CN115145533A

CN115145533A - Data processing method and device, electronic equipment and storage medium

Info

Publication number: CN115145533A
Application number: CN202210699214.7A
Authority: CN
Inventors: 李晓彤
Original assignee: Beijing Dajia Internet Information Technology Co Ltd
Current assignee: Beijing Dajia Internet Information Technology Co Ltd
Priority date: 2022-06-20
Filing date: 2022-06-20
Publication date: 2022-10-04

Abstract

Disclosed are a data processing method, an apparatus, an electronic device and a storage medium, including: acquiring data to be processed; the data to be processed comprises account attribute data and account number corresponding to the account attribute data; sequencing the account attribute data to obtain an account attribute sequence of the account attribute data; determining a ranking result of the account attribute data according to the arrangement sequence of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data and a preset ranking strategy; and taking the ranking result of the account attribute data as the ranking result of the account corresponding to the account attribute data. By adopting the method, the processing efficiency of the ranking result of the account can be improved.

Description

Data processing method and device, electronic equipment and storage medium

Technical Field

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

Background

As the ordering requirements in big data scenarios become more prevalent, more and more services are required to provide ranking information for accounts.

The current account sorting methods are various, such as: adopting a skip list algorithm, a bucket counting method or a hive (a data warehouse tool based on Hadoop (a distributed system basic framework)) dividing and sorting method and the like. When the methods are used for ranking, the accounts need to be ranked one by one to obtain the ranking order of each account.

However, as the number of accounts increases, the above-mentioned method of ranking accounts one by one increases the computation amount and computation complexity of the server, resulting in low ranking efficiency.

Disclosure of Invention

The disclosure provides a data processing method and device, an electronic device and a storage medium, which are used for at least solving the problem of low account ranking efficiency in the related art. The technical scheme of the disclosure is as follows:

according to a first aspect of the embodiments of the present disclosure, there is provided a data processing method, including:

acquiring data to be processed; the data to be processed comprises at least one account attribute data and the account number corresponding to each account attribute data;

sequencing the account attribute data to obtain the account attribute sequence;

for each account attribute data, determining a ranking result of the account attribute data according to the arrangement sequence of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data and a preset ranking strategy;

and taking the ranking result of the account attribute data as the ranking result of at least one account corresponding to the account attribute data.

In one embodiment, the determining a ranking result of the account attribute data according to the arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy includes:

for first account attribute data in the account attribute sequence, determining the account number corresponding to the first account attribute data as a ranking result corresponding to the first account attribute data;

and for each other account attribute data except the first account attribute data in the account attribute sequence, determining the ranking result of the other current account attribute data according to the account quantity corresponding to each other account attribute data and the ranking result corresponding to the account attribute data which is one of the other current account attribute data in the account attribute sequence and is previous to the other current account attribute data.

In one embodiment, after determining the ranking result of the account attribute data according to the ranking order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy, the method further includes:

obtaining a ranking query table according to each account attribute data and the corresponding ranking result;

and responding to a ranking query request aiming at a target account, and determining a ranking result of the target account in a ranking query table according to a preset ranking table query strategy and current account attribute data corresponding to the target account.

In one embodiment, the determining, in response to a ranking query request for a target account, a ranking result of the target account in the ranking query table according to a preset ranking table query policy and current account attribute data corresponding to the target account includes:

responding to a ranking query request aiming at a target account, and querying whether current account attribute data of the target account exists in the ranking query table;

if the account attribute data do not exist, filling new account attribute data in the data interval of any adjacent account attribute data in the ranking query table; the new account attribute data is obtained by taking two adjacent account attribute data as limiting values and taking values in the data interval according to the preset numerical value interval;

determining a ranking result corresponding to the smaller account attribute data in the two account attribute data as a ranking result corresponding to the new account attribute data to obtain an updated ranking query table;

and determining the ranking result of the target account according to the current account attribute data corresponding to the target account in the updated ranking query table.

In one embodiment, after the ranking result of the account attribute data is used as the ranking result of the account corresponding to the account attribute data, the method further includes:

acquiring a preset target ranking threshold, and determining an attribute data threshold according to the target ranking threshold and the ranking result of the account attribute data;

responding to a grade query request aiming at a target account, and determining the grade corresponding to the target account according to the current account attribute data of the target account and the attribute data threshold.

In one embodiment, the determining an attribute data threshold according to the target ranking threshold and the ranking result of the account attribute data includes:

according to the target ranking threshold, whether a target ranking result identical to the target ranking threshold exists in the ranking results of the account attribute data is inquired;

if a target ranking result identical to the target ranking threshold exists, taking account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold;

if the target ranking result which is the same as the target ranking threshold does not exist, determining the minimum ranking result as the target ranking result in all the ranking results which are larger than the target ranking threshold, and adding a fixed threshold to account attribute data corresponding to the target ranking result to be used as an attribute data threshold corresponding to the target ranking threshold.

