CN115757448A

CN115757448A - Data processing method and device, electronic equipment and storage medium

Info

Publication number: CN115757448A
Application number: CN202211457910.3A
Authority: CN
Inventors: 游学莹; 毛小亮; 黄婷; 杨洋
Original assignee: Jingdong Technology Information Technology Co Ltd
Current assignee: Jingdong Technology Information Technology Co Ltd
Priority date: 2022-11-21
Filing date: 2022-11-21
Publication date: 2023-03-07

Abstract

The embodiment of the invention discloses a data processing method, a data processing device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring original basic data based on the data pointer, and determining target screening data from the original basic data based on at least one index item; determining at least one aggregation identifier based on the data content of a target index item in the at least one index item; and updating historical storage data in the database based on at least one aggregation identifier and corresponding target screening data to obtain target data. The technical scheme of the embodiment of the invention solves the problems of poor system elasticity, poor maintainability and high time cost and labor cost caused by the fact that a large number of codes need to be changed to realize functions when the index service requirement is changed in the prior art, and realizes flexible loading of basic data according to the aggregation pointer, thereby achieving the technical effect of saving labor and time cost.

Description

Data processing method and device, electronic equipment and storage medium

Technical Field

Embodiments of the present invention relate to the field of computer technologies, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium.

Background

At present, after basic data corresponding to customer service consultation is obtained, an existing customer service monitoring system can determine aggregation dimensions according to service requirements, and then aggregate the aggregation dimensions into a single index by executing a scheduling task.

When the present invention is implemented based on the above-described embodiments, the inventors have found that the following problems occur:

all data index aggregation logics need to be developed according to requirements in a customized mode, dimension is solidified, and reusability is low. When the same index service requirement is changed, a large number of codes are required to be changed to realize the function, and the system has poor elasticity and maintainability. The lack of mechanism ensures flexible control of the task of the aggregated computation, which results in that any error and data change in one computation need to be calculated in full amount, and the problems of time and computation waste and high cost exist.

Disclosure of Invention

The invention provides a data processing method, a data processing device, electronic equipment and a storage medium, and aims to achieve the technical effect of convenience in data processing.

In a first aspect, an embodiment of the present invention provides a data processing method, where the method includes:

acquiring original basic data based on a data pointer, and determining target screening data from the original basic data based on at least one index item;

determining at least one aggregation identifier based on the data content of a target index item in the at least one index item;

and updating historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain target data.

Further, the obtaining the original basic data based on the data pointer includes: determining a current data pointer from a pointer record table based on the received timing task; and acquiring original basic data corresponding to the timing task from a basic data table based on the current data pointer.

Further, the determining target screening data from the original basic data based on at least one index item includes: acquiring a target aggregation key consistent with the task identifier of the timing task from an aggregation key table; the target aggregation comprises at least one index item, and the index item corresponds to a data dimension.

Further, the target screening data includes data content corresponding to at least one target index item, and the determining at least one aggregation identifier based on the data content of the target index item in the at least one index item includes: determining at least one target index item with fixed data content from the at least one index item; determining at least one first identifier based on the data content corresponding to the at least one target index item; classifying the at least one first identifier, and determining at least one aggregation identifier; wherein each aggregation identity corresponds to at least one first identity.

Further, the updating the historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain the target data includes: and aiming at each aggregation identifier, if the database comprises the current aggregation identifier, determining the target data based on the target screening data corresponding to the current aggregation identifier and the historical storage data which is stored in the database and corresponds to the current aggregation identifier.

Further, the updating the historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain the target data includes: and for each aggregation identifier, if the database does not include the current aggregation identifier, updating target screening data corresponding to the current aggregation identifier into the database as the target data.

Further, the method further comprises: and determining a data pointer to be updated based on the acquired original basic data, and updating the data pointer to be updated in the pointer record table so as to acquire corresponding original basic data based on the data pointer in the pointer record table when the timing task is received.

