CN115357611A

CN115357611A - Data processing method and device, electronic equipment and storage medium

Info

Publication number: CN115357611A
Application number: CN202210836826.6A
Authority: CN
Inventors: 贾光楠; 刘彦江; 尉乃升; 许韩晨玺
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-07-15
Filing date: 2022-07-15
Publication date: 2022-11-18

Abstract

The disclosure provides a data processing method, a data processing device, electronic equipment and a storage medium, and relates to the field of artificial intelligence such as big data processing and data warehouses, wherein the method comprises the following steps: acquiring source data corresponding to the information to be processed from a media platform for delivering the information to be processed; aggregating the obtained source data to obtain an aggregation result; acquiring a query request of a user, determining an aggregation result matched with the query request, and generating result display information corresponding to the query request according to the matched aggregation result. By applying the scheme disclosed by the disclosure, required data service support and the like can be provided for related services.

Description

Data processing method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of artificial intelligence technologies, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium in the fields of big data processing and data warehouse.

Background

In recent years, with the rapid development of electronic information network technology, advertisement marketing services have been rapidly developed, and advertisers hope to acquire relevant data after placing advertisements on a media platform so as to optimize advertisement marketing schemes and the like.

Disclosure of Invention

The disclosure provides a data processing method, a data processing device, an electronic device and a storage medium.

A method of data processing, comprising:

acquiring source data corresponding to information to be processed from a media platform for delivering the information to be processed;

aggregating the obtained source data to obtain an aggregation result;

the method comprises the steps of obtaining a query request of a user, determining an aggregation result matched with the query request, and generating result display information corresponding to the query request according to the matched aggregation result.

A data processing apparatus comprising: the system comprises a media data access module, an intermediate index processing module and an application index display module;

the media data access module is used for acquiring source data corresponding to the information to be processed from a media platform for delivering the information to be processed;

the intermediate index processing module is used for aggregating the acquired source data to obtain an aggregation result;

the application index display module is used for acquiring a query request of a user, determining an aggregation result matched with the query request, and generating result display information corresponding to the query request according to the matched aggregation result.

An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method as described above.

A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method as described above.

A computer program product comprising computer programs/instructions which, when executed by a processor, implement a method as described above.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of an embodiment of a data processing method according to the present disclosure;

FIG. 2 is a schematic diagram of an overall implementation process of the data processing method according to the present disclosure;

FIG. 3 is a schematic diagram of a data processing apparatus 300 according to an embodiment of the present disclosure;

FIG. 4 shows a schematic block diagram of an electronic device 400 that may be used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In addition, it should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter associated objects are in an "or" relationship.

Fig. 1 is a flowchart of an embodiment of a data processing method according to the present disclosure. As shown in fig. 1, the following detailed implementation is included.

In step 101, source data corresponding to information to be processed is obtained from a media platform delivering the information to be processed.

In step 102, the acquired source data is aggregated to obtain an aggregation result.

In step 103, a query request of the user is obtained, an aggregation result matched with the query request is determined, and result display information corresponding to the query request is generated according to the matched aggregation result.

By adopting the scheme of the method embodiment, the corresponding source data can be automatically acquired from the media platform for delivering the information to be processed aiming at the information to be processed, and the result display information which meets the query requirement of the user, such as the advertisement delivery effect or the delivery effect comparison information, can be generated based on the acquired source data, so that the data service support is provided for the advertisement marketing business, the advertisement marketing scheme is convenient to optimize, and the like.

The scheme of the present disclosure can be implemented based on a massively parallel processing architecture. The information to be processed may refer to a certain advertisement or a certain type of advertisement, etc.

The scheme of the present disclosure is realized by mainly including three parts, which are respectively: media data access, intermediate index processing, and application index presentation, which are described below.

1) Media data access

The information to be processed can be delivered to one or more media platforms, and accordingly, source data corresponding to the information to be processed can be obtained from the media platforms.

In one embodiment of the present disclosure, the source data may be acquired from the media platform in an incremental acquisition manner in response to determining that the predetermined point in time has been reached.