In one embodiment, the acquiring the data to be processed includes:

acquiring account attribute data of all accounts, and performing aggregation processing on the account attribute data of all accounts to obtain account groups of the accounts containing the same account attribute data;

and counting the account number contained in each account group, and associating the account attribute data of each account group with the account number corresponding to the account attribute data to obtain the to-be-processed data.

According to a second aspect of the embodiments of the present disclosure, there is provided a data processing apparatus including:

an acquisition unit configured to perform acquisition of data to be processed; the data to be processed comprises at least one account attribute data and the account number corresponding to each account attribute data;

the sorting unit is configured to perform sorting on each account attribute data to obtain an account attribute sequence of the account attribute data;

the determining unit is configured to execute, aiming at each piece of account attribute data, determining a ranking result of the account attribute data according to the arrangement sequence of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data and a preset ranking strategy;

and the matching unit is configured to execute the ranking result of the account attribute data as the ranking result of at least one account corresponding to the account attribute data.

In one embodiment, the determining unit further comprises:

the first determining subunit is configured to determine, for a first account attribute data in the account attribute sequence, an account number corresponding to the first account attribute data as a ranking result corresponding to the first account attribute data;

a second determining subunit, configured to execute, for each piece of other account attribute data in the account attribute sequence except for the first account attribute data, determining, according to the account number corresponding to each piece of other account attribute data and the ranking result corresponding to the account attribute data that is previous to the other account attribute data in the account attribute sequence, the ranking result of the other account attribute data that is present.

In one embodiment, the data processing apparatus further comprises:

the construction unit is configured to execute ranking according to each account attribute data and the corresponding ranking result to obtain a ranking query table;

the query unit is configured to execute a ranking query request for a target account, and determine a ranking result of the target account in the ranking query table according to a preset ranking table query strategy and current account attribute data corresponding to the target account.

In one embodiment, the query unit further comprises:

a first query subunit configured to perform a query to determine whether current account attribute data of a target account exists in the ranking query table in response to a ranking query request for the target account;

a filling subunit, configured to perform filling new account attribute data in a data interval of any adjacent account attribute data in the ranking lookup table in the absence; the new account attribute data is obtained by taking two adjacent account attribute data as limiting values and taking values in the data interval according to the preset numerical value interval;

a third determining subunit, configured to perform determining, as a ranking result corresponding to the new account attribute data, a ranking result corresponding to the smaller of the two account attribute data, to obtain an updated ranking lookup table;

and the fourth determining subunit is configured to execute the step of determining the ranking result of the target account according to the current account attribute data corresponding to the target account in the updated ranking lookup table.

In one embodiment, the data processing apparatus further comprises:

the acquisition determining unit is configured to execute acquisition of a preset target ranking threshold value and determine an attribute data threshold value according to the target ranking threshold value and the ranking result of the account attribute data;

the grade determining unit is configured to execute a grade query request aiming at a target account, and determine a grade corresponding to the target account according to the current account attribute data of the target account and the attribute data threshold.

In one embodiment, the acquisition determining unit further includes:

the query judging subunit is configured to execute to query whether a target ranking result identical to the target ranking threshold exists in the ranking results of the account attribute data according to the target ranking threshold;

a fifth determining subunit, configured to execute, if there is a target ranking result that is the same as the target ranking threshold, taking account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold;

a sixth determining subunit, configured to determine, if there is no target ranking result that is the same as the target ranking threshold, a minimum ranking result as a target ranking result among all ranking results that are greater than the target ranking threshold, and add a fixed threshold to account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold.

In one embodiment, the obtaining unit includes:

the acquiring subunit is configured to execute acquiring account attribute data of all accounts, and aggregate the account attribute data of all accounts to obtain account groups of accounts containing the same account attribute data;

and the counting subunit is configured to perform counting on the account number included in each account group, and associate the account attribute data of each account group with the account number corresponding to the account attribute data to obtain the to-be-processed data.

According to a third aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the data processing method as described in any of the embodiments of the first aspect above.

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium comprising:

the instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method of any of the embodiments of the first aspect.

According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising: .

The instructions, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method of any of the embodiments of the first aspect.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

acquiring data to be processed; the data to be processed comprises at least one account attribute data and the account number corresponding to each account attribute data; sequencing the account attribute data to obtain the account attribute sequence; for each account attribute data, determining a ranking result of the account attribute data according to the arrangement sequence of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data and a preset ranking strategy; and taking the ranking result of the account attribute data as the ranking result of at least one account corresponding to the account attribute data. By adopting the method, the ranking result of the account attribute data is determined according to the account number, and then the ranking result of the account attribute data is used as the ranking result of the corresponding account, so that the data processing amount in the account ranking process is reduced, and the account ranking efficiency is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.