In a second aspect, an embodiment of the present invention further provides a data processing apparatus, where the apparatus includes:

the target screening data determining module is used for acquiring original basic data based on the data pointer and determining target screening data from the original basic data based on at least one index item;

the aggregation identifier determining module is used for determining at least one aggregation identifier based on the data content of a target index item in the at least one index item;

and the target data determining module is used for updating the historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain target data.

In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:

one or more processors;

a storage device for storing one or more programs,

when the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method according to any one of the embodiments of the present invention.

In a fourth aspect, the embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are used for executing the data processing method according to any one of the embodiments of the present invention.

According to the technical scheme of the embodiment of the invention, the original basic data is obtained based on the data pointer, the corresponding target screening data is determined from the original basic data according to at least one index item, then at least one aggregation identifier is determined according to the data content of the target index item in the at least one index item, and after the aggregation identifier is determined, historical stored data in the database is updated based on the at least one aggregation identifier and the corresponding target screening data to obtain the target data.

Drawings

In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It is clear that the described figures are only figures of a part of the embodiments of the invention to be described, not all figures, and that for a person skilled in the art, without inventive effort, other figures can also be derived from them.

Fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of index generation according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of a data processing method according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a data acquisition method according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.

Before the technical solution is introduced, an application scenario may be exemplarily described. When the existing data processing method processes data, data aggregation dimensions are aggregated into a single index based on a specific scheduling task after basic data stored in a system is obtained, for example, when indexes such as customer service satisfaction and the like need to be aggregated, corresponding program codes need to be developed and tested to be put into use, and the problems of long development period and high time cost exist. Further, when the aggregation dimension changes, corresponding program codes need to be re-developed, and the problems of high cost and long period exist.

Fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present invention, where the embodiment is applicable to a situation where at least one reference indicator is determined based on a configuration item to obtain data corresponding to the corresponding reference indicator, and the method may be executed by a data processing apparatus, where the apparatus may be implemented in a form of software and/or hardware, where the hardware may be an electronic device for processing data, and the electronic device may execute the data processing method according to the embodiment of the present disclosure to extract target screening data from basic data according to a task set by a user, and obtain corresponding target data according to an aggregation identifier.

It should be noted that the apparatus for executing the data processing method provided by the embodiment of the present disclosure may be integrated into application software supporting data processing, and the application software may be installed in an electronic device, and optionally, the electronic device may be a mobile terminal or a PC terminal, and the like. The application software may be any software that needs data processing, and specific application software thereof is not described herein any more, as long as data processing can be implemented. Or integrated in the corresponding page, and the user can realize data processing through the page integrated in the PC terminal.

As shown in fig. 1, the method includes:

s110, acquiring original basic data based on the data pointer, and determining target screening data from the original basic data based on at least one index item.

Wherein a data pointer may be understood as a location of data in a data table. The original basic data is based on all customer service data collected by a customer service monitoring system, and the customer service data comprises at least one of session data between users and customer services, comment data of the users to the customer services, evaluation star-level data of the users to the customers and satisfaction data. Meanwhile, the source of the original basic data also comprises at least one type, and the source can be taken as different data to be imported. Optionally, the data entry dimension may include at least one of a channel dimension, an entry dimension, a skill set dimension, a customer service dimension, and a time period dimension. The channel dimension can be understood as a channel of a data source, for example, data jumping to a specified page from different applications, pages, and the like can be used as the channel dimension; the entry dimension can be understood as an entry into the functional interface, for example, when a user needs to consult a customer service, the user can enter the customer service interface through different interfaces, the user can jump to the customer service interface through an interactive button in the my information page, the user can jump to the customer service interface through an interactive button in the after-sales service interface, and the like, and the manner of entering the customer service consultation interface is used as an entry channel; the customer service dimension can be the type of customer service, and the type can be an artificial customer service type and an intelligent customer service type. Meanwhile, the contents of different artificial customer service or intelligent customer service are different, for example, the artificial customer service a is mainly pre-sale information, and the artificial customer service B is mainly post-sale information. Illustratively, different numbers of customer service numbers correspond to different tasks, the customer service numbers 1-10 can be responsible for answering services, the customer service numbers 11-20 can be responsible for after-sales services, and the like, and corresponding intelligent customer service numbers can also have different responsible directions; the time period dimension may be a statistical time period, e.g., data is counted every half hour, etc., i.e., the time dimension mainly refers to the statistical time period. The index item is related to target data which needs to be obtained, for example, if the problem resolution of customer service is to be counted, a problem resolution index can be included in the index item. The target screening data may be understood as being based on statistical data determined from the raw base data according to the index terms.

