Operation method of electronic device for providing information, and electronic device supporting same

Abstract

According to the present disclosure, disclosed is a method by which an electronic device provides information, the method comprising the steps of: obtaining information about a user define function set for big data operation processing related to a service provided by the electronic device; confirming an operation processing method to be applied to an operation by the user define function among an offline big data operation processing method and an online big data operation processing method on the basis of the information about the user define function; performing operation processing for input data to be operated by the user define function on the basis of the user define function and the confirmed operation processing method; and providing information about output data obtained in response to the operation processing.

Description

Method of operation of an electronic device providing information and an electronic device supporting the same

[0001] The present invention relates to a method and device for providing information, and more particularly, to a method and an electronic device for providing information on output data according to an operation performed based on a user-defined function set for big data operation processing related to a service.

[0002] With the advancement of electronic technology, e-commerce has become a prominent part of the shopping experience. Customers can purchase items online without having to visit a physical shopping mall or market, and items purchased online are delivered to the customer's requested delivery address.

[0003] In the case of e-commerce, providing detailed and accurate product information significantly impacts customer satisfaction, so various methods for providing more detailed and accurate information are being discussed.

[0004] In this regard, reference may be made to prior literature such as KR101756594B1 or KR101500849B1.

[0005] According to the method of the present invention, an electronic device can provide information on output data according to an operation performed based on a user-defined function set for big data operation processing related to a service.

[0006] The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by a person having ordinary skill in the technical field to which the present invention belongs from the description below.

[0007] Various embodiments may provide a method of operating an electronic device for providing information and an electronic device supporting the same.

[0008] A method for an electronic device to provide information according to various embodiments may include: obtaining information on a user-defined function set for big data operation processing related to a service provided by the electronic device; confirming, based on the information on the user-defined function, an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method; performing operation processing on input data that is a target of an operation by the user-defined function based on the user-defined function and the confirmed operation processing method; and providing information on output data obtained in response to the operation processing.

[0009] In an exemplary embodiment, the operation processing method to be applied to an operation by the user-defined function may be determined based on the operation complexity of the user-defined function.

[0010] In an exemplary embodiment, when the computational complexity is below a preset level, the offline big data computational processing method may be set to be applied to the computation by the user-defined function, and when the computational complexity is above the preset level, the online big data computational processing method may be set to be applied to the computation by the user-defined function.

[0011] In an exemplary embodiment, when the offline big data operation processing method is applied to an operation by the user-defined function, the operation by the user-defined function may be performed by the electronic device to obtain the output data.

[0012] In an exemplary embodiment, when the online big data operation processing method is applied to an operation by the user-defined function, the step of performing the operation processing may include the step of transmitting operation processing request information for the user-defined function and the input data to an online big data operation processing device; and the step of receiving, in response to the operation processing request information and the input data, the output data obtained by the online big data operation processing device performing the operation by the user-defined function from the online big data operation processing device.

[0013] In an exemplary embodiment, the online big data operation processing device may correspond to a device set to perform an operation by a user-defined function by calling an API (Application Programming Interface) related to the user-defined function.

[0014] In an exemplary embodiment, the output data may be set to have its accuracy verified based on an operation accuracy judgment model linked to the online big data operation processing device.

[0015] In an exemplary embodiment, the operation processing request information may include information instructing the online big data operation processing device to perform an operation by the user-defined function as the online big data operation processing method is applied to the operation by the user-defined function.

[0016] In an exemplary embodiment, the operation processing request information may include information about one or more APIs (Application Programming Interfaces) on the service that are called for an operation by the user-defined function.

[0017] In an exemplary embodiment, the operation processing request information may include information on setting parameters and conditions for the operation by the user-defined function.

[0018] In an exemplary embodiment, the user-defined function may correspond to a function created by an operator of the service for offline big data computation processing related to the service provided by the electronic device.

[0019] In an exemplary embodiment, the information providing method may further include a step of setting a user-defined function management list including a plurality of user-defined functions created by a plurality of workers of the service.

[0020] In an exemplary embodiment, the information providing method may further include: obtaining a function use approval request for using a first user-defined function included in the user-defined function management list from a specific worker; providing the function use approval request to a first worker who created the first user-defined function; and, when a function use approval response for the first user-defined function is obtained from the first worker in response to the function use approval request, providing the function use approval response and usage details for the first user-defined function to the specific worker.

[0021] In an exemplary embodiment, the information providing method may further include a step of setting up, when the first worker is absent, a request for approval to use the function to be provided to a superior manager of the first worker and an acquisition of a response to approval to use the function to be obtained.

[0022] In an exemplary embodiment, a module may be set up to perform providing of a function usage authorization request and obtaining of a function usage authorization response.

