Data Encapsulation Method, Device, and Storage Medium for Parallel Recall

Abstract

The present disclosure relates to a data encapsulation method, apparatus, and storage medium for parallel recall. The data encapsulation method includes: transforming one or more serial encapsulation cards into parallel encapsulation cards, where an exception capture and timeout fast return strategy is executed; abstracting the common services of the parallel encapsulation cards to generate a responsibility chain for parameter encapsulation and recall processing; and generating resource bits for data encapsulation based on the responsibility chain abstraction, and using the resource bits in combination with the responsibility chain to implement the front-end display of data.

Description

Technical Field

[0001] The present disclosure relates to the technology of server - side data encapsulation in multi - service scenarios, and specifically, to a data encapsulation method, device, and storage medium for parallel recall. Background Art

[0002] In recent years, with the rapid rise of the mobile Internet, the high - latency interface returns caused by the serial call of data encapsulation under high traffic cannot meet the requirements of the industrial Internet and user experience. Technically, multi - thread technology has been used to transform it into parallel recall. Under parallel multi - path recall, with the increase in the number of business scenarios and complexity, building a recall engine that can quickly access new resource positions in terms of business and has concise code in terms of technology has become a trend, which requires implementing functional features such as high stability, low latency, exception fallback, and flexible dynamic configuration.

[0003] The currently commonly used solution is a recommendation recall engine. The recommendation recall engine is an engine that performs parallel multi - path recall through multi - thread technology. It recalls as much data of different business scenarios as possible under a certain latency, provides data supplementation for subsequent fine - ranking sorting, and gradually improves the recommendation effect and user experience. The main drawback is that the recommendation recall engine only provides a technical idea of changing from serial to parallel call, and cannot better solve the flexible dynamic configuration of resource positions and quickly meet the business - changing scenarios. Summary of the Invention

[0004] The present application proposes a data encapsulation method, device, and storage medium for parallel recall.

[0005] According to the first aspect of the embodiments of the present disclosure, a data encapsulation method for parallel recall is provided, including: transforming one or more serial encapsulation cards into parallel encapsulation cards, where an exception capture and timeout fast - return strategy is executed; abstracting the common services of the parallel encapsulation cards to generate a responsibility chain for parameter encapsulation and recall processing; and generating resource positions for data encapsulation based on the responsibility - chain abstraction, and using the resource positions in combination with the responsibility chain to implement the front - end display of data. By implementing the serial - to - parallel conversion in the recommendation recall engine, the data encapsulation process has relative independence, and can avoid the problem that the entire link collapses due to a logical exception occurring during the encapsulation of a certain service in serial encapsulation. On the other hand, the responsibility - chain pattern is used to achieve logical abstraction and code reuse. When implementing each special business function, only json (JavaScript Object Notation, JS object notation) parameter parsing needs to be performed during technical implementation, so as to quickly read the configuration and re - encapsulate.

[0006] In some embodiments, the transformation of parallel encapsulation cards includes implementing the common business logic of one or more serial encapsulation cards into a common abstract class and encapsulating the special business logic into their respective implementation classes.

[0007] In some embodiments, the transformation of parallel encapsulation cards further includes submitting the business logic of one or more serial encapsulation cards to a thread pool for asynchronous parallel processing.

[0008] In some embodiments, after the business logic of one or more serial encapsulation cards is submitted, wait in parallel for a first period of time to confirm that all the submitted business logic data has been encapsulated.

[0009] In some embodiments, the timeout fast return policy includes when, after waiting for the first period of time, the first card has not completed data encapsulation and a logical exception is captured, then assigning the business logic data corresponding to the first card to preset data.

[0010] In some embodiments, the chain of responsibility includes a parameter encapsulation module, a recall processing module, a sorting processing module, and a creative encapsulation module.

[0011] In some embodiments, the chain of responsibility defines the processing entry for technical implementation, the method for executing special business logic, and the annotation indicating the next processing.

