CN116911973A

CN116911973A - Automatic account checking analysis method and device, electronic equipment and readable storage medium

Info

Publication number: CN116911973A
Application number: CN202311005250.XA
Authority: CN
Inventors: 丁家琳
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2023-08-09
Filing date: 2023-08-09
Publication date: 2023-10-20

Abstract

The application relates to the technical field of financial science and technology, and provides an automatic account checking analysis method, an automatic account checking analysis device, electronic equipment and a computer readable storage medium, wherein the method comprises the following steps: detecting a log table every time a preset time interval passes to obtain log state information, wherein the log table is obtained by executing a preset first task and a preset second task; under the condition that log state information characterizes that the execution of the first task and the second task is completed, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table, and determining a corresponding general account checking task according to the task message queue key value; executing the general account checking task to obtain account checking data; performing account checking detection processing on account checking data based on a preset account checking script to obtain account checking statistical data; and storing and processing the account checking statistical data based on a preset account checking result table. Through the technical scheme, the data checking efficiency can be improved.

Description

Automatic account checking analysis method and device, electronic equipment and readable storage medium

Technical Field

The embodiment of the application relates to the technical field of financial science and technology, in particular to an automatic reconciliation analysis method, an automatic reconciliation analysis device, electronic equipment and a computer readable storage medium.

Background

Currently, various systems have been increasingly utilized in the financial industry to manage various financial services; in the upgrading and reconstruction process of the financial system, reconstruction and reconstruction of batch programs are often required, and verification is required to be performed after the program reconstruction is completed in a test operation period; the test run needs to be executed in parallel with the original task, and data comparison is continuously carried out with the original task to ensure that the logic of the reconstructed task is correct, and after the data comparison is consistent, the reconstructed task can be formally switched to put into production, and the old task can be put off line. However, data consistency comparison is a cumbersome process, and a large amount of manpower is required to perform comparison analysis, thereby causing huge workload.

Disclosure of Invention

The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

In order to solve the problems mentioned in the background art, embodiments of the present application provide an automatic reconciliation analysis method, an apparatus, an electronic device, and a computer readable storage medium, which can improve the efficiency of data reconciliation.

In a first aspect, an embodiment of the present application provides an automatic reconciliation analysis method, including:

Detecting a log table every time a preset time interval passes to obtain log state information, wherein the log table is obtained by executing a preset first task and a preset second task;

under the condition that the log state information characterizes that the execution of the first task and the execution of the second task are completed, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table;

determining a corresponding general account checking task according to the task message queue key value;

executing the general account checking task to obtain account checking data;

checking account detection processing is carried out on the checking account data based on a preset checking account script to obtain checking account statistical data;

and storing and processing the reconciliation statistics data based on a preset reconciliation result table.

According to some embodiments of the present application, the detecting the log table every time a preset time interval passes to obtain log status information includes:

setting the waiting time of a preset heartbeat task to obtain task waiting time;

determining the task waiting time as the preset time interval;

and carrying out state matching processing on the configuration information in the automatic trigger task configuration table and the log in the log table to obtain the log state information every time the preset time interval passes.

According to some embodiments of the present application, the reconciliation script includes a checking script and a statistics script, and the reconciliation detection processing is performed on the reconciliation data based on a preset reconciliation script to obtain reconciliation statistics data, including:

performing integrity check processing on the account checking data based on the check script to obtain check information;

and under the condition that the checking information characterizes that the reconciliation data is generated, carrying out statistical processing on the reconciliation data based on the statistical script to obtain the reconciliation statistical data.

According to some embodiments of the application, the log status information includes log attribute information, and the extracting the corresponding task message queue key value from the preset auto-triggering task configuration table includes:

matching the log attribute information with task attributes carried by the automatic triggering task configuration table to obtain a matching result;

and extracting the task message queue key value corresponding to the task attribute from the automatic trigger task configuration table according to the matching result.

According to some embodiments of the application, the performing the general reconciliation task to obtain reconciliation data includes:

Comparing the first execution data with the second execution data according to the general reconciliation task to obtain reconciliation data;

wherein the first execution data is obtained by executing the first task, and the second execution data is obtained by executing the second task.

According to some embodiments of the application, after the storing the accounting data based on the preset accounting result table, the method further includes:

extracting the account checking statistical data in the account checking result table;

packaging the extracted account checking statistical data to obtain a statistical data packet;

and sending the statistical data packet to a preset mailbox address.