[0023] In an electronic device providing information according to various embodiments, the electronic device comprises: a processor; and one or more memories storing one or more instructions, wherein the one or more instructions, when executed, cause the processor to perform: a step of obtaining information about a user-defined function set for big data operation processing related to a service provided by the electronic device; a step of confirming, based on the information about the user-defined function, an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method; a step of performing operation processing on input data that is a target of an operation by the user-defined function based on the user-defined function and the confirmed operation processing method; and a step of providing information about output data obtained in response to the operation processing.

[0024] The various embodiments of the present disclosure described above are only some of the preferred embodiments of the present disclosure, and various embodiments reflecting the technical features of the various embodiments of the present disclosure can be derived and understood by a person having ordinary skill in the art based on the detailed description to be described below.

[0025] The present invention provides a method for an electronic device to provide information on output data according to an operation performed based on a user-defined function set for processing big data operations related to a service, thereby having a technical effect in that big data operations can be effectively performed through a user-defined function.

[0026] The effects that can be obtained from the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by a person having ordinary skill in the art to which the present invention belongs from the description below.

[0027] FIG. 1 is a drawing for explaining an information providing system in which an operating method of an electronic device for providing information according to various embodiments can be implemented.

[0028] FIG. 2 is a diagram illustrating a configuration of a server device and a user device according to various embodiments.

[0029] FIG. 3 is a diagram illustrating an operation method of a server device for providing information according to various embodiments.

[0030] Figure 4 is a diagram illustrating a server device performing computational processing using a user-defined function according to an offline big data computational processing method or an online big data computational processing method.

[0031] FIG. 5 is a diagram illustrating an example of an operation in which a server device manages a user-defined function for processing big data operations related to a service through a user-defined function management list.

[0032] FIG. 6 is a diagram illustrating a server device managing user-defined functions for processing big data operations related to a service based on a user-defined function management list and a use approval module.

[0033] The following embodiments combine components and features of various embodiments in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, various embodiments may be formed by combining some components and features. The order of operations described in various embodiments may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment.

[0034] In the description of the drawings, procedures or steps that may obscure the gist of various embodiments are not described, and procedures or steps that can be understood by a person with ordinary skill in the art are also not described.

[0035] Throughout the specification, when a part is said to "comprising" (or including) a certain component, this does not mean that other components are excluded, but rather that other components can be included, unless specifically stated otherwise. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the singular and plural sense in the context of describing various embodiments (especially in the context of the claims below) unless otherwise indicated herein or clearly contradicted by context.

[0036] Hereinafter, preferred embodiments according to various embodiments will be described in detail with reference to the attached drawings. The detailed description set forth below, together with the attached drawings, is intended to explain exemplary embodiments of various embodiments and is not intended to represent the only embodiments.

[0037] Additionally, specific terms used in various embodiments are provided to aid understanding of the various embodiments, and the use of such specific terms may be changed in other forms without departing from the technical spirit of the various embodiments.

[0038] FIG. 1 is a drawing for explaining an information providing system in which an operating method of an electronic device for providing information according to various embodiments can be implemented.

[0039] Referring to FIG. 1, the information providing system according to various embodiments may be implemented in various types of electronic devices. For example, the information providing system may be implemented in a server device (100) and a user device (200). In other words, the server device (100) and the user device (200) may perform operations according to various embodiments of the present disclosure based on the information providing system implemented in each device. For example, in various embodiments according to the present disclosure, the server device (100) may provide information on output data acquired in response to operation processing by a user-defined function to a user device (200) corresponding to an administrator. Meanwhile, the information providing system according to various embodiments is not limited to that illustrated in FIG. 1, and may be implemented in a wider variety of electronic devices and servers.

[0040] According to various embodiments, a server device (100) may be a device that performs wireless and wired communication with a plurality of user devices (200) and includes storage with a large storage capacity. For example, the server device (100) may be a cloud device that is linked with a plurality of user devices (200).

[0041] The user device (200) according to various embodiments may be a device that can be used by individual users, such as a desktop PC, tablet PC, or mobile terminal. In addition, other electronic devices that perform similar functions may be used as the user device (200).

[0042] An information providing system according to various embodiments may include various modules for operation. The modules included in the information providing system may be computer codes or one or more instructions implemented so that a physical device (e.g., a server device (100) and a user device (200)) in which the information providing system is implemented (or included in a physical device) can perform a specified operation. In other words, a physical device in which the information providing system is implemented stores a plurality of modules in a memory in the form of computer codes, and when the plurality of modules stored in the memory are executed, the plurality of modules can cause the physical device to perform specified operations corresponding to the plurality of modules.

[0043] FIG. 2 is a diagram illustrating a configuration of a server device and a user device according to various embodiments.