Specifically, the data identifier corresponding to the current pointer data is n, and at this time, the data identified by the data identifier n may be considered as a starting point for acquiring the original basic data. Furthermore, the original basic data can be filtered according to at least one index item, and then the target screening data is determined. For example, when the goodness of customer service in a time period needs to be examined, taking ten to ten o 'clock in the morning as an example, data between ten and ten o' clock in the morning is extracted based on the pointer data and is used as original basic data, since the goodness of service index needs to be examined, the original basic data can be filtered based on the goodness of service index and the customer service index, and if the extracted original basic data is 1000 pieces of data, and the data obtained by filtering the extracted original basic data based on the goodness of service index and the customer service index is 100 pieces of data, the 100 pieces of data obtained by filtering the extracted original basic data is used as target screening data.

Illustratively, as shown in FIG. 2, the source of the large amount of base data (raw base data) may be divided into different statistical dimensions. Correspondingly, data stacking can be completed under the combined action of a plurality of conditions according to business requirements, and indexes are generated through logical operation. Logical operations may include summing, taking a maximum, taking a minimum, and so on. When different grouping logics are required to be executed according to different index service requirements, the same bottom layer code is used, and different grouping logic requirements can be realized only by configuring different aggregation keys.

On the basis of the above scheme, the acquiring original basic data based on the data pointer includes: determining a current data pointer from a pointer record table based on the received timing task; and acquiring original basic data corresponding to the timing task from a basic data table based on the current data pointer.

The timing task may be a task to be executed, which is preset by a user, and it can be understood that the user may set a plurality of timing tasks according to the requirement, different timing tasks may have the same or different content to be executed, the user may set the timing tasks according to the requirement, and the timing tasks may include information such as task identifiers, data obtaining step lengths, data obtaining intervals, and task duration. The pointer record table may be understood as a table for recording position information of a data pointer and a history data record. The basic data table may be a table for recording basic data, and it should be noted that the basic data table may be a log of the system, or a storage space for recording all data processed by the system.

Specifically, according to the timing task set by the user, the position to which the data pointer points at the moment is obtained from the pointer record table, and corresponding original basic data is obtained from the basic data table according to the current data pointer and the timing task set by the user.

For example, assuming that an operator needs to examine data served by customers at ten o ' clock to ten o ' clock in the morning, the operator may preset the duration of a task to be ten o ' clock to ten o ' clock in the morning, set the step length of the acquired data to be 100, and set the interval of the acquired data to be 3 minutes, when the time is ten o ' clock in the morning, pull data from the basic data in a manner of pulling 100 pieces of data each time every 3 minutes until an end condition is met, and as shown in fig. 4, according to a data id corresponding to a data pointer, load N pieces of data after the basic data table to serve as original basic data for the task statistics. The value of the number N of the obtained basic data can be flexibly changed according to the business requirement, and if the number of the remaining basic data is less than N, all the remaining basic data are loaded. Further, if the purpose of pulling the data is to obtain the goodness of customer service, the task identifier of the timing task may be set for goodness of customer service, and it may be known that 10 times of data need to be obtained according to the task duration and the data obtaining interval, and it may be known that the final pulled data is 1000 pieces according to the data obtaining step length and the data obtaining times, and the 1000 pieces of data obtained by pulling are used as the original basic data corresponding to the timing task executed this time.

