CN110515946B - Data extraction method, device, equipment and computer readable storage medium - Google Patents
Data extraction method, device, equipment and computer readable storage medium Download PDFInfo
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- CN110515946B CN110515946B CN201910767997.6A CN201910767997A CN110515946B CN 110515946 B CN110515946 B CN 110515946B CN 201910767997 A CN201910767997 A CN 201910767997A CN 110515946 B CN110515946 B CN 110515946B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2291—User-Defined Types; Storage management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
- G06F16/24573—Query processing with adaptation to user needs using data annotations, e.g. user-defined metadata
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The invention discloses a data extraction method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: when detecting a completion identification generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction; adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction; when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request; and extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table. According to the scheme, the data is extracted through the operation number based on big data analysis to generate the data extraction table, all sources of the extracted target extraction data are recorded, and the positioning and tracking time of the data is saved.
Description
Technical Field
The present invention relates generally to the field of data processing technologies, and in particular, to a data extraction method, apparatus, device, and computer readable storage medium.
Background
With the advent of the information age and the development of computer technology, the types and the scope of data processed by a computer are increasing, wherein the data includes storing and recording input data, and when various processing requests for the stored data are received, the stored data are read to perform various processing.
At present, in the process of receiving a data extraction request and extracting data, the source is not distinguished for the data of the same type, and the data of the same type is extracted as long as the data of the same type is extracted, and the data of the same type is not concerned about generating the data according to different scenes at different times; in this way, in the case that the source monitoring needs to be performed on the extracted data, the different sources of each data of the same type cannot be distinguished, and in this case, it takes more time to perform positioning tracking on each data, and even the situation that tracking cannot be performed occurs.
Disclosure of Invention
The invention mainly aims to provide a data extraction method, a device, equipment and a computer readable storage medium, which aim to solve the problem that the sources of the same type of data cannot be distinguished when the data is extracted in the prior art.
In order to achieve the above object, the present invention provides a data extraction method, comprising the steps of:
When detecting a completion identification generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction;
adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction;
when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request;
and extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table.
Preferably, the step of determining target extraction data from the account database according to the extraction data amount information carried by the extraction request includes:
reading the data volume of each item of sub data in the account database, and judging whether target data volume consistent with the extracted data volume information exists in each data volume;
if the target data quantity consistent with the extracted data quantity information exists, determining sub-data corresponding to the target data quantity as target extracted data;
and if the target data quantity consistent with the extracted data quantity information does not exist, determining target extracted data according to the time sequence of generating the sub data of each item.
Preferably, the step of determining the target extraction data according to the time sequence of generating the sub-data of each item includes:
according to the time sequence, reading first sub-data positioned at the first bit of the time sequence, and judging whether the data volume of the first sub-data is larger than the extracted data volume;
if the data quantity of the first sub-data is larger than the extraction data quantity, determining the first sub-data as target extraction data;
and if the data quantity of the first sub data is not larger than the extracted data quantity, determining target extracted data according to other sub data positioned behind the first sub data in the time sequence.
Preferably, the step of determining the target extraction data according to the other sub-data located at the rear of the first sub-data in the time sequence includes:
reading sub-data positioned at the next bit of the first sub-data, and adding the data quantity of the first sub-data and the data quantity of the sub-data to generate an addition result;
judging whether the addition result is larger than the extraction data amount, if so, determining the first sub-data and the sub-data as target extraction data;
If the addition result is not greater than the extracted data quantity, reading the secondary sub-data positioned at the next bit after the secondary sub-data, and adding the data quantity of the secondary sub-data and the addition result to update the addition result;
and executing the step of judging whether the addition result is larger than the extraction data amount or not on the updated addition result until the addition result is larger than the extraction data amount, and determining each item of sub-data generating the addition result as target extraction data.
Preferably, the step of extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table includes:
extracting the target extraction data, judging whether the item number of the sub data corresponding to the target extraction data is a single item, and if the item number is a single item, reading the operation number of the sub data corresponding to the target extraction data in the account database and adding the operation number to a preset data table to obtain a data extraction table;
and if the item number is not a single item, sequentially reading the operation numbers of all sub-data corresponding to the target extraction data in the account database, and adding the operation numbers to a preset data table to obtain a data extraction table.
Preferably, the step of reading the data amounts of the sub data in the account database and determining whether the target data amount consistent with the extracted data amount information exists in each data amount includes, before:
reading the extraction time limit of each piece of sub-data in the account database, and judging whether a target extraction time limit smaller than a preset time limit exists in each extraction time limit;
if the target extraction time limit is smaller than the preset time limit, determining sub-data corresponding to the target extraction time limit as intermediate extraction data, and determining target extraction data according to the size relation between the data quantity of the intermediate extraction data and the data quantity corresponding to the extraction data quantity information;
and if the target extraction time limit which is smaller than the preset time limit does not exist, executing the step of reading the data quantity of each item of sub-data in the account database.
Preferably, the step of determining the target extraction data according to the size relationship between the data amount of the intermediate extraction data and the data amount corresponding to the extraction data amount information includes:
judging whether the data quantity of the intermediate extraction data is larger than the data quantity corresponding to the extraction data quantity information, and if so, determining the intermediate extraction data as target extraction data;
And if the data quantity is not greater than the data quantity corresponding to the extracted data quantity information, setting the intermediate extracted data as first sub-data positioned at the first position of the time sequence, and executing the step of determining target extracted data according to other sub-data positioned at the rear position of the first sub-data in the time sequence.
