CN117132413A - Account checking method and device based on network live broadcast scene - Google Patents
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Abstract
The application provides a method and a device for checking account based on a network live broadcast scene, wherein the method for checking account based on the network live broadcast scene comprises the following steps: dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data; generating corresponding sub processing tasks for each data block, and generating corresponding processing results; and checking account data according to the processing result in a pre-generated offline database. Under the condition of not affecting on-line business, the application automatically checks the gift sending flow, the settlement flow, the divided amount and the user account amount in order dimension in a shorter time through synchronous off-line data so as to ensure that abnormal accounts are found in a shorter time.
Description
Technical Field
The application relates to the technical field of information processing, in particular to the technical field of financial data processing under financial business, and particularly relates to a method and a device for checking accounts based on a network live broadcast scene.
Background
At present, with the rapid development of internet technology, the market of network live broadcast is larger and larger, in a network live broadcast scene, a host broadcast pushes video data to audiences to realize application purposes such as talent showing, information sharing, good recommendation, knowledge education and the like, correspondingly, some audiences can send out some gifts to the host broadcast, the host broadcast obtains benefits, the audiences of some host broadcast are numerous, the corresponding benefits of the host broadcast are more, and the benefits need to be divided with a live broadcast platform, so that the benefits need to be checked out, and in the prior art, the checking method generally comprises the following steps:
the method comprises the following steps: manual reconciliation was performed using excel. The method is only suitable for checking in a small amount of data, and is time-consuming and labor-consuming by manual checking in a large data scene, and the possibility of errors is greatly increased
The second method is as follows: the account checking is checked using a special program when the month settlement is performed next month. However, the error of the bill of the method can not be found in time in the worst case only after a natural month
And a third method: after each transaction is completed, the program automatically performs a secondary check in real time. The method slows down the processing speed of the program, and simultaneously reads the business data, thereby increasing the burden of the database
In view of the foregoing, there is a need in the art for a billing method in a live webcast scenario that occupies less network and effort and saves manpower.
Disclosure of Invention
According to the account checking method and device based on the network live broadcast scene, provided by the application, the check of the gift sending line, the settlement line, the divided amount and the user account amount is automatically carried out in order dimension in a shorter time through synchronous offline data under the condition of not affecting online business, so that abnormal accounts can be found in a shorter time.
In order to achieve the above object, in a first aspect, the present application provides a reconciliation method based on a live network scenario, including:
dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
generating corresponding sub processing tasks for each data block, and generating corresponding processing results;
and checking account data according to the processing result in a pre-generated offline database.
In an embodiment, the dividing the accounting data into at least two data blocks according to the accounting data structure of the live network scene includes:
dividing the accounting data according to the primary key and/or the column in the accounting data structure.
In one embodiment, the sub-processing tasks include at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
In one embodiment, the accounting data in the processing result is a database table;
the account checking method based on the network live broadcast scene further comprises the following steps:
and importing the processing result into the offline database.
In an embodiment, the checking the accounting data according to the processing result in the pre-generated offline database includes:
converting the sub-processing tasks into a programming model;
mapping the data structure of the processing result into key value pairs according to the programming model;
generating a reduction function according to the programming model and the accounting data structure;
and checking the account data according to the reduction function and the key value in a pre-generated offline database.
In a second aspect, the present application provides a reconciliation device in a live network scenario, the device comprising:
the accounting data dividing module is used for dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
the processing result generation module is used for generating corresponding sub processing tasks for each data block and generating corresponding processing results;
and the accounting checking module is used for checking the accounting data according to the processing result in the pre-generated offline database.
In one embodiment, the accounting data dividing module includes:
and the accounting data dividing unit is used for dividing the accounting data according to the main key and/or the column in the accounting data structure.
In one embodiment, the sub-processing tasks include at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
In one embodiment, the accounting data in the processing result is a database table;
the account checking device based on the network live broadcast scene further comprises:
and the result importing module is used for importing the processing result into the offline database.