[0012] In some embodiments, based on the context of the data abstracted by the chain of responsibility, and abstracting the configuration of resource positions into the json data format.

[0013] In some embodiments, in response to the need to execute the function corresponding to the specified business logic, perform json parameter parsing on the function, and perform data reading and re-encapsulation.

[0014] According to a second aspect of the embodiments of the present disclosure, there is provided a data encapsulation device for parallel recall, which runs on a user terminal and includes: a parallel encapsulation transformation unit configured to transform one or more serial encapsulation cards into parallel encapsulation cards, where exception capture and timeout fast return policies are executed; a chain of responsibility abstraction unit configured to abstract the common business of the parallel encapsulation cards to generate a chain of responsibility for parameter encapsulation and recall processing; and a resource position generation unit configured to generate a resource position for data encapsulation based on the chain of responsibility abstraction, and use the resource position in combination with the chain of responsibility to implement the front-end display of data.

[0015] According to a third aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium storing program instructions, which when executed cause a computer to implement the data encapsulation method according to the first aspect of the embodiments of the present disclosure.

[0016] According to a fourth aspect of embodiments of the present disclosure, there is provided a computer program product including computer program instructions that, when executed by a processor, implement the data encapsulation method according to the first aspect of embodiments of the present disclosure.

[0017] The advantages of embodiments of the present disclosure are that during the recommendation recall process, the encapsulation changes from serial to parallel, which can prevent problems in the entire link due to interface crashes, thereby reducing the interface latency and improving the interface stability.

[0018] Another advantage of embodiments of the present disclosure is that a responsibility chain including parameter encapsulation and recall processing functions is established as a scaffold for the recall engine, such that each time a special service is called, only JSON parameter parsing needs to be performed, and the configuration is read and then encapsulated, so as to implement simple general code to complete the requirement of data encapsulation with convenient operations.

[0019] It should be recognized that the above advantages do not need to be all realized in one or some specific embodiments, but can be partially distributed in different embodiments according to the present disclosure. Embodiments according to the present disclosure may have one or some of the above advantages, or alternatively or additionally may have other advantages.

[0020] Other features and advantages of the present invention will become clearer through the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic diagram of a service architecture of a data encapsulation method for parallel recall according to an embodiment of the present disclosure.

[0022] Figure 2 is a schematic configuration diagram of a data encapsulation device for parallel recall according to an embodiment of the present disclosure.

[0023] Figures 3A - 3B is a schematic diagram of serial encapsulation and parallel encapsulation of a data encapsulation method for parallel recall according to an embodiment of the present disclosure.

[0024] Figure 4 is a schematic diagram of resource bit abstract calls of a data encapsulation method for parallel recall according to an embodiment of the present disclosure.

[0025] Figure 5 is a schematic diagram of steps of a data encapsulation method for parallel recall according to an embodiment of the present disclosure.

[0026] Figure 6 shows an exemplary configuration of a computing device that can implement embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Various exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure.

[0028] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way a limitation on the present disclosure or its application or use. That is, the structures and methods herein are shown in an exemplary manner to illustrate different embodiments of the structures and methods in the present disclosure. However, those skilled in the art will understand that they merely illustrate exemplary ways in which the present disclosure can be implemented, rather than exhaustive ways. In addition, the drawings are not necessarily drawn to scale, and some features may be enlarged to show details of specific components.

[0029] Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies, methods, and devices should be regarded as part of the authorization specification.

[0030] Generally speaking, the technical solution of the present disclosure is mainly applied to data encapsulation of industrial Internet and social platform software, and particularly applied to services and their recommendation and recall in multiple scenarios. Existing serial calls may cause problems such as high interface return latency and business logic crashes, which will be more significant in the current situation of increasing and complicating business scenarios. Therefore, it has become a trend to build a recall engine that can quickly access resources in business, especially to convert serial logic into parallel logic through multi-threading technology, so as to solve the problems of high interface crash rate and increased interface request time caused by serial data encapsulation, how to perform fast exception fallback return and data re-encapsulation after parallel encapsulation, and how to use the concept of resource positions to dynamically and quickly support new business scenarios, so as to make the business highly cohesive and loosely coupled, improve the code reuse rate, and achieve dynamic configuration.

