CN111340490A - Transaction certificate management method, data processing system and computer storage medium - Google Patents
Transaction certificate management method, data processing system and computer storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a transaction certificate management method, a data processing system and a computer storage medium, which are used for solving the problem that the generation time of a transaction certificate is prolonged because the data processing system needs to process a large amount of data. The method in the embodiment of the application comprises the following steps: the data processing system predicts that the required quantity of the transaction voucher at the next peak time of the current time point is n according to a prediction algorithm, controls the number of the identification information stored in the cache of the data processing system to be at least n, and calls one target identification information from the at least n identification information stored in the cache and sends the target identification information to the terminal when receiving each identification information request sent by the terminal.
Description
Technical Field
The embodiment of the application relates to the field of data processing, in particular to a transaction certificate management method, a data processing system and a computer storage medium.
Background
The data processing system is used in daily operation of the restaurant, for example, the data processing system is used for managing financial data of the restaurant, and generating a consumption document or a stored value document when a customer consumes or stores a value for a consumption card. The restaurant uses a point of sale information system (POS) to generate documents. In the process of generating the bill by the POS system, the POS system calls an Application Programming Interface (API) of a database of the data processing system, acquires identification information of the bill from the database, and further generates a corresponding bill. The identification information of the document is used for identifying the document generated by each transaction, and each document has unique identification information, so that the management of the document by restaurant stores is facilitated.
At the peak of Chinese food consumption and dinner consumption of restaurant stores, a large number of customers enter the store for consumption or value storage at the peak, a large number of consumption documents or value storage documents need to be generated and printed at the moment, API of the database can frequently access the database to acquire identification information of the documents, the database can be frequently accessed to form a bottleneck, the data volume needing to be processed by the database is increased, the generation time of the documents is prolonged, the overtime ratio of the page is large, and the user experience is poor.
Therefore, a problem that a large amount of data needs to be processed by a data processing system during a peak consumption period of a restaurant store, so that the generation time of documents is prolonged is urgently solved.
Disclosure of Invention
The embodiment of the application provides a transaction certificate management method, a data processing system and a computer storage medium, which are used for solving the problem that the generation time of a transaction certificate is prolonged because the data processing system needs to process a large amount of data.
In a first aspect, an embodiment of the present application provides a transaction credential management method, applied to a data processing system, where the method includes:
predicting n transaction voucher demands in the next peak period of the current time point according to a prediction algorithm, wherein the peak period is a time period for generating a large number of transaction vouchers, and n is a positive integer;
controlling the number of identification information stored in a cache of the data processing system to be at least n, wherein each identification information corresponds to a unique transaction certificate, and the at least n identification information stored in the cache are different from each other;
when each identification information request sent by a terminal is received, one target identification information is called from at least n identification information stored in the cache, and the target identification information is sent to the terminal, so that the terminal fills the target identification information into a transaction certificate corresponding to the identification information request.
Preferably, the data processing system comprises a database, the database storing identification information;
the controlling the number of the identification information stored in the cache of the data processing system to be at least n includes:
judging whether the number m of the identification information stored in the cache is less than n, wherein m is an integer;
if yes, acquiring at least (n-m) identification information from the database;
storing the obtained at least (n-m) pieces of identification information in the cache.
Preferably, the controlling the number of the identification information stored in the cache of the data processing system to be at least n includes:
and when a target time point is reached, controlling the number of the identification information stored in the cache to be at least n, wherein the target time point is any time point in a time period from the current time point to the time starting point of the next peak period.
Preferably, the prediction algorithm is an artificial intelligence AI prediction algorithm;
the predicting according to the prediction algorithm obtains n transaction voucher demands in the next peak period of the current time point, and the method comprises the following steps:
and calculating the historical transaction voucher demand quantity in the historical peak period by using the AI prediction algorithm to obtain n transaction voucher demand quantities in the next peak period, wherein the historical peak period is the peak period before the next peak period.
Preferably, the calculating the historical transaction voucher requirement amount of the historical peak period by using the AI prediction algorithm comprises:
judging whether an influence factor exists in the next peak period, wherein the influence factor is the condition of influencing the demand of the transaction voucher;
and if so, calculating the historical transaction voucher demand of the historical peak period with the influence factor by using the AI prediction algorithm.