In one embodiment, the accounting checking module includes:
the programming model conversion unit is used for converting the subsection processing task into a programming model;
the data structure mapping unit is used for mapping the data structure of the processing result into key value pairs according to the programming model;
a reduction function generating unit for generating a reduction function according to the programming model and the accounting data structure;
and the accounting checking unit is used for checking the accounting data according to the reduction function and the key value in a pre-generated offline database.
In a third aspect, the present application provides a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of a reconciliation method in a live-network-based scenario.
In a fourth aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing steps of a reconciliation method in a live-network-based scenario when the program is executed by the processor.
In a fifth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a reconciliation method in a live-network-based scenario.
As can be seen from the above description, the accounting method and device based on the network live broadcast scene provided by the embodiment of the application include: firstly, dividing accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data; then, generating corresponding sub processing tasks for each data block, and generating corresponding processing results; and finally, checking account data according to the processing result in a pre-generated offline database.
By using the account checking method and device based on the network live broadcast scene provided by the embodiment of the application, offline data corresponding to account checking data can be used in the live broadcast scene, and the correctness of gift sending flow, settlement flow, divided amount and user account amount can be automatically checked in T+1 days, so that the abnormal amount condition of the order level can be found in time.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a reconciliation method based on a network live scenario provided in an embodiment of the present application;
fig. 2 is a flowchart illustrating a step 100 of a reconciliation method in a live-network scenario in an embodiment of the application;
fig. 3 is another flow chart of a reconciliation method based on a live network scenario provided in an embodiment of the present application;
fig. 4 is a flowchart illustrating a step 300 of a reconciliation method in a live-network scenario in an embodiment of the application;
fig. 5 is a schematic flow chart of a reconciliation method based on a live network scenario in a specific application example of the present application;
FIG. 6 is a schematic diagram of the composition of data sources and reconciliation tasks in an embodiment of the application;
fig. 7 is a diagram illustrating the mind of a reconciliation method based on a live scene in a specific application example of the present application;
fig. 8 is a schematic structural diagram of a reconciliation device in a live network scenario in an embodiment of the application;
fig. 9 is a schematic structural diagram of an accounting data dividing module 10 according to an embodiment of the present application;
fig. 10 is a schematic diagram of another structure of a reconciliation device in a live network scenario according to an embodiment of the application;
fig. 11 is a schematic structural diagram of an accounting module 30 according to an embodiment of the present application;
fig. 12 is a schematic structural diagram of an electronic device in an embodiment of the application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present application and in the foregoing figures, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
According to the technical scheme, the data are acquired, stored, used and processed according with relevant regulations of laws and regulations.
The embodiment of the application provides a specific implementation manner of a reconciliation method based on a network live broadcast scene, and referring to fig. 1, the method specifically comprises the following steps:
step 100: dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
step 200: generating corresponding sub processing tasks for each data block, and generating corresponding processing results;
step 300: and checking account data according to the processing result in a pre-generated offline database.
As can be seen from the above description, the accounting method based on the network live broadcast scene provided by the embodiment of the present application includes: firstly, dividing accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data; then, generating corresponding sub processing tasks for each data block, and generating corresponding processing results; and finally, checking account data according to the processing result in a pre-generated offline database.
By using the account checking method based on the network live broadcast scene provided by the embodiment of the application, the account checking error sensing can be shortened to be within 24 hours, so that the fund security of live broadcast gift delivery and live broadcast commodity settlement can be ensured.
For step 100, the accounting data generally includes: sales revenue, rewards revenue, platform rewards, pot fees, and advertising fees, and in addition, the accounting data structure includes at least one of: an array, stack, queue, linked list, tree, graph, skip list, heap, and hash table.
The array is used for storing the same type of data in the accounting data, and the data can be accessed and updated through the array name and the subscript. The storage of the elements in the array is performed according to the sequence, and meanwhile, the elements are continuously stored in the memory according to the sequence. The spacing of memory addresses between adjacent elements of an array is typically the size of the array data type.
