type data corresponding to the fields, and filtering the preset type data to obtain the data link relationship; The data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, and the correspondence between the second result table and the shared layer business detail table is obtained. This includes: iteratively extracting all lineage links from the second result table corresponding to the data platform analysis layer to the shared layer business detail table, obtaining all shared layer data tables corresponding to the second result table of each analysis layer, and storing them in the form of a data list.

2. The tracing method according to claim 1, characterized in that, After integrating the entire link relationship of the target data service from the database to the shared layer based at least on the correspondence and the data link relationship, the method further includes: The number of business detail tables in the shared layer used by the target data service is obtained; The quantity is compared with preset data to mark the service complexity of the target data service.

3. The tracing method according to claim 1, characterized in that, After obtaining the target application interface corresponding to the target data service, the method further includes: The access frequency and last access time of the target data service within the target time period are obtained through the original data table of the data platform.

4. The tracing method according to claim 3, characterized in that, After obtaining the access frequency and the last access time of the target data service within the target time period through the data warehouse data table of the data middle platform, the method further includes: The availability of the target data service is determined based on the last access time. If the target data service is determined to be available, the activity level of the target data service is determined based on the number of accesses within the target time period.

5. The tracing method according to claim 4, characterized in that, Determining whether the target data service is available based on the last access time includes: Obtain the real-time time corresponding to the current moment, and determine the difference between the last access time and the real-time time; If the difference is greater than a preset time, the target data service is determined to be unavailable and is taken offline.

6. The method according to any one of claims 1 to 5, characterized in that, The preset database type includes: RDS database.

7. A device for tracing the source of an application programming interface (API) for a data service, characterized in that, include: The first acquisition module is used to acquire the target application interface corresponding to the target data service; The second acquisition module is used to acquire the first result table corresponding to the target application interface in a preset type database through the data warehouse data table of the data platform; The sorting module is used to sort out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer, and to obtain the correspondence between the second result table and the shared layer business detail table. An integration module is used to integrate the entire link relationship of the target data service from the database to the shared layer, based at least on the correspondence relationship and the data link relationship. The process of sorting out the data link relationship between the first result table and the second result table corresponding to the data platform analysis layer includes: extracting preset type fields from the original data table, parsing the fields to obtain the preset type data corresponding to the fields, and filtering the preset type data to obtain the data link relationship; The data link relationship between the first result table and the second result table corresponding to the data platform analysis layer is sorted out, and the correspondence between the second result table and the shared layer business detail table is obtained. This includes: iteratively extracting all lineage links from the second result table corresponding to the data platform analysis layer to the shared layer business detail table, obtaining all shared layer data tables corresponding to the second result table of each analysis layer, and storing them in the form of a data list.

8. A non-volatile storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, a tracing method is used to control the device where the storage medium is located to execute the application programming interface of the data service according to any one of claims 1 to 6.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the tracing method of the application programming interface of the data service as described in any one of claims 1 to 6.

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