Preferably, the influence factor is one or more of weather conditions, store promotion conditions, the date of the next peak period is working days or holidays, and a custom influence factor.
Preferably, the at least n identification information stored in the cache are n serial numbers sequentially arranged in sequence;
the retrieving of one target identification information from at least n identification information stored in the cache includes:
and when each identification information request is received, sequentially calling a target serial number from the n serial numbers according to the arrangement sequence of the n serial numbers.
Preferably, the serial number is one or two of a database main key of the transaction certificate and a serial number of the transaction certificate.
Preferably, the identification information requests transaction information including transaction credentials;
after the target identification information is sent to the terminal, the method further includes:
and establishing association between the target identification information and the transaction information of the transaction certificate included in the identification information request, and storing the association into a database of the data processing system.
A second aspect of the embodiments of the present application provides a data processing system, including:
the system comprises a prediction unit, a calculation unit and a processing unit, wherein the prediction unit is used for predicting n transaction voucher demand quantities of a next peak period of a current time point according to a prediction algorithm, the peak period is a time period for generating a large number of transaction vouchers, and n is a positive integer;
the control unit is used for controlling the number of the identification information stored in the cache of the data processing system to be at least n, wherein each identification information corresponds to a unique transaction certificate, and the at least n identification information stored in the cache are different from each other;
and the calling unit is used for calling one target identification information from at least n identification information stored in the cache when receiving each identification information request sent by the terminal, and sending the target identification information to the terminal so that the terminal fills the target identification information into the transaction voucher corresponding to the identification information request.
Preferably, the data processing system comprises a database, the database storing identification information;
the control unit includes:
a judging subunit, configured to judge whether the number m of the identification information stored in the cache is less than n, where m is an integer;
an obtaining subunit, configured to obtain at least (n-m) pieces of identification information from the database when the number m of identification information stored in the cache is less than n;
a storage subunit, configured to store the obtained at least (n-m) pieces of identification information in the cache.
Preferably, the control unit is specifically configured to control the number of the identification information stored in the cache to be at least n when a target time point is reached, where the target time point is any time point in a time period from the current time point to a time start point of the next peak period.
Preferably, the prediction algorithm is an artificial intelligence AI prediction algorithm;
the prediction unit includes:
and the prediction subunit is used for calculating the historical transaction voucher demand quantity in the historical peak period by using the AI prediction algorithm to obtain n transaction voucher demand quantities in the next peak period, wherein the historical peak period is the peak period before the next peak period.
Preferably, the predictor unit includes:
the judging module is used for judging whether an influence factor exists in the next peak period, wherein the influence factor is the condition of influencing the demand quantity of the transaction voucher;
and the calculation module is used for calculating the historical transaction voucher demand of the historical peak period with the influence factor by using the AI prediction algorithm when the influence factor exists in the next peak period.
Preferably, the influence factor is one or more of weather conditions, store promotion conditions, the date of the next peak period is working days or holidays, and a custom influence factor.
Preferably, the at least n identification information stored in the cache are n serial numbers sequentially arranged in sequence;
the retrieval unit includes:
and the calling subunit is configured to, when receiving each identification information request, sequentially call a target sequence number from the n sequence numbers according to the arrangement order of the n sequence numbers.
Preferably, the serial number is one or two of a database main key of the transaction certificate and a serial number of the transaction certificate.
Preferably, the identification information requests transaction information including transaction credentials;
the data processing system further comprises:
and the storage unit is used for establishing association between the target identification information and the transaction information of the transaction certificate included in the identification information request and storing the association into a database of the data processing system.
A third aspect of the embodiments of the present application provides a data processing system, including:
a processor, a memory, an input and output device;
the processor is connected with the memory and the input and output equipment;
the processor is used for predicting n transaction voucher demands at the next peak time of the current time point according to a prediction algorithm, the peak time is a time period for generating a large number of transaction vouchers, wherein n is a positive integer, the number of identification information stored in a cache of the data processing system is controlled to be at least n, each identification information corresponds to a unique transaction voucher, the at least n identification information stored in the cache are different from each other, and when each identification information request sent by a terminal is received, one target identification information is called from the at least n identification information stored in the cache;
the input and output equipment is used for sending the target identification information to the terminal so that the terminal fills the target identification information into a transaction certificate corresponding to the identification information request.