FIG. 1 is a flow diagram illustrating a method of data processing in accordance with an exemplary embodiment;

FIG. 2 is a flowchart illustrating one step of determining account attribute data ranking results in accordance with an exemplary embodiment;

FIG. 3 is a flowchart illustrating a step of determining a target account ranking result in accordance with an exemplary embodiment;

FIG. 4 is a flowchart illustrating a target account query ranking results step in accordance with an exemplary embodiment;

FIG. 5 is a flowchart illustrating a target account query ranking step in accordance with an exemplary embodiment;

FIG. 6 is a flowchart illustrating a step of determining a target account correspondence level in accordance with an exemplary embodiment;

FIG. 7 is a flowchart illustrating a step of obtaining data to be processed in accordance with an exemplary embodiment;

FIG. 8 is a block diagram illustrating a data processing apparatus in accordance with an exemplary embodiment;

FIG. 9 is a block diagram illustrating an electronic device in accordance with an example embodiment.

Detailed Description

In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

It should be further noted that the account information (including but not limited to account device information, account personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) referred to in the present disclosure are information and data that are authorized by the account or sufficiently authorized by the parties.

Fig. 1 is a flowchart illustrating a data processing method according to an exemplary embodiment, and as shown in fig. 1, the data processing method may be applied to a server or a terminal, but the embodiment of the present disclosure is not limited thereto, and in the embodiment of the present disclosure, the server or the terminal are generally referred to as a computer device for general description, and then the data processing method includes the following steps.

In step S110, data to be processed is acquired.

The data to be processed comprises at least one account attribute data and the account number corresponding to each account attribute data.

In implementation, when all accounts in the system need to be ranked, the computer device obtains to-be-processed data corresponding to all accounts. The data to be processed includes attribute values (i.e., account attribute data) corresponding to account attributes of all accounts and the account number corresponding to each account attribute data. The account attribute in the data to be processed may be an evaluation index for evaluating an account, for example, an account score, and the specific content of the account attribute is not limited in the embodiment of the present disclosure. The data to be processed may be stored in a local cache of the computer device, so that the computer device may directly obtain the data or store the data in a database.

For example, as shown in table 1, taking account attributes as account scores for example, among the data to be processed, the account score value (i.e., attribute value): 1000, corresponding account number 90 (person), account credit value: 900, corresponding account number 10 (person), account credit value: 800, corresponding account number 40 (person), account credit value: 650, corresponding account number 20 (people).

TABLE 1

Account attribute data (Account credit value)	Account quantity (human)
		1000	90
900	10
		800	40
650	20

Optionally, the data processing process (that is, including the step of obtaining the data to be processed) in the embodiment of the present disclosure may be a cyclic process, that is, according to a preset time interval, the computer device obtains the data to be processed at regular time, and processes the data to be processed in each time interval, so as to obtain a real-time ranking result of the account.

In step S120, the account attribute data are sorted to obtain an account attribute sequence.

In implementation, because a plurality of accounts have the same account attribute data, that is, there is a many-to-one correspondence between the accounts and the account attribute data, the ranking process for the accounts can be converted into the ranking process for the account attribute data, so that the data processing amount in the ranking process is reduced, and the ranking efficiency is improved. After the computer device obtains the data to be processed, different account attribute data in the data to be processed can be sorted from large to small to obtain an account attribute sequence containing different account attribute data.

Specifically, in the process of sorting different account attribute data, the computer device may sort the account attribute data in order of big to small by using a group by () method, so as to obtain an account attribute sequence of the sorted account attribute data. Taking table 1 as an example, the account attribute sequence of the account attribute data sorting shown in table 1 is { account attribute data 1000, account attribute data 900, account attribute number, 800, account attribute number 650}.

In step S130, for each account attribute data, a ranking result of the account attribute data is determined according to the arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy.

In implementation, each account attribute data is sequentially processed according to the arrangement sequence of the account attribute data in the account attribute sequence from large to small, that is, the ranking result of the current account attribute data is determined according to the account number corresponding to the account attribute data and a preset ranking strategy. Further, the computer device stores the ranking result of the account attribute data into TreeMap.

The ranking results corresponding to the accounts are the same aiming at the same account attribute data corresponding to the accounts, and the ranking result account attribute sequence formed by the ranking results corresponding to the account attribute data is not a continuous data account attribute sequence. For example, the ranking result account attribute sequence may be (units: name): 90. 100, 120, 160, 175 … …, i.e., the ranking results are not a continuous sequence of sequential account attributes.

In step S140, the ranking result of the account attribute data is used as the ranking result of at least one account corresponding to the account attribute data.

In an implementation, the computer device may map the ranked results of the account attribute data to the ranked results of the accounts based on a correspondence between the account attribute data and the accounts. Then, the computer device can push the ranking results of the accounts to the corresponding account display pages respectively, so that each account can clearly determine the ranking condition of the account in all accounts.

Specifically, for each account attribute data, the rank of each account corresponding to the account attribute data is determined as the rank of the account attribute data. For example, after the computer device executes the processing procedure of step S130, the computer device determines that the account attribute data and the ranking result of the account attribute data are shown in table 2 below:

TABLE 2

Account attribute data	Account number (human)	Ranking results (names)
			1000	90	90
900	10	100
			800	40	140
650	60	160

As can be seen from table 2, since the ranking results of the account attribute data are determined based on the number of accounts, the ranking results of the accounts with the same account attribute data are the same, and the ranking results of the accounts are not a continuous account attribute sequence. For example, if the account attribute data corresponding to a certain account is 900, the ranking result corresponding to the account is 100. If the account attribute data corresponding to a certain account is 650, the ranking result corresponding to the account is 160, and thus, the ranking results of all accounts can be determined according to the account attribute data corresponding to the accounts.