According to some embodiments of the application, the packaging the extracted accounting statistics to obtain a statistics packet includes:

compressing the account checking statistical data to obtain a compressed data packet;

and marking the compressed data packet to obtain the statistical data packet.

In a second aspect, an embodiment of the present application further provides an automatic reconciliation analysis apparatus, including:

the first processing module is used for detecting and processing the log table every time a preset time interval passes to obtain log state information, wherein the log table is obtained by executing a preset first task and a preset second task;

The second processing module is used for extracting a corresponding task message queue key value from a preset automatic trigger task configuration table under the condition that the log state information characterizes that the execution of the first task and the execution of the second task are completed;

the third processing module is used for determining a corresponding general account checking task according to the task message queue key value;

the fourth processing module is used for executing the general reconciliation task to obtain reconciliation data;

the fifth processing module is used for performing checking detection processing on the checking data based on a preset checking script to obtain checking statistical data;

and the sixth processing module is used for storing and processing the reconciliation statistics data based on a preset reconciliation result table.

In a third aspect, an embodiment of the present application further 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 the automated reconciliation analysis method as described in the first aspect above when the computer program is executed.

In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium storing computer-executable instructions for performing the automated reconciliation analysis method of the first aspect described above.

According to the automatic account checking analysis method provided by the embodiment of the application, the method has at least the following beneficial effects: in the process of automatic account checking analysis, detecting and processing a log table every time a preset time interval passes to obtain log state information, wherein the log table is obtained by executing a preset first task and a preset second task; under the condition that the log state information characterizes that the execution of the first task and the execution of the second task are completed, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table; then determining a corresponding general account checking task according to the task message queue key value; the general account checking task is executed to obtain account checking data; then, checking account detection processing is carried out on the checking account data based on a preset checking account script, so that checking account statistical data can be obtained; and finally, storing and processing the account checking statistical data based on a preset account checking result table. Through the technical scheme, the data checking efficiency can be improved.

Drawings

The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate and do not limit the application.

FIG. 1 is a flow chart of an automated reconciliation analysis method provided by an embodiment of the application;

FIG. 2 is a specific flowchart of S100 provided by one embodiment of the present application;

FIG. 3 is a specific flowchart of S500 provided by one embodiment of the present application;

FIG. 4 is a specific flowchart of S200 provided by one embodiment of the present application;

FIG. 5 is a specific flowchart of S400 provided by one embodiment of the present application;

FIG. 6 is a flow chart of an automated reconciliation method of the present application;

FIG. 7 is a specific flowchart of S720 provided by one embodiment of the present application;

FIG. 8 is a schematic view of the configuration of an automatic reconciliation analysis apparatus provided by an embodiment of the application;

fig. 9 is a schematic diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. 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 application.

It should be noted that although functional block division is performed in the apparatus schematic and logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than block division in the apparatus or in the flowchart. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

It is to be noted that all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs unless defined otherwise. The terminology used herein is for the purpose of describing embodiments of the application only and is not intended to be limiting of the application.

The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.

AI is a new technical science to study, develop theories, methods, techniques and application systems for simulating, extending and expanding human intelligence; artificial intelligence is a branch of computer science that attempts to understand the nature of intelligence and to produce a new intelligent machine that can react in a manner similar to human intelligence, research in this field including robotics, language recognition, image recognition, natural language processing, and expert systems. Artificial intelligence can simulate the information process of consciousness and thinking of people. Artificial intelligence is also a theory, method, technique, and application system that utilizes a digital computer or digital computer-controlled machine to simulate, extend, and expand human intelligence, sense the environment, acquire knowledge, and use knowledge to obtain optimal results.

Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.

The artificial intelligence is AI, which is the theory, method, technique and application system that uses digital computer or the machine controlled by digital computer to simulate, extend and expand the human intelligence, sense the environment, acquire knowledge and use knowledge to obtain the best result.

The server related to the artificial intelligence technology can be an independent server, or can be a cloud server for providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDNs), basic cloud computing services such as big data and artificial intelligence platforms, and the like.