Additionally, in one embodiment of the present disclosure, the source data may include: and recording information with the finest data granularity corresponding to the information to be processed.

Taking advertising as an example, assume that the data hierarchy in media platform a can be divided as follows: and acquiring data corresponding to the creative level, namely recording information of the finest data granularity, wherein information such as the display number, the cost number, the user click and the like of the advertisement can be recorded.

It should be noted that the above hierarchical division manner is merely an example, and is not used to limit the technical solution of the present disclosure, and for different media platforms, the hierarchical division manner may be the same or different, but whatever division manner is adopted, it is necessary to ensure that the obtained source data is data with the finest data granularity, such as the record information, that is, information such as a user click condition on the lowest hierarchy on the service level needs to be mined, so that the release effect of the information to be processed can be more accurately reflected.

In practical application, a record can be generated on the media platform at intervals of a preset time, such as one hour, and can be stored in the media platform data resource library, and the interface can ensure the integrity and the correctness of data in a full-reading mode. Accordingly, for each media platform, when it is determined that the predetermined time point is reached, the source data may be acquired from each media platform by an incremental acquisition manner, that is, by an incremental time. The specific predetermined time points may be determined according to actual needs, and may be, for example, zero point of each day, or zero point of the first day of each week, or time delayed by one to two minutes every hour, etc.

The time points are reasonably set, the required source data information can be acquired in time, so that a good foundation is laid for subsequent processing, and an incremental acquisition mode can be adopted, namely only newly increased source data between two adjacent time points are acquired, so that the data quantity required to be acquired is reduced, and the resource consumption is reduced.

In addition, when the source data is acquired from the media platform data repository, the source data in the media platform data repository may be directly read, or the source data may be transmitted by using a Object representation (JSON, javaScript Object notification) file, and the specific manner is not limited.

In the scheme of the present disclosure, a Data warehouse technology may also be adopted, and accordingly, the acquired Source Data may be stored in a Data warehouse Source layer (DS). The data warehouse has many advantages, such as supporting access to streaming data and batch data simultaneously, and can satisfy extraction-transformation-Load (ETL) tasks of real-time and offline data, and can control data query delay within a second level.

In practical applications, before storing the source data in the data warehouse pasting layer, the source data may be converted into a predetermined type, such as a type required by the data warehouse, and then the converted source data may be stored in the data warehouse pasting layer, thereby implementing the normalized processing of the data. In addition, in addition to type conversion, in order to reduce redundancy, data elimination processing can be performed on the source data, that is, redundant data in the source data can be eliminated, so that storage resources are saved, workload of subsequent processing is reduced, and the like.

2) Intermediate index processing

And further processing the acquired source data, namely processing basic indexes according to the source data.

In an embodiment of the present disclosure, the acquired source data may be aggregated according to a hierarchy dimension and/or a time dimension, so as to obtain an aggregation result.

Specifically, in an embodiment of the present disclosure, aggregating the acquired source data according to a hierarchy dimension and/or a time dimension may include: respectively aggregating the source data belonging to the same hierarchy for different predefined hierarchies, and/or respectively aggregating the source data belonging to the same time region for different predefined time regions, and/or respectively aggregating the source data belonging to the same hierarchy for different predefined time regions.

In one embodiment of the present disclosure, when the information to be processed is an advertisement, the different levels may include: the media platform ID, the promotion plan ID, the unit ID, and the creative ID may be the first hierarchy, i.e., the highest hierarchy, of all the service tables, the promotion plan ID may be the second hierarchy, the unit ID may be the third hierarchy, and the creative ID may be the fourth hierarchy.

The source data of different media platforms can be processed in a unified manner according to the advertising marketing requirements, so that relatively complete intermediate data with the same granularity are established, and the usability, the sharing performance and the like of the data are enhanced.

Because the obtained source data is data with the finest data granularity, the source data can be directly aggregated according to the hierarchy, that is, the source data belonging to the same hierarchy are aggregated, for example, the source data belonging to the same media platform ID are aggregated, the source data belonging to the same promotion plan ID are aggregated, the source data belonging to the same unit ID are aggregated, and the source data belonging to the same creative ID are aggregated.