In addition, in order to achieve the above object, the present invention also proposes a data extraction device including:
the detection module is used for generating operation data of the account according to the operation factors corresponding to the operation transaction when detecting the completion identification generated by the account on the operation transaction;
the recording module is used for adding the operation data into an account database of the account and generating an operation number for distinguishing the operation transaction;
the extraction module is used for determining target extraction data from the account database according to the extraction data amount information carried by the extraction request when the extraction request of the operation data is received;
the generation module is used for extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table.
In addition, in order to achieve the above object, the present invention also proposes a data extraction apparatus including: a memory, a processor, a communication bus, and a data extraction program stored on the memory;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute the data extraction program to implement the steps of:
when detecting a completion identification generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction;
adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction;
when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request;
and extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table.
In addition, to achieve the above object, the present invention also provides a computer-readable storage medium storing one or more programs executable by one or more processors for:
When detecting a completion identification generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction;
adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction;
when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request;
and extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table.
According to the data extraction method, when the completion identification generated by the account for the operation transaction is detected, operation data of the account is generated according to the operation factor corresponding to the operation transaction; adding the generated operation data into an account database of the account to generate an operation number for distinguishing operation transactions; and if the extraction request of the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request to perform extraction operation, and simultaneously extracting the operation number of the target extraction data in the account database to obtain a data extraction table. According to the scheme, after an operation number generated according to an operation transaction is added to an account database, an operation number for distinguishing the operation things is generated; when an extraction request is received to extract data, determining extractable target extraction data from an account database according to the extraction data amount information carried by the extraction request; and simultaneously extracting the operation number of the target extraction data in the account database to obtain a data extraction table. Because the operation numbers represent the operation transaction from which the target extraction data is derived, each source of the extracted target extraction data can be recorded through the data extraction table obtained by the operation numbers, the problem that the sources of the extracted data of the same type cannot be distinguished is avoided, and the time for positioning and tracking the data is saved.
Drawings
FIG. 1 is a flow chart of a first embodiment of a data extraction method of the present invention;
FIG. 2 is a schematic diagram of functional modules of a first embodiment of the data extraction device of the present invention;
FIG. 3 is a schematic diagram of a device architecture of a hardware operating environment involved in a method according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a data extraction method.
Referring to fig. 1, fig. 1 is a flowchart illustrating a data extraction method according to a first embodiment of the invention. In this embodiment, the data extraction method includes:
step S10, when detecting a completion identifier generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction;
the data extraction method is applied to the server, is suitable for extracting the data through the server and distinguishing the sources of the extracted data; the data which can be used for extraction are the same type of data generated by the user operating the same operation transaction in different time, such as the promotion data of the corresponding performance of the user due to certain work, the recharging data of the game recharging in the network platform, and the like. At present, when extracting the data, the extraction can be supported as long as the data available for extraction can meet the data requirement of actual extraction in amount, and the data available for extraction is not concerned with which performance or which recharging is generated; the embodiment is suitable for distinguishing the source of each extracted data when the data is extracted. Specifically, taking the proposed data as an example, the operation transaction corresponding to the generation of the proposed data may be a transaction of selling various physical products, such as a computer, a mobile phone, a house, etc., or may be a transaction of selling various virtual products, such as insurance products, financial products, etc. Taking personnel selling the various operation transactions as users, and operating through a registered account; after the user completes the operation transaction operation, namely the sales is successful, a completion identification is generated through the account.
When the server detects the completion identification generated by the account for the operation transaction, generating operation data of the account according to the operation factor corresponding to the operation transaction; the operation factors corresponding to the operation transaction represent the promotion factors of the sales products corresponding to the operation transaction, such as promotion duty ratio, promotion amount and the like, and are stored in the server together with the account in advance. The completion identification carries the sales amount of the sales product corresponding to the characterization operation transaction, and the server searches the operation factor according to the account corresponding to the completion identification; and reading the operation factors, integrating the sales amount by using the operation factors, and generating operation data of the account. Wherein the integration can include multiplication integration or comparison search, and the multiplication integration is performed by using the operation factor and the sales amount, and the result obtained by the multiplication is the operation data; for comparison and integration, a corresponding relation is preset among the operation factors, the sales amount and the operation data, the operation factors and the sales amount are compared with the corresponding relation, and the corresponding operation data is determined; the user is characterized by the operational data in the operational transaction, and the obtained quota is presented.
Step S20, adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction;
it is to be understood that the operation of the user on the operation transaction involves multiple times, each time operation generates operation data, in order to store each time operation data, an account database is preset for each account, the operation data generated by each operation transaction is added into the account database of the account to be stored, and information in the account database is used for describing the corresponding relation among the operation transaction, the operation data and the operation number. And adding the operation data generated according to the current completion identification into an account database of the account, and adding the operation data with the account data originally in the account database to generate the original account data into operation total data, wherein the operation total data characterizes the total sum of the user. Meanwhile, for the generated operation data, a mechanism for generating an operation number is also arranged, wherein the operation number is used for distinguishing the corresponding relation between different operation data and different operation transactions; i.e. assigning an operation number for the operation transaction that generated the operation data, characterizing which operation transaction the operation data was generated from at which time.
