阅读说明：本技术 数据处理方法、装置、PaaS及存储介质 (Data processing method and device, PaaS and storage medium ) 是由 罗路天 韩凯 张佳宝 王港加 于 2020-04-30 设计创作，主要内容包括：本申请公开了一种数据处理方法、装置、PaaS及存储介质,属于运营分析领域。所述方法包括：在PaaS中,通过数据平台采集第三方应用的运营数据；通过数据平台中创建的运营分析任务,对运营数据中运营分析任务对应的任务数据进行分析处理；通过开发者平台中创建的服务应用,为第三方应用提供运营分析服务,运营分析服务包括服务接口,服务接口用于从数据平台中获取运营分析任务对应的分析处理结果。本申请通过在PaaS的数据平台中创建满足运营分析需求的运营分析任务,并在开发者平台中创建服务应用,可以利用PaaS平台快速构建运营分析系统,并以接口的形式提供给第三方应用,开发成本较低,提高了开发效率,且具有持续运营能力。(The application discloses a data processing method and device, a PaaS and a storage medium, and belongs to the field of operation analysis. The method comprises the following steps: in PaaS, acquiring operation data of a third-party application through a data platform; analyzing and processing task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform; and providing operation analysis service for the third-party application through the service application established in the developer platform, wherein the operation analysis service comprises a service interface, and the service interface is used for acquiring an analysis processing result corresponding to the operation analysis task from the data platform. According to the method and the system, the operation analysis task meeting the operation analysis requirement is established in the data platform of the PaaS, the service application is established in the developer platform, the operation analysis system can be quickly established by using the PaaS platform and is provided for the third party application in an interface mode, the development cost is low, the development efficiency is improved, and the continuous operation capability is achieved.)

1. A data processing method is applied to a PaaS (platform as a service), wherein the PaaS comprises a data platform and a developer platform, and the method comprises the following steps:

acquiring operation data of a third-party application through the data platform;

analyzing and processing task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform;

and providing operation analysis service for the third-party application through the service application created in the developer platform, wherein the operation analysis service comprises a service interface, and the service interface is used for acquiring an analysis processing result corresponding to the operation analysis task from the data platform.

2. The method of claim 1, wherein analyzing and processing task data corresponding to the operation analysis task in the operation data comprises the following steps:

performing data cleaning on the task data;

storing the cleaned task data in a message queue;

analyzing and processing the data in the message queue;

and storing the analysis processing result of the data in the message queue.

3. The method of claim 1, wherein prior to providing the operation analysis service for the third party application through the service application created in the developer platform, further comprising:

creating, by the developer platform, the service application;

and compiling a service interface for acquiring an analysis processing result corresponding to the operation analysis task for the service application through the developer platform.

4. The method of claim 3, wherein after the creating of the service application by the developer platform, further comprising:

deploying the operation analysis service provided by the service application in an asynchronous deployment mode;

and expanding the service resources of the service application by adopting a multi-resource deployment mode.

5. The method of claim 1, wherein the method further comprises:

monitoring the data acquisition condition of the operation data of the third-party application, and if the data acquisition abnormity is monitored, alarming the data abnormity;

and monitoring the service interface, and if the service interface is monitored to be abnormal, alarming the interface abnormality.

6. The method of claim 5, wherein the data acquisition anomaly comprises at least one of:

the data are not obtained for a first preset time;

acquiring invalid data in the data, wherein the proportion of the invalid data is greater than or equal to a first preset proportion;

the data acquisition quantity at the current moment is reduced by a second preset proportion compared with the data acquisition quantity at the same moment before a second preset duration;

the data time delay is greater than or equal to a third preset time length;

the processing time delay is greater than or equal to a fourth preset time length;

and obtaining the operation analysis task execution exception corresponding to the data.