Each node in the linked list contains the data for that node and a pointer to the address of the next node. The pointer is used for searching and accessing the next data element, so that the freedom degree of the linked list is higher. This is represented by the fact that when nodes are added and deleted, only the pointer address of the previous node needs to be modified, and other nodes do not need to be changed. However, things have two poles, and the pointer brings high freedom degree and naturally sacrifices the efficiency of data searching and the use of redundant space. It is common to have a single-stranded list with a head and a tail, and reverse link pointer fields, and may also form a doubly linked list or a circularly linked list.
In addition, it should be noted that the accounting data in step 100 is not current accounting data, but historical accounting data, preferably accounting data before t+1 days (e.g., 1 day before nature) is selected.
In one embodiment, the generation of the distributed processing tasks for each data block in step 200 is dependent on the structure of the accounting data, the volume of the accounting data, and the corresponding live scenes (sales revenue, rewards, platform rewards, pit fees, and advertising fees).
It can be understood that the accounting data of the network live broadcast scene is imported into the offline database for checking account, so that the aims of checking the gift sending line, the settlement line, the divided amount and the user account amount automatically in order dimension in a shorter time can be achieved through the synchronous offline data under the condition of not influencing the online service.
In one embodiment, referring to fig. 2, step 100 comprises:
step 101: dividing the accounting data according to the primary key and/or the column in the accounting data structure.
The primary key is here a column or a combination of columns whose value can uniquely identify each row in the table, which can enhance the physical integrity of the table. The primary key is mainly associated with foreign keys of other tables, and the modification and deletion of text records.
The primary keys are typically of the following types:
the single field primary key, which contains only one field primary key, is typically of a self-growing integer type. The primary key has the advantages of simplicity and easiness in use, but has the disadvantages of possibly causing hot spot problems and poor data expansibility.
The composite primary key is a primary key composed of a plurality of fields. The advantage of such a primary key is that a record can be identified more accurately, but the disadvantage is that the efficiency of querying and updating is low.
Globally unique primary keys are implemented using Globally Unique Identifiers (GUIDs). The advantage of such a primary key is that the uniqueness of the data can be guaranteed in a distributed system, but the disadvantage is that the occupation space is large and the query efficiency is low.
The natural main key is a main key composed of some attributes of the record itself, such as an identification card number, a mobile phone number, etc. The advantage of such a primary key is easy understanding and use, but the disadvantage is that it may lead to problems of poor data extensibility.
When the primary key is a single-field primary key or a globally unique primary key, and the type of the column is a date-time type (year, timestamp, time, date, datetime), the accounting data is vertically divided, namely, a table with a preset number of columns is created, and part of columns of each table source table are created, so that the data can be distinguished.
When the primary key is a compound primary key or a natural primary key, and the type of the column is a character string (year, timestamp, time, date, datetime), the accounting data is stored into different tables according to different partitioning algorithms.
In one embodiment, the sub-processing tasks include at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
Preferably, the sub-processing task is a MapReduce task, which mainly comprises two parts: map tasks and Reduce tasks. The Map task is responsible for acquiring, dividing and processing data, and the core execution method is a Map () method. Specifically, input data is obtained from an HDFS system, an input large data set is divided into a plurality of small data sets, the small data sets are calculated in parallel, the results are summarized, and the final calculation result is obtained and is output to the HDFS system.
In one embodiment, the accounting data in the processing result is a database table;
specifically, the database table includes: data table name, table structure, field name, type, value, and header information (including primary key, foreign key, index, etc.).
The step of creating the database table corresponding to the accounting data comprises the following steps: and then, mapping the accounting data into the database table according to the parameters of the logical file names, the physical files, the initial sizes, the file groups and the like of the data files and the log files.