A fourth aspect of embodiments of the present application provides a computer storage medium having instructions stored therein, which when executed on a computer, cause the computer to perform the method of the first aspect.
According to the technical scheme, the embodiment of the application has the following advantages:
the data processing system predicts that the required quantity of the transaction voucher at the next peak time of the current time point is n according to a prediction algorithm, controls the number of the identification information stored in the cache of the data processing system to be at least n, and calls one target identification information from the at least n identification information stored in the cache when receiving each identification information request sent by the terminal, and sends the target identification information to the terminal, so that the terminal fills the target identification information into the transaction voucher corresponding to the identification information request.
Drawings
FIG. 1 is a flow chart illustrating a transaction voucher management method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a transaction voucher management method according to an embodiment of the present application;
FIG. 3 is a block diagram of a data processing system according to an embodiment of the present application;
FIG. 4 is a schematic diagram of another embodiment of a data processing system;
fig. 5 is a schematic structural diagram of another data processing system according to an embodiment of the present application.
Detailed Description
The embodiment of the application provides a transaction certificate management method, a data processing system and a computer storage medium, which are used for solving the problem that the generation time of a transaction certificate is prolonged because the data processing system needs to process a large amount of data.
Referring to fig. 1, an embodiment of a transaction credential management method in the embodiment of the present application includes:
101. predicting n transaction voucher demands at the next peak time of the current time point according to a prediction algorithm;
the transaction voucher management method of this embodiment is applied to a data processing system, which is a system capable of performing data processing, and includes an Enterprise Resource Planning (ERP) system, a Customer Relationship Management (CRM) system, a database system, or another type of data processing system, and a specific network device of the data processing system may be a server, for example, an application server or another type of server.
In this embodiment, the rush hour refers to a time period when a provider of service or goods needs to generate or print a large amount of transaction credentials, wherein the transaction credentials refer to data recorded with transaction information, and for example, the transaction credentials may be documents, invoices, shopping tickets, orders or other types of transaction credentials. The transaction information includes any information related to transaction activities, and may be merchandise information, transaction time, transaction type or serial number of the transaction, and other transaction information.
For example, the provider of the service may be a restaurant, and the peak hours of the restaurant may be the noon meal hours or the dinner hours; the provider of the goods may be retailer exceeded, and the peak period for retailer exceeded may be weekends, holidays, or evening hours.
In this embodiment, the specific time period of the peak period is not limited, and may be a time period artificially defined according to actual situations.
To facilitate management of the transaction voucher, the provider of the service or goods can use the terminal to perform communication connection with the data processing system of the embodiment and realize data transmission. For example, for a restaurant store or retailer, the terminal used by it may be a POS system. In this embodiment, the terminal is a device for generating a transaction certificate, and may be any terminal device as long as the terminal device can be used for generating a transaction certificate, for example, the aforementioned POS system, and the specific type of the terminal is not limited.
The data processing system determines a peak period of a provider of the service or the goods and determines a next peak period of a current time point, the next peak period being a first peak period reached by advancing along a time axis with the current time point as a starting point. The current time point is any one time point, and if the current time point is a time point in a peak period, the peak period in which the current time point is located is not taken as the next peak period.
For example, the data processing system determines that the peak hours of the provider of the service or goods are several of: 07: 30-09: 00, 11: 00-13: 00, 17: 30-19: 30, if the current time point is 10:38, with 10:38 as the time starting point, the time is shifted forward along the time axis, and the first peak period reached is 11: 00-13: 00, and 11: 00-13: 00 is the next peak period of the current time point 10: 38.
For another example, if the current time point is 11:42, since the time point 11:42 is already in the peak period of 11:00 to 13:00, the peak period of 11:00 to 13:00 is not used as the next peak period. Taking 11:42 as a time starting point, advancing along a time axis, wherein the first peak period is 17: 30-19: 30, and the first peak period is 17: 30-19: 30, namely the next peak period of the current time point 11: 42.
The data processing system may determine the peak period for the provider of the service or good in a number of ways, for example, by receiving a number of peak periods sent by the provider of the service or good to determine the peak period; or the person sets the peak period on the data processing system according to actual conditions, so that the data processing system can determine the specific peak period. The manner in which the data processing system determines the peak periods is not limited.