[0044] Referring to FIG. 2, the server device (100) and the user device (200) may include an input / output unit (210), a transceiver (or communication unit) (220), storage (230), and a processor (240).

[0045] The input / output unit (210) may be various interfaces or connection ports that receive user input or output information to the user. The input / output unit (210) may include an input module and an output module, and the input module receives user input from the user. The user input may be in various forms, including key input, touch input, and voice input. Examples of input modules that can receive such user input include not only a traditional keypad, keyboard, or mouse, but also a touch sensor that detects the user's touch, a microphone that receives a voice signal, a camera that recognizes gestures through image recognition, a proximity sensor including at least one of an illuminance sensor or an infrared sensor that detects the user's approach, a motion sensor that recognizes the user's movement through an acceleration sensor or a gyro sensor, and various other forms of input means that detect or receive various forms of user input, and the input module according to an embodiment of the present disclosure may include at least one of the devices listed above. Here, the touch sensor can be implemented as a piezoelectric or electrostatic touch sensor that detects touch through a touch panel or touch film attached to the display panel, an optical touch sensor that detects touch by an optical method, etc. In addition, the input module can be implemented in the form of an input interface (USB port, PS / 2 port, etc.) that connects an external input device that receives user input instead of a device that detects user input on its own. In addition, the output module can output various types of information. The output module can include at least one of a display that outputs an image, a speaker that outputs a sound, a haptic device that generates vibration, and various other forms of output means. In addition, the output module can be implemented in the form of a port-type output interface that connects the individual output means described above.

[0046] For example, an output module in the form of a display can display text, still images, and moving images. The display can include at least one of a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, a flat panel display (FPD), a transparent display, a curved display, a flexible display, a 3D display, a holographic display, a projector, and various other devices capable of performing an image output function. Such a display can also be in the form of a touch display that is integrated with a touch sensor of the input module.

[0047] The transceiver (220) can communicate with other devices. Accordingly, the server device (100) and the user device (200) can transmit and receive information with other devices via the transceiver (220). For example, the server device (100) and the user device (200) can communicate with each other or with other devices using the transceiver (220).

[0048] Here, communication, i.e., transmission and reception of data, can be performed wired or wirelessly. To this end, the transceiver (220) may include a wired communication module that connects to the Internet, etc., via a LAN (Local Area Network), a mobile communication module that connects to a mobile communication network via a mobile communication base station and transmits and receives data, a short-range communication module that uses a WLAN (Wireless Local Area Network) series communication method such as Wi-Fi or a WPAN (Wireless Personal Area Network) series communication method such as Bluetooth or Zigbee, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as a GPS (Global Positioning System), or a combination thereof.

[0049] Storage (230) can store various types of information. Storage (230) can store data temporarily or semi-permanently. For example, the storage (230) of the server device (100) can store an operating program (OS: Operating System) for operating the server device (100), data for hosting a website, a program for generating Braille, or data related to an application (e.g., a web application). In addition, the storage (230) can store modules in the form of computer code, as described above.

[0050] Examples of storage (230) may include a hard disk drive (HDD), a solid state drive (SSD), flash memory, read-only memory (ROM), random access memory (RAM), etc. This storage (230) may be provided as a built-in type or a detachable type.

[0051] The processor (240) controls the overall operation of the server device (100) and the user device (200). To this end, the processor (240) may perform calculations and processing of various types of information and control the operation of components of the server device (100). For example, the processor (240) may execute a program or application for providing information. The processor (240) may be implemented as a computer or a similar device according to hardware, software, or a combination thereof. In terms of hardware, the processor (240) may be implemented in the form of an electronic circuit that processes electrical signals to perform control functions, and in terms of software, it may be implemented in the form of a program that drives the hardware processor (240). Meanwhile, unless otherwise specified in the following description, the operations of the server device (100) and the user device (200) may be interpreted as being performed under the control of the processor (240). That is, when the modules implemented in the above-described information provision system are executed, the modules can be interpreted as controlling the processor (240) to perform the following operations on the server device (100) and the user device (200).

[0052] In summary, the various embodiments may be implemented through various means. For example, the various embodiments may be implemented through hardware, firmware, software, or a combination thereof.

[0053] In the case of hardware implementation, the methods according to various embodiments may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.

[0054] When implemented via firmware or software, the methods according to various embodiments may be implemented in the form of modules, procedures, or functions that perform the functions or operations described below. For example, software code may be stored in memory and executed by a processor. The memory may be located within or external to the processor and may exchange data with the processor via various known means.

[0055] Below, various embodiments are described in more detail based on the above technical concepts. The previously described concepts may be applied to the various embodiments described below. For example, operations, functions, terms, etc. not defined in the various embodiments described below may be performed and explained based on the previously described concepts.