7. The method of claim 5, wherein the interface anomaly comprises at least one of:

the request number of the access requests of the service interface changes abnormally;

the request number of the error access requests of the service interface changes abnormally;

the proportion change of the error access request of the service interface is abnormal;

and the response time delay of the access request of the service interface changes abnormally.

8. A data processing apparatus, characterized in that the apparatus comprises:

the acquisition module is used for acquiring operation data of the third-party application through a data platform of PaaS;

analyzing and processing task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform;

and providing operation analysis service for the third-party application through the service application created in the PaaS developer platform, wherein the operation analysis service comprises a service interface, and the service interface is used for acquiring a processing result corresponding to the task from the data platform.

9. A PaaS, characterized in that the PaaS comprises at least one server, each of the at least one server comprising a processor and a memory, the memory of the at least one server having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which instruction, program, set of codes, or set of instructions is loaded and executed by the processor of the at least one server to implement the data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, having stored therein at least one instruction, at least one program, a set of codes, or a set of instructions, which is loaded and executed by a processor to implement the data processing method according to any one of claims 1 to 7.

Technical Field

The present application relates to the field of operation analysis, and in particular, to a data processing method and apparatus, a PaaS, and a storage medium.

Background

With the advent of the new cultural creation era, third-party applications such as games and reading become important components of the cultural industrial content, and in order to improve the user stickiness of these applications, it is necessary to develop an operation system capable of providing data processing capabilities such as operation analysis for these applications.

The traditional operation system is generally built on basic resources such as computing resources, storage resources, network resources and system resources, and is an application system with specific operation analysis capability developed on the basic resources. The computing resources and the storage resources are mostly provided by hardware devices or containers, the network resources are provided by network devices, and the system resources generally refer to Linux or windows and other system servers. Moreover, the traditional operation systems mostly adopt a chimney type development mode, that is, data, interfaces and monitoring of each operation system need to be developed by different personnel, functions and functions of each operation system are relatively independent, each operation system realizes service deployment and closed loop in the respective system, basic service capability cannot be shared between the systems, and calling between the systems presents a star-shaped structure in space.

Because the data, the interface and the monitoring of the traditional operation system are required to be developed by different personnel, the functions and the functions of the operation systems are relatively independent and cannot share basic service capacity, if an operation system is newly added or a system is newly added in the operation system, multiple parties are required to coordinate, the development process is complex, and the labor cost of development and maintenance is high.

Disclosure of Invention

The embodiment of the application provides a data processing method and device, a PaaS and a storage medium, and can be used for solving the problems that an operation system development process is complex and the labor cost of development and maintenance is high in the related technology. The technical scheme is as follows:

in one aspect, a data processing method is provided, which is applied to PaaS, where the PaaS includes a data platform and a developer platform, and the method includes:

acquiring operation data of a third-party application through the data platform;

analyzing and processing task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform;

and providing operation analysis service for the third-party application through the service application created in the developer platform, wherein the operation analysis service is used for acquiring an analysis processing result corresponding to the operation analysis task from the data platform.

In another aspect, there is provided a data processing apparatus, the apparatus comprising:

the acquisition module is used for acquiring operation data of the third-party application through a data platform of PaaS;

the processing module is used for analyzing and processing task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform;

and the service module is used for providing operation analysis service for the third-party application through the service application established in the PaaS developer platform, wherein the operation analysis service comprises a service interface, and the service interface is used for acquiring a processing result corresponding to the task from the data platform.

In another aspect, a PaaS is provided, the PaaS comprising at least one server, each of the at least one server comprising a processor and a memory, the memory of the at least one server having stored therein at least one instruction, at least one program, set of codes, or set of instructions, the instruction, the program, the set of codes, or the set of instructions being loaded and executed by the processor of the at least one server to implement any of the above-mentioned data processing methods.

In another aspect, a computer-readable storage medium is provided, in which at least one instruction, at least one program, a set of codes, or a set of instructions is stored, which is loaded by a processor and executes any one of the above data processing methods.