According to the technical scheme provided by the embodiment of the disclosure, the current pointer data is determined from the pointer record table according to the received timing task, and the original basic data corresponding to the timing task is acquired, so that the correspondence between the acquired data and the task is ensured, and the data acquisition efficiency is improved.

On the basis of the above scheme, the determining target screening data from the original basic data based on at least one index item includes: and acquiring a target aggregation key consistent with the task identifier of the timing task from an aggregation key table.

The aggregation key table may be a table for storing preset aggregation keys. The task identifier may be an identifier for identifying a current timing task, and the task identifier may also be used to characterize what kind of index needs to be used to filter data. The target aggregation key comprises at least one index item, and the index item corresponds to the data dimension. The target aggregation key may be an identified consistent aggregation key obtained from the aggregation key table based on the task identification. It can be understood that different types of tasks need to obtain different target screening data, so that different types of tasks need corresponding different aggregation keys, and further, a user may need to simultaneously examine a plurality of task items when examining a service, so that the aggregation key may include a plurality of index items.

Specifically, according to a task identifier included in the timed task, a target aggregation key matched with the task identifier is obtained from the aggregation key table. For example, the aggregation key table may store the aggregation key and the task identifier correspondingly, that is, when the corresponding aggregation key needs to be searched according to the task identifier, the task identifier and the task identifier stored in the aggregation key table are matched one by one, and when the matching is successful, the corresponding aggregation key is determined to be the target aggregation key.

For example, with continued reference to fig. 3, the user may set corresponding parameters in the timed task according to the requirement before processing the data, the corresponding parameters may include "the satisfaction rate and the goodness of customer service in ten to ten and a half hours of the morning", and may set that the basic data is acquired every three minutes, and each time 100 pieces of data are queried. Based on the set timing task, the initial position of the data pointer and the dimension of the original basic data to be inquired can be obtained, and then the corresponding original basic data can be inquired from the basic data table according to the inquiry step length set by the user.

According to the technical scheme provided by the embodiment of the disclosure, the target aggregation key consistent with the task identifier of the timing task is obtained from the aggregation key table, so that a user can set the corresponding aggregation key according to requirements, and select the corresponding aggregation key according to the timing task, the selection efficiency of the aggregation key is improved, and the selection accuracy is ensured.

And S120, determining at least one aggregation identifier based on the data content of the target index item in the at least one index item.

The target index item may be an index item that needs to generate an aggregation identifier, and assuming that comprehensive data of customer services is desired to be considered, because different customer services exist, corresponding aggregation identifiers may be generated for different customer services, for example, a number of a client may be used as the target index item, and for "customer service 1", "customer service 2", "customer service 3", and the like, corresponding aggregation identifiers need to be generated, the number of the aggregation identifiers may be one, two, or more, for example, the number of the aggregation identifiers may correspond to the number of the customer services, and a method for generating the aggregation identifiers may be an identifier obtained by processing a customer service number through a hash algorithm, or a corresponding aggregation identifier obtained through a snowflake algorithm, and the like. The data content may be the basic data to be acquired in the target index item. The aggregate identity may be understood as identity information generated for the content of different target index items.

Specifically, at least one aggregation identifier is determined based on the data content in the target index item in the at least one index item. For example, when an operator needs to examine two index items, namely a good evaluation rate and a problem resolution rate of customer service, a corresponding aggregation identifier can be generated according to the good evaluation rate, the problem resolution rate and a corresponding customer service identifier. Further, in a specific application, an operator may select the number of customer services to be evaluated according to a requirement, for example, the number of the customer services "customer service 1" and "customer service 3" need to be evaluated, and then the corresponding aggregation identifier may be determined according to the data content corresponding to the number of the customer services "customer service 1" and "customer service 3".

On the basis of the foregoing technical solution, the target screening data includes data content corresponding to at least one target index item, and the determining at least one aggregation identifier based on the data content of the target index item in the at least one index item includes: determining at least one target index item with fixed data content from the at least one index item; determining at least one first identifier based on the data content corresponding to the at least one target index item; and processing the at least one first identifier in a classification mode, and determining at least one aggregation identifier.