Step S30, when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request;
further, the user can extract the operation data in the account database, namely, the total proposal amount is presented; when the request is met, the amount of the to-be-presented is represented, namely the amount of the extracted data forms a presentation request through a display interface of a terminal held by a user. The terminal held by the user is in communication connection with the server, and the request for presenting the operation data is sent to the server through the terminal. When the server receives the request, the server firstly reads the information of the extracted data quantity carried in the request, and determines target extracted data in an account database according to the information of the extracted data quantity. The extracted data amount information can characterize extraction of all data of the account, namely all operation data, and can also extract part of the operation data; and carrying out all or part of rendering processing on the total sum of the offers. The target extraction data is determined according to the size relation between the data quantity of each operation data in the account database and the data quantity represented by the extraction data quantity information, specifically, the step of determining the target extraction data from the account database according to the extraction data quantity information carried by the extraction request comprises the following steps:
Step S31, reading the data volume of each item of sub data in the account database, and judging whether the target data volume consistent with the extracted data volume information exists in each data volume;
further, the operation data generated by each operation transaction is used as each item of sub-data in the account database; and reading the data quantity of each item of sub data, comparing each data quantity with the represented data quantity in the extracted data quantity information one by one, and judging whether the target data quantity consistent with the represented data quantity in the extracted data quantity information exists in each data quantity. Wherein, a plurality of data volumes may exist in each data volume and are consistent with the data volume represented by the extracted data volume information, or any data volume may not exist and is consistent with the data volume represented by the extracted data volume information; if a plurality of data amounts exist, the plurality of data amounts are all taken as target data amounts, and if any one data amount does not exist, the fact that the data amount does not exist in each data amount is indicated.
Step S32, if the target data quantity consistent with the extracted data quantity information exists, determining sub-data corresponding to the target data quantity as target extracted data;
further, if it is judged that the target data amount exists, the sub data having the target data amount is determined as target extraction data to be extracted. In the case where the target data amount includes a plurality of data amounts, the time corresponding to the plurality of data amounts is read, that is, the generation time of each sub data having the plurality of data amounts is read. And then determining the first-time sub data, namely the sub data with the longest generation time, as target extraction data according to the time sequence relation.
And step S33, if the target data quantity consistent with the extracted data quantity information does not exist, determining target extracted data according to the time sequence of generating the sub data of each item.
Further, if it is judged that the target data quantity consistent with the data quantity represented by the extracted data quantity information does not exist in the data quantities, it is indicated that the sub data completely consistent with the data quantity of the data to be extracted does not exist in all the sub data of the generated operation total data; at this time, the data amount of each item of sub data needs to be added to obtain an addition result consistent with the extracted data amount, and sub data corresponding to the addition result is further extracted as target extracted data. The adding is carried out according to the time sequence generated by each piece of sub data, and the sub data with the previous generation time in the total operation data is added preferentially, so that the target extraction data is determined according to the time sequence generated by each piece of sub data.
Specifically, the step of determining the target extraction data according to the time sequence of generating the sub-data of each item includes:
step S331, reading first sub-data positioned at the first bit of the time sequence according to the time sequence, and judging whether the data volume of the first sub-data is larger than the extracted data volume;
Further, the time generated by each item of sub-data in the total data of the operation is read, and the time sequence generated by each item of sub-data is obtained by arranging the sub-data according to the time sequence relation. The preset sorting mechanism is preset and used for sorting, and can be preset queue sorting or preset bubbling sorting. For sequencing a preset queue, firstly recording the generation time of each item of sub data, and storing each item of sub data in the queue according to the sequence of the time; after some item of sub data in the queue is extracted, the sub data at the position above the extracted sub data is moved to the position for extracting the sub data, so that the remaining items of sub data stored in the queue are ensured to be arranged according to the time sequence, and the time sequence of each item of sub data is formed. For preset bubbling sequencing, firstly reading the generation time of each item of sub-data to form an arbitrary sequence, then reading two adjacent elements in the arbitrary sequence for comparison, and judging the front-back relationship of the time between the two elements; if the generation time of the former element is later than that of the latter element, the position relations between the former element and the latter element are exchanged until the position relations of all elements in any sequence are that the generation time of the former element is earlier than that of the latter element, and the sequencing of all sub-data according to the respective generation time is completed, so that the time sequence of all sub-data is generated; and for the sub data which newly appears subsequently, the sub data is directly arranged in the later column of the sequence so as to update the time sequence of each sub data formed by sequencing. And then, according to the time sequence of each item of sub data, reading the sub data arranged at the first bit in the time sequence as first sub data, further reading the data quantity of the first sub data, comparing the data quantity with the extracted data quantity, and judging whether the read data quantity is larger than the extracted data quantity.
Step S332, if the data size of the first sub-data is greater than the extracted data size, determining the first sub-data as target extracted data;
if the data quantity is larger than the extraction data quantity, the data quantity of the first sub-data meets the data quantity requirement of the required extraction data, so that the first sub-data is determined to be the target sub-data for extraction. Because the data size of the first sub data is larger than the extraction data size, after the first sub data is used as the target sub data for extraction, the first sub data still contains the data which is not extracted; at this time, a difference is made between the data amount of the first sub-data and the extracted data amount, and the data amount of the first sub-data is updated by using the obtained difference result, so as to characterize the remaining data of the first sub-data after extraction. The total sum of the allowance as characterized by the operation total data is 500 yuan, the amount of money required to be presented by the user is 100 yuan; the sequence obtained by arranging all sub-data in the total data according to the time sequence is 150 yuan, 120 yuan, 80 yuan and 150 yuan, and the 150 yuan of the first sub-data is extracted according to the amount to be extracted, namely 100 yuan is extracted; thereafter, the remaining 50 elements are stored as data remaining as the first sub data.