Optionally, after the account ranking result is obtained by each data processing, the ranking results of all accounts may be added with a version identifier (e.g., version number) and sealed, so as to query the historical ranking results of the past ranking process based on the version identifier.

In the data processing method, the computer equipment acquires data to be processed. The data to be processed comprises account attribute data and account quantity corresponding to the account attribute data. Then, the computer device sorts the account attribute data in the data to be processed to obtain an account attribute sequence of the account attribute data. Furthermore, the computer device determines a ranking result of the account attribute data according to the arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking strategy. And finally, the computer equipment takes the ranking result of the account attribute data as the ranking result of each account. By adopting the method, the ranking result of the account attribute data is determined based on the account number, and then the ranking result of the account attribute data is used as the ranking result of the corresponding account, so that the data processing amount in the data processing process is reduced, and the account ranking efficiency is improved.

In an exemplary embodiment, as shown in fig. 2, in step S130, determining the ranking result of the account attribute data according to the arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy may specifically be implemented by the following steps:

in step S131, for the first account attribute data in the account attribute sequence, the account number corresponding to the first account attribute data is determined as the ranking result corresponding to the first account attribute data.

In implementation, the data values of the account attribute data in the account attribute sequence of the account attribute data are arranged in descending order. The computer device may determine the ranking results corresponding to each account attribute data in sequence. Wherein, different ranking strategies can be adopted for account attribute data with different sorting orders. Therefore, the computer device may determine a ranking policy corresponding to the account attribute data according to the sorting order of the account attribute data, so as to determine a ranking result of the account attribute data based on the ranking policy.

Specifically, for the first account attribute data in the account attribute sequence (i.e., the largest account attribute data in the account attribute sequence), the computer device may determine the account number corresponding to the first account attribute data as the ranking result corresponding to the first account attribute data. For example, in the account attribute sequence of the account attribute data, 1000 is the first account attribute data (i.e. the largest account attribute data) in the account attribute sequence, the number of accounts corresponding to the account attribute data 1000 is 90, and the ranking result of the account attribute data 1000 is 90. For another example, 1010 is the first account attribute data (i.e. the largest account attribute data) in the account attribute sequence, and if the account attribute data corresponding to the account attribute data 1010 is 60 persons, the ranking result of the account attribute data 1010 is 60 names.

In step S132, for each piece of other account attribute data in the account attribute sequence except for the first account attribute data, the ranking result of the current other account attribute data is determined according to the account number corresponding to each piece of other account attribute data and the ranking result corresponding to the previous account attribute data of the current other account attribute data in the account attribute sequence.

In an implementation, for other account attribute data in the account attribute sequence except for the first account attribute data, the computer device may sequentially calculate a sum of the account quantity corresponding to each other account attribute data and the ranking result corresponding to the previous account attribute data, and determine the sum as the ranking result of the other account attribute data. The last account attribute data is the account attribute data that is ranked one bit before the other account attribute data in the account attribute sequence.

For example, the account attribute data 900 is other account attribute data except the first account attribute data, the account number corresponding to the account attribute data 900 is 10 persons, and the ranking result corresponding to the previous account attribute data 1000 is 90, then the computer device calculates the sum of the account number corresponding to the current account attribute data 900 and the ranking result of the previous account attribute data to be 10+90=100. The computer device then determines the calculated sum value of 100 as the ranking result, i.e., 100, of the account attribute data 900.

In this embodiment, when the computer device ranks the account attribute data, the ranking result of the account attribute data is determined based on the number of accounts corresponding to the account attribute data and the arrangement order of the account attribute data in the account attribute sequence, so that processing logic for ranking the account attribute data one by one is simplified, data processing amount is reduced, and data processing efficiency is improved.

In an exemplary embodiment, as shown in fig. 3, in addition to relying on the ranking results of the accounts periodically pushed by the computer device, each account may also actively query the current ranking results during the execution of the service, and therefore, the data processing method further includes:

in step S310, a ranking look-up table is obtained according to the account attribute data and the corresponding ranking result.

In implementation, the computer device determines the ranking result corresponding to each account attribute data, and may establish a corresponding relationship between the account attribute data and the ranking result to obtain a ranking lookup table (also referred to as userRankMap). Specifically, the ranking look-up table is shown in table 3 below:

TABLE 3

Account attribute data	Ranking results (names)
		1000	90
900	100
		…	…

In the ranking look-up table (i.e., table 3), the obtained account attribute data of any target account corresponds to a ranking result, and the data values of the ranking results are not continuous, for example, there are no 99 names.

In step S320, in response to the ranking query request for the target account, a ranking result of the target account is determined in the ranking query table according to a preset ranking table query policy and current account attribute data corresponding to the target account.