In another aspect, a computer program product is provided for implementing any of the above data processing methods when executed.

The technical scheme provided by the embodiment of the application has the following beneficial effects:

in the embodiment of the application, the operation data of the third-party application can be acquired on a data platform of the PaaS, the task data corresponding to the operation analysis task in the operation data is analyzed and processed through the operation analysis task established in the data platform, then the operation analysis service is provided for the third-party application through the service application established in the developer platform, the operation analysis service comprises a service interface, and the third-party application can acquire the analysis processing result corresponding to the operation analysis task from the data platform through the service interface. That is, in the application, by creating an operation analysis task meeting an operation analysis requirement in a data platform of PaaS and creating a service application in a developer platform, an operation analysis system can be quickly constructed by using the PaaS platform and provided to a third party application in an interface form to provide an operation analysis capability for the third party application, the development process is simple, the development efficiency is improved, the labor cost for development and maintenance is saved, and the continuous operation capability is provided.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a system architecture diagram of a PaaS development platform provided in an embodiment of the present application;

fig. 2 is a system architecture diagram of another PaaS development platform provided in an embodiment of the present application;

fig. 3 is a flowchart of a data processing method provided in an embodiment of the present application;

FIG. 4 is a schematic diagram of task processing logic for performing analysis tasks according to an embodiment of the present disclosure;

fig. 5 is a schematic diagram of an operation analysis task list created in a data platform according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a task logic arrangement provided by an embodiment of the present application;

FIG. 7 is a schematic diagram of creating a service application in a developer platform according to an embodiment of the present application;

fig. 8 is a schematic diagram of a multi-resource deployment manner extended service resource provided in an embodiment of the present application;

fig. 9 is a schematic diagram of an alarm policy provided in an embodiment of the present application;

fig. 10 is a graph illustrating a variation of the number of requests for access requests of a service interface in one week according to an embodiment of the present application;

fig. 11 is a graph illustrating a variation of the number of requests for a wrong access request of a service interface in one week according to an embodiment of the present application;

fig. 12 is an application interface schematic diagram before a third-party application accesses a PaaS operation system according to an embodiment of the present application;

fig. 13 is an application interface schematic diagram after a third-party application accesses a PaaS operation system according to an embodiment of the present application;

fig. 14 is a schematic diagram of a performance overview presentation effect provided by an embodiment of the present application;

FIG. 15 is a schematic diagram illustrating effects of game flow and game details provided by an embodiment of the present application;

FIG. 16 is a schematic diagram illustrating a ranking trend according to an embodiment of the present disclosure;

fig. 17 is a block diagram of a data processing apparatus according to an embodiment of the present application;

fig. 18 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

Before explaining the embodiments of the present application in detail, an application scenario of the embodiments of the present application will be described.

With the advent of the creative era of new texts, the third-party applications such as games and reading are used as important components of the contents of the cultural industry, and the continuous fine operation plays an important role in improving the user stickiness. In the cloud era, the application provides a continuous operation solution based on a Platform as a Service (PaaS) mode, a data Platform of the PaaS is fully utilized, cloud and big data technologies are combined, an operation system is quickly constructed, operation analysis capability is provided for third-party applications such as games and reading, and finally the third-party applications are provided in an interface mode. The scheme has the characteristics of low cost and no operation and maintenance, and has important significance for continuous analysis in the operation process.

For example, taking the third-party application as a game application and the operation system as a battle performance analysis system as an example, the analysis result of the battle performance analysis system can be provided to the game application in an interface manner, and the player can perform global understanding on the battle performance of the player and the friends through the game application, so as to further improve the competitive attribute of the player.

Next, an implementation environment related to the embodiments of the present application will be described.

Fig. 1 is a system architecture diagram of a PaaS development platform according to an embodiment of the present disclosure, and as shown in fig. 1, the development platform includes an IaaS (Infrastructure as a Service) layer 10, a PaaS layer 20, and a SaaS layer (Software as a Service) 30.