Step S333, if the data size of the first sub-data is not greater than the extracted data size, determining target extracted data according to other sub-data located at the rear of the first sub-data in the time sequence.
If the data quantity of the read first sub data is not larger than the extracted data quantity, the data quantity of the first sub data is not satisfied with the data quantity of the required extracted data, and the target extracted data is determined according to other sub data arranged in the time sequence behind the first sub data. And when the sum of the data quantity of the other sub-data and the data quantity of the first sub-data is larger than the extraction data quantity, and the data quantity of the first sub-data and the other sub-data together meets the data quantity of the required extraction data, the first sub-data and the other sub-data are taken as target extraction data together. Considering that the other sub-data arranged in the rear column of the first sub-data in time sequence is numerous, other sub-data which forms target extraction data together with the first sub-data needs to be determined according to the data quantity of the first sub-data; specifically, the step of determining the target extraction data according to the other sub-data positioned at the rear of the first sub-data in the time sequence includes:
Step a, reading sub-bit sub-data positioned at the next bit of the first-bit sub-data, and adding the data quantity of the first-bit sub-data and the data quantity of the sub-bit sub-data to generate an addition result;
b, judging whether the addition result is larger than the extraction data amount, if so, determining the first sub-data and the sub-data as target extraction data;
further, sub data arranged one after the first sub data in time sequence is read as sub data, and the data amount of the first sub data and the data amount of the sub data are added to generate an added addition result. And comparing the added result with the extracted data quantity, judging whether the added result is larger than the extracted data quantity, and if so, indicating that the data quantity shared by the first sub-data and the sub-data meets the data quantity requirement of the required extracted data, so that the first sub-data and the sub-data are shared as target extracted data for extraction.
Step c, if the addition result is not greater than the extracted data quantity, reading the secondary sub-data positioned at the next bit after the secondary sub-data, and adding the data quantity of the secondary sub-data and the addition result to update the addition result;
And d, executing the step of judging whether the addition result is larger than the extraction data amount or not on the updated addition result, and determining each item of sub-data generating the addition result as target extraction data until the addition result is larger than the extraction data amount.
If the result of the addition is not greater than the data quantity, the data quantity of the first sub data and the second sub data still cannot meet the data quantity requirement of the required extracted data; and at the moment, reading the sub data positioned at the next bit after the sub data of the next bit as the sub data of the next bit again according to the time sequence, and accumulating the data quantity of the sub data of the next bit and the summation result to update the summation result. Comparing the updated addition result with the extracted data amount, judging whether the updated addition result is larger than the extracted data amount, if so, indicating that the data amount shared by all sub-data for generating the addition result can meet the data amount requirement of the extracted data, and determining all the sub-data corresponding to the addition result as target extracted data; if the sum is not greater than the extraction data amount, continuing to sum the sub-data according to the time sequence until the obtained sum result is greater than the extraction data amount, and setting the sub-data generating the sum result as target extraction data.
Wherein the process of updating the addition result can use a preset formula sigma a i More than or equal to x represents, ai represents the data quantity of each item of sub data arranged according to time sequence, x is the extracted data quantity, i is accumulated by an accumulation unit 1 on the basis of a numerical value 2; firstly judging whether (a1+a2) is larger than x, namely judging whether the common data quantity of the first sub data and the second sub data is larger than the extracted data quantity, and stopping the type if the common data quantity is larger than the extracted data quantity; otherwise, the value of i is 3, judging whether (a1+a2+a3) is larger than x, namely, whether the data volume of the addition result and the secondary sub-data together is larger than the extraction data volume; sequentially accumulating until the value k of i is greater than or equal to x, and taking the first k sub-data in the time sequence as target extraction data.
And step S40, extracting the target extraction data and the operation numbers of the target extraction data in the account database to obtain a data extraction table.
Further, after determining the target extraction data in the account database, extracting the target extraction data, and simultaneously lifting the operation number of the target extraction data in the account database; the operation numbers in the account database are the operation numbers recorded in the generation process of each item of operation data, and the operation numbers of the target extraction data in the account database are the operation numbers of each item of sub-data forming the target extraction data in the account database. And integrating the extraction time of the target extraction data, the data quantity of each piece of sub data corresponding to the target extraction data and the operation numbers corresponding to each piece of sub data to obtain a data extraction table, and characterizing the time and the source of the data extracted by the extraction request through the operation numbers in the data extraction table to realize the distinction of the extracted data sources.
In view of the fact that the sub data forming the target extraction data may be plural items or may be single items, when generating the data extraction table, there are different generation manners depending on differences of the single items or the plural items. Specifically, the step of extracting the target extraction data and the operation number of the target extraction data in the account database to obtain the data extraction table includes:
step S41, extracting the target extraction data, judging whether the item number of the sub data corresponding to the target extraction data is a single item, and if the item number is a single item, reading the operation number of the sub data corresponding to the target extraction data in the account database and adding the operation number to a preset data table to obtain a data extraction table;
further, extracting the target extraction data, judging whether the item number of the sub data forming the target extraction data is a single item, and when the data quantity of a certain item of sub data in the account database is consistent with the extraction data quantity or the data quantity of the first sub data is larger than the extraction data quantity, indicating that the item number of the sub data corresponding to the target extraction data is a single item; otherwise, if the data quantity of the operation data is not consistent with the extraction data quantity of a certain item of sub data and the data quantity of the first sub data is not larger than the extraction data quantity, the item number of the sub data corresponding to the target extraction data is judged to be not a single item.