In an implementation, a computer device receives a ranking query request from a target account, and obtains current account attribute data of the target account according to the ranking query request. And the computer equipment responds to the ranking query request, and determines the ranking result of the target account in the ranking query table according to a preset ranking table query strategy and the current account attribute data of the target account and the time complexity of O (1).

In the embodiment, the target account actively queries the ranking result by initiating the ranking query request, and further, the computer device constructs the ranking query table based on the determined ranking result of the account attribute data, so that based on the ranking query table, the target account can more quickly query the ranking result of the current account attribute data, the ranking query complexity is reduced, and the timeliness of the ranking result query is enhanced.

Since the target account is in a certain data processing period (i.e., after the last ranking result is pushed, in a time interval before the next ranking result is pushed) during the query, in this data processing period, the current account attribute data of the target account may have changed compared with the account attribute data when the ranking query table is constructed, and therefore, in the current ranking query table, the query of the ranking result is performed based on the changed account attribute data, and a situation that the current account attribute data cannot be queried in the current ranking query table (i.e., the current ranking query table does not contain the changed account attribute data) may occur, so that the preset ranking table query policy includes a filling method of the query table, so that the ranking query table after being filled and updated may include the account attribute data after the account is updated. Correspondingly, as shown in fig. 4, in step S320, according to the preset ranking table query policy and the current account attribute data corresponding to the target account, determining the ranking result of the target account in the ranking query table may specifically be implemented by the following steps:

in step S321, in response to the ranking query request for the target account, it is queried whether current account attribute data of the target account exists in the ranking query table.

In an implementation, a computer device queries, in response to a ranking query request for a target account, whether current account attribute data for the target account exists in a ranking query table.

In step S322, if the data section does not exist, new account attribute data is filled in the data section of any adjacent account attribute data in the ranking lookup table.

And the new account attribute data is obtained by taking the values of the two adjacent account attribute data as limit values and in a data interval according to a preset numerical value interval.

In implementation, in a case that the account attribute data does not exist, the computer device fills new account attribute data in a data interval formed by any two adjacent account attribute data in the ranking query table according to a preset ranking table query strategy and a preset data value interval. For example, if the preset data value interval is 1, and two adjacent account attribute data in the ranking lookup table are 1000 and 900, respectively, the data interval formed by the two account attribute data is filled into the data interval of the computer device according to the data value interval of 1, and then the data interval becomes [1000, 999, 998, 997, 996, 995, 994, …, 901, 900]. The new account attribute data populated in this data interval is 999, 998, 997 … 901.

The preset data value interval may be preset based on the distribution characteristics of the current account attribute data, and the embodiment of the present disclosure is not limited.

In step S323, the ranking result corresponding to the smaller account attribute data of the two account attribute data is determined as the ranking result corresponding to the new account attribute data, and an updated ranking lookup table is obtained.

In implementation, the computer device determines the ranking result corresponding to the smaller account attribute data in the boundary values of the data intervals corresponding to every two account attribute data as the ranking result corresponding to the new account attribute data, and then obtains the updated ranking query table. Specifically, for example, in the filled data interval [1000, 999, 998, 997, 996, 995, 994, … 901, 900], 999, 998, 997 …, and the like are all new account attribute data, and the ranking result of the new account attribute data is determined as the ranking result corresponding to the account attribute data 900, that is, the ranking results corresponding to the account attribute data 999 to 900 are all 100, so that the updated ranking lookup table is obtained. As shown in table 4 below:

TABLE 4

The part of the ranking query table shown in table 4, which is only filled in the data interval of [1000,900], is filled in the data interval of the other pairwise spaced account attribute data in the ranking query table according to the preset numerical interval, and the ranking result of the new account attribute data is determined, which is not described in detail in the embodiment of the present disclosure. And after the data interval of the original account attribute data in all the ranking query tables is filled, the computer equipment obtains the updated complete ranking query table.

In step S324, in the updated ranking lookup table, a ranking result of the target account is determined according to the current account attribute data corresponding to the target account.

In implementation, the computer device determines the ranking result of the target account according to the current account attribute data corresponding to the target account in the updated ranking lookup table. For example, if the current account attribute data of the target account corresponds to 950, the computer device queries the updated ranking look-up table to obtain 100 ranking results of the target account based on the current account attribute data 950.

The ranking result obtained by initiating the ranking query request by the target account can also be regarded as the current temporary ranking result of the target account, and the temporary ranking result queried in the periodic data processing process can be further refreshed and replaced by the ranking result of the account pushed next time.

In the embodiment, the ranking result query method for filling the ranking query table is provided for the condition that the current account attribute data of the target account does not exist in the ranking query table.

In an exemplary embodiment, as shown in fig. 5, when ranking the accounts, besides obtaining the ranking result of each account, the data processing method may also determine the rank of each account based on the ranking condition of all accounts, and further includes:

in step S510, a preset target ranking threshold is obtained, and an attribute data threshold is determined according to the target ranking threshold and the ranking result of the account attribute data.