In addition, considering that the advertisement data has strong timeliness, data at different times can have great influence on business analysis, in order to ensure good adaptability to user requirements, the source data can be aggregated according to time dimensions, namely, the source data belonging to the same time region are aggregated respectively, the time dimensions can include year, month, day, week, hour and the like, for example, the source data belonging to the same week are aggregated, the source data belonging to the same day are aggregated, and the like.

Alternatively, the hierarchy dimension and the time dimension may be combined, for example, the source data belonging to the same hierarchy are aggregated according to different time regions to which the source data belong. For example, for a certain promotion plan ID, the source data belonging to the hierarchy may be aggregated separately according to the week or day to which the source data belongs.

Specifically, which polymerization mode is adopted can be determined according to actual needs, and is very flexible and convenient, and in addition, different levels, different time regions and the like can be flexibly set according to actual needs.

Through the processing, the data of each media platform can be integrated and pulled through, and various aggregation results meeting the convenience of data use and the requirement of quick query can be obtained.

In addition, as described above, the obtained source data may be stored in the data warehouse overlay layer, and accordingly, in one embodiment of the present disclosure, the source data in the data warehouse overlay layer may be aggregated to obtain an aggregation result, and may be stored in a data warehouse intermediate layer (DW, dataWarehouse), for example, in an intermediate table of the data warehouse intermediate layer. For example, when aggregating source data in time dimensions of year, month, day, even hour, etc., structured Query Language (SQL) time sequences such as year, month, day, minute and second type formatting (format) operations may be provided for the source data in the source pasting layer of the data warehouse, and meanwhile, in combination with a solution of SQL code clauses (groupby), an aggregation result of source data of different media platforms in year, month, day, even hour, etc. is formed.

3) Application index display

And finally processing and displaying according to the basic indexes, specifically, acquiring the query request of the user, determining the aggregation result matched with the query request, and generating result display information corresponding to the query request according to the matched aggregation result.

In an embodiment of the present disclosure, an aggregation result matched with the query request may be determined according to parameter information carried in the query request, that is, the intermediate layer data is selected, where the parameter information may include: temporal region and/or hierarchy information of the query.

For example, two different time regions may be included in the parameter information, and accordingly, the aggregated result corresponding to the two time regions may be used as the aggregated result matching the query request. For another example, the parameter information may include two different levels, such as two corresponding promotion plan IDs, and then the aggregation result corresponding to the two promotion plan IDs may be used as the aggregation result matching the query request. For another example, the parameter information may include a time region and two media platforms, and then an aggregation result corresponding to the time region in the aggregation results corresponding to the two media platforms may be used as a matching aggregation result. For another example, the parameter information may include two time regions and one media platform, and then the aggregation result corresponding to the two time regions in the aggregation result corresponding to the media platform may be used as the matching aggregation result.

It can be seen that by means of the parameter information, the aggregation result matched with the query request can be determined efficiently and accurately.

As described above, the source data in the data warehouse source layer may be aggregated to obtain an aggregation result, and the aggregation result is stored in the data warehouse intermediate layer, and accordingly, in an embodiment of the present disclosure, an aggregation result matching the query request may be determined from the aggregation results stored in the data warehouse intermediate layer, and the matching aggregation result may be stored in the data warehouse application layer (DM, dataMart), and then, the result display information corresponding to the query request may be generated according to the matching aggregation result.

Generally, the number of matched aggregation results is greater than one, such as two as described above, or may be three or more, and in practical applications, there may be only one, for example, only one time region is included in the parameter information.

However, in most cases, the user needs to compare information, and therefore, the number of the obtained matching aggregation results is usually greater than one, that is, in an embodiment of the present disclosure, the matching aggregation results may include: at least two aggregation results which need to be compared, and accordingly, the result display information may include: and comparing results to display information.