Wherein the first identifier is determined according to the target index item. The target beacon item is determined according to the data content of each index item. For example, if the index item includes a customer service index item, the aggregate identifier, that is, the first identifier, may be determined according to specific information in the customer service index item. The number of aggregation identities may be one or more. It can be understood that, when the data of one customer service needs to be evaluated, each aggregate identifier corresponds to at least one first identifier, because the customer service may have multiple dimensions of original basic data, such as session data, evaluation data, and the like.

Specifically, the data content in which the index items are limited and variable and known can be determined according to the data content corresponding to each index item, based on which, such index items can be used as target index items, and correspondingly, the corresponding aggregation identifier can be generated according to the data content corresponding to the target index items. At this time, the number of the aggregation identifiers may be one or more, meanwhile, the aggregation identifiers may be the same or different, and in order to perform overall processing on the data, the data with the same aggregation identifier may be classified, that is, when the aggregation identifiers are the same, it is described that the corresponding data is data corresponding to one customer service or user. The classification process may be understood as associating data content that is the same for all aggregate identities with the same aggregate identity to obtain data that resembles a tree structure.

According to the technical scheme provided by the embodiment of the disclosure, the corresponding first identifier is determined according to the data content in the target index item, and the first identifier is classified, so that the correctness of data classification is ensured, and the efficiency of data classification is improved.

S130, updating historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain target data.

The historical storage data may be data stored after the historical timed task is executed. That is, the target filtering data stored in the database before the current time is history storage data. The target data can be understood as data which are obtained after the current timing task is executed and need to be stored in a database.

Specifically, the historical storage data in the database is updated according to the at least one determined aggregation identifier and the corresponding target screening data, so that the corresponding target data is obtained. For example, after the obtained target screening data is aggregated according to the aggregation identifier, corresponding index data is obtained, whether the index data corresponding to the aggregation identifier exists or not is searched in the database according to the aggregation identifier, and if the index data exists, the data is updated, so that the corresponding target data is obtained.

On the basis of the above scheme, the updating the historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain target data includes: and aiming at each aggregation identifier, if the database comprises the current aggregation identifier, determining the target data based on the target screening data corresponding to the current aggregation identifier and the historical storage data which is stored in the database and corresponds to the current aggregation identifier.

Specifically, it can be described with reference to fig. 3 that after the index data corresponding to the aggregation identifier is obtained through statistics, whether the historical storage data corresponding to the aggregation identifier exists in the database is queried according to the index data, and if the historical storage data corresponding to the aggregation identifier exists in the database, the index data determined according to the aggregation identifier at present is updated to the data stored in the database.

On the basis of the above scheme, the updating the historical storage data in the database based on the at least one aggregation identifier and the corresponding target screening data to obtain target data includes: and for each aggregation identifier, if the database does not include the current aggregation identifier, updating target screening data corresponding to the current aggregation identifier into the database as the target data.

Specifically, matching is performed in the database according to each aggregation identifier, if index data corresponding to the aggregation identifier does not exist in the database, new index data is created in the database based on the current aggregation identifier, and the index data obtained based on the current aggregation identifier and the target screening data is correspondingly stored in the newly created data item, so that the target data is obtained.

Exemplarily, as shown in fig. 3, in the stage of aggregating data, the entity classes of multidimensional different data are distinguished in the aggregation task by obtaining the aggregation key of this time. The underlying data is grouped according to multiple dimensions in the aggregated key. The dimensions generally include channels, portals, skill sets, customer services, time intervals, and the like. And traversing the grouped basic data, summing and summarizing the satisfaction degrees of different session evaluations, and generating the group of aggregation index data. And finally, comparing the data with the existing aggregation index data in the database to judge whether the index data exists. If not, saving the aggregation index data; and if so, accumulating the evaluation quantity and updating the aggregation index data.