Among them, the IaaS layer 10 is used to provide basic resources such as computation, network, and system. Most computing resources are provided by hardware devices or containers, network resources are provided by network devices, and system resources generally refer to Linux or windows and other system servers.

Among them, the PaaS layer 20 is located in the middle layer in the system architecture, the upper layer is the SaaS layer, and the lower layer is the IaaS layer. The PaaS20 layer comprises a data platform and a developer platform, and the application can acquire, calculate and store operation data by using the data platform, create service applications for third-party applications by using the developer platform, and write service interfaces for the service applications to provide network services for the third-party applications.

The SaaS layer 30 is configured to provide software services, that is, network services, for third-party applications through a network.

As an example, as shown in fig. 2, the PaaS20 layers may include an iPaaS (integration Platform as a Service) layer 21 and an aPaaS (application Platform as a Service) layer 22.

The iPaaS layer 21 may provide a public operation atom (such as a resource management platform, a data platform, a developer platform, etc.), and the public operation atom is an independent system in the horizontal direction, and provides services to the upper-layer aPaaS layer 22 in a unified manner by using a service component or a cloud API (Application Programming Interface). The aPaaS layer 22 can build any operation system by performing modular development through various service components or cloud APIs provided by the iPaaS layer 21.

In the application, the core responsibility of the data layer is to acquire, calculate and store the basic operation data, and the layer is mainly focused on the iPaaS layer 21, for example, focused on the data platform of the iPaaS layer 21. As one example, the iPaaS layer 21 includes functional platforms such as a data platform, a developer platform, resource management, code hosting, environment deployment, log query, service monitoring, data management, and test tool. The method and the system can acquire, calculate and store the operation data by using the data platform, create the service application for the third-party application by using the developer platform, and compile the service interface for the service application so as to provide the operation analysis service for the third-party application.

Fig. 3 is a flowchart of a data processing method provided in an embodiment of the present application, where the method is applied to the PaaS in fig. 1 or fig. 2. Referring to fig. 3, the method comprises the steps of:

step 301: and the PaaS acquires the operation data of the third-party application through the data platform.

The operation data of the third-party application refers to data generated by the third-party application in the operation process. For example, if the third-party application is a game application, the operation data of the game application may be game data generated by a player in the process of using the game application.

It should be noted that the operation data of the third-party application may be actively collected by the data platform, or may be actively reported by the third-party application. That is, the data platform of PaaS may actively acquire the operation data of the third-party application, and may also receive the operation data reported by the third-party application.

Step 302: and the PaaS analyzes and processes the task data corresponding to the operation analysis task in the operation data through the operation analysis task established in the data platform.

As an example, before analyzing and processing task data corresponding to an operation analysis task in operation data through the operation analysis task created in the data platform, an operation analysis task meeting the operation analysis requirement may be created in the data platform according to an operation analysis requirement of a third-party application. That is, the task processing logic of the operation analysis task may be set according to the corresponding operation analysis requirement.

Moreover, different operation analysis tasks can be created according to different operation analysis requirements. That is, in the present application, the processing of data is based on task as a basic unit, and each operation analysis task can process different kinds of data according to the operation analysis requirement, and set different task processing logics according to the operation analysis requirement.

As an example, N operation analysis tasks may be created in the data platform according to the operation analysis requirements, where N is an integer greater than or equal to 1. Wherein the N operation analysis tasks correspond to the N operation analysis requirements.

For example, taking the third-party application as a game application as an example, the correspondingly created operation analysis task may be a task related to battle performance analysis, such as a battle performance overview analysis task, a mission flow analysis task, a mission detail analysis task, or a ranking trend analysis task. Of course, the operation analysis task may also be set as another task according to the operation analysis requirement, which is not limited in this embodiment of the present application.