[0031] Figure 1The figure shows a schematic business architecture diagram of a data encapsulation method for parallel recall according to an embodiment of the present disclosure. Taking Soul App as an example, the business architecture of the planet cards for recommendation recall that includes data encapsulation mainly includes a parameter encapsulation processing class 1200, a recall processing class 1400, a sorting processing class 1600, and a creative encapsulation class 1800, and also includes a context encapsulation 1010 and a resource position policy configuration encapsulation 1020. In a non-limiting embodiment, the parameter encapsulation processing class 1200 may include, but is not limited to, the encapsulation of the number of online users, experimental parameters, and business content encapsulation specific to the Soul implementation, such as the query of the love bell status for friend-making information recommendation, etc. The recall processing class 1400 may include, but is not limited to, a general ability 1210, a business logic ability 1220, and other general abilities 1230, etc., and is mainly used to recall the rough ranking recommendation list of the current user from a vast amount of information. Among them, the general ability 1210 such as experimental filtering, version filtering, and default card encapsulation; the business logic ability 1220 mainly corresponds to various business function cards that require data encapsulation, such as the soul matching card, voice matching card, video matching card, love bell card, text group chat card, group chat queuing card, video queuing card, campus bar card, masked matching card, etc. of Soul; other general abilities 1230 such as static configuration re-coverage, etc. The sorting processing class 1600 may include, but is not limited to, business content such as priority sorting, etc., and is mainly used for the merge sorting of concurrent recall, such as further fine-tuning the recalled data according to parameters such as the priority of the user or content. The creative encapsulation class 1800 is mainly used for degradation fallback encapsulation and activity encapsulation in multiple scenarios. An example of the encapsulated creativity is the skin change of the soul matching theme day activity of Soul, etc.

[0032] In some embodiments, one or more serially encapsulated cards are first transformed into a parallel encapsulated card using multi-threading technology, and an exception capture and timeout fast return strategy is implemented to prevent interface crashes, thereby reducing the latency of the interface and improving the stability of the interface. These serially encapsulated cards can be, for example, business cards included in the recall processing class 1400. Subsequently, common functions are abstracted. For example, user basic data, experiment parameters, user status, etc. are encapsulated and abstracted into a parameter encapsulation processing class 1200 for convenient subsequent data sharing; the fallback and business re-encapsulation strategies when the card returns an exception are abstracted into a creative encapsulation class 1800. Based on this, it is overall abstracted into a chain of responsibility pattern, thus forming a chain of responsibility of parameter encapsulation -> concurrent recall -> sorting -> creative encapsulation, achieving logical abstraction and code reuse. Further, on the basis of the chain of responsibility, the context of the data (i.e., context encapsulation 1010) is abstracted, and the configuration of the encapsulated resource bits is resource-abstracted into a JSON string of key-value (k-v) (i.e., resource bit policy configuration encapsulation 1020). Additionally, the aforementioned data such as the JSON string is configured on a distributed configuration management center (such as remote Apollo configuration), facilitating dynamic policy changes and new resource bit access for business and technology at any time. Alternatively, the processed data can also be stored in a relational database mysql or cached in an in-memory database redis for data transmission.

[0033] Next, please refer to Figure 2 , Figure 2 FIG. is a schematic configuration diagram showing a data encapsulation device 2000 for parallel recall according to an embodiment of the present disclosure. In some embodiments, the data encapsulation device 2000 can implement the corresponding functions of the data encapsulation method for parallel recall. The device 2000 may include a processor 2100. The processor 2100 of the device 2000 can provide various functions of the data encapsulation device 2000. A processor can refer to various implementations of digital circuit systems, analog circuit systems, or mixed-signal (a combination of analog and digital) circuit systems that perform functions in a computing system. The processing circuit can include, for example, circuits such as integrated circuits (ICs), application-specific integrated circuits (ASICs), parts or circuits of a single processor core, the entire processor core, a single processor, programmable hardware devices such as field-programmable gate arrays (FPGAs), and / or systems including multiple processors.