The application provides an automatic account checking analysis method, an automatic account checking analysis device, electronic equipment and a computer readable storage medium, wherein in the process of automatic account checking analysis, log state information can be obtained by detecting and processing a log table every time a preset time interval passes, wherein the log table is obtained by executing a preset first task and a preset second task; under the condition that the log state information characterizes that the execution of the first task and the execution of the second task are completed, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table; then determining a corresponding general account checking task according to the task message queue key value; the general account checking task is executed to obtain account checking data; then, checking account detection processing is carried out on the checking account data based on a preset checking account script, so that checking account statistical data can be obtained; and finally, storing and processing the account checking statistical data based on a preset account checking result table. Through the technical scheme, the data checking efficiency can be improved.

The embodiment of the application provides an automatic account checking analysis method, which relates to the technical field of financial science and technology. The automatic account checking analysis method provided by the embodiment of the application can be applied to a terminal, a server and software running in the terminal or the server. In some embodiments, the terminal may be a smart phone, tablet, notebook, desktop, etc.; the server side can be configured as an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and a cloud server for providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligent platforms and the like; the software may be an application or the like that implements the automatic reconciliation analysis method, but is not limited to the above form.

The application is operational with numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

It should be noted that, in each specific embodiment of the present application, when related processing is required according to user information, user behavior data, user history data, user location information, and other data related to user identity or characteristics, permission or consent of the user is obtained first, and the collection, use, processing, and the like of the data comply with related laws and regulations and standards. In addition, when the embodiment of the application needs to acquire the sensitive personal information of the user, the independent permission or independent consent of the user is acquired through popup or jump to a confirmation page and the like, and after the independent permission or independent consent of the user is definitely acquired, the necessary relevant data of the user for enabling the embodiment of the application to normally operate is acquired.

Embodiments of the present application will be further described below with reference to the accompanying drawings.

As shown in fig. 1, fig. 1 is a flowchart of an automatic reconciliation method provided in one embodiment of the application, including but not limited to steps S100 to S600.

Step S100, detecting and processing a log table every time a preset time interval passes to obtain log state information, wherein the log table is obtained by executing a preset first task and a preset second task;

Step S200, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table under the condition that the log state information indicates that the execution of the first task and the execution of the second task are completed;

step S300, determining a corresponding general account checking task according to a task message queue key value;

step S400, executing the general account checking task to obtain account checking data;

step S500, performing account checking detection processing on account checking data based on a preset account checking script to obtain account checking statistical data;

step S600, storing and processing the account checking statistical data based on a preset account checking result table.

It should be noted that, in the process of automatic account checking analysis, log state information can be obtained by detecting and processing a log table every time a preset time interval passes, where the log table is obtained by executing a preset first task and a preset second task; under the condition that the log state information characterizes that the execution of the first task and the execution of the second task are completed, extracting a corresponding task message queue key value from a preset automatic trigger task configuration table; then determining a corresponding general account checking task according to the task message queue key value; the general account checking task is executed to obtain account checking data; then, checking account detection processing is carried out on the checking account data based on a preset checking account script, so that checking account statistical data can be obtained; and finally, storing and processing the account checking statistical data based on a preset account checking result table. Through the technical scheme, the data checking efficiency can be improved.

In the financial industry, various businesses in the financial industry are managed and monitored by various systems; when reconstructing and reforming a batch program, a trial operation period exists when the program is reformed and online operated, the trial operation period needs to be executed in parallel with an original task, and data comparison is needed to be continuously carried out with the original task so as to ensure that the logic of the reformed task is correct, the reformed task can be formally switched to put into production after the data comparison is consistent, and the old task is offline; however, the data consistency comparison is a tedious process, a large amount of manpower is required to analyze the data, especially if the task needs to be executed frequently, more manpower needs to be input, and sometimes, one task may not be reconstructed when the task is reconstructed, and the task of the whole system may be reconstructed, so that a large amount of tasks need to be reconstructed, each task needs to take a large amount of manpower to manually check the data, and the input workload is huge; because of the different table structure and data composition of each task, there is no fast reconciliation automation tool currently available in the industry. According to the embodiment of the application, automatic account checking processing is realized through an automatic account checking analysis method, and the labor cost and the time cost are well saved.