[0056] The following description describes various embodiments assuming that the server device (100) performs an operation of providing information on output data obtained in response to an operation processing by a user-defined function.

[0057] FIG. 3 is a diagram illustrating an operation method of a server device for providing information according to various embodiments.

[0058] According to FIG. 3, the server device (100) obtains information about a user-defined function set for big data operation processing related to a service (301), and, based on the information about the user-defined function, confirms an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method (303), and, based on the user-defined function and the confirmed operation processing method, performs operation processing on input data that is a target of the operation by the user-defined function (305), and provides information about output data obtained in response to the operation processing (307).

[0059] According to FIG. 3, the operation of providing information on output data acquired in response to an operation processing by a user-defined function by the server device (100) may be performed for a service provided by the server device (100) or a service related to the server device (100), and the service may correspond to a service in which multiple users using the service can order and purchase multiple items sold in the service. The multiple items sold in the service are not limited to the type or type of the items and may include various types or types of items registered by the seller to sell the items.

[0060] According to various embodiments, in operation 301, the server device (100) may obtain information about a user defined function set for big data operation processing related to a service.

[0061] For example, big data operations related to services can mean operations that perform learning based on a large amount of structured or unstructured data that occurs in the process of providing a service, and obtain desired output data in response to a series of input data based on repeated learning. Such operations on big data can be performed basically by offline operation processing methods or online operation processing methods. Offline operation processing means a method that performs learning based on a fixed big data set of recorded experiences without additional interaction with the external environment, applies operations to input data, and obtains result data. Online operation processing means a method that performs learning based on a big data set that can collect data based on interaction with the external environment, applies operations to input data, and obtains result data.

[0062] Offline computation processing methods do not incur costs and computational burdens due to interaction with the external environment, but may have difficulty in collecting or computing data influenced by the external environment, whereas online computation processing methods may have the characteristics of incurring costs and computational burdens due to interaction with the external environment, although they allow for the collection or computing of data influenced by the external environment. Considering the characteristics of offline computation processing methods and online computation processing methods, in the present invention, computations based on functions that have relatively low computational complexity and do not require less consideration of the influence of the external environment are directly performed by the server device (100) in an offline computation processing method, while computations based on functions that have relatively high computational complexity and require more consideration of the influence of the external environment are managed to be performed in an online computation processing method by an online big data computation processing device linked to the server device (100).

[0063] For example, a user-defined function may correspond to a function created by a service worker for computational processing of big data related to the service. That is, a service worker may directly define and create a function to be used in the computational processing for big data, and the server device (100) may obtain information about the user-defined function created by the worker and utilize it for computational processing of big data. For example, a service worker may create a user-defined function for offline big data computational processing during online or offline big data computational processing, and the server device (100) may obtain information about the created user-defined function and directly perform offline big data computational processing related to the user-defined function based on the user-defined function. Alternatively, if there is a reason such as a high computational complexity burden confirmed in big data computational processing according to the user-defined function created by the worker, the server device (100) may switch and manage such that big data computational processing is performed through the user-defined function according to the online big data computational processing method.

[0064] According to various embodiments, in operation 303, the server device (100) can determine, based on information about the user-defined function, an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method.

[0065] For example, among the offline big data operation processing method and the online big data operation processing method, the operation processing method to be applied to the operation by the user-defined function may be determined based on the operation complexity of the user-defined function. In this case, in operation 301, the information about the user-defined function acquired by the server device (100) may include information indicating the operation complexity of the corresponding user-defined function, and the server device (100) may perform an operation process of checking the operation complexity of the corresponding user-defined function in the acquired information about the user-defined function and determining or checking the operation processing method to be applied to the operation by the corresponding user-defined function.

[0066] For example, if the computational complexity of the user-defined function is lower than a preset level, the server device (100) sets the offline big data computational processing method among the offline big data computational processing method and the online big data computational processing method to be applied to the computation by the user-defined function, and can directly perform the computation by the user-defined function. That is, if the computational complexity of the user-defined function is low, it is expected that there will be no particular processing burden even if the server device (100) directly performs the computation by the user-defined function, and therefore the computation by the user-defined function can be managed to be performed according to the offline big data computational processing method.

[0067] Conversely, if the computational complexity of the user-defined function is higher than a preset level, the server device (100) may set the online big data computational processing method among the offline big data computational processing method and the online big data computational processing method to be applied to the computation by the user-defined function, and may manage the computation by the user-defined function to be performed by the online big data computational processing device linked to the server device (100). That is, if the computational complexity of the user-defined function is high, a processing load may occur when the server device (100) directly performs the computation by the user-defined function, and therefore, the server device (100) may not directly perform the computation by the user-defined function, and may manage the computation by the user-defined function to be performed by the online big data computational processing device according to the online big data computational processing method.