[0034] In some embodiments, the data encapsulation device 2000 for parallel recall may further include a memory (not shown in the figure). The memory of the device 2000 may store information generated by the processor 2100 and programs and data for the operation of the processor. The memory may be volatile memory and / or non-volatile memory. For example, the memory may include, but is not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), and flash memory. Generally, the processor may be configured to execute instructions stored in the memory to implement the data encapsulation method for parallel recall as described above.

[0035] Specifically, as Figure 2 shown, in some embodiments, the data encapsulation device 2000 for parallel recall according to an embodiment of the present disclosure may include a parallel encapsulation transformation unit 2010, a responsibility chain abstraction unit 2020, a resource bit generation unit 2030, and an exception warning unit 2040. It should be understood that Figure 2 each functional unit of the data encapsulation device 2000 shown is only a logical module divided according to its specific implemented function, rather than being used to limit the specific implementation manner. In actual implementation, the above-mentioned each module may be implemented as an independent physical entity, or may also be implemented by a single entity (for example, a processor (CPU or DSP, etc.), an integrated circuit, etc.).

[0036] In some embodiments, the parallel encapsulation transformation unit 2010 is configured to transform one or more serial encapsulation cards into parallel encapsulation cards, where an exception capture and timeout fast return strategy is executed. A non-limiting embodiment of the serial-to-parallel conversion may refer to Figure 3A and Figure 3B , which respectively show schematic diagrams of serial encapsulation and parallel encapsulation of the data encapsulation method for parallel recall according to an embodiment of the present disclosure. Figure 3A The serial card service encapsulation in Figure 1 may include multiple cards of the recall processing class 1400 as shown in Figure 3B , such as SoulMatchCard, LoveBellCard, VoiceMatchCard, VideoMatchCard, FaceGiNiCard, and / or ChatRoomCard, etc., which perform serial encapsulation of data in sequence according to the arrow direction shown in the figure. The serial encapsulation logic is transformed into parallel encapsulation using multi-threading technology. As shown in

[0037] Specifically, in some embodiments, the parallel packaging transformation unit 2010 first implements the common business logic of one or more serial packaging cards into the common abstract class BaseRecallStrategy, and encapsulates the special business logic into their respective implementation classes xxxRecallStrategy ("xxx" is the name of the specific business). Among them, some common methods are implemented inside BaseRecallStrategy, such as common logics like experiment control and client version control; cards for concurrent recall such as soul matching cards and voice matching cards inherit BaseRecallStrategy and its common methods, and directly override the methods during the special transformation of the business to achieve the purpose of specific business use. Such a design can achieve the effects of code reuse and simplification. Subsequently, the parallel packaging transformation unit 2010 submits the logic encapsulated in all the original one or more cards to the thread pool 320 for asynchronous parallel processing, and performs exception capture on each submitted business card in a manner including but not limited to try-catch to prevent logical exceptions from crashing. It should be understood that in real-time data packaging and application program operation, there is a probability of exceptions occurring in the packaging cards representing different functions. In the case of serial packaging, the business crash of a certain card will cause the entire link to crash, while in the case of parallel packaging as in the embodiments of the present disclosure, each card and its respective special business logic are relatively independent. Therefore, exceptions that may occur on a certain card can be handled separately without affecting the operation of the entire link.