As one example, the task processing logic that operates the analysis tasks may include data collection, data grounding, data cleansing, store message queues, consume message queues, data storage, and the like. The data acquisition refers to acquiring task data required by an operation analysis task from operation data. Data landing refers to format conversion and the like of data. The data cleansing is processing for correcting errors and the like of the task data. Data cleansing refers to finding and correcting recognizable errors in data, including checking data consistency, processing invalid and missing values, and the like. Storing the message queue refers to storing data to be processed into the message queue. Consuming the message queue refers to analyzing and processing data in the message queue according to corresponding analysis and processing logic. The data storage refers to storing analysis processing results of data, and the analysis processing results may be stored in a storage system of a data platform or a third-party storage system, which is not limited in the embodiment of the present application.

Referring to fig. 4, taking a third-party application as a game application and an operation data of the third-party application as a game data of the game application as an example, a plurality of operation analysis tasks may be created in a data platform, where different operation analysis tasks are used to process different game data, and a task processing logic of each operation analysis task includes data landing, data cleaning, message storage queue, message consumption queue, and data storage.

Referring to fig. 5, fig. 5 is a schematic diagram of an operation analysis task list created in a data platform according to an embodiment of the present application. Taking a game application in which the third-party application is a sports game as an example, as shown in fig. 5, operation analysis tasks such as friend ranking/ranking score, game running log, daily ranking, and the like can be created for the game application in the data platform.

As an example, each operation analysis task may perform task logic arrangement in a graphical dragging manner, so as to improve task logic arrangement efficiency. For example, referring to fig. 6, fig. 6 is a schematic diagram of task logic arrangement provided in an embodiment of the present application, and as shown in fig. 6, for a friend and a friend ranking/ranking task, task logic of the task may be arranged in a task logic arrangement area by adopting a graphical drag mode.

As an example, the operation analysis task may be divided into a real-time computing task and an offline computing task, and in order to improve reliability of the data service, the real-time computing task may be backed up, that is, the task is cloned, and a task processing result is stored as a duplicate. Aiming at the off-line computing task, the data compensation function provided by the data platform can be fully utilized for processing.

Step 303: the PaaS provides operation analysis service for the third-party application through the service application established in the developer platform, wherein the operation analysis service comprises a service interface, and the service interface is used for acquiring an analysis processing result corresponding to an operation analysis task from the data platform.

That is, the operation analysis of the operation data of the third-party application can be performed through the data platform, and the operation data is provided to the third-party application in the form of an interface, so that the third-party application can access the service interface of the service application to obtain the operation analysis result of the operation data.

The developer platform is used for providing development services for developers, and may also be called a developer center. Before providing the operation analysis service for the third-party application through the service application created in the developer platform, the service application may be created through the developer platform, and a service interface for obtaining an analysis processing result corresponding to the operation analysis task may be written for the service application.

That is, a service application may be created in a developer platform of PaaS, and the service application is used to provide an operation analysis service for a third-party application. The operation analysis service may be a Web page (Web) service or the like. In addition, a service interface can be written for the service application in the developer platform, so that a third-party application can obtain an analysis processing result corresponding to the operation analysis task through the service interface.

As one example, a service interface may be written for a service application in a modular manner at the application layer of the service application. For example, different service interfaces may be written for the service application, where the different service interfaces correspond to different operation analysis tasks and are used to obtain analysis processing results of the different operation analysis tasks.

By way of example, the service interface may be an API interface.

Referring to fig. 7, fig. 7 is a schematic diagram of creating a service application in a developer platform according to an embodiment of the present application, and taking a third-party application as a game application of a sports class as an example, a battle performance query application for providing a battle performance analysis and query service for the game application may be created in the developer platform.

Further, in order to improve high concurrency of the service interface of the service application, the operation analysis service provided by the service application may also be deployed in an asynchronous deployment manner, for example, the operation analysis service provided by the service application may be asynchronously deployed by using a getent (a third party broker library).