In an embodiment, referring to fig. 3, the reconciliation method in the live webcast scenario further includes:
step 400: and importing the processing result into the offline database.
An offline database is a database that can be used without a connection to a network. Are commonly used for data storage and management without an internet connection. It can perform operations on data without a network, such as storing and retrieving data.
The using method of the offline database is as follows: first a database needs to be installed on the local computer. Then, in the installed client software, the name and the password of the database to be used are input, and the client software logs in to the corresponding server. Next, a new offline database is created in the client software and connected to the local computer. Finally, the data is copied from the server to a local offline database.
Offline databases have many advantages over online databases. Firstly, under the condition of no internet connection, the offline database can manage and operate the data through the local computer; second, since all data is stored on the local computer, a faster data response speed can be obtained; finally, the offline database may guarantee the privacy and security of the data because it cannot be accessed through the internet.
In one embodiment, referring to fig. 4, step 300 comprises:
step 301: converting the sub-processing tasks into a programming model;
preferably, the programming model is MapReduce, which is used to perform corresponding processing on multiple data blocks in parallel.
Step 302: mapping the data structure of the processing result into key value pairs according to the programming model;
first, a set of intermediate key-value pairs is generated following the key-value pairs of the processing result. Next, the MapReduce framework passes the key-identical values in the intermediate key-value pairs generated by the map function to a reduce function that merges the key-identical values to generate a set of smaller-scale values, i.e., key-value pairs in step 302.
Step 303: generating a reduction function according to the programming model and the accounting data structure;
the reduction function in step 303 is used to apply the sub-processing task successively to the elements of the processing result and to accumulate the previous results to reduce a series of values to one value.
Step 304: and checking the account data according to the reduction function and the key value in a pre-generated offline database.
And utilizing a reduction function to account data characterized in the key value pair so as to fulfill the aim of checking account data.
As can be seen from the above description, the accounting method based on the network live broadcast scene provided by the embodiment of the present application includes: firstly, dividing accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data; then, generating corresponding sub processing tasks for each data block, and generating corresponding processing results; and finally, checking account data according to the processing result in a pre-generated offline database.
By using the account checking method based on the network live broadcast scene provided by the embodiment of the application, offline data corresponding to account checking data can be used in the live broadcast scene, and the correctness of gift sending flow, settlement flow, divided amount and user account amount can be automatically checked in T+1 days, so that the abnormal amount condition of the order level can be found in time.
To further illustrate the solution, the present application provides a specific application example of the reconciliation method in a live network scenario, which specifically includes the following matters, see fig. 5 to 7.
The application aims to provide a checking method based on a network live broadcast scene, which automatically checks gift sending line, settlement line, divided amount and user account amount in order dimension on T+1 day through offline data synchronized by big data tools (without affecting online business) so as to ensure that abnormal orders are found in a short time (within 24 h).
S1: and synchronizing data in the reconciliation database in the live broadcast scene after T+1 days into an offline large data table.
It will be appreciated that the offline data query and calculation will not affect the online business, and it should be noted that, in a live scenario, for activities with asset changes, such as gift delivery and merchandise purchase, a duplex billing method is adopted, and both the upstream and downstream systems need to record the order (both the upstream and downstream systems use the duplex billing method, each of which independently stores the order records).
Specifically, the Sqoop tool is used for synchronizing the accounting data into the Hive data warehouse, the Sqoop bottom layer realizes extraction, conversion and loading by using a tez program, in the synchronization process, parallelization and high fault tolerance are required to be ensured, compared with the traditional ETL tools such as Kettle, tasks run on the Hadoop cluster, the use condition of ETL server resources is reduced, and the on-line service is not influenced by the query and calculation of off-line data in the data warehouse.
Further, referring to FIG. 6, the data sources (gift sending system/gift sending record, settlement system/settlement record, and wallet system/line detail record) are synchronized into a large data table offline.
S2: the reconciliation task is written using the ETL tool.