[0038] Particularly, after submitting the business logic of the aforementioned one or more serial packaging cards, the parallel packaging transformation unit 2010 enters the parallel waiting 3400 and continuously waits for a certain period of time (for example, denoted as the first time) to confirm whether all the submitted business logic data has been encapsulated. In a non-limiting embodiment, the parallel waiting 3400 uses, for example, the CountDownLatch.await(500) method of the computer language Java, and the first time is, for example, waiting for 500 ms. The timeout fast return strategy for data packaging is that if a certain card (for example, denoted as the first card) does not complete data packaging within the 500 ms time period, it is judged that a logical exception is captured, and the interface assigns the business logic data corresponding to the first card to the preset data and returns quickly. Generally, the preset data is used to ensure the normal operation of the business in case of data packaging timeout and can be null. At this time, problems such as logical crashes of the first card will not affect other cards that have completed packaging within the first time, and the entire parallel packaging link can achieve recall with a relatively reasonable time delay. At the same time, the captured logical exceptions are also convenient for subsequent modules such as NullPointerExcpetion to identify and implement exception re-encapsulation.

[0039] In some embodiments, the responsibility chain abstraction unit 2020 is configured to abstract the common services of parallel encapsulated cards to generate a responsibility chain for parameter encapsulation and recall processing. Specifically, first, the abstract responsibility chain engine method is performed, in which the handler abstract class is abstracted, which contains the handle() method for technical implementation, the handleRequest() method as a special business logic execution method, and the nextHandler attribute indicating the next processing. Specifically, after entering the processing, the nextHandler attribute is traversed to execute the next processing class method. Based on this core abstraction, the following four major categories are ReqParamHandler for parameter encapsulation, RecallHandler for recall processing, RankHandler for sorting processing, and CreativeHandler for creative encapsulation. Corresponding to the foregoing Figure 1 business architecture, specifically, parameter encapsulation includes, for example, resource position policy parsing, and encapsulating user basic data, portrait data, experimental data, etc.; recall processing includes, for example, parallel recall using a thread pool, fast abnormal return, etc.; sorting processing includes, for example, merge sorting of row concurrent recall; and creative encapsulation includes re-encapsulation strategies such as downgrading fallback encapsulation for abnormal return, activity encapsulation, etc. The main responsibility chain, as the scaffold of the recall engine, can be represented in the following form:

[0040] ReqParamHander->RecallHandler->RankHandler->CreativeHandler

[0041] In particular, each special business function only needs to perform json parameter parsing during technical implementation, and read and re-encapsulate the configuration to complete the reuse and rapid configuration of the function. In a non-limiting embodiment, in the processing class of creative encapsulation, only the card id and the fallback configuration after abnormal downgrading need to be configured, or when the current card is in a specific activity, only the re-encapsulation configuration needs to be encapsulated. Thus, the code implementation of the parallel encapsulation responsibility chain is simple and general, and the operation during call is simple, which is beneficial to improving the efficiency of data encapsulation.

[0042] In some embodiments, the resource position generation unit 2030 is configured to generate a resource position for data encapsulation based on the responsibility chain abstraction, and use the resource position in combination with the responsibility chain to implement the front-end display of data. Specifically, reference can be made to Figure 4, which shows a schematic diagram of the resource bit abstract call of the data encapsulation method for parallel recall according to an embodiment of the present disclosure. Pages 401, 402, and 403 with card surface IDs ("resId") of 6, 5, and 4 respectively are processed by the card recall engine 420 and display corresponding card resources and page policies 441, 442, and 443, which include card surface IDs, encapsulation parameters ("reqParam"), recall parameters ("recallParam"), creative parameters ("creativeParam"), etc. The abstracted resource bits are used to configure different parameter encapsulations respectively, such as using strategies for recall, sorting, and re-encapsulating creativity, and the resource bit policies are parsed in JSON format and placed on the remote Apollo configuration to quickly respond to parsing changes. Based on this, for the same set of front-end display layers, only by passing different resource bit codes to the card recall engine 420, different card resources and policies can be displayed on the front end in combination with the responsibility chain, greatly saving R & D manpower.