[0068] According to various embodiments, in operation 305, the server device (100) may perform operation processing on input data that is a target of an operation by a user-defined function based on a user-defined function and a verified operation processing method.

[0069] For example, in operation 305, when an operation by a user-defined function is performed according to the offline big data operation processing method among the offline big data operation processing method and the online big data operation processing method, the server device (100) can directly perform the operation and obtain output data as a result thereof.

[0070] Conversely, in operation 305, when an operation is performed by a user-defined function according to an online big data operation processing method, the operation is managed to be performed by an online big data operation processing device linked to the server device (100), and the server device (100) can obtain output data according to the operation result from the online big data operation processing device. In this case, the operation in which the server device (100) performs the operation processing according to operation 305 may include an operation in which the operation processing request information for the user-defined function and the input data to be the operation target are transmitted to the online big data operation processing device, and the online big data operation processing device performs the operation by the user-defined function and receives the output data obtained from the online big data operation processing device as a response to the operation processing request information and the input data.

[0071] For example, when the server device (100) manages to perform an operation by a user-defined function according to an online big data operation processing method, the online big data operation processing device that performs the operation can correspond to a device set to perform the operation by the user-defined function by calling an API (Application Programming Interface) related to the user-defined function. That is, the online big data operation processing device is also linked to the service provided by the server device (100), can check information on the APIs that constitute the service, and can operate to call the API necessary for performing the operation by the user-defined function when receiving operation processing request information and input data to be the operation target from the server device (100).

[0072] At this time, when the online big data operation processing device obtains output data by performing an operation by a user-defined function according to the online big data operation processing method, a model for verifying the accuracy or similarity of the output data is separately set so that the appropriateness of the operation result performed by the online big data operation processing device can be determined. That is, a model such as a calculation accuracy judgment model is set to be linked to the online big data operation processing device, and can operate so as to verify the accuracy or similarity of the output data output as a result of the operation. Through the setting of such a model, the problem that the verification of the data confirmed as a result of the operation is insufficient because the server device (100) does not directly perform the operation in the online big data operation processing method can be supplemented.

[0073] For example, when an operation is performed by a user-defined function according to an online big data operation processing method, the operation processing request information transmitted by the server device (100) to the online big data operation processing device may include information instructing the online big data operation processing device to perform the operation by the user-defined function as the online big data operation processing method is applied to the operation by the user-defined function. That is, instruction information instructing the performance of an operation by the user-defined function according to the online big data operation processing method may be included in the operation processing request information.

[0074] For example, when an operation is performed by a user-defined function according to an online big data operation processing method, the operation processing request information that the server device (100) transmits to the online big data operation processing device may include information on one or more APIs (Application Programming Interfaces) on the service that are called for the operation by the user-defined function. That is, as described above, the online big data operation processing device may operate to check the APIs that constitute the service and call the APIs necessary for performing the operation by the user-defined function, and at this time, information on the APIs necessary for performing the operation by the user-defined function is transmitted from the server device (100) to the online big data operation processing device so that the online big data operation processing device can check and call the APIs indicated by the server device (100).

[0075] For example, when an operation is performed by a user-defined function according to an online big data operation processing method, the operation processing request information that the server device (100) transmits to the online big data operation processing device may include information on setting parameters and conditions for the operation by the user-defined function. In order to perform an operation by a user-defined function, various parameters related to the setting of the operation execution or conditions for the operation execution must be confirmed or input in advance, and thus, information related thereto may be transmitted from the server device (100) to the online big data operation processing device.

[0076] According to various embodiments, in operation 307, the server device (100) may provide information about output data obtained in response to the operation processing.

[0077] For example, the output data that the server device (100) provides information for in operation 307 may correspond to output data obtained when the server device (100) performs an operation by a user-defined function on the input data directly based on an offline big data operation processing method.

[0078] For example, in operation 307, the output data that the server device (100) provides information may correspond to output data obtained when an online big data operation processing device linked to the server device (100) performs an operation by a user-defined function on input data based on an online big data operation processing method.

[0079] For example, the server device (100) provides information on output data corresponding to the operation result of the user-defined function to the user device (200) corresponding to the manager of the service through operation 307, thereby enabling the manager of the service to effectively analyze the results of big data operation processing related to the service.

[0080] According to FIG. 3, the operation of the server device (100) performing calculation processing based on a user-defined function and providing information on output data corresponding to the calculation result may not be limited to an offline big data calculation processing method or an online big data calculation processing method. For example, the user-defined function utilized by the server device (100) of FIG. 3 in the calculation process has been described as being processed by big data calculation offline or online, but if the calculation by the user-defined function is very simple, such as a simple mathematical calculation of data values ​​without requiring analysis of a large amount of data, the user-defined function utilized by the server device (100) for the calculation may be managed to be processed simply, rather than being processed by big data calculation offline or online.