In an implementation, a computer device obtains a preset target ranking threshold. The target ranking threshold can be set according to actual requirements and is used for dividing the corresponding grades of the accounts. Specifically, under the condition that the account attribute data of each account keeps changing dynamically, the target ranking threshold value may be fixed and unchanged, so even if the account attribute data corresponding to the target ranking threshold value changes continuously, the ranking distribution of the rank determined by the target ranking threshold value with respect to the whole accounts does not change, and the principle that the account rank ratio is unchanged is met. Therefore, the computer device determines the attribute data threshold corresponding to the target ranking threshold by presetting the target ranking threshold, and then divides the grades of all accounts under the current account attribute data based on the attribute data threshold. For example, the target ranking threshold is 100, as shown in table 1, the computer device determines, from the correspondence between the account attribute data and the ranking result in table 1, that the ranking result is equal to 100, that is, the account attribute data 900, and determines the account attribute data 900 as the attribute data threshold.

Optionally, the number of the target ranking threshold may be one or more, the specific number may be set according to actual grading requirements, and the number of the target ranking threshold is not limited in the embodiment of the present disclosure. For the case that the number of the target ranking thresholds is multiple, the computer device may determine the attribute data threshold corresponding to each target ranking threshold respectively through step S510, so as to rank the accounts subsequently.

In step S520, in response to the level query request for the target account, a level corresponding to the target account is determined according to the current account attribute data of the target account and the attribute data threshold.

In an implementation, the computer device may obtain current account attribute data for the target account in response to a rating query request for the target account, and then compare the current account attribute data to an attribute data threshold to determine a rating for the target account. For example, the current account attribute data of the target account is 950, and the computer device divides all account attribute data into three levels according to the determined attribute data threshold values (900 and 1001, respectively) corresponding to the levels, and divides the account attribute data into "LAST" levels when the account attribute data is less than 900; greater than or equal to 900, less than 1000 are classified as "SECOND" class; and 1001 or more are classified as "TOP" levels. Further, the computer device compares the current account attribute data 950 with the attribute data threshold corresponding to each level, and determines that the current level of the target account is the "SECOND" level.

In this embodiment, a method for querying a ranking level is provided, by which a query service of a ranking level is provided for a target account.

In an exemplary embodiment, as shown in fig. 6, in step S520, determining the level corresponding to the target account according to the current account attribute data of the target account and the attribute data threshold may specifically be implemented by the following steps:

in step S521, it is queried whether there is a target ranking result identical to the target ranking threshold in the ranking results of the account attribute data according to the target ranking threshold.

In practice, due to the disclosed embodiments, there is a discontinuity between the ranking results of the account attribute data. Therefore, a situation that the target ranking threshold value cannot be directly queried in each ranking result may occur, so when the computer device obtains the preset target ranking threshold value, it may first query whether a target ranking result that is the same as the target ranking threshold value exists in the ranking results of the account attribute data according to the target ranking threshold value.

For example, if a predetermined target ranking threshold is 100, the ranking results of the account attribute data shown in table 1 above have the same target ranking result as the target ranking threshold. If a predetermined target ranking threshold is 10, the ranking results of the account attribute data shown in table 1 do not have the same target ranking result as the target ranking threshold. Thus, the computer device may perform two different level determination strategies for the two different situations, respectively.

In step S522, if there is a target ranking result that is the same as the target ranking threshold, the account attribute data corresponding to the target ranking result is used as the attribute data threshold corresponding to the target ranking threshold.

In implementation, if a target ranking result identical to the target ranking threshold exists, the computer device directly determines account attribute data corresponding to the target ranking result. Furthermore, the computer device takes the account attribute data corresponding to the target ranking result as the attribute data threshold of the rank less than or equal to the target ranking threshold. For example, for a preset target ranking threshold of 100 in step S610, the same target ranking result as the target ranking threshold exists in the ranking results of the account attribute data shown in table 1. The account attribute data 900 corresponding to the target ranking result, the computer device takes 900 as the attribute data threshold of the rank of 100 (target ranking threshold) or less.

In step S523, if there is no target ranking result that is the same as the target ranking threshold, the minimum ranking result is determined as the target ranking result among all ranking results that are greater than the target ranking threshold, and a fixed threshold is added to account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold.

In implementation, if there is no target ranking result that is the same as the target ranking threshold, the computer device may first determine, as the target ranking result, a ranking result that is greater than the target ranking threshold from among the ranking results corresponding to all account attribute data, and then determine, as the target ranking result, a minimum ranking result, for example, when a certain preset target ranking threshold is 10, there is no target ranking result that is the same as the target ranking threshold from among the ranking results of the account attribute data shown in table 3, and each ranking result shown in table 3 is greater than the preset target ranking threshold, the computer device determines, as the target ranking result, the minimum ranking result, that is, 90, from among all ranking results that are greater than 10. Then, the computer device adds a fixed threshold to account attribute data corresponding to the target ranking result (90) as an attribute data threshold of the rank less than or equal to the target ranking threshold. For example, after determining that 90 names are the target ranking results, adding a fixed threshold (for example, the fixed threshold is 1) to account attribute data 1000 corresponding to 90 names (target ranking results), and the sum of the two values is equal to 1001, the computer device takes the 1001 as the attribute data threshold of the level at which the target ranking threshold (10 names) is less than or equal to.