[0043] In some embodiments, the data encapsulation device 2000 for parallel recall may further include other auxiliary functional units, such as an exception warning unit 2040. The exception warning unit 2040 is configured to warn an external system or module when the parallel encapsulation transformation unit 2010 captures a logical crash. In a non-limiting embodiment, the warning signal may include information such as the card ID where the logical crash occurs, the code exception location, and the exception type, so as to quickly troubleshoot exceptions for the users of the data encapsulation device 2000 or implement exception re-encapsulation after the exception default fallback returns.

[0044] Additionally, the data encapsulation device 2000 for parallel recall may also have an input unit and an output unit (not shown in the figure) built-in or externally connected. The input unit may include devices for users or managers to input various data or instructions, such as operating devices like buttons, touchpads, keyboards, microphones, switches, and other devices capable of receiving inputs by methods such as sound and action. In addition, for example, the input unit may be a remote control device with infrared light or other radio waves, or may be a mobile device suitable for the operation of the data encapsulation device 2000. Based on the data or instructions input by the user, for example, the input unit generates an input signal and supplies the input signal to other functional units in the data encapsulation device 2000.

[0045] The output unit includes devices capable of outputting visual information or auditory information to the user or administrator of the data encapsulation device 2000. For example, the output unit includes a display screen, a speaker, a buzzer, a projector, a lamp, etc. The display device included in the output unit can be a device with a normal display, or a device that displays visual information in other systems, etc. Based on this, the data encapsulation device 2000 can display operation progress such as completed encapsulation and abnormal return as visual information such as graphic data or auditory information such as voice prompts, so that the user or administrator can obtain or adjust the target of the recall engine, etc.

[0046] Figure 5 is a schematic diagram showing the steps of a data encapsulation method for parallel recall according to an embodiment of the present disclosure. In step S501, one or more serial encapsulation cards are transformed into parallel encapsulation cards, and an exception capture and timeout fast return strategy is executed. In step S502, the common services of the parallel encapsulation cards are abstracted to generate a responsibility chain for parameter encapsulation and recall processing. In step S503, resource bits for data encapsulation are generated based on the responsibility chain abstraction, and the resource bits are used in combination with the responsibility chain to implement the front-end display of data. It should be understood that Figure 5 the division of each step in Figure 2 is only for illustration and not a limitation on the embodiments of the present application. These steps can be completed independently by Figure 3B and Figure 4 the respective entities shown, jointly completed by two or more of them, or completed in cooperation with the illustrated entities by an external system not shown, and are not limited to the illustrated steps, and can be completed sequentially in the illustrated order or in parallel in accordance with the data flow direction and system operation rules, and can be completed step by step or in combination. The details of the above steps S501 to S503 are similar to the descriptions with reference to

[0047] Figure 6 shows an exemplary configuration of a computing device that can implement an embodiment of the present disclosure. The computing device includes one or more processors 601, an input / output interface 605 connected to the processor 601 via a bus 604, and memories 602 and 603 connected to the bus 604. In some embodiments, the memory 602 can be a read-only memory (ROM), and the memory 603 can be a random access memory (RAM).

[0048] The processor 601 can be any type of processor and can include, but is not limited to, one or more general-purpose processors or special-purpose processors (such as special processing chips). The memories 602 and 603 can be any non-transitory storage devices that can implement data storage and can include, but are not limited to, disk drives, optical storage devices, solid-state memories, floppy disks, flexible disks, hard disks, magnetic tapes, or any other magnetic medium, compact disks, or any other optical medium, cache memories, and / or any other storage chips or modules, and / or any other medium from which a computer can read data, instructions, and / or code.

[0049] The bus 604 can include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus, etc.

[0050] In some embodiments, the input / output interface 605 is connected to the following units: an input unit 606 configured by input devices such as a keyboard and a mouse for a user to input operation commands, an output unit 607 that outputs images of a processing operation screen and processing results to a display device, a storage unit 608 including a hard disk drive for storing programs and various data, etc., and a communication unit 609 including a local area network (LAN) adapter, etc., and performing communication processing via a network represented by the Internet. In addition, a drive 610 is also connected, and the drive 610 reads data from and writes data on a removable storage medium 611.