The method comprises the steps of presetting a preset data table for generating a data extraction table, reading an operation number of sub data for generating target extraction data in an account database as a single operation number in the case that the number of items is single, and adding the single operation number, the data quantity of the target extraction data and the current extraction time to different positions in the preset data table to obtain the data extraction table.
Step S42, if the item number is not a single item, sequentially reading operation numbers of all sub-data corresponding to the target extraction data in the account database, and adding the operation numbers to a preset data table to obtain a data extraction table.
Further, when the number of items of the sub data corresponding to the target extraction data is judged to be not a single item, the operation numbers of the sub data of the target extraction data in the account database are sequentially read, and the read operation numbers are used as target operation numbers. Because the multiple sub-data forming the target extraction data have time sequence, the method can be sequentially carried out according to the time sequence when reading each target operation number; and simultaneously adding the read target operation numbers, the data quantity of each piece of sub data forming the target extraction data and the current extraction time to different positions in a preset data table according to the time sequence to obtain a data extraction table.
Understandably, the amount of data in the account database is reduced after the target extraction data is extracted from the account database; after extracting the target extraction data, updating the data volume of the account database according to the data volume of the target extraction data; the total data volume of the account database and the data volume of the target extraction data are used as difference values, and the obtained difference value result is the residual data volume of the account database after extraction; new operating data are subsequently generated or data extraction is carried out on the basis of the remaining data quantity.
According to the data extraction method, when the completion identification generated by the account for the operation transaction is detected, operation data of the account is generated according to the operation factor corresponding to the operation transaction; adding the generated operation data into an account database of the account to generate an operation number for distinguishing operation transactions; and if the extraction request of the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request to perform extraction operation, and simultaneously extracting the operation number of the target extraction data in the account database to obtain a data extraction table. According to the scheme, after an operation number generated according to an operation transaction is added to an account database, an operation number for distinguishing the operation things is generated; when an extraction request is received to extract data, determining extractable target extraction data from an account database according to the extraction data amount information carried by the extraction request; and simultaneously extracting the operation number of the target extraction data in the account database to obtain a data extraction table. Because the operation numbers represent the operation transaction from which the target extraction data is derived, each source of the extracted target extraction data can be recorded through the data extraction table obtained by the operation numbers, the problem that the sources of the extracted data of the same type cannot be distinguished is avoided, and the time for positioning and tracking the data is saved.
Further, in another embodiment of the data extraction method of the present invention, the step of reading the data amounts of the sub-data items in the account database and determining whether the target data amount consistent with the extracted data amount information exists in each data amount includes:
step S34, reading the extraction time limit of each piece of sub-data in the account database, and judging whether a target extraction time limit smaller than a preset time limit exists in each extraction time limit;
it is understood that the operation data formed in the account database are generated at different times, and in order to facilitate data management, when the data extraction request is received, the sub data with the longest time from the current time generated in the account database is preferentially extracted. Specifically, a uniform extraction time limit of each operation data is preset, such as setting to be within half a year from when the operation data is generated, or extracting within one year, etc.; the operation data forming the account database are generated at different times so that when the extraction request is received, the extraction time limit remaining for each piece of sub-data in the account database is different. Setting a preset time limit representing the preferential extraction, for example, setting operation data which is about to reach half a year or one month before one year as the operation data of the preferential extraction; if the operation data is generated in 1 month No. 1, the same extraction time limit is half a year, the extraction time limit is 6 months No. 1, and if the extraction request is received in 5 months No. 2, the operation data is the operation data extracted preferentially.
Further, before receiving an extraction request to form a target data volume for extraction, reading the residual extraction time limit of each piece of sub-data in the account database, comparing each residual extraction time limit with a preset time limit, and judging whether a target extraction time limit smaller than the preset time limit exists in each extraction time limit; the sub data from which the target extraction time limit is derived is the sub data closest to the unified extraction time limit, the generation time is longer than the current time, and the extraction needs to be carried out preferentially.