The key point of advertisement marketing is how to optimize future or even future marketing schemes according to marketing results of days, weeks or even months in the past. Accordingly, for the same advertisement or the same type of advertisement, the impression effect of the past two weeks or three weeks can be compared, so that the display information of the comparison result is obtained. Or aiming at the same advertisement or the same type of advertisement, the releasing effects of the same advertisement or the same type of advertisement on different media platforms can be compared, so that the display information of the comparison result is obtained, and the like.

The information is displayed by means of the comparison result, so that a user can conveniently and intuitively know the required comparison result, and further processing is carried out based on the comparison result.

How to obtain the comparison result display information is not limited, and the specific form of the comparison result display information is not limited. For example, the comparative result display information including graphs and/or tables and/or characters can be obtained by performing summary analysis, comparison and the like on the source data in each aggregated result.

In an embodiment of the disclosure, for the information to be processed, an optimized delivery scheme (e.g., an optimized advertisement marketing scheme) may be generated based on the comparison result display information, and an optimization suggestion may be given for the user to refer to, so that the work of the user is reduced, and the use experience of the user is improved.

Based on the above description, fig. 2 is a schematic diagram of an overall implementation process of the data processing method according to the present disclosure. As shown in fig. 2, the method mainly includes three parts, namely media data access, intermediate index processing, and application index display, which respectively correspond to the data warehouse source layer, the data warehouse intermediate layer, and the data warehouse application layer, and specific implementation can refer to the foregoing related description and is not described again.

It is noted that while for simplicity of explanation, the foregoing method embodiments are described as a series of acts, those skilled in the art will appreciate that the present disclosure is not limited by the order of acts, as some steps may, in accordance with the present disclosure, occur in other orders and concurrently. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required for the disclosure.

In a word, by adopting the method disclosed by the invention, the information to be processed is taken as the advertisement as an example, and the comparison of the putting effect of various dimensions can be supported, so that the data service support is provided for the advertisement marketing business, and the advertisement marketing scheme is convenient to optimize and the like.

The above is a description of embodiments of the method, and the embodiments of the apparatus are further described below.

Fig. 3 is a schematic diagram illustrating a structure of a data processing apparatus 300 according to an embodiment of the present disclosure. As shown in fig. 3, includes: a media data access module 301, an intermediate index processing module 302, and an application index display module 303.

The media data access module 301 is configured to obtain source data corresponding to the information to be processed from a media platform delivering the information to be processed.

And an intermediate index processing module 302, configured to aggregate the obtained source data to obtain an aggregation result.

The application index display module 303 is configured to obtain a query request of a user, determine an aggregation result matched with the query request, and generate result display information corresponding to the query request according to the matched aggregation result.

By adopting the scheme of the embodiment of the device, the corresponding source data can be automatically acquired from the media platform for delivering the information to be processed aiming at the information to be processed, and result display information meeting the query requirement of a user, such as advertisement delivery effect or delivery effect comparison information, can be generated based on the acquired source data, so that data service support is provided for advertisement marketing business, and the advertisement marketing scheme and the like are convenient to optimize.

The information to be processed may be delivered to one or more media platforms, and accordingly, the media data access module 301 may obtain source data corresponding to the information to be processed from the media platforms.

In one embodiment of the present disclosure, the media data access module 301 may acquire the source data from the media platform in an incremental acquisition manner in response to determining that the predetermined time point is reached.

Taking advertising as an example, assume that the data hierarchy in media platform a can be divided as follows: the promotion plan ID, the unit ID, and the creative ID, the media data access module 301 may obtain data corresponding to the creative hierarchy, that is, the record information of the finest data granularity, in which information such as the number of displays, the number of costs, and the number of clicks of the user of the advertisement may be recorded.

In practical applications, a record may be generated on the media platform at predetermined time intervals, such as one hour, and may be stored in the media platform data repository. Accordingly, for each media platform, the media data access module 301 may acquire the source data from the data repository of each media platform in an incremental acquisition manner when it is determined that the predetermined time point is reached.

And (4) further processing the acquired source data, namely processing basic indexes according to the source data.

In an embodiment of the present disclosure, the intermediate indicator processing module 302 may aggregate the acquired source data according to a hierarchy dimension and/or a time dimension to obtain an aggregation result.