[0051] Each aspect, embodiment, specific implementation, or feature of the foregoing embodiments can be used alone or in any combination. Each aspect of the foregoing embodiments can be implemented by software, hardware, or a combination of hardware and software.

[0052] For example, the foregoing embodiments can be embodied as computer-readable code on a computer-readable medium. A computer-readable medium is any data storage device that can store data, which can then be read by a computer system. Examples of computer-readable media include read-only memory, random access memory, CD-ROM, DVD, magnetic tape, hard disk drive, solid-state drive, and optical data storage devices. The computer-readable medium can also be distributed in network-coupled computer systems such that the computer-readable code is stored and executed in a distributed manner.

[0053] For example, the foregoing embodiments may take the form of hardware circuits. The hardware circuits may include any combination of combinational logic circuits, clock storage devices (such as floppy disks, flip-flops, latches, etc.), finite state machines, memories such as static random access memories or embedded dynamic random access memories, custom designed circuits, programmable logic arrays, and the like.

[0054] In one embodiment, the hardware circuits according to the present disclosure may be implemented by encoding and designing one or more integrated circuits in a hardware description language (HDL) such as Verilog or VHDL or by using discrete circuits in combination.

[0055] The terms used herein are for the purpose of describing particular exemplary embodiments only and are not intended to limit the present disclosure. Unless the context clearly indicates otherwise, the singular forms "a" and "the" used herein are intended to include the plural forms as well. It should also be understood that the term "comprising" when used herein specifies the presence of the stated features, wholes, steps, operations, units, and / or components, but does not preclude the presence or addition of one or more other features, wholes, steps, operations, units, and / or components and / or combinations thereof. In addition, in the description of the present disclosure, the terms "first", "second", etc. are used for descriptive purposes only and should not be construed as indicating or implying relative importance or order. In addition, in the description of the present disclosure, unless otherwise specified, "a plurality of" means two or more.

[0056] References in this specification to "an embodiment" or similar expressions mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one specific embodiment of the present disclosure. Thus, the appearances of the phrases "in an embodiment of the present disclosure" and similar expressions in this specification do not necessarily refer to the same embodiment.

[0057] Those skilled in the art should know that the present disclosure may be implemented in various forms, such as a complete hardware embodiment, a complete software embodiment (including firmware, resident software, microcode, etc.), or may also be implemented in a form combining software and hardware, which will be referred to as "circuit", "module", "unit", or "system" hereinafter. In addition, the present disclosure may also be implemented as a computer program product in any tangible medium form, having computer-usable program code stored thereon.

[0058] The relevant description of the present disclosure will be described with reference to the flowcharts and / or block diagrams of systems, devices, methods, and computer program products according to specific embodiments of the present disclosure. It can be understood that each block in each flowchart and / or block diagram, as well as any combination of blocks in the flowchart and / or block diagram, can be implemented using computer program instructions. These computer program instructions can be executed by a machine composed of a processor of a general-purpose computer or a special computer or other programmable data processing devices, and the instructions are processed by the computer or other programmable data processing devices to implement the functions or operations described in the flowchart and / or block diagram.

[0059] The flowcharts and block diagrams in the accompanying drawings show the architectures, functions, and operations that can be implemented by systems, devices, methods, and computer program products according to various embodiments of the present disclosure. Therefore, each block in the flowchart or block diagram can represent a module, section, or part of program code, which includes one or more executable instructions to implement the specified logical function. Additionally, it should be noted that in some other embodiments, the functions described in the blocks may not be performed in the order shown in the figures. For example, two connected blocks in the figures may actually be executed simultaneously, or in some cases, depending on the functions involved, they may be executed in the reverse order of the figures. Furthermore, it should be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a system based on dedicated hardware or by a combination of dedicated hardware and computer instructions to perform specific functions or operations.