In addition, in order to improve the high concurrency of the service interface of the service application, the service resource of the service application can be expanded by adopting a multi-resource deployment mode. For example, referring to fig. 8, the number of service resources of the service application can be increased from 1 to 5.

As an example, in order to ensure the reliability and stability of data, deployment and control may be performed in a data layer to monitor a data acquisition situation of operation data applied by a third party, and if it is monitored that data acquisition is abnormal, a data abnormality alarm is performed.

The data acquisition mode of the data platform for the operation data of the third-party application comprises two modes: one is that the data platform actively collects the operation data of the third party application, and the other is that the third party application reports the operation data to the data platform. Therefore, monitoring the data acquisition condition of the operation data of the third-party application may also include two types: monitoring the data acquisition condition of the operation data of the third-party application, and if the data acquisition is monitored to be abnormal, alarming the data abnormality; and the other method is to monitor the data reporting condition of the operation data of the third-party application, and if the data reporting is monitored to be abnormal, the data abnormity warning is carried out.

As an example, a corresponding data set alarm policy may also be configured for task data corresponding to the operation analysis task, and if data acquisition abnormality is monitored according to the corresponding data alarm policy, a data abnormality alarm is performed. Further, different data alarm strategies can be configured for task data corresponding to different operation analysis tasks.

As one example, the data acquisition anomaly may include at least one of: the data are not obtained for a first preset time; acquiring invalid data in the data, wherein the proportion of the invalid data is greater than or equal to a first preset proportion; the data acquisition quantity at the current moment is reduced by a second preset proportion compared with the data acquisition quantity at the same moment before a second preset duration; the data time delay is greater than or equal to a third preset time length; the processing time delay is greater than or equal to a fourth preset time length; data interruption; and obtaining the operation analysis task execution exception corresponding to the data.

Referring to fig. 9, fig. 9 is a schematic diagram of an alarm policy provided in an embodiment of the present application, and as shown in fig. 9, an alarm policy may be configured for a data source of a combat performance analysis project in a data platform, and the alarm policy is as shown in fig. 9. The operation analysis task corresponding to the battle performance analysis project can comprise a plurality of operation analysis tasks.

As an example, in order to ensure the reliability and stability of the interface, the interface layer may also be configured to monitor the service interface, for example, monitor an access condition and a response condition of the service interface, and if it is monitored that the interface access is abnormal, perform an interface abnormal alarm.

The monitoring data of the service interface may include at least one of a request number of access requests of the service interface, a request number of error access requests of the service interface, a duty ratio of the error access requests of the service interface, and a response delay of the access requests of the service interface.

Wherein the interface abnormality comprises at least one of the following conditions: the request number of the access requests of the service interface changes abnormally; the request number of the error access request of the service interface is abnormal; the proportion change of the error access request of the service interface is abnormal; the response delay of the access request of the service interface changes abnormally.

As an example, the change in the number of requests for access requests may be a decrease in the number of requests for access requests, the change in the number of requests for erroneous access requests may be an increase in the number of requests for erroneous access requests, the change in the fraction of erroneous access requests may be an increase in the percentage of erroneous access requests, and the change in the response delay for access requests may be an increase in the response delay.

As an example, the change of the request number of the access request of the service interface, the change of the request number of the error access request of the service interface, and the percentage and average delay change of the error access request of the service interface may be counted according to the monitoring data of the service interface, and whether an interface abnormality occurs may be determined according to these changes.

When monitoring the operation data and the service interface, a threshold monitoring mode or an AI (Artificial Intelligence) mode may be adopted.

For example, when an AI monitoring mode is adopted, model training may be performed by using some historical abnormal data to obtain a monitoring model for detecting abnormal data, after the monitoring data is obtained through actual monitoring, the monitoring data is used as an input of the monitoring model to detect whether the monitoring data is abnormal or not, and if the monitoring data is abnormal, an abnormal alarm is given. The monitoring data may include data obtained by monitoring a data acquisition condition of the operation data, and interface data obtained by monitoring the service interface.