[0081] Figure 4 is a diagram illustrating a server device performing computational processing using a user-defined function according to an offline big data computational processing method or an online big data computational processing method.

[0082] In FIG. 4, the server device (100) can check a user-defined function for performing an operation and manage to perform an operation by the user-defined function at regular intervals such as daily, time zone, etc., and at this time, a certain SQL (Structured Query Language) tool for performing a query and operation on data according to each user-defined function is set in the server device (100), so that the server device (100) can perform an operation by each user-defined function based on the set SQL tool (401, Hive SQL).

[0083] The server device (100) can directly perform calculation processing for calculations by user-defined functions with low calculation complexity and obtain and provide the output data (405) (Output Hive, indicated by dotted lines), and for calculations by user-defined functions with high calculation complexity, the server device (100) can transmit calculation processing request information including information about an API on a service to be called for calculation by the user-defined function and information about setting parameters or conditions for calculation by the user-defined function to an online big data calculation processing device (403, Online Service), so that the online big data calculation processing device can call the API, perform calculation by the user-defined function, and receive and provide the obtained output data (405) (Output Hive, indicated by solid lines). At this time, the online big data calculation processing device of FIG. 4 may be linked with a calculation accuracy judgment model so that the online big data calculation processing device can be managed to verify the similarity or accuracy of the output data obtained by performing calculation by the user-defined function (DS Model).

[0084] In the SQL tool set in the server device (100) in FIG. 4, not only operations by one user-defined function are performed at a time, but operations for multiple user-defined functions managed so that the server device (100) performs operations at regular intervals can be performed simultaneously. In the operation of the server device (100) according to FIG. 3, it was described that the computational burden of the server device (100) can be reduced by considering the computational complexity of each user-defined function and managing the computation for user-defined functions with high computational complexity to be performed in an online big data computation processing device. However, if the number of user-defined functions that the server device (100) directly performs operations according to the offline big data computation processing method is large, the computational burden may also be placed on the server device (100).

[0085] Accordingly, the server device (100) can operate to check the number of user-defined functions that the server device (100) directly performs calculations on according to the offline big data calculation processing method among all user-defined functions set to perform calculations based on the SQL tool, and, depending on whether the checked number is greater than or equal to a threshold number, determine whether to perform calculations on all user-defined functions that perform direct calculations at once or to preferentially perform calculations on only some of the user-defined functions that perform direct calculations.

[0086] Specifically, if the number of user-defined functions for which the server device (100) performs direct calculations according to the offline big data calculation processing method based on the SQL tool is less than a preset threshold number, the server device (100) determines that there will be no significant computational burden even if calculations for all user-defined functions for which the server device (100) performs direct calculations are performed at once, and thus all calculations by the user-defined functions for which the server device (100) performs direct calculations can be processed simultaneously. On the other hand, if the number of user-defined functions for which the server device (100) performs direct calculations according to the offline big data calculation processing method based on the SQL tool is greater than or equal to a preset threshold number, the server device (100) determines that there will be a high computational burden when calculations for all user-defined functions for which the server device (100) performs direct calculations are performed at once, and thus only calculations by some of the user-defined functions for which the server device (100) performs direct calculations can be preferentially processed simultaneously.

[0087] At this time, in the case where the number of user-defined functions for which the server device (100) performs direct operations according to the offline big data operation processing method based on the SQL tool is greater than or equal to a preset threshold number, the server device (100) can select some user-defined functions to be processed with priority by reflecting the priority of each user-defined function included in the user-defined functions for which the server device (100) performs direct operations according to the offline big data operation processing method. For example, the server device (100) can set the priority of each user-defined function by considering whether the user-defined function is frequently used in various big data operation processing for the service, whether there are many requests for permission to use the user-defined function from workers of the service, the importance of analysis for input data that is the target of operation by the user-defined function, or the importance of analysis for output data that is the result of operation by the user-defined function, and so on, and selects some user-defined functions up to the threshold number in order of priority, and performs operations by some of the selected user-defined functions first, while performing operations by the remaining user-defined functions secondarily, thereby reducing the computational burden due to simultaneous operations on the user-defined functions.

[0088] Meanwhile, various user-defined functions can be created for the service provided by the server device (100) and used for various big data operation processing related to the service. The server device (100) can also perform an operation as shown in FIG. 5 to manage various user-defined functions set for big data operation processing.

[0089] FIG. 5 is a diagram illustrating an example of an operation in which a server device manages a user-defined function for processing big data operations related to a service through a user-defined function management list.