[0060] The various embodiments of the present disclosure have been described above. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, the practical application, or the technical improvement of the market technology, or to enable other ordinary skill in the art in the technical field to understand the embodiments disclosed herein.

Claims

1. A data encapsulation method for parallel recall, comprising: Transforming one or more serially packaged cards into parallel packaged cards, wherein an exception capture and timeout fast return strategy are implemented; Abstracting the common business of the parallel packaged card to generate a responsibility chain for parameter packaging and recall processing; as well as Generate resource bits for data encapsulation based on the responsibility chain abstraction, and use the resource bits in combination with the responsibility chain to implement front-end display of data. The transformation of the parallel packaged card includes submitting the business logic of the one or more serial packaged cards to a thread pool for asynchronous parallel processing. The timeout fast return strategy includes waiting for a first time in parallel after the business logic submission of the one or more serially packaged cards is completed, and when the first card has not completed data packaging, it is determined that a logic exception is captured, and the business logic data corresponding to the first card is assigned to preset data, and The generation of the resource bit includes abstracting the data context based on the responsibility chain, and abstracting the configuration resource of the resource bit into a json data format.

2. The data encapsulation method according to claim 1, wherein: The transformation of the parallel packaged cards includes implementing the common business logic of the one or more serial packaged cards into a common abstract class, and encapsulating the special business logic into respective implementation classes, wherein the special business logic is the respective business logic of each serial packaged card in the one or more serial packaged cards that is different from the common business logic.

3. The data encapsulation method according to claim 1, wherein: After the business logic submission of the one or more serially packaged cards is completed, the first time is waited in parallel to confirm that the submitted business logic data has been packaged.

4. The data encapsulation method according to claim 1, wherein: The responsibility chain includes a parameter encapsulation module, a recall processing module, a sorting processing module and a creative encapsulation module.

5. The data encapsulation method according to claim 2, wherein: The responsibility chain defines a processing entry for technical implementation, a special business logic execution method, and a label indicating the next process.

6. The data encapsulation method according to claim 1, wherein: In response to the need to execute a function corresponding to the specified business logic, the function is parsed for JSON parameters, and the data is read and repackaged.

7. A data encapsulation device for parallel recall, running on a user terminal, comprising: A parallel packaging transformation unit is configured to transform one or more serial packaging cards into parallel packaging cards, wherein an exception capture and timeout fast return strategy are executed; A responsibility chain abstraction unit, configured to abstract the common business of the parallel packaged card to generate a responsibility chain for parameter packaging and recall processing; as well as A resource bit generation unit is configured to generate resource bits for data encapsulation based on the responsibility chain abstraction, and use the resource bits in combination with the responsibility chain to implement front-end display of data. The parallel packaging transformation unit is further configured to submit the business logic of the one or more serial packaging cards to the thread pool for asynchronous parallel processing. The timeout fast return strategy includes waiting for a first time in parallel after the business logic submission of the one or more serially packaged cards is completed, and when the first card has not completed data packaging, it is determined that a logic exception is captured, and the business logic data corresponding to the first card is assigned to preset data, and The responsibility chain abstraction unit is also configured to abstract the configuration resources of the resource bits into a json data format based on the context of the responsibility chain abstraction data.

8. The data encapsulation device according to claim 7, wherein: The parallel encapsulation transformation unit is also configured to wait in parallel for a first time after the business logic submission of the one or more serially encapsulated cards is completed to confirm that the submitted business logic data has been encapsulated.

9. The data encapsulation device according to claim 7, wherein: The resource bit generation unit is also configured to perform json parameter parsing on the function in response to the need to execute the function corresponding to the specified business logic, and to read and re-encapsulate the data.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor is enabled to execute the data encapsulation method according to any one of claims 1 to 6.

11. A computer program product, comprising computer program instructions, wherein when the computer program instructions are executed by a processor, the data encapsulation method according to any one of claims 1 to 6 is implemented.

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