Reconciliation data processing method and device, terminal equipment and readable storage medium
By obtaining reconciliation information of reconciliation tasks and hashing processing, and combining Aviator engine and Redis to compare reconciliation data, the problem of low efficiency and accuracy of existing reconciliation data is solved, and more efficient and refined reconciliation processing.
Patent Information
- Application Number
- CN202411137460.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-19
- Publication Date
- 2024-12-10
AI Technical Summary
The existing reconciliation data processing methods are low in efficiency and accuracy, and cannot be processed in a refined manner.
By obtaining the reconciliation information of the target reconciliation task, hashing processing to obtain the merged identifier, and checking it based on the reconciliation data, merged identifier, reconciliation transaction number and reconciliation amount, and efficient comparison with the Aviator engine and Redis. The summary processing results are used as the reconciliation processing results.
It improves the execution efficiency and accuracy of the reconciliation process, achieves a higher degree of refinement, and is more versatile and applicable than Java native methods.
Smart Images
Figure CN119107193A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of reconciliation data processing, and in particular to a reconciliation data processing method, device, terminal equipment and computer-readable storage medium. Background Art
[0002] Reconciliation is an important part of accounting, which can ensure the accuracy and consistency of financial information, and its role cannot be ignored. At present, the working mode in the accounting field is mainly to manually operate the report data of different systems, and then upload the report data to the corresponding institutional end, business end, payment end and financial end respectively; convert different types of files into model data through the background Java, and then compare the data of each end through Java's native method to find out the data differences. The reconciliation data processing based on this method is not sophisticated enough, so there are problems with the execution efficiency and accuracy of the reconciliation process. Summary of the invention
[0003] The present invention provides a method, an apparatus, a terminal device and a computer-readable storage medium for processing reconciliation data to solve the technical problem of how to improve the execution efficiency and accuracy of the reconciliation process.
[0004] In order to solve the above technical problems, an embodiment of the present invention provides a method for processing reconciliation data, including:
[0005] Obtain a target reconciliation task and set the reconciliation information of the target reconciliation task; perform hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end;
[0006] According to the target reconciliation task, respectively obtain the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within the target reconciliation time interval;
[0007] According to the reconciliation information, reconciliation data is obtained; according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, verification is performed; and the verification result is summarized and processed, and the summary processing result is used as the reconciliation processing result.
[0008] As a preferred solution, the checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount includes:
[0009] Performing a general check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain the reconciliation consistent data; wherein the general check means that all the attributes to be checked on the source end and the clearing end are the same;
[0010] According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, a unilateral verification is performed to obtain unilateral verification data; wherein the unilateral verification refers to the fact that any one of the source end and the clearing end lacks the attribute to be verified;
[0011] Perform difference checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain difference checking data; wherein the difference checking refers to the same primary key attribute being the same and the attributes to be checked being different;
[0012] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0013] As a preferred solution, the checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount also includes:
[0014] When performing the general verification, the merge identifier is used to filter out the data required for the general verification from the reconciliation data of the source end and the clearing end, and the general verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the verification consistent data;
[0015] When the unilateral verification is adopted, the data required for the unilateral verification is filtered out from the reconciliation data of either the source end or the clearing end by using the merging identifier, and the unilateral verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the unilateral verification data;
[0016] When the difference check is adopted, the merge identifier is used to filter out the data required for the difference check from the reconciliation data of the source end and the clearing end, and the difference check is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the difference check data;
[0017] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0018] As a preferred solution, the checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount includes:
[0019] According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, when the data volume is less than or equal to the preset threshold, the Aviator engine is used for verification; when the data volume is greater than the preset threshold, redis is used for verification.
[0020] As a preferred solution, the setting of the reconciliation information of the target reconciliation task includes:
[0021] Set the task number, reconciliation date, reconciliation type, reconciliation prefix code, amount unit, reconciliation data acquisition type, parser code, terminal code, field delimiter, ftp connection parameters, database connection string and string encoding type of the target reconciliation task.
[0022] As a preferred solution, the step of obtaining reconciliation data according to the reconciliation information includes:
[0023] Querying a pre-configuration table for reconciliation; wherein the pre-configuration table for reconciliation configures the data acquisition method of the source end and the clearing end;
[0024] According to the acquisition method, initial data is acquired;
[0025] The initial data is processed using a preset configuration field parser and file parser to obtain the reconciliation data.
[0026] As a preferred solution, before setting the reconciliation information of the target reconciliation task, the method further includes:
[0027] Set the status of the reconciliation task configuration table to being reconciled; initialize the reconciliation task result table, and delete the last reconciliation result data, the last reconciliation detail data, and the last reconciliation detail history data.
[0028] Accordingly, an embodiment of the present invention further provides a reconciliation data processing device, comprising a setting module, an acquisition module and a checking module; wherein:
[0029] The setting module is used to obtain a target reconciliation task and set the reconciliation information of the target reconciliation task; perform hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end;
[0030] The acquisition module is used to acquire the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within the target reconciliation time interval according to the target reconciliation task;
[0031] The checking module is used to obtain the reconciliation data according to the reconciliation information; to check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount; to summarize the checking results and use the summary results as the reconciliation results.
[0032] As a preferred solution, the checking module performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, including:
[0033] The checking module performs a general check according to the reconciliation data, the merging identifier, the number of reconciliation items and the number of reconciliation amounts to obtain the check consistent data; wherein the general check means that all the attributes to be checked on the source end and the clearing end are the same;
[0034] According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, a unilateral verification is performed to obtain unilateral verification data; wherein the unilateral verification refers to the fact that any one of the source end and the clearing end lacks the attribute to be verified;
[0035] Perform difference checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain difference checking data; wherein the difference checking refers to the same primary key attribute being the same and the attributes to be checked being different;
[0036] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0037] As a preferred solution, the checking module performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, and further includes:
[0038] When performing the general verification, the verification module uses the merge identifier to filter out the data required for the general verification from the reconciliation data of the source end and the clearing end, and performs the general verification based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the verification consistent data;
[0039] When the unilateral verification is adopted, the verification module uses the merge identifier to filter out the data required for the unilateral verification from the reconciliation data of either the source end or the clearing end, and performs the unilateral verification based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the unilateral verification data;
[0040] When the difference check is adopted, the check module uses the merge identifier to filter out the data required for the difference check from the reconciliation data of the source end and the clearing end, and performs the difference check according to the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the difference check data;
[0041] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0042] As a preferred solution, the checking module performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, including:
[0043] The verification module uses the Aviator engine to verify the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount when the data volume is less than or equal to a preset threshold; and uses redis to verify the data when the data volume is greater than the preset threshold.
[0044] As a preferred solution, the setting module sets the reconciliation information of the target reconciliation task, including:
[0045] The setting module sets the task number, reconciliation date, reconciliation type, reconciliation prefix code, amount unit, reconciliation data acquisition type, parser code, terminal code, field delimiter, FTP connection parameters, database connection string and string encoding type of the target reconciliation task.
[0046] As a preferred solution, the checking module obtains reconciliation data according to the reconciliation information, including:
[0047] The checking module queries the pre-configuration table for reconciliation; wherein the pre-configuration table for reconciliation configures the data acquisition method of the source end and the clearing end;
[0048] According to the acquisition method, initial data is acquired;
[0049] The initial data is processed using a preset configuration field parser and file parser to obtain the reconciliation data.
[0050] As a preferred solution, the reconciliation data processing device further includes an initialization module, and the initialization module is used for, before the setting module sets the reconciliation information of the target reconciliation task:
[0051] Set the status of the reconciliation task configuration table to being