Step S35, if a target extraction time limit smaller than a preset time limit exists, determining sub-data corresponding to the target extraction time limit as intermediate extraction data, and determining target extraction data according to the size relation between the data amount of the intermediate extraction data and the data amount corresponding to the extraction data amount information;
further, if it is determined that there is a target extraction time limit less than the preset time limit in each extraction time limit, it is indicated that the sub-data corresponding to the target extraction time limit is the sub-data extracted preferentially, and it is determined as intermediate extraction data. Then, determining target extraction data according to the size relation between the data quantity of the intermediate extraction data and the data quantity represented by the extraction data quantity information; the size relation between the two characterizes whether the data volume of the intermediate extraction data can meet the data volume requirement of the required extraction data. Specifically, the step of determining the target extraction data according to the magnitude relation between the data amount of the intermediate extraction data and the data amount corresponding to the extraction data amount information includes:
Step S351, judging whether the data volume of the intermediate extraction data is larger than the data volume corresponding to the extraction data volume information, and if so, determining the intermediate extraction data as target extraction data;
further, comparing the data volume of the intermediate extraction data with the data volume corresponding to the extraction data volume information, and judging whether the data volume of the intermediate extraction data is larger than the data volume represented by the extraction data volume information; if the data quantity of the intermediate extraction data is larger than the data quantity requirement of the required extraction data, the data quantity of the intermediate extraction data is indicated to meet the data quantity requirement of the required extraction data, and therefore the intermediate extraction data is determined to be target extraction data. Considering that the intermediate extraction data may be generated from a plurality of sub-data, that is, the extraction time limit of the plurality of sub-data existing in the operation total data is smaller than the preset time limit, the plurality of sub-data simultaneously form the intermediate extraction data. When intermediate extraction data containing a plurality of items of sub data is formed into target extraction data, the sub data with the longest time from the current time, namely the sub data closest to the same extraction limit, are preferentially set as the target extraction data according to the sequence of the sub data. If the amount of extracted data is a, the sub data in the intermediate extracted data includes D1, D2, D3 and D4, and the sum of the amounts of data between D1 and D2 is larger than the amount of extracted data a, and the sum of the amounts of data between D1 and D3 is also larger than the amount of extracted data a, but the generation time of D2 is longer than D3, then D1 and D2 are preferentially formed as target extracted data. And outputting prompt information for the residual data which is not determined to be the target extraction data in the middle extraction data so as to remind the user that the residual data is about to reach the extraction time limit, and facilitating the timely extraction of the user.
And step S352, if the data quantity corresponding to the extracted data quantity information is not greater than the data quantity corresponding to the extracted data quantity information, setting the intermediate extracted data as first sub-data positioned at the first bit of the time sequence, and executing the step of determining target extracted data according to other sub-data positioned at the rear of the first sub-data in the time sequence.
Further, if the data size of the intermediate extraction data is not greater than the data size corresponding to the extraction data size information, it is indicated that the data size of the intermediate extraction data does not meet the data size requirement of the required extraction data, and the data size requirement of the required extraction data needs to be met together with other sub-data. At this time, the intermediate extraction data is set as first sub-data arranged in the first bit in the time sequence, and target extraction data is determined together according to other sub-data positioned behind the first sub-data in the time sequence; when the data quantity of some sub data in the middle extraction data and the time sequence is commonly larger than the extraction data quantity, the middle extraction data and the sub data are commonly determined to be target extraction data.
Step S36, if the target extraction time limit which is smaller than the preset time limit does not exist, the step of reading the data quantity of each item of sub-data in the account database is executed.
Further, when target extraction data smaller than a preset time limit does not exist in each extraction time limit, the fact that the residual extraction time limit of each piece of sub-data in the account database is longer is indicated, and extraction cannot be performed preferentially; at this time, the data amount of each item of sub data in the account database is read, and the target extraction data is determined by the size relationship between each data amount and the extraction data amount.
In addition, referring to fig. 2, the present invention provides a data extraction device, in a first embodiment of the data extraction device of the present invention, the data extraction device includes:
the detection module 10 is configured to generate operation data of an account according to an operation factor corresponding to an operation transaction when detecting a completion identifier generated by the account for the operation transaction;
a recording module 20 for adding the operation data to an account database of the account and generating an operation number for distinguishing the operation transaction;
an extraction module 30, configured to determine, when an extraction request for the operation data is received, target extraction data from the account database according to information of an amount of extraction data carried by the extraction request;
the generating module 40 is configured to extract the target extraction data and an operation number of the target extraction data in the account database, so as to obtain a data extraction table.
In the data extraction device of the embodiment, when the detection module 10 detects the completion identifier generated by the account for the operation transaction, operation data of the account is generated according to the operation factor corresponding to the operation transaction; and the record module 20 adds the generated operation data to an account database of the account to generate an operation number for distinguishing operation transactions; after that, if an extraction request for the operation data is received, the extraction module 30 determines target extraction data from the account database according to the extraction data amount information carried by the extraction request to perform an extraction operation; the generating module 40 extracts the operation number of the target extraction data in the account database to obtain a data extraction table. According to the scheme, after an operation number generated according to an operation transaction is added to an account database, an operation number for distinguishing the operation things is generated; when an extraction request is received to extract data, determining extractable target extraction data from an account database according to the extraction data amount information carried by the extraction request; and simultaneously extracting the operation number of the target extraction data in the account database to obtain a data extraction table. Because the operation numbers represent the operation transaction from which the target extraction data is derived, each source of the extracted target extraction data can be recorded through the data extraction table obtained by the operation numbers, the problem that the sources of the extracted data of the same type cannot be distinguished is avoided, and the time for positioning and tracking the data is saved.
Further, in another embodiment of the data extraction device of the present invention, the extraction module further includes:
the reading unit is used for reading the data volume of each item of sub data in the account database and judging whether the target data volume consistent with the extracted data volume information exists in each data volume;
a determining unit configured to determine sub data corresponding to the target data amount as target extraction data if there is the target data amount consistent with the extraction data amount information;
the determining unit is further configured to: and if the target data quantity consistent with the extracted data quantity information does not exist, determining target extracted data according to the time sequence of generating the sub data of each item.
Further, in another embodiment of the data extraction device of the present invention, the determining unit is further configured to:
according to the time sequence, reading first sub-data positioned at the first bit of the time sequence, and judging whether the data volume of the first sub-data is larger than the extracted data volume;
if the data quantity of the first sub-data is larger than the extraction data quantity, determining the first sub-data as target extraction data;
And if the data quantity of the first sub data is not larger than the extracted data quantity, determining target extracted data according to other sub data positioned behind the first sub data in the time sequence.