[0090] The server device (100) can set a user-defined function management list containing multiple user-defined functions, targeting multiple user-defined functions created by multiple workers of the service for big data operation processing related to the service (501). In other words, various user-defined functions created by multiple workers for the service can be created as a list and managed.

[0091] The server device (100) that sets the user-defined function management list can manage a verification and approval process so that when another worker wants to use a user-defined function created by one worker, considering that each user-defined function created by each worker may correspond to the work of each worker. Specifically, when a function use approval request for using a first user-defined function included in the user-defined function management list is obtained from a specific worker (503), the server device (100) can provide the function use approval request to the first worker who created the first user-defined function (505). When a function use approval response for the first user-defined function is obtained from the first worker in response to such a function use approval request (507), the server device (100) can provide the function use approval response and usage details for the first user-defined function to the specific worker, thereby managing the specific worker to use the first user-defined function (509).

[0092] At this time, the server device (100) may be configured to perform the procedure of providing a function use approval request of FIG. 5 and obtaining a function use approval response to the superior manager of the first worker when the first worker is absent, in order to prevent a case where the above procedure is not expected to be performed due to the absence of the first worker.

[0093] As shown in Fig. 5, the procedure for providing a function use approval request and obtaining a function use approval response between workers performed by the server device (100) may be managed so that a use approval module for performing the procedure is separately set by the server device (100) and the function use approval request or function use approval response is mutually transmitted between workers based on the set module.

[0094] FIG. 6 is a diagram illustrating a server device managing user-defined functions for processing big data operations related to a service based on a user-defined function management list and a use approval module.

[0095] In FIG. 6, the server device (100) can set a user-defined function management list including a user-defined function (UDF) created by a service worker (Engineer) (601, UDF list), and when setting the user-defined function management list, the worker can manage to write, submit, or input information about metadata and usage details for the user-defined function he or she created.

[0096] In addition, the worker can use the user-defined function included in the user-defined function management list for big data operation processing, and can send a function use request to the owner worker who created the user-defined function to be used for approval. The owner worker who received the function use request can enter a function use approval response or a function use rejection response in response to the function use approval request. If a function use approval response is entered, the function use approval response and detailed usage information about the user-defined function created by the owner worker are provided to the worker who requested approval of the user-defined function, so that the worker who requested approval of the user-defined function can use the user-defined function. If the owner worker is absent and cannot process the use approval procedure as described above, the owner worker's superior administrator (Admin) can be managed to process the use approval procedure on behalf of the owner worker.

[0097] At this time, the usage approval procedure for the user-defined function as shown in FIG. 6 can be managed to be processed according to the usage approval module set by the server device (100) (603, Permission Module).

[0098] It is obvious that each piece of information can be combined in various forms in the process of performing the operation method in which the server device (100) provides information on output data acquired in response to the operation processing by the user-defined function according to FIGS. 3 to 6.

[0099] The embodiments of the present invention disclosed in this specification and drawings are merely specific examples to easily explain the technical content of the present invention and to facilitate understanding of the present invention, and are not intended to limit the scope of the present invention. In other words, it will be apparent to those skilled in the art that other modifications based on the technical concept of the present invention are possible. Furthermore, the above-described embodiments can be combined and operated as needed. For example, all embodiments of the present invention can be implemented as a system by combining parts with each other.

[0100] In addition, the method according to the system or the like according to the present invention may be implemented in the form of program commands that can be executed through various computer means and recorded on a computer-readable medium.

[0101] As such, various embodiments of the present invention can be implemented as computer-readable code on a computer-readable recording medium in certain aspects. A computer-readable recording medium is any data storage device capable of storing data that can be read by a computer system. Examples of computer-readable recording media may include read-only memories (ROMs), random access memories (RAMs), compact disk-read-only memories (CD-ROMs), magnetic tapes, floppy disks, and optical data storage devices. The computer-readable recording medium can also be distributed through network-connected computer systems, so that the computer-readable code is stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for achieving various embodiments of the present invention can be easily interpreted by programmers skilled in the art to which the present invention is applied.

[0102] It will also be appreciated that devices and methods according to various embodiments of the present invention can be implemented in the form of hardware, software, or a combination of hardware and software. Such software may be stored in a volatile or non-volatile storage device, such as a ROM, for example, regardless of whether it is erasable or rewritable, or in a memory, such as a RAM, a memory chip, a device, or an integrated circuit, or in a storage medium that is optically or magnetically recordable and machine-readable (e.g., a computer), such as a compact disk (CD), a DVD, a magnetic disk, or a magnetic tape. It will be appreciated that methods according to various embodiments of the present invention can be implemented by a computer including a control unit and a memory, or a vehicle including such a memory or a computer, and such a memory is an example of a machine-readable storage medium suitable for storing a program or programs including commands for implementing embodiments of the present invention.