On the basis of the scheme, the method further comprises the following steps: and determining a data pointer to be updated based on the acquired original basic data, and updating the data pointer to be updated in the pointer record table so as to acquire corresponding original basic data based on the data pointer in the pointer record table when the timing task is received.

The data pointer to be updated may be a position in the basic data table where the data pointer exists after the original basic data is obtained.

Specifically, after data are acquired in the basic data table according to the data acquisition step length set by the user, the data pointer after the data are acquired is updated in the pointer record table for recording the pointing position of the data pointer at the moment, and then when the data are captured next time, the original basic data can be correctly acquired according to the content recorded in the pointer record table. That is, when the timing task is received next time, the current pointer position may be obtained from the pointer record table according to the received timing task, and corresponding data may be called.

For example, as shown in fig. 3, in the pointer updating stage, after each time of generating the aggregation indicator data, according to a position of the last piece of basic data loaded by the current task in the basic data table, a position of the current last piece of basic data in the basic data table is recorded in the basic data table, and the position is used as a position of the current data pointer, so that data in the basic data table can be obtained when the task is executed next time. Furthermore, when the pointer record table records the position pointed by the data pointer, the current aggregation index can be correspondingly stored in the pointer record table, and further when the aggregation index data is found to be wrong, the original wrong data can be covered through index callback.

According to the technical scheme of the embodiment of the invention, the original basic data is obtained based on the data pointer, the corresponding target screening data is determined from the original basic data according to at least one index item, at least one aggregation identifier is further determined according to the data content of the target index item in the at least one index item, and after the aggregation identifier is determined, historical stored data in the database is updated based on the at least one aggregation identifier and the corresponding target screening data to obtain the target data.

Fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention, and as shown in fig. 5, the apparatus includes: a target screening data determination module 510, an aggregate identification determination module 520, and a target data determination module 530.

A target screening data determining module 510, configured to obtain original basic data based on the data pointer, and determine target screening data from the original basic data based on at least one index item;

an aggregate identity determination module 520, configured to determine at least one aggregate identity based on the data content of a target metric item of the at least one metric item;

a target data determining module 530, configured to update the historical stored data in the database based on the at least one aggregation identifier and the corresponding target screening data, to obtain target data.

On the basis of the above technical solution, the target screening data determining module further includes:

a data pointer determining unit, configured to determine a current data pointer from a pointer record table based on the received timing task;

and the original basic data determining unit is used for acquiring original basic data corresponding to the timing task from a basic data table based on the current data pointer.

On the basis of the technical scheme, the target screening data determining module comprises:

the aggregation key determining unit is used for acquiring a target aggregation key consistent with the task identifier of the timing task from an aggregation key table; the target aggregation comprises at least one index item, and the index item corresponds to a data dimension.

On the basis of the foregoing technical solution, the aggregation identifier determining module is specifically configured to: determining at least one target index item with fixed data content from the at least one index item; determining at least one first identifier based on the data content corresponding to the at least one target index item; classifying the at least one first identifier, and determining at least one aggregation identifier; wherein each aggregation identity corresponds to at least one first identity.

On the basis of the above technical solution, the target data determining module includes:

and the target data updating unit is used for determining the target data based on the target screening data corresponding to the current aggregation identifier and the historical storage data corresponding to the current aggregation identifier and stored in the database if the database comprises the current aggregation identifier.

On the basis of the above technical solution, the target data determining module further includes:

and the target data creating unit is used for updating target screening data corresponding to the current aggregation identifier into the database as the target data if the database does not comprise the current aggregation identifier aiming at each aggregation identifier.

On the basis of the above technical solution, the apparatus further includes:

and the data pointer updating module is used for determining a data pointer to be updated based on the acquired original basic data, updating the data pointer to be updated in the pointer record table, and acquiring corresponding original basic data based on the data pointer in the pointer record table when a timing task is received.

The data processing device provided by the embodiment of the invention can execute the data processing method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.