Checking the amount of the upstream and downstream flow records, checking the difference, specifically using SQL flexible customization rules, associating the form data (such as gift sending order and settlement order, settlement order and recharging order) related to the upstream and downstream according to the time period and the flow number, screening abnormal orders with inconsistent amount and missing amount, and finally writing the abnormal order records into a designated data warehouse table.
Specifically, referring to fig. 6, the reconciliation task in step S2 is divided into daily reconciliation and monthly reconciliation in time, where the daily reconciliation and monthly reconciliation further include: gift records, settlement records, and wallet details records.
S3: and summarizing the checking result and the difference order information.
And finally, informing relevant staff of the checking result and the difference order information through mail.
Based on the same inventive concept, the embodiment of the application also provides a reconciliation device based on a network live broadcast scene, which can be used for realizing the method described in the above embodiment, such as the following embodiment. Because the principle of solving the problem based on the account checking device in the network live broadcast scene is similar to that based on the account checking method in the network live broadcast scene, the implementation of the account checking device in the network live broadcast scene can be implemented by referring to the account checking method in the network live broadcast scene, and the repetition is omitted. As used below, the term "unit" or "module" may be a combination of software and/or hardware that implements the intended function. While the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The embodiment of the application provides a concrete implementation mode of a checking device based on a network live broadcast scene, which can realize a checking method based on the network live broadcast scene, referring to fig. 8, the checking device based on the network live broadcast scene specifically comprises the following contents:
the accounting data dividing module 10 is configured to divide the accounting data into at least two data blocks according to an accounting data structure of a live network scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
a processing result generating module 20, configured to generate a corresponding sub-processing task for each data block, and generate a corresponding processing result;
and the accounting checking module 30 is configured to check the accounting data according to the processing result in a pre-generated offline database.
In one embodiment, referring to fig. 9, the accounting data dividing module 10 includes:
and the accounting data dividing unit 10a is used for dividing the accounting data according to the primary key and/or the column in the accounting data structure.
In one embodiment, the sub-processing tasks include at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
In one embodiment, the accounting data in the processing result is a database table;
in an embodiment, referring to fig. 10, the reconciliation device in the live webcast scenario further includes:
and a result importing module 40, configured to import the processing result into the offline database.
In one embodiment, referring to fig. 11, the accounting module 30 includes:
a programming model conversion unit 30a for converting the sub-processing tasks into programming models;
a data structure mapping unit 30b, configured to map the data structure of the processing result into key value pairs according to the programming model;
a reduction function generating unit 30c for generating a reduction function according to the programming model and the accounting data structure;
and the accounting checking unit 30d is configured to check the accounting data according to the reduction function and the key value in a pre-generated offline database.
As can be seen from the above description, the accounting device based on the network live broadcast scene provided by the embodiment of the present application includes: firstly, dividing accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data; then, generating corresponding sub processing tasks for each data block, and generating corresponding processing results; and finally, checking account data according to the processing result in a pre-generated offline database.
By using the account checking device based on the network live broadcast scene provided by the embodiment of the application, offline data corresponding to account checking data can be used in the live broadcast scene, and the correctness of gift sending flow, settlement flow, divided amount and user account amount can be automatically checked in T+1 days, so that the abnormal amount condition of the order level can be found in time.
The embodiment of the present application further provides a specific implementation manner of an electronic device capable of implementing all the steps in the accounting method based on the network live broadcast scene in the foregoing embodiment, and referring to fig. 12, the electronic device specifically includes the following contents:
a processor 1201, a memory 1202, a communication interface (Communications Interface) 1203, and a bus 1204;
wherein the processor 1201, the memory 1202 and the communication interface 1203 perform communication with each other through the bus 1204; the communication interface 1203 is configured to implement information transmission between related devices such as a server device, a power measurement device, and a user device.