In an exemplary embodiment, as shown in fig. 7, in step S130, the specific process of acquiring the data to be processed may be implemented by the following steps:

in step S710, account attribute data of all accounts are acquired, and the account attribute data of all accounts are aggregated to obtain an account group including accounts with the same account attribute data.

In implementation, the computer device acquires the account attribute data of all the accounts in a multi-thread scanning manner, and performs aggregation processing on the account attribute data of all the accounts so as to divide the accounts with the same account attribute data into the same account group. For example, if the account attribute data of each of the multiple accounts is 1000, the multiple accounts are determined to be one account group, and if the account attribute data of the multiple accounts is 900, the multiple accounts are determined to be another account group.

Optionally, the data applying period is preset by the computer device, and further, the computer device may periodically obtain the account attribute data of all accounts based on the applying period.

In step S720, the account number included in each account group is counted, and the account attribute data of each account group and the account number corresponding to the account attribute data are used as the data to be processed.

In an implementation, the computer device counts the number of accounts contained in each account group. For example, the account number is 90 in the account group having the account attribute data of 1000, and the account number is 10 in the account group having the account attribute data of 900. And then, the computer equipment takes the account attribute data of each account group and the account number corresponding to the account attribute data as data to be processed so as to rank the accounts in the current round and obtain the ranking result of each account.

It should be understood that although the various steps in the flowcharts of fig. 1-7 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-7 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.

It is understood that the same/similar parts between the embodiments of the method described above in this specification can be referred to each other, and each embodiment focuses on the differences from the other embodiments, and it is sufficient that the relevant points are referred to the descriptions of the other method embodiments.

Fig. 8 is a block diagram illustrating an apparatus according to an example embodiment. Referring to fig. 8, the apparatus includes an acquisition unit 801, a sorting unit 802, a determination unit 803, and a matching unit 804.

The acquisition unit 801 is configured to perform acquisition of data to be processed; the data to be processed comprises at least one account attribute data and the account number corresponding to each account attribute data.

The sorting unit 802 is configured to perform sorting of the account attribute data to obtain an account attribute sequence of the account attribute data.

The determining unit 803 is configured to perform, for each account attribute data, determining a ranking result of the account attribute data according to an arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy.

The matching unit 804 is configured to execute ranking results of the account attribute data as ranking results of at least one account corresponding to the account attribute data.

In an exemplary embodiment, the determining unit 803 further includes:

and the second determining subunit is configured to execute, for each piece of other account attribute data in the account attribute sequence except the first account attribute data, determining a ranking result of the current other account attribute data according to the account number corresponding to each piece of other account attribute data and the ranking result corresponding to the previous account attribute data of the current other account attribute data in the account attribute sequence.

In an exemplary embodiment, the data processing apparatus 800 further includes:

the construction unit is configured to execute ranking according to the account attribute data and the corresponding ranking result to obtain a ranking query table;

and the query unit is configured to execute a ranking query request for the target account, and determine a ranking result of the target account in the ranking query table according to a preset ranking table query strategy and current account attribute data corresponding to the target account.

In an exemplary embodiment, the query unit further comprises:

the first inquiry subunit is configured to execute inquiry whether current account attribute data of the target account exists in the ranking inquiry table or not in response to the ranking inquiry request aiming at the target account;

the filling subunit is configured to fill new account attribute data in a data interval of any adjacent account attribute data in the ranking query table according to a preset numerical interval under the condition that the new account attribute data do not exist; the new account attribute data is obtained by taking the values of two adjacent account attribute data as limit values and in a data interval according to a preset numerical value interval;

the third determining subunit is configured to determine the ranking result corresponding to the smaller account attribute data of the two account attribute data as the ranking result corresponding to the new account attribute data, so as to obtain an updated ranking query table;

In an exemplary embodiment, the data processing apparatus further includes:

the acquisition determining unit is configured to execute acquisition of a preset target ranking threshold value and determine an attribute data threshold value according to the target ranking threshold value and a ranking result of the account attribute data;

and the grade determining unit is configured to execute a grade query request aiming at the target account, and determine the grade corresponding to the target account according to the current account attribute data of the target account and the attribute data threshold.

In an exemplary embodiment, the acquisition determining unit further includes:

the inquiry judging subunit is configured to execute inquiry whether a target ranking result identical to the target ranking threshold exists in the ranking results of the account attribute data according to the target ranking threshold;

the fifth determining subunit is configured to execute, if a target ranking result identical to the target ranking threshold exists, taking account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold;

and the sixth determining subunit is configured to determine, if there is no target ranking result that is the same as the target ranking threshold, a minimum ranking result as a target ranking result among all ranking results that are greater than the target ranking threshold, and add a fixed threshold to account attribute data corresponding to the target ranking result as an attribute data threshold corresponding to the target ranking threshold.