Notably, in the embodiment of the application, after the first task and the second task are executed, the reconciliation task is automatically triggered without manual intervention; the account checking task is a general task and is suitable for batch program task account checking under most scenes; the newly added account checking task can be rapidly online only by simple configuration and writing of an access script. For example, in order to accurately and timely track that the new task and the old task have been executed, a log table is needed after the task is completed, an automatic trigger task configuration table is needed, the tasks for triggering checking are required to be configured into the automatic trigger task configuration table, then the logs of the log table are matched according to configuration information in the automatic trigger task configuration table through a timed heartbeat task, and if the logs meeting the conditions for triggering the subsequent automatic tasks are needed, the corresponding message queue key values in the configuration table are produced. The message queue key value is matched with the consumer through the key value, and the general reconciliation task executes the reconciliation logic of the task according to the reconciliation task code, so that the triggering of automatic reconciliation is completed.

It should be noted that, in the process of executing the first task and the second task, the execution conditions of the tasks are stored in the log table; detecting the log table after a period of time, so as to obtain log state information; under the condition that the obtained log state information indicates that the execution of the first task and the second task is completed, a corresponding task message queue key value can be extracted from a preset automatic trigger task configuration table; then determining a corresponding general account checking task according to the task message queue key value; then, executing the general account checking task to obtain account checking data; then, checking account detection processing is carried out on checking account data based on a preset checking account script, so that checking account statistical data can be obtained; and finally, storing and processing the account checking statistical data based on a preset account checking result table.

Illustratively, in the financial industry, the auto-triggering task configuration table can store different reconciliation data, and the reconciliation result table needs to contain (evaluation day, reconciliation task code, data type, data amount, result table name, general amount 1-10 (10 fields are reserved first), remarks (mainly explanation of general amount)), to meet the needs of various table data storage. And a configuration table (information such as reconciliation task codes, SQL script types, SQL script IDs and the like) of the reconciliation tasks is provided, and a check script, a statistics script and a statistics script are provided for the reconciliation tasks. When the universal checking interface is called up by the automatic triggering mechanism, the universal checking task configuration table is searched according to the checking task code, the checking script and the statistical script of the task are obtained, then the checking script is executed through reflection, whether the data are generated or not is judged, if the re-executing statistical script is generated, the data are obtained, the data are written into the universal checking result table, and the data obtaining statistical process is completed.

It is worth noting that by the automatic account checking analysis method provided by the embodiment of the application, the reconstruction task can be timely and accurately acquired, the configuration of the new account checking task can be rapidly supported on line, the investment of manual inspection is greatly reduced, and the rapid production and use of the reconstruction task is indirectly promoted.

In some embodiments, as shown in fig. 2, the step S100 may include, but is not limited to, steps S110 to S130.

Step S110, setting the waiting time of a preset heartbeat task to obtain task waiting time;

step S120, determining task waiting time as a preset time interval;

and step S130, carrying out state matching processing on the configuration information in the automatic trigger task configuration table and the log in the log table to obtain log state information every time a preset time interval passes.

In the process of detecting and processing the log table every time a preset time interval passes, firstly, setting and processing the waiting time of a preset heartbeat task to obtain the task waiting time; then determining the task waiting time as a preset time interval; and finally, carrying out state matching processing on the configuration information in the automatic trigger task configuration table and the log in the log table every time a preset time interval passes, so as to obtain log state information.

It is noted that, the heartbeat task is a task that is executed at intervals of a preset time interval; setting the waiting time of a preset heartbeat task to obtain the task waiting time; then determining the task waiting time as a preset time interval; and then, carrying out state matching processing on the configuration information in the automatic trigger task configuration table and the log in the log table every time a preset time interval passes, so as to obtain log state information. Through the technical scheme, the state of the log in the log table can be matched and detected regularly, automatic account checking processing can be carried out under the condition that the condition is met, and then automatic account checking processing can be realized, and the realization process is simple, convenient and reliable.

In some embodiments, as shown in fig. 3, the reconciliation script includes a check script and a statistics script, and the step S500 may further include, but is not limited to, steps S510 to S520.

Step S510, integrity check processing is carried out on the account checking data based on the checking script to obtain checking information;

step S520, performing statistical processing on the reconciliation data based on the statistical script to obtain the reconciliation statistics data when the inspection information characterizes the reconciliation data.

When checking the checking data by using the checking script, checking information can be obtained by checking the integrity of the checking data based on the checking script; and then under the condition that the checking information characterizes the generation of the reconciliation data, the reconciliation statistics data can be obtained by carrying out statistical processing on the reconciliation data based on the statistical script.