It should be noted that, the units and modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the invention.

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. FIG. 6 illustrates a block diagram of an exemplary electronic device 60 suitable for use in implementing embodiments of the present invention. The electronic device 60 shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.

As shown in fig. 6, the electronic device 60 is in the form of a general purpose computing device. The components of the electronic device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 that couples various system components including the system memory 602 and the processing unit 601.

Bus 603 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Electronic device 60 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 60 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 602 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 604 and/or cache memory 605. The electronic device 60 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 606 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 603 by one or more data media interfaces. Memory 602 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

A program/utility 608 having a set (at least one) of program modules 607 may be stored, for example, in memory 602, such program modules 607 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. The program modules 607 generally perform the functions and/or methods of the described embodiments of the invention.

Electronic device 60 may also communicate with one or more external devices 609 (e.g., keyboard, pointing device, display 610, etc.), with one or more devices that enable a user to interact with electronic device 60, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 60 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 611. Also, the electronic device 60 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 612. As shown, the network adapter 612 communicates with the other modules of the electronic device 60 via the bus 603. It should be appreciated that although not shown in FIG. 6, other hardware and/or software modules may be used in conjunction with electronic device 60, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

The processing unit 601 executes various functional applications and data processing, for example, implementing a data processing method provided by an embodiment of the present invention, by running a program stored in the system memory 602.

Embodiments of the present invention also provide a storage medium containing computer-executable instructions for performing a data processing method when executed by a computer processor.

The method comprises the following steps:

Computer storage media for embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having 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 portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It is to be noted that the foregoing description is only exemplary of the invention and that the principles of the technology may be employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in some detail by the above embodiments, the invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the invention, and the scope of the invention is determined by the scope of the appended claims.

Claims

1. A data processing method, comprising:

2. The method of claim 1, wherein the obtaining the raw base data based on the data pointer comprises:

determining a current data pointer from a pointer record table based on the received timing task;

and acquiring original basic data corresponding to the timing task from a basic data table based on the current data pointer.

3. The method of claim 2, wherein determining target screening data from the raw base data based on at least one indicator term comprises:

acquiring a target aggregation key consistent with the task identifier of the timing task from an aggregation key table;

the target aggregation comprises at least one index item, and the index item corresponds to a data dimension.

4. The method of claim 1, wherein the target screening data includes data content corresponding to at least one target metric item, and the determining at least one aggregate identifier based on the data content of the target metric item of the at least one metric item includes:

determining at least one target index item with fixed data content from the at least one index item;

determining at least one first identifier based on the data content corresponding to the at least one target index item;

classifying the at least one first identifier, and determining at least one aggregation identifier;

wherein each aggregation identifier corresponds to at least one first identifier.

5. The method of claim 1, wherein updating the historically stored data in the database based on the at least one aggregate identifier and corresponding target screening data to obtain target data comprises:

and aiming at each aggregation identifier, if the database comprises the current aggregation identifier, determining the target data based on the target screening data corresponding to the current aggregation identifier and the historical storage data which is stored in the database and corresponds to the current aggregation identifier.

6. The method of claim 1, wherein updating the historically stored data in the database based on the at least one aggregate identifier and corresponding target screening data to obtain target data comprises:

and for each aggregation identifier, if the database does not include the current aggregation identifier, updating target screening data corresponding to the current aggregation identifier into the database as the target data.

7. The method of claim 1, further comprising:

and determining a data pointer to be updated based on the acquired original basic data, and updating the data pointer to be updated in the pointer record table so as to acquire corresponding original basic data based on the data pointer in the pointer record table when a timing task is received.

8. A data processing apparatus, comprising:

9. An electronic device, characterized in that the electronic device comprises:

one or more processors;

a storage device to store one or more programs,

when executed by the one or more processors, cause the one or more processors to implement a data processing method as claimed in any one of claims 1-7.

10. A storage medium containing computer-executable instructions for performing the data processing method of any one of claims 1-7 when executed by a computer processor.