In an exemplary embodiment, the obtaining unit 801 includes:

the acquiring subunit is configured to execute acquiring account attribute data of all accounts, and perform aggregation processing on the account attribute data of all accounts to obtain account groups of accounts containing the same account attribute data;

and the counting subunit is configured to perform counting on the account number included in each account group, and associate the account attribute data of each account group with the account number corresponding to the account attribute data to obtain the data to be processed.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

FIG. 9 is a block diagram illustrating an electronic device 900 for use in accordance with an example embodiment. For example, the electronic device 900 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a gaming console, a tablet device, a medical device, a fitness device, a personal digital assistant, and so forth.

Referring to fig. 9, electronic device 900 may include one or more of the following components: processing component 902, memory 904, power component 906, multimedia component 908, audio component 910, input/output (I/O) interface 912, sensor component 914, and communication component 916.

The processing component 902 generally controls overall operation of the electronic device 900, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. Processing component 902 may include one or more processors 920 to execute instructions to perform all or a portion of the steps of the methods described above. Further, processing component 902 can include one or more modules that facilitate interaction between processing component 902 and other components. For example, the processing component 902 can include a multimedia module to facilitate interaction between the multimedia component 908 and the processing component 902.

The memory 904 is configured to store various types of data to support operation at the electronic device 900. Examples of such data include instructions for any application or method operating on the electronic device 900, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 904 may be implemented by any type or combination of volatile or non-volatile storage devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, optical disk, or graphene memory.

The power supply component 906 provides power to the various components of the electronic device 900. The power components 906 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 900.

The multimedia component 908 includes a screen that provides an output interface between the electronic device 900 and an account. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the account. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 908 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 900 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 910 is configured to output and/or input audio signals. For example, the audio component 910 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 900 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 904 or transmitted via the communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

The I/O interface 912 provides an interface between the processing component 902 and a peripheral interface module, which may be a keyboard, click wheel, button, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor component 914 includes one or more sensors for providing status evaluations of various aspects of the electronic device 900. For example, sensor assembly 914 may detect an open/closed status of electronic device 900, the relative positioning of components, such as a display and keypad of electronic device 900, sensor assembly 914 may also detect a change in the position of electronic device 900 or components of electronic device 900, the presence or absence of an account in contact with electronic device 900, orientation or acceleration/deceleration of device 900, and a change in the temperature of electronic device 900. The sensor assembly 914 may include a proximity sensor configured to detect the presence of a nearby object in the absence of any physical contact. The sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 914 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 916 is configured to facilitate wired or wireless communication between the electronic device 900 and other devices. The electronic device 900 may access a wireless network based on a communication standard, such as WiFi, an operator network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component 916 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 916 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 900 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a computer-readable storage medium comprising instructions, such as the memory 904 comprising instructions, executable by the processor 920 of the electronic device 900 to perform the above-described method is also provided. For example, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, a computer program product is also provided, which includes instructions executable by the processor 920 of the electronic device 900 to perform the above-described method.

In an exemplary embodiment, a computer program product is also provided, which includes instructions executable by a processor of the electronic device S00 to perform the above method.

It should be noted that the descriptions of the above apparatus, the electronic device, the computer-readable storage medium, the computer program product, and the like according to the method embodiments may also include other embodiments, and specific implementation manners may refer to the descriptions of the related method embodiments, which are not described in detail herein.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method of data processing, the method comprising:

sequencing the account attribute data to obtain the account attribute sequence;

2. The data processing method according to claim 1, wherein the determining the ranking result of the account attribute data according to the arrangement order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy includes:

determining the account number corresponding to the first account attribute data as a ranking result corresponding to the first account attribute data aiming at the first account attribute data in the account attribute sequence;

and for each other account attribute data except the first account attribute data in the account attribute sequence, determining the ranking result of the other current account attribute data according to the account quantity corresponding to each other account attribute data and the ranking result corresponding to the account attribute data which is previous to the other current account attribute data in the account attribute sequence.

3. The data processing method according to claim 1, wherein after determining the ranking result of the account attribute data according to the ranking order of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data, and a preset ranking policy, the method further comprises:

responding to a ranking query request aiming at a target account, and determining a ranking result of the target account in a ranking query table according to a preset ranking table query strategy and current account attribute data corresponding to the target account.

4. The data processing method of claim 3, wherein the determining, in response to the ranking query request for the target account, the ranking result of the target account in the ranking query table according to a preset ranking table query policy and current account attribute data corresponding to the target account comprises:

5. The data processing method of claim 1, wherein after the ranking result of the account attribute data is used as the ranking result of the account corresponding to the account attribute data, the method further comprises:

6. The data processing method of claim 5, wherein determining the attribute data threshold according to the target ranking threshold and the ranking result of the account attribute data comprises:

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

the determining unit is configured to execute, aiming at each account attribute data, determining a ranking result of the account attribute data according to the arrangement sequence of the account attribute data in the account attribute sequence, the account number corresponding to the account attribute data and a preset ranking strategy;

8. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the data processing method of any one of claims 1 to 6.

9. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method of any of claims 1 to 6.

10. A computer program product comprising instructions which, when executed by a processor of an electronic device, enable the electronic device to perform the data processing method of any one of claims 1 to 6.