It should be noted that, in the process of detecting and processing the reconciliation data by using the reconciliation script, the integrity check processing is performed on the reconciliation data based on the check script, and the accounting statistics data is obtained by performing the statistics processing on the reconciliation data by using the statistics script only when the generation of the reconciliation data is completed by the check information characterization.

In some embodiments, as shown in fig. 4, the log status information includes log attribute information, and the step S200 may further include, but is not limited to, steps S210 to S220.

Step S210, matching the log attribute information with task attributes carried by the automatic triggering task configuration table to obtain a matching result;

step S220, extracting a task message queue key value corresponding to the task attribute from the automatic trigger task configuration table according to the matching result.

In the process of extracting the corresponding task message queue key value from the preset automatic trigger task configuration table, matching the log attribute information with the task attribute carried by the automatic trigger task configuration table to obtain a matching result; and extracting a task message queue key value corresponding to the task attribute from the automatic trigger task configuration table according to the matching result.

Notably, the log state information comprises log attribute information, and the log attribute information is matched with task attributes carried by the automatic trigger task configuration table to obtain a matching result; therefore, the task message queue key value corresponding to the task attribute can be extracted from the automatic trigger task configuration table according to the matching result.

In some embodiments, as shown in fig. 5, the step S400 may further include, but is not limited to, step S410.

Step S410, comparing the first execution data and the second execution data according to the general account checking task to obtain account checking data; wherein the first execution data is obtained by executing a first task and the second execution data is obtained by executing a second task.

In the process of executing the general reconciliation task, the reconciliation data can be obtained by comparing the first execution data and the second execution data according to the general reconciliation task; wherein the first execution data is obtained by executing a first task and the second execution data is obtained by executing a second task.

It is noted that, the reconciliation data may be obtained by comparing the first execution data obtained by executing the first task with the second execution data obtained by executing the second task, and the reconciliation data characterizes a difference between the first execution data obtained by executing the first task and the second execution data obtained by executing the second task, where the difference is a result of automatic reconciliation.

In some embodiments, as shown in fig. 6, after the step S600 is performed, steps S710 to S730 may be further included, but are not limited to.

Step S710, extracting and processing account checking statistical data in an account checking result table;

step S720, packaging the extracted account checking statistical data to obtain a statistical data packet;

step S730, sending the statistical data packet to a preset mailbox address.

After the accounting data is stored, the accounting data in the accounting result table may be extracted; then, packaging the extracted account checking statistical data to obtain a statistical data packet; and then sending the statistical data packet to a preset mailbox address to inform the maintenance personnel of the related system of the automatic account checking result.

It should be noted that, for example, a general presentation template mail is designed according to the attribute of the general account checking result table, after the data generation is completed, the mail sending program will be immediately called up, the mail sending program will send the corresponding data to the general account checking result table according to the account checking code, collect statistics will be performed, the result will be matched to the general template mail, and the mail will be sent out according to the sender configured by the mail configuration table, so as to realize the notification processing of the account checking result.

In some embodiments, as shown in fig. 7, the step S720 may further include, but is not limited to, steps S721 to S722.

Step S721, compressing the account checking statistical data to obtain a compressed data packet;

in step S722, the compressed data packet is marked to obtain a statistical data packet.

In the process of packaging the accounting data, firstly, compressing the accounting data to obtain a compressed data packet; and then, marking the compressed data packet to obtain the statistical data packet. The data storage space can be reduced by compressing the account checking statistical data, and the storage operation is more convenient.

In addition, as shown in fig. 8, an embodiment of the present application further provides an automatic reconciliation analysis apparatus 10, including:

the first processing module 100 is configured to perform detection processing on a log table every time a preset time interval passes to obtain log state information, where the log table is obtained by executing a preset first task and a preset second task;

the second processing module 200 is configured to extract a corresponding task message queue key value from a preset automatic trigger task configuration table when the log state information indicates that the execution of both the first task and the second task is completed;

The third processing module 300 is configured to determine a corresponding general account checking task according to the task message queue key value;

a fourth processing module 400, configured to perform processing on the general reconciliation task to obtain reconciliation data;

a fifth processing module 500, configured to perform reconciliation detection processing on the reconciliation data based on a preset reconciliation script to obtain reconciliation statistics data;

and a sixth processing module 600, configured to store and process the accounting statistics based on a preset accounting result table.