Referring to fig. 10 and fig. 11, fig. 10 is a graph illustrating a variation of the number of requests for access requests of a service interface within one week according to an embodiment of the present application, and fig. 11 is a graph illustrating a variation of the number of requests for erroneous access requests of a service interface within one week according to an embodiment of the present application.

Referring to table 1, table 1 is a list of the percentage of erroneous access requests and the average delay variation of the service interface in one week provided in the embodiment of the present application.

TABLE 1

Step 304: and the terminal sends an access request for a service interface of the service application to the PaaS through the third-party application.

As an example, the third party application may display an access entry of the service application in the application interface, and the user may trigger the access request to the service interface of the service application by a triggering operation on the access entry of the service application displayed in the third party application.

The access entry of the service application may be displayed in the form of an icon, an option, a menu, or the like, which is not limited in this embodiment of the application.

Referring to fig. 12 and fig. 13, fig. 12 is a schematic application interface before a third party application accesses a PaaS operation system according to an embodiment of the present application, fig. 13 is a schematic application interface after the third party application accesses the PaaS operation system according to the embodiment of the present application, and as can be seen by comparing fig. 12 and fig. 13, an access entry of a battle performance query service is added in fig. 13: all the battle performance menu and the gun king blasting menu.

Step 305: and the PaaS receives the access request, calls a service interface according to the access request, and acquires an analysis processing result of an operation analysis task corresponding to the service interface from a data platform through the service interface.

Step 306: and the PaaS sends the analysis processing result to the terminal.

As an example, according to the method provided by the embodiment of the present application, an operation analysis task with dimensions such as a battle performance overview, a game flow and game details, and a ranking trend may be developed for a game application through PaaS, and a corresponding service interface may be provided to a third-party application.

Referring to fig. 14-16, fig. 14 is a schematic diagram of a performance overview, fig. 15 is a schematic diagram of a show effect of a game flow and game details, and fig. 16 is a schematic diagram of a show effect of a ranking trend.

It should be noted that, in the present application, only the acquisition, the operation, and the storage of the data source are all completed on the data platform of PaaS, but in practical application, the data source acquisition, the operation, and the storage can be implemented on other platforms with similar functions. In addition, in the application, the high concurrency of the interface layer is realized by adopting a solution based on asynchronous deployment and resource deployment, and of course, other schemes suitable for high concurrency scenes, such as longitudinal extension, cache, sub-base sub-table and the like, can also be adopted.

In the embodiment of the application, the operation data of the third-party application can be acquired on a data platform of the PaaS, the task data corresponding to the operation analysis task in the operation data is analyzed and processed through the operation analysis task established in the data platform, then the operation analysis service is provided for the third-party application through the service application established in the developer platform, the operation analysis service comprises a service interface, and the third-party application can acquire the analysis processing result corresponding to the operation analysis task from the data platform through the service interface. That is, in the application, by creating an operation analysis task meeting an operation analysis requirement in a data platform of PaaS and serving an application in a developer platform, an operation analysis system can be quickly constructed by using the PaaS platform and provided to a third party application in an interface form to provide an operation analysis capability for the third party application, the development process is simple, the development efficiency is improved, the labor cost for development and maintenance is saved, and the continuous operation capability is provided.

Fig. 17 is a block diagram of a data processing apparatus integrated in PaaS according to an embodiment of the present application, where the apparatus includes:

the acquisition module 1701 is used for acquiring the operation data of the third-party application through a data platform of PaaS;

a processing module 1702, configured to analyze and process task data corresponding to the operation analysis task in the operation data through the operation analysis task created in the data platform;

a service module 1703, configured to provide, through a service application created in the developer platform of the PaaS, an operation analysis service for the third-party application, where the operation analysis service includes a service interface, and the service interface is used to obtain a processing result corresponding to the task from the data platform.