The processor 1201 is configured to invoke a computer program in the memory 1202, and when the processor executes the computer program, the processor implements all the steps in the reconciliation method based on the live webcast scenario in the above embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
step 100: dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
step 200: generating corresponding sub processing tasks for each data block, and generating corresponding processing results;
step 300: and checking account data according to the processing result in a pre-generated offline database.
The embodiment of the present application also provides a computer-readable storage medium capable of implementing all the steps in the accounting method in the network live-based scenario in the above embodiment, on which a computer program is stored, which when executed by a processor implements all the steps in the accounting method in the network live-based scenario in the above embodiment, for example, the processor implements the following steps when executing the computer program:
step 100: dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
step 200: generating corresponding sub processing tasks for each data block, and generating corresponding processing results;
step 300: and checking account data according to the processing result in a pre-generated offline database.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for a hardware+program class embodiment, the description is relatively simple, as it is substantially similar to the method embodiment, as relevant see the partial description of the method embodiment.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Although the application provides method operational steps as an example or a flowchart, more or fewer operational steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When implemented by an actual device or client product, the instructions may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment) as shown in the embodiments or figures.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present application have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (13)
1. The account checking method based on the network live broadcast scene is characterized by comprising the following steps of:
dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
generating corresponding sub processing tasks for each data block, and generating corresponding processing results;
and checking account data according to the processing result in a pre-generated offline database.
2. The method of claim 1, wherein the dividing the accounting data into at least two data blocks according to an accounting data structure of a live network scene comprises:
dividing the accounting data according to the primary key and/or the column in the accounting data structure.
3. The reconciliation method of claim 1, wherein the branch processing tasks comprise at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
4. The reconciliation method of claim 1, wherein the accounting data in the processing results is a database table;
the account checking method based on the network live broadcast scene further comprises the following steps:
and importing the processing result into the offline database.
5. The reconciliation method of claim 1, wherein reconciling the accounting data based on the processing results in the pre-generated offline database comprises:
converting the sub-processing tasks into a programming model;
mapping the data structure of the processing result into key value pairs according to the programming model;
generating a reduction function according to the programming model and the accounting data structure;
and checking the account data according to the reduction function and the key value in a pre-generated offline database.
6. The utility model provides a checking account device based on network live broadcast scene, its characterized in that includes:
the accounting data dividing module is used for dividing the accounting data into at least two data blocks according to an accounting data structure of a network live broadcast scene, wherein the accounting data structure is a relational data structure, and the accounting data is historical accounting data;
the processing result generation module is used for generating corresponding sub processing tasks for each data block and generating corresponding processing results;
and the accounting checking module is used for checking the accounting data according to the processing result in the pre-generated offline database.
7. The reconciliation apparatus of claim 6, wherein the accounting data splitting module comprises:
and the accounting data dividing unit is used for dividing the accounting data according to the main key and/or the column in the accounting data structure.
8. The reconciliation apparatus of claim 6, wherein the subsection processing tasks comprise at least one of: acquisition, segmentation, distributed storage, work scheduling, load balancing, and fault tolerance processing.
9. The reconciliation apparatus of claim 6, wherein the accounting data in the processing results is a database table;
the account checking device based on the network live broadcast scene further comprises:
and the result importing module is used for importing the processing result into the offline database.
10. The reconciliation apparatus of claim 6, wherein the accounting reconciliation module comprises:
the programming model conversion unit is used for converting the subsection processing task into a programming model;
the data structure mapping unit is used for mapping the data structure of the processing result into key value pairs according to the programming model;
a reduction function generating unit for generating a reduction function according to the programming model and the accounting data structure;
and the accounting checking unit is used for checking the accounting data according to the reduction function and the key value in a pre-generated offline database.
11. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the reconciliation method in a live-network-based scenario of any one of claims 1 to 5.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method for checking accounts in a live network-based scenario according to any one of claims 1 to 5 when the program is executed by the processor.
13. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the reconciliation method in a live-network-based scenario of any of claims 1 to 5.
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