It should be noted that, in this embodiment, the time unit of the current time point and the peak period may be accurate to seconds or milliseconds, or only minute or hour, or even only date, and the accuracy of the time unit may be set arbitrarily, and this embodiment does not limit the accuracy of the time unit.
After determining the next peak period of the current time point, the data processing system calculates and predicts the big data by using a prediction algorithm based on the existing big data, and predicts the transaction certificate demand of the next peak period, wherein the prediction algorithm is any algorithm which can calculate and predict the future data trend according to the existing big data, for example, a mathematical algorithm such as a simple average method, a moving average method, an exponential smoothing method, a linear regression method, or an Artificial Intelligence (AI) algorithm, and the specific type of the prediction algorithm is not limited. The big data on which the predicted transaction credential demand depends is any data related to the transaction credential demand, such as historical transaction credential demand or other data, and the specific data type will be described in the embodiments that follow.
The data processing system predicts n transaction voucher demands in the next peak period of the current time point, wherein n is a positive integer. The transaction voucher demand is the number of transaction vouchers that need to be generated during peak hours.
102. Controlling the number of the identification information stored in the cache of the data processing system to be at least n;
after the data processing system determines that the transaction voucher demand quantity of the next peak period of the current time point is n, the data processing system controls the number of the identification information stored in the cache of the data processing system to be at least n, wherein the identification information refers to the identification information of the transaction voucher and is used for identifying each transaction voucher. Thus, each identification information should correspond to only a unique one of the transaction credentials. The specific form of the identification information may be any, as long as it can uniquely identify a transaction credential.
The purpose of this step is to control the number of identification information in the cache to be greater than or equal to the number of transaction voucher demands of the next peak period of the current time point, and each identification information only corresponds to one unique transaction voucher, so that all transaction vouchers generated in the peak period are ensured to be identified by the corresponding identification information, and each identification information in at least n identification information stored in the cache is required to be different from each other.
And each transaction certificate is identified by using the identification information, so that the transaction certificates are convenient to manage, and meanwhile, the corresponding transaction certificates can be conveniently and quickly inquired according to the identification information.
103. Calling a target identification information from at least n identification information stored in the cache, and sending the target identification information to the terminal;
in the next peak period of the current time point, the terminal of the provider of the goods or services can continuously generate the transaction voucher, at the moment, if the terminal needs to generate a certain transaction voucher, an identification information request corresponding to the certain transaction voucher is generated, then the identification information request is sent to the data processing system, and the data processing system is requested to distribute identification information for the identification information request. When receiving each identification information request, the data processing system calls a target identification information from at least n identification information stored in the cache and sends the target identification information to the terminal, wherein one target identification information can identify a transaction certificate. Therefore, after the terminal receives the target identification information, the target identification information can be filled into the transaction certificate corresponding to the identification information request.
In the embodiment, the data processing system does not need to access the database for multiple times when processing multiple identification information requests, but directly obtains the identification information from the cache, so that the processing data volume of the database is reduced, the acquisition speed of the target identification information is greatly improved, the waiting time of the terminal is reduced, and the timeout rate is reduced.
Referring to fig. 2, another embodiment of the transaction voucher management method in the embodiment of the present application includes:
201. predicting n transaction voucher demands at the next peak time of the current time point according to a prediction algorithm;
the operation performed in this step is similar to the operation performed in step 101 in the embodiment shown in fig. 1. More specifically, the prediction algorithm of the present embodiment is an artificial intelligence AI prediction algorithm.
In this embodiment, the data processing system determines that the big data relied upon in predicting the transaction voucher demand after the next peak at the current time point is the historical transaction voucher demand for the historical peak, wherein the historical peak is the peak before the next peak at the current time point.
For example, for a restaurant, a noon meal time period and a evening meal time period are peak times, when the data processing system predicts the transaction voucher demand of the noon meal time period of a certain day, the historical peak time period may be the noon meal time period of the past day of the restaurant, and the relied big data may be the transaction voucher demand of the noon meal time period of the past day, that is, the historical transaction voucher demand. Or the historical peak periods can be all peak periods of the previous day, including the peak periods of the lunch time period, the dinner time period and other time periods, and the predicted big data is all historical transaction voucher demands of all the peak periods of the previous day.
After the data processing system determines big data on which transaction voucher demand prediction depends, an AI prediction algorithm is used for calculating and predicting historical transaction voucher demands, the AI prediction algorithm is used for building a data prediction model by searching a change rule of the data in the large quantity of historical transaction voucher demands, the large quantity of historical transaction voucher demands are used as input of the data prediction model, parameters of the mathematical model are continuously adjusted through a series of calculation processes of the AI prediction algorithm, so that a predicted value calculated by the mathematical model is continuously close to a true value, a perfect data prediction model can be finally obtained through model training, and the predicted value calculated by the mathematical model can be used as the transaction voucher demands in the next peak period of the current time point.
In real life, the number of transaction certificates may be influenced by various factors, for example, weather conditions may influence the flow of people in restaurant stores, thereby influencing the number of transaction certificates in a certain peak period. Thus, in predicting the transaction credential demand, if an impact factor exists, the impact factor may be taken into account. The influence factors are any conditions influencing the transaction voucher demand, for example, weather conditions, store sales promotion conditions, and the date of the next peak of the current time point is a working day or a holiday, and all the influence factors influence the flow of people in stores, and further influence the transaction voucher demand. The impact factor may also be a custom impact factor, i.e. a case of human definition.
Specifically, when the influence of the influence factor on the transaction voucher demand is calculated, whether the influence factor exists in the next peak of the current time point or not is judged. If so, an AI prediction algorithm is used to calculate the historical transaction voucher requirements during the historical peak period with the same influence factor.
For example, the data processing system determines that there is an influence factor in the noon dining period of the restaurant, where the influence factor is a weather condition, and the current day is rainy, and the big data on which the data processing system predicts the transaction voucher demand is the historical transaction voucher demand in the historical peak period where the influence factor of the rainy day also exists, that is, the transaction voucher demand in the peak period of the rainy day in the previous day. By analogy, if the impact factor is a store promotional activity, the big data relied upon is predicted to be the peak transaction voucher demand for previous promotional activities.
It should be noted that, if the influence factor has a small influence on the transaction voucher required amount, and the influence degree can be almost ignored, the influence factor does not need to be considered when predicting the transaction voucher required amount, and the influence degree of the influence factor does not need to be calculated.
202. Controlling the number of the identification information stored in the cache of the data processing system to be at least n;
the operation performed in this step is similar to the operation performed in step 102 in the embodiment shown in fig. 1. The data processing system controls the number of the identification information stored in the cache, and the specific modes include the following modes:
in this embodiment, the data processing system may set a target time point, where the target time point is any time point in a time period from the current time point to the time start point of the next peak period. For example, the current time point is 10:38, the next peak period of 10:38 is 11:00 to 13:00, and the time start point of the peak period is 11:00, and then any time point can be set as the target time point in the time period of 10:38 to 11: 00.
The target time point is used for controlling the number of the identification information when the target time point is reached, namely, when the time reaches the target time point, the data processing system starts to control the number of the identification information stored in the cache, and the number of the identification information is ensured to be at least n. The target time point is set, so that the step is ensured to be completed at one time at the target time point, and meanwhile, the timing function is realized, and the action of controlling the quantity of the identification information can be executed at regular time.
It will be appreciated that the data processing system may also perform this step a plurality of times at a plurality of points in time during the period from the current point in time to the start of the next peak period without setting a target point in time, as long as it is ensured that at least n of the stored identification information is cached before the peak period.
In this embodiment, the data processing system includes a database, where the database stores identification information, and the data processing system may obtain the identification information from the database and store the obtained identification information in the cache.
Since the identification information stored in the cache is determined according to the transaction certificate demand, that is, when the transaction certificate demand is n, the identification information stored in the cache should be more than or equal to n. However, in practice, the transaction voucher may be voided for a particular reason before the identification information is retrieved, such as by the customer canceling the purchase of the item, resulting in the order being voided. At this time, the voided transaction voucher does not need to obtain the identification information, the identification information stored in the cache is remained, and the rest of the identification information can be used in the next peak period.
Therefore, in order to avoid the increase of the burden of the cache on data storage due to the storage of too much identification information in the cache, it may be determined whether the number m of the identification information stored in the cache is less than n, where m is an integer. And if the number m of the identification information stored in the cache is less than n, acquiring at least (n-m) identification information from the database, and storing the acquired at least (n-m) identification information into the cache so as to control the identification information stored in the cache.
In addition, the target time point can be set to judge the number of the identification information stored in the cache at regular time, and the identification information can be acquired from the database at one time.
It is understood that if the number m of the identification information stored in the cache is greater than or equal to the transaction certificate demand n, the identification information may not be acquired from the database.
203. Calling a target identification information from at least n identification information stored in the cache, and sending the target identification information to the terminal;
the operation performed in this step is similar to the operation performed in step 103 in the embodiment shown in fig. 1.
In this embodiment, the at least n identification information stored in the cache may be n serial numbers sequentially arranged in sequence. When receiving each identification information request sent by the terminal, the data processing system sequentially calls a target serial number from the n serial numbers according to the arrangement sequence of the n serial numbers and sends the target serial number to the terminal, wherein the target serial number can uniquely identify a transaction voucher. Therefore, after the terminal receives the target serial number, the target serial number can be filled in the transaction certificate corresponding to the identification information request.
Wherein, the serial number is one or two of the database key of the transaction voucher and the serial number of the transaction voucher. The database primary key and serial number can each uniquely represent a transaction credential. The specific form of the database primary key may be the FID field and the specific form of the serial number may be the FNO field.
For example, the at least n serial numbers stored by the cache may be database primary keys and stream numbers, the n database primary keys may be represented as 10001, 10002, 10003 … 1000n, and the n stream numbers may be represented as XFBH00001, XFBH00002, XFBH00003 … XFBH0000 n. When receiving a first identification information request sent by a terminal, a data processing system calls a database primary key 10001 and a serial number XFBH00001 and sends the first identification information request to the terminal; when receiving the second identification information request sent by the terminal, the data processing system calls the database primary key 10002 and the serial number XFBH00002, sends … … to the terminal, and so on, and when subsequently receiving each identification information request sent by the terminal, the data processing system calls a target serial number from the n serial numbers in sequence according to the arrangement sequence of the n serial numbers and sends the target serial number to the terminal.
The transaction voucher is identified by the serial number, so that the corresponding transaction voucher can be conveniently and quickly inquired, and the transaction voucher can be conveniently managed.
204. Establishing association between the target identification information and the transaction information of the transaction voucher included in the identification information request, and storing the association in a database of the data processing system;
in this embodiment, the identification information request sent by the terminal to the data processing system further includes transaction information of the transaction certificate. After the data processing system sends the target identification information to the terminal, the target identification information and the transaction information of the transaction voucher included in the identification information request are associated and stored in a database of the data processing system, so that the terminal is assisted to manage the transaction voucher, meanwhile, a platform for inquiring the transaction voucher is provided, and the corresponding transaction voucher can be inquired on the data processing system according to the target identification information.
In this embodiment, the data processing system identifies the transaction voucher by using the serial number, so that the corresponding transaction voucher can be conveniently and quickly queried, the transaction voucher can be conveniently managed, and the realizability of the scheme is improved.
The above describes the transaction credential management method in the embodiment of the present application, and the following describes the data processing system in the embodiment of the present application, referring to fig. 3, an embodiment of the data processing system in the embodiment of the present application includes:
the prediction unit 301 is configured to predict, according to a prediction algorithm, that the required amount of the transaction vouchers in a next peak period of a current time point is n, where the peak period is a time period in which a large amount of transaction vouchers are generated, and n is a positive integer;
the control unit 302 is configured to control the number of the identification information stored in the cache of the data processing system to be at least n, where each identification information corresponds to a unique transaction credential, and the at least n identification information stored in the cache are different from each other;
the retrieving unit 303 is configured to, when receiving each identification information request sent by the terminal, retrieve one piece of target identification information from at least n pieces of identification information stored in the cache, and send the target identification information to the terminal, so that the terminal fills the target identification information into the transaction certificate corresponding to the identification information request.
In this embodiment, operations performed by each unit in the data processing system are similar to those described in the embodiment shown in fig. 1, and are not described again here.
In the embodiment, the data processing system does not need to access the database for multiple times when processing multiple identification information requests, but directly obtains the identification information from the cache, so that the processing data volume of the database is reduced, the acquisition speed of the target identification information is greatly improved, the waiting time of the terminal is reduced, and the timeout rate is reduced.
Referring to fig. 4, another embodiment of the data processing system in the embodiment of the present application includes:
the prediction unit 401 is configured to predict, according to a prediction algorithm, that the required amount of the transaction vouchers in a next peak period of a current time point is n, where the peak period is a time period in which a large amount of transaction vouchers are generated, where n is a positive integer;
a control unit 402, configured to control the number of identification information stored in a cache of the data processing system to be at least n, where each identification information corresponds to a unique transaction credential, and the at least n identification information stored in the cache are different from each other;
a retrieving unit 403, configured to, when receiving each identification information request sent by the terminal, retrieve one piece of target identification information from at least n pieces of identification information stored in the cache, and send the target identification information to the terminal, so that the terminal fills the target identification information into the transaction certificate corresponding to the identification information request.
In one implementation manner of this embodiment, the data processing system includes a database, where the database stores identification information;
the control unit 402 includes:
a determining subunit 4021, configured to determine whether the number m of the identification information stored in the cache is less than n, where m is an integer;
an obtaining subunit 4022, configured to obtain at least (n-m) pieces of identification information from the database when the number m of identification information stored in the cache is less than n;
the storage subunit 4023 is configured to store the acquired at least (n-m) pieces of identification information in the cache.
In another implementation manner of this embodiment, the control unit is specifically configured to control the number of the identification information stored in the cache to be at least n when the target time point is reached, where the target time point is any time point in a time period from a current time point to a time start point of a next peak period.
In another implementation of this embodiment, the prediction algorithm is an artificial intelligence AI prediction algorithm;
the prediction unit 401 includes:
the forecasting sub-unit 4011 is configured to calculate the historical transaction voucher demand amount in the historical peak period by using an AI forecasting algorithm, so that the transaction voucher demand amount in the next peak period is n, and the historical peak period is a peak period before the next peak period.
Preferably, the predictor unit 4011 includes:
the judging module 40111 is configured to judge whether an influence factor exists in a next peak period, where the influence factor influences a transaction voucher demand;
a calculating module 40112, configured to calculate, by using an AI prediction algorithm, a historical transaction voucher requirement during the historical peak period where the impact factor exists, when the impact factor exists in the next peak period.
Wherein, the influence factor is one or more of weather condition, store promotion condition, the date of next peak period is working day or holiday, and custom influence factor.
In another implementation manner of this embodiment, the at least n pieces of identification information stored in the cache are n serial numbers sequentially arranged in order;
the retrieval unit 403 includes:
an invoking subunit 4031, configured to, when receiving each identifier information request, invoke a target serial number from the n serial numbers in sequence according to the sequence order of the n serial numbers.
Wherein, the serial number is one or two of the database key of the transaction voucher and the serial number of the transaction voucher.
In this embodiment, the identification information request includes transaction information of the transaction credential;
the data processing system further comprises:
the storing unit 404 is configured to associate the target identification information with the transaction information of the transaction credential included in the identification information request, and store the target identification information and the transaction information in a database of the data processing system.
In this embodiment, operations performed by each unit in the data processing system are similar to those described in the embodiment shown in fig. 2, and are not described again here.
Referring to fig. 5, a data processing system in an embodiment of the present application is described below, where an embodiment of the data processing system in the embodiment of the present application includes:
the data processing system 500 may include one or more Central Processing Units (CPUs) 501 and a memory 505, where one or more applications or data are stored in the memory 505.
The data processing system 500 may also include one or more power supplies 502, one or more wired or wireless network interfaces 503, one or more input-output interfaces 504, and/or one or more operating systems, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.
The central processing unit 501 may perform the operations performed by the data processing system in the embodiments shown in fig. 1 to fig. 2, and details thereof are not repeated herein.
An embodiment of the present application further provides a computer storage medium, where one embodiment includes: the computer storage medium has stored therein instructions that, when executed on a computer, cause the computer to perform the operations described above as being performed by the data processing system in the embodiments of fig. 1-2.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various other media capable of storing program codes.
Claims (12)
1. A transaction credential management method, applied to a data processing system, the method comprising:
predicting n transaction voucher demands in the next peak period of the current time point according to a prediction algorithm, wherein the peak period is a time period for generating a large number of transaction vouchers, and n is a positive integer;
controlling the number of identification information stored in a cache of the data processing system to be at least n, wherein each identification information corresponds to a unique transaction certificate, and the at least n identification information stored in the cache are different from each other;
when each identification information request sent by a terminal is received, one target identification information is called from at least n identification information stored in the cache, and the target identification information is sent to the terminal, so that the terminal fills the target identification information into a transaction certificate corresponding to the identification information request.
2. The transaction credential management method of claim 1, wherein the data processing system includes a database, the database storing identification information;
the controlling the number of the identification information stored in the cache of the data processing system to be at least n includes:
judging whether the number m of the identification information stored in the cache is less than n, wherein m is an integer;
if yes, acquiring at least (n-m) identification information from the database;
storing the obtained at least (n-m) pieces of identification information in the cache.
3. The transaction credential management method of claim 1, wherein controlling the number of identification information stored by the cache of the data processing system to be at least n comprises:
and when a target time point is reached, controlling the number of the identification information stored in the cache to be at least n, wherein the target time point is any time point in a time period from the current time point to the time starting point of the next peak period.
4. The transaction voucher management method of claim 1, wherein the predictive algorithm is an Artificial Intelligence (AI) predictive algorithm;
the predicting according to the prediction algorithm obtains n transaction voucher demands in the next peak period of the current time point, and the method comprises the following steps:
and calculating the historical transaction voucher demand quantity in the historical peak period by using the AI prediction algorithm to obtain n transaction voucher demand quantities in the next peak period, wherein the historical peak period is the peak period before the next peak period.
5. The transaction credential management method of claim 4, wherein the calculating of the historical transaction credential demand for historical peak periods using the AI prediction algorithm comprises:
judging whether an influence factor exists in the next peak period, wherein the influence factor is the condition of influencing the demand of the transaction voucher;
and if so, calculating the historical transaction voucher demand of the historical peak period with the influence factor by using the AI prediction algorithm.
6. The transaction voucher management method of claim 5, wherein the impact factor is one or more of a weather condition, a store promotion condition, a date of the next peak period being a weekday or holiday, and a custom impact factor.
7. The transaction voucher management method of any one of claims 1 to 6, wherein the at least n identification information stored in the cache is n serial numbers sequentially arranged in order;
the retrieving of one target identification information from at least n identification information stored in the cache includes:
and when each identification information request is received, sequentially calling a target serial number from the n serial numbers according to the arrangement sequence of the n serial numbers.
8. The transaction credential management method of claim 7, wherein the serial number is one or both of a database key of the transaction credential, a serial number of the transaction credential.
9. The transaction credential management method of claim 1, wherein the identification information request includes transaction information of the transaction credential;
after the target identification information is sent to the terminal, the method further includes:
and establishing association between the target identification information and the transaction information of the transaction certificate included in the identification information request, and storing the association into a database of the data processing system.
10. A data processing system, characterized in that the data processing system comprises:
the system comprises a prediction unit, a calculation unit and a processing unit, wherein the prediction unit is used for predicting n transaction voucher demand quantities of a next peak period of a current time point according to a prediction algorithm, the peak period is a time period for generating a large number of transaction vouchers, and n is a positive integer;
the control unit is used for controlling the number of the identification information stored in the cache of the data processing system to be at least n, wherein each identification information corresponds to a unique transaction certificate, and the at least n identification information stored in the cache are different from each other;
and the calling unit is used for calling one target identification information from at least n identification information stored in the cache when receiving each identification information request sent by the terminal, and sending the target identification information to the terminal so that the terminal fills the target identification information into the transaction voucher corresponding to the identification information request.
11. A data processing system, comprising:
a processor, a memory, an input and output device;
the processor is connected with the memory and the input and output equipment;
the processor is used for predicting n transaction voucher demands at the next peak time of the current time point according to a prediction algorithm, the peak time is a time period for generating a large number of transaction vouchers, wherein n is a positive integer, the number of identification information stored in a cache of the data processing system is controlled to be at least n, each identification information corresponds to a unique transaction voucher, the at least n identification information stored in the cache are different from each other, and when each identification information request sent by a terminal is received, one target identification information is called from the at least n identification information stored in the cache;
the input and output equipment is used for sending the target identification information to the terminal so that the terminal fills the target identification information into a transaction certificate corresponding to the identification information request.
12. A computer storage medium having stored therein instructions that, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 9.
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