Further, in another embodiment of the data extraction device of the present invention, the determining unit is further configured to:
reading sub-data positioned at the next bit of the first sub-data, and adding the data quantity of the first sub-data and the data quantity of the sub-data to generate an addition result;
judging whether the addition result is larger than the extraction data amount, if so, determining the first sub-data and the sub-data as target extraction data;
if the addition result is not greater than the extracted data quantity, reading the secondary sub-data positioned at the next bit after the secondary sub-data, and adding the data quantity of the secondary sub-data and the addition result to update the addition result;
and executing the step of judging whether the addition result is larger than the extraction data amount or not on the updated addition result until the addition result is larger than the extraction data amount, and determining each item of sub-data generating the addition result as target extraction data.
Further, in another embodiment of the data extraction device of the present invention, the generating module further includes:
the first judging unit is used for extracting the target extraction data, judging whether the item number of the sub data corresponding to the target extraction data is a single item or not, and if the item number is a single item, reading the operation number of the sub data corresponding to the target extraction data in the account database and adding the operation number to a preset data table to obtain a data extraction table;
and the adding unit is used for sequentially reading the operation numbers of all sub-data corresponding to the target extraction data in the account database and adding the operation numbers to a preset data table if the number of the items is not single, so as to obtain a data extraction table.
Further, in another embodiment of the data extraction device of the present invention, the extraction module further includes:
the second judging unit is used for reading the extraction time limit of each piece of sub-data in the account database and judging whether a target extraction time limit smaller than a preset time limit exists in each extraction time limit;
the determining unit is further configured to: if the target extraction time limit is smaller than the preset time limit, determining sub-data corresponding to the target extraction time limit as intermediate extraction data, and determining target extraction data according to the size relation between the data quantity of the intermediate extraction data and the data quantity corresponding to the extraction data quantity information;
And the execution unit is used for executing the step of reading the data quantity of each item of sub-data in the account database if the target extraction time limit which is smaller than the preset time limit does not exist.
Further, in another embodiment of the data extraction device of the present invention, the determining unit is further configured to:
judging whether the data quantity of the intermediate extraction data is larger than the data quantity corresponding to the extraction data quantity information, and if so, determining the intermediate extraction data as target extraction data;
and if the data quantity is not greater than the data quantity corresponding to the extracted data quantity information, setting the intermediate extracted data as first sub-data positioned at the first position of the time sequence, and executing the step of determining target extracted data according to other sub-data positioned at the rear position of the first sub-data in the time sequence.
The virtual function modules of the data extraction apparatus are stored in the memory 1005 of the data extraction device shown in fig. 3, and when the processor 1001 executes the data extraction program, the functions of the modules in the embodiment shown in fig. 2 are implemented.
Referring to fig. 3, fig. 3 is a schematic device structure of a hardware running environment related to a method according to an embodiment of the present invention.
The data extraction device in the embodiment of the invention can be a PC (personal computer ) or terminal devices such as a smart phone, a tablet personal computer, an electronic book reader, a portable computer and the like.
As shown in fig. 3, the data extraction apparatus may include: a processor 1001, such as a CPU (Central Processing Unit ), a memory 1005, and a communication bus 1002. Wherein a communication bus 1002 is used to enable connected communication between the processor 1001 and a memory 1005. The memory 1005 may be a high-speed RAM (random access memory ) or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Optionally, the data extraction device may further include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, audio circuitry, wiFi (Wireless Fidelity, wireless broadband) modules, and the like. The user interface may comprise a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).
It will be appreciated by those skilled in the art that the data extraction device structure shown in fig. 3 does not constitute a limitation of the data extraction device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 3, an operating system, a network communication module, and a data extraction program may be included in the memory 1005, which is one type of computer-readable storage medium. An operating system is a program that manages and controls the hardware and software resources of a data extraction device, supporting the execution of data extraction programs and other software and/or programs. The network communication module is used to enable communication between components within the memory 1005 and with other hardware and software in the data extraction device.
In the data extraction apparatus shown in fig. 3, a processor 1001 is configured to execute a data extraction program stored in a memory 1005, and implement the steps in the embodiments of the data extraction method described above.
The present invention provides a computer-readable storage medium storing one or more programs that are further executable by one or more processors for implementing the steps in the embodiments of the data extraction method described above.
It should also be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a computer readable storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structural changes made by the specification and drawings of the present invention or direct/indirect application in other related technical fields are included in the scope of the present invention.