Optionally, the processing module 1701 is configured to perform the following steps:

performing data cleaning on the task data;

storing the cleaned task data in a message queue;

analyzing and processing the data in the message queue;

and storing the analysis processing result of the data in the message queue.

Optionally, the apparatus further comprises:

a first development module for creating the service application through the developer platform;

and the second development module is used for writing a service interface for acquiring an analysis processing result corresponding to the operation analysis task for the service application through the developer platform.

Optionally, the apparatus further comprises:

the third development module is used for adopting an asynchronous deployment mode to deploy the operation analysis service provided by the service application;

and the fourth forwarding module is used for expanding the service resources of the service application by adopting a multi-resource deployment mode.

Optionally, the apparatus further comprises:

the first monitoring module is used for monitoring the data acquisition condition of the operation data of the third-party application, and if the data acquisition abnormity is monitored, the data abnormity warning is carried out;

and the second monitoring module is used for monitoring the service interface and giving an alarm to the interface if the service interface is monitored to be abnormal.

Optionally, the data collection anomaly comprises at least one of:

the data are not obtained for a first preset time;

acquiring invalid data in the data, wherein the proportion of the invalid data is greater than or equal to a first preset proportion;

the data acquisition quantity at the current moment is reduced by a second preset proportion compared with the data acquisition quantity at the same moment before a second preset duration;

the data time delay is greater than or equal to a third preset time length;

the processing time delay is greater than or equal to a fourth preset time length;

and obtaining the operation analysis task execution exception corresponding to the data.

Optionally, the interface access exception includes at least one of:

the request number of the access request of the service interface is abnormal;

the request number of the error access request of the service interface is abnormal;

the proportion change of the error access request of the service interface is abnormal;

the response delay of the access request of the service interface changes abnormally.

In the embodiment of the application, the operation data of the third-party application can be acquired on a data platform of the PaaS, the task data corresponding to the operation analysis task in the operation data is analyzed and processed through the operation analysis task established in the data platform, then the operation analysis service is provided for the third-party application through the service application established in the developer platform, the operation analysis service comprises a service interface, and the third-party application can acquire the analysis processing result corresponding to the operation analysis task from the data platform through the service interface. That is, in the application, by creating an operation analysis task meeting an operation analysis requirement in a data platform of PaaS and serving an application in a developer platform, an operation analysis system can be quickly constructed by using the PaaS platform and provided to a third party application in an interface form to provide an operation analysis capability for the third party application, the development process is simple, the development efficiency is improved, the labor cost for development and maintenance is saved, and the continuous operation capability is provided.

It should be noted that: in the data processing apparatus provided in the above embodiment, only the division of the functional modules is illustrated when performing data processing, and in practical applications, the functions may be distributed by different functional modules as needed, that is, the internal structure of the apparatus may be divided into different functional modules to complete all or part of the functions described above. In addition, the data processing apparatus and the data processing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.

Fig. 18 is a schematic structural diagram of a server 1800 according to an embodiment of the present application, where the server 1800 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 1801 and one or more memories 1802, where the memory 1802 stores at least one instruction, and the at least one instruction is loaded and executed by the processors 1801 to implement the data Processing method provided by the foregoing method embodiments. Of course, the server 1800 may also have components such as a wired or wireless network interface, a keyboard, and an input/output interface, so as to perform input/output, and the server 1800 may also include other components for implementing device functions, which are not described herein again.

In an exemplary embodiment, a computer-readable storage medium is also provided, which has instructions stored thereon, which when executed by a processor, implement the above-mentioned data processing method.

In an exemplary embodiment, a computer program product is also provided, which, when executed, is adapted to implement the above-mentioned data processing method.

It should be understood that reference to "a plurality" herein means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The above description is only exemplary of the present application and should not be taken as limiting, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.