Specifically, in an embodiment of the present disclosure, the aggregating the acquired source data according to the hierarchy dimension and/or the time dimension by the intermediate index processing module 302 may include: respectively aggregating the source data belonging to the same hierarchy for different predefined hierarchies, and/or respectively aggregating the source data belonging to the same time region for different predefined time regions, and/or respectively aggregating the source data belonging to the same hierarchy for different predefined time regions.

In one embodiment of the present disclosure, when the information to be processed is an advertisement, the different levels may include: the media platform ID, the promotion plan ID, the unit ID, and the creative ID may be the first hierarchy, i.e., the highest hierarchy, of all the business tables, the promotion plan ID may be the second hierarchy, the unit ID may be the third hierarchy, and the creative ID may be the fourth hierarchy.

Further, the application index display module 303 may obtain the query request of the user, determine the aggregation result matched with the query request, and generate the result display information corresponding to the query request according to the matched aggregation result.

In an embodiment of the present disclosure, the application index displaying module 303 may determine, according to parameter information carried in the query request, an aggregation result matched with the query request, where the parameter information may include: temporal region and/or hierarchy information of the query.

In an embodiment of the present disclosure, for the to-be-processed information, the application index presentation module 303 may further generate an optimized delivery scheme (e.g., an optimized advertisement marketing scheme) based on the comparison result presentation information, so as to provide an optimization suggestion for the user to refer to.

In addition, the solution of the present disclosure may be implemented by means of a data warehouse, and accordingly, in an embodiment of the present disclosure, the media data access module 301 may store the obtained source data in the data warehouse overlay layer, the intermediate indicator processing module 302 may aggregate the source data in the data warehouse overlay layer to obtain an aggregation result, and store the aggregation result in the data warehouse intermediate layer, and the application indicator display module 303 may determine, from the aggregation result stored in the data warehouse intermediate layer, an aggregation result matching the query request, and store the matching aggregation result in the data warehouse application layer.

The specific working flow of the embodiment of the apparatus shown in fig. 3 can refer to the related description of the foregoing method embodiments.

In a word, by adopting the device disclosed by the disclosure, taking information to be processed as an advertisement as an example, the contrast of the putting effect of various dimensions can be supported, so that data service support is provided for advertisement marketing business, and the advertisement marketing scheme and the like are convenient to optimize.

The scheme disclosed by the disclosure can be applied to the field of artificial intelligence, in particular to the fields of big data processing, data warehouse and the like. Artificial intelligence is a subject for studying a computer to simulate some thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning and the like) of a human, and has a hardware technology and a software technology, the artificial intelligence hardware technology generally comprises technologies such as a sensor, a special artificial intelligence chip, cloud computing, distributed storage, big data processing and the like, and the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, machine learning/deep learning, a big data processing technology, a knowledge graph technology and the like.

The source data, the result display information, and the like in the embodiments of the present disclosure are not specific to a certain user, and cannot reflect personal information of a certain user. In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 4 shows a schematic block diagram of an electronic device 400 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 4, the apparatus 400 includes a computing unit 401 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the device 400 can also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

A number of components in device 400 are connected to I/O interface 405, including: an input unit 406 such as a keyboard, a mouse, or the like; an output unit 407 such as various types of displays, speakers, and the like; a storage unit 408 such as a magnetic disk, optical disk, or the like; and a communication unit 409 such as a network card, modem, wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

Computing unit 401 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 401 performs the various methods and processes described above, such as the methods described in this disclosure. For example, in some embodiments, the methods described in this disclosure may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 400 via the ROM 402 and/or the communication unit 409. When loaded into RAM 403 and executed by computing unit 401, may perform one or more steps of the methods described in the present disclosure. Alternatively, in other embodiments, the computing unit 401 may be configured in any other suitable manner (e.g., by means of firmware) to perform the methods described in the present disclosure.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, causes the functions/acts specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

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

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method of data processing, comprising:

aggregating the obtained source data to obtain an aggregation result;

2. The method of claim 1, wherein,

the obtaining of the source data corresponding to the information to be processed from the media platform delivering the information to be processed includes: in response to determining that a predetermined point in time has been reached, the source data is acquired from the media platform in an incremental acquisition manner.