[0103] Accordingly, the present invention encompasses a program containing code for implementing the devices or methods described in the claims of this specification, and a machine-readable storage medium (e.g., a computer) storing such a program. Furthermore, such a program may be transmitted electronically via any medium, such as a communication signal transmitted via a wired or wireless connection, and the present invention appropriately encompasses equivalents thereof.

[0104] Although the present invention has been described above with reference to embodiments, the embodiments of the present invention disclosed in this specification and drawings are merely specific examples to easily explain the technical content of the present invention and assist in understanding the present invention, and are not intended to limit the scope of the present invention. Furthermore, the embodiments of the present invention described above are merely exemplary, and those skilled in the art will understand that various modifications and equivalent embodiments are possible. Therefore, the true technical protection scope of the present invention should be defined by the following claims.

Claims

1. In the method of providing information by an electronic device, A step of acquiring information about a user defined function set for big data operation processing related to a service provided by the electronic device; A step of determining an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method based on information about the user-defined function; A step of performing operation processing on input data that is the target of operation by the user-defined function based on the user-defined function and the confirmed operation processing method; and A step of providing information on output data obtained in response to the above operation processing, How to provide information.

2. In paragraph 1, The operation processing method to be applied to the operation by the above user-defined function is determined based on the operation complexity of the above user-defined function. How to provide information.

3. In paragraph 2, If the above operation complexity is below a preset level, the offline big data operation processing method is set to be applied to the operation by the user-defined function. If the above operation complexity is higher than the preset level, the online big data operation processing method is set to be applied to the operation by the user-defined function. How to provide information.

4. In paragraph 1, When the above offline big data operation processing method is applied to an operation by the user-defined function, the operation by the user-defined function is performed by the electronic device and the output data is obtained. How to provide information.

5. In paragraph 1, When the above online big data operation processing method is applied to the operation by the user-defined function, the step of performing the operation processing is: A step of transmitting operation processing request information and the input data for the user-defined function to an online big data operation processing device; and In response to the above operation processing request information and the input data, the online big data operation processing device performs an operation by the user-defined function and receives the output data obtained from the online big data operation processing device. How to provide information.

6. In paragraph 5, The above online big data operation processing device corresponds to a device set to perform an operation by a user-defined function by calling an API (Application Programming Interface) related to the user-defined function. How to provide information.

7. In paragraph 5, The above output data is set to have its accuracy verified based on an operation accuracy judgment model linked to the online big data operation processing device. How to provide information.

8. In paragraph 5, The above operation processing request information includes information instructing the online big data operation processing device to perform an operation by the user-defined function as the online big data operation processing method is applied to an operation by the user-defined function. How to provide information.

9. In paragraph 5, The above operation processing request information includes information about one or more APIs (Application Programming Interfaces) on the service called for operation by the user-defined function. How to provide information.

10. In paragraph 5, The above operation processing request information includes information on setting parameters and conditions for the operation by the user-defined function. How to provide information.

11. In paragraph 1, The above user-defined function corresponds to a function created by a worker of the service for offline big data operation processing related to the service provided by the electronic device. How to provide information.

12. In paragraph 11, The method of providing the above information is: Further comprising the step of setting a user-defined function management list including a plurality of user-defined functions created by a plurality of workers of the above service. How to provide information.

13. In paragraph 12, The method of providing the above information is: A step of obtaining a function use approval request for using a first user-defined function included in the above user-defined function management list from a specific worker; A step of providing a request for approval to use the above function to the first worker who created the above first user-defined function; and In response to the function use approval request, if a function use approval response for the first user-defined function is obtained from the first worker, further comprising the step of providing the function use approval response and usage details for the first user-defined function to the specific worker. How to provide information.

14. In paragraph 13, The method of providing the above information is: Further comprising a step of setting up a method for providing a request for approval of use of the function to a superior manager of the first worker and obtaining a response for approval of use of the function when the first worker is absent. How to provide information.

15. In paragraph 13, A module is set up to perform provision of a request for approval of use of the above function and acquisition of a response for approval of use of the above function. How to provide information.

16. In an electronic device that provides information, processor; and Contains one or more memories that store one or more instructions, The one or more instructions, when executed, cause the processor to: A step of acquiring information about a user defined function set for big data operation processing related to a service provided by the electronic device; A step of determining an operation processing method to be applied to an operation by the user-defined function among an offline big data operation processing method and an online big data operation processing method based on information about the user-defined function; A step of performing operation processing on input data that is the target of operation by the user-defined function based on the user-defined function and the confirmed operation processing method; and A step of providing information on output data obtained in response to the above operation processing, Electronic devices.

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