The specific embodiment of the automatic reconciliation analysis apparatus 10 is substantially the same as the specific embodiment of the automatic reconciliation analysis method described above, and will not be described again here.

In addition, as shown in fig. 9, an embodiment of the present application further provides an electronic device 700, including: memory 720, processor 710, and computer programs stored on memory 720 and executable on processor 710.

Processor 710 and memory 720 may be connected by a bus or other means.

The non-transitory software programs and instructions required to implement the automated reconciliation method of the embodiments described above are stored in memory 720, which when executed by processor 710, perform the automated reconciliation method of the embodiments described above, e.g., performing method steps S100 through S600 in fig. 1, method steps S110 through S130 in fig. 2, method steps S510 through S520 in fig. 3, method steps S210 through S220 in fig. 4, method step S410 in fig. 5, method steps S710 through S730 in fig. 6, and method steps S721 through S722 in fig. 7, described above.

The above described apparatus embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Furthermore, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions that are executed by a processor 710 or a controller, for example, by the processor 710 in the above-described device embodiment, which may cause the processor 710 to perform the automatic accounting analysis method in the above-described embodiment, for example, the method steps S100 to S600 in fig. 1, the method steps S110 to S130 in fig. 2, the method steps S510 to S520 in fig. 3, the method steps S210 to S220 in fig. 4, the method step S410 in fig. 5, the method steps S710 to S730 in fig. 6, and the method steps S721 to S722 in fig. 7 described above.

The embodiments described above may be combined, and modules with the same names may be the same or different between different embodiments.

The foregoing describes certain embodiments of the application, other embodiments being 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. Furthermore, the processes depicted in the accompanying drawings do not necessarily have to be in 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.

The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for apparatus, devices, computer readable storage medium embodiments, the description is relatively simple as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.

The apparatus, the device, the computer readable storage medium and the method provided by the embodiments of the present application correspond to each other, and therefore, the apparatus, the device, the non-volatile computer storage medium also have similar beneficial technical effects as those of the corresponding method, and since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, device, and computer storage medium are not described here again.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each unit may be implemented in the same piece or pieces of software and/or hardware when implementing the embodiments of the present 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, embodiments of 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, embodiments of the application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present description 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.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or Flash memory (Flash RAM), among others, in a computer readable medium. Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable Media, as defined herein, does not include Transitory computer-readable Media (transmission Media), such as modulated data signals and carrier waves.

It should also be noted that 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.

In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relation of association objects, and indicates that there may be three kinds of relations, for example, a and/or B, and may indicate that a alone exists, a and B together, and B alone exists. Wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of the following" and the like means any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a and b, a and c, b and c or a and b and c, wherein a, b and c can be single or multiple.

Embodiments of the application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Embodiments of the application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

The foregoing description is only exemplary embodiments of the application and is not intended to limit the application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.

Claims

1. An automated reconciliation method, comprising:

executing the general account checking task to obtain account checking data;

2. The automatic reconciliation analysis method of claim 1, wherein detecting the log table every time a predetermined time interval elapses to obtain log status information comprises:

determining the task waiting time as the preset time interval;

3. The automatic reconciliation analysis method according to claim 1, wherein the reconciliation script comprises a check script and a statistics script, and the reconciliation detection processing of the reconciliation data based on the preset reconciliation script obtains reconciliation statistics data, comprising:

4. The automatic reconciliation analysis method of claim 1, wherein the log status information comprises log attribute information, and wherein the extracting the corresponding task message queue key value from the preset auto-trigger task configuration table comprises:

5. The automatic reconciliation analysis method of claim 1, wherein performing processing on the generic reconciliation task results in reconciliation data comprising:

6. The automatic reconciliation analysis method of claim 1, wherein after the storing process of the reconciliation statistics based on the preset reconciliation result table, the method further comprises:

and sending the statistical data packet to a preset mailbox address.

7. The automatic reconciliation analysis method of claim 6, wherein the packaging the extracted reconciliation statistics to obtain a statistics package comprises:

and marking the compressed data packet to obtain the statistical data packet.

8. An automatic reconciliation analysis device, comprising:

9. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the automated reconciliation analysis method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing computer-executable instructions for performing the automated reconciliation method of any of claims 1-7.