3. The method of claim 1, wherein,

the source data includes: and recording information with the finest data granularity corresponding to the information to be processed.

4. The method of claim 1, wherein,

the aggregating the acquired source data includes: aggregating the source data according to a hierarchy dimension and/or a time dimension.

5. The method of claim 4, wherein,

the aggregating the source data according to a hierarchical dimension and/or a time dimension comprises:

respectively aggregating the source data belonging to the same level aiming at different predefined levels;

and/or aggregating the source data belonging to the same time region respectively for different predefined time regions;

and/or respectively aggregating the source data belonging to the same hierarchy according to the different time regions to which the source data belong.

6. The method of claim 5, wherein,

the information to be processed includes: advertising;

the different levels include: media platform identification, promotion plan identification, unit identification and creative identification.

7. The method of claim 5, wherein,

the acquiring of the query request of the user and the determining of the aggregation result matched with the query request comprise:

determining an aggregation result matched with the query request according to parameter information carried in the query request, wherein the parameter information comprises: temporal region and/or hierarchy information of the query.

8. The method of claim 1, wherein,

the matched aggregation results comprise: at least two polymerization results that need to be compared;

the result presentation information includes: and comparing results to display information.

9. The method of claim 8, further comprising:

and aiming at the information to be processed, generating an optimized putting scheme based on the comparison result display information.

10. The method according to any one of claims 1 to 9,

the obtaining of the source data corresponding to the information to be processed from the media platform delivering the information to be processed includes: storing the acquired source data to a data warehouse source pasting layer;

the aggregating the acquired source data to obtain an aggregation result comprises: aggregating the source data in the data warehouse source pasting layer to obtain an aggregation result, and storing the aggregation result in a data warehouse middle layer;

the determining of the aggregation result matched with the query request comprises: and determining an aggregation result matched with the query request from the aggregation results stored in the data warehouse middle layer, and storing the matched aggregation result in the data warehouse application layer.

11. A data processing apparatus comprising: the system comprises a media data access module, an intermediate index processing module and an application index display module;

12. The apparatus of claim 11, wherein,

and the media data access module acquires the source data from the media platform in an incremental acquisition mode in response to the fact that the preset time point is reached.

13. The apparatus of claim 11, wherein,

14. The apparatus of claim 11, wherein,

the intermediate index processing module aggregates the source data according to a hierarchy dimension and/or a time dimension.

15. The apparatus of claim 14, wherein,

the intermediate index processing module respectively aggregates the source data belonging to the same level aiming at different predefined levels, and/or respectively aggregates the source data belonging to the same time zone aiming at different predefined time zones, and/or respectively aggregates the source data belonging to the same level according to different belonging time zones.

16. The apparatus of claim 15, wherein,

the information to be processed comprises: advertising;

17. The apparatus of claim 15, wherein,

the application index display module determines an aggregation result matched with the query request according to parameter information carried in the query request, wherein the parameter information comprises: temporal region and/or hierarchy information of the query.

18. The apparatus of claim 11, wherein,

the result display information includes: and comparing results to display information.

19. The apparatus of claim 18, wherein,

the application index display module is further used for generating an optimized putting scheme based on the comparison result display information aiming at the information to be processed.

20. The apparatus of any one of claims 11-19,

the media data access module is further used for storing the acquired source data to a data warehouse source pasting layer;

the intermediate index processing module is further used for aggregating the source data in the data warehouse source pasting layer to obtain an aggregation result and storing the aggregation result in a data warehouse intermediate layer;

the application index display module is further configured to determine an aggregation result matched with the query request from the aggregation results stored in the data warehouse intermediate layer, and store the matched aggregation result in the data warehouse application layer.

21. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-10.

22. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1-10.

23. A computer program product comprising a computer program/instructions which, when executed by a processor, implement the method of any one of claims 1-10.