Claims (7)
1. A data extraction method, characterized in that the data extraction method comprises the steps of:
when detecting a completion identification generated by an account for an operation transaction, generating operation data of the account according to an operation factor corresponding to the operation transaction;
adding the operation data to an account database of the account, and generating an operation number for distinguishing the operation transaction;
when an extraction request for the operation data is received, determining target extraction data from the account database according to the extraction data amount information carried by the extraction request;
extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table;
the step of determining target extraction data from the account database according to the extraction data amount information carried by the extraction request comprises the following steps:
Reading the data volume of each item of sub data in the account database, and judging whether target data volume consistent with the extracted data volume information exists in each data volume;
if the target data quantity consistent with the extracted data quantity information exists, determining sub-data corresponding to the target data quantity as target extracted data;
if the target data quantity consistent with the extracted data quantity information does not exist, determining target extracted data according to the time sequence of generating the sub data of each item;
wherein, the step of determining the target extraction data according to the time sequence of generating the sub data of each item comprises the following steps:
according to the time sequence, reading first sub-data positioned at the first bit of the time sequence, and judging whether the data volume of the first sub-data is larger than the extracted data volume;
if the data quantity of the first sub-data is larger than the extraction data quantity, determining the first sub-data as target extraction data;
if the data quantity of the first sub data is not larger than the extracted data quantity, determining target extracted data according to other sub data positioned behind the first sub data in the time sequence;
The step of extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table comprises the following steps:
extracting the target extraction data, judging whether the item number of the sub data corresponding to the target extraction data is a single item, and if the item number is a single item, reading the operation number of the sub data corresponding to the target extraction data in the account database and adding the operation number to a preset data table to obtain a data extraction table;
and if the item number is not a single item, sequentially reading the operation numbers of all sub-data corresponding to the target extraction data in the account database, and adding the operation numbers to a preset data table to obtain a data extraction table.
2. The data extraction method as claimed in claim 1, wherein the step of determining target extraction data based on other sub-data located after the first sub-data in the chronological order comprises:
reading sub-data positioned at the next bit of the first sub-data, and adding the data quantity of the first sub-data and the data quantity of the sub-data to generate an addition result;
Judging whether the addition result is larger than the extraction data amount, if so, determining the first sub-data and the sub-data as target extraction data;
if the addition result is not greater than the extracted data quantity, reading the secondary sub-data positioned at the next bit after the secondary sub-data, and adding the data quantity of the secondary sub-data and the addition result to update the addition result;
and executing the step of judging whether the addition result is larger than the extraction data amount or not on the updated addition result until the addition result is larger than the extraction data amount, and determining each item of sub-data generating the addition result as target extraction data.
3. The data extraction method according to claim 1, wherein the step of reading the data amounts of the respective sub-data items in the account database and judging whether or not there is a target data amount in accordance with the extracted data amount information in the respective data amounts includes, before:
reading the extraction time limit of each piece of sub-data in the account database, and judging whether a target extraction time limit smaller than a preset time limit exists in each extraction time limit;
If the target extraction time limit is smaller than the preset time limit, determining sub-data corresponding to the target extraction time limit as intermediate extraction data, and determining target extraction data according to the size relation between the data quantity of the intermediate extraction data and the data quantity corresponding to the extraction data quantity information;
and if the target extraction time limit which is smaller than the preset time limit does not exist, executing the step of reading the data quantity of each item of sub-data in the account database.
4. The data extraction method as claimed in claim 3, wherein the step of determining the target extraction data based on a size relationship between the data amount of the intermediate extraction data and the data amount corresponding to the extraction data amount information comprises:
judging whether the data quantity of the intermediate extraction data is larger than the data quantity corresponding to the extraction data quantity information, and if so, determining the intermediate extraction data as target extraction data;
and if the data quantity is not greater than the data quantity corresponding to the extracted data quantity information, setting the intermediate extracted data as first sub-data positioned at the first position of the time sequence, and executing the step of determining target extracted data according to other sub-data positioned at the rear position of the first sub-data in the time sequence.
5. A data extraction device, characterized in that the data extraction device comprises:
the detection module is used for generating operation data of the account according to the operation factors corresponding to the operation transaction when detecting the completion identification generated by the account on the operation transaction;
the recording module is used for adding the operation data into an account database of the account and generating an operation number for distinguishing the operation transaction;
the extraction module is used for determining target extraction data from the account database according to the extraction data amount information carried by the extraction request when the extraction request of the operation data is received;
the generation module is used for extracting the target extraction data and the operation number of the target extraction data in the account database to obtain a data extraction table;
the extraction module is further used for reading the data volume of each item of sub data in the account database and judging whether the target data volume consistent with the extracted data volume information exists in each data volume; if the target data quantity consistent with the extracted data quantity information exists, determining sub-data corresponding to the target data quantity as target extracted data; if the target data quantity consistent with the extracted data quantity information does not exist, determining target extracted data according to the time sequence of generating the sub data of each item;
The extraction module is further used for reading first sub-data positioned at the first position of the time sequence according to the time sequence, and judging whether the data volume of the first sub-data is larger than the extraction data volume; if the data quantity of the first sub-data is larger than the extraction data quantity, determining the first sub-data as target extraction data; if the data quantity of the first sub data is not larger than the extracted data quantity, determining target extracted data according to other sub data positioned behind the first sub data in the time sequence;
the generation module is further configured to extract the target extraction data, determine whether the number of items of the sub-data corresponding to the target extraction data is a single item, and if the number of items is a single item, read an operation number of the sub-data corresponding to the target extraction data in the account database and add the operation number to a preset data table to obtain a data extraction table; and if the item number is not a single item, sequentially reading the operation numbers of all sub-data corresponding to the target extraction data in the account database, and adding the operation numbers to a preset data table to obtain a data extraction table.
6. A data extraction apparatus, characterized in that the data extraction apparatus comprises: a memory, a processor, a communication bus, and a data extraction program stored on the memory;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute the data extraction program to implement the steps of the data extraction method according to any one of claims 1-4.
7. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a data extraction program which, when executed by a processor, implements the steps of the data extraction method according to any one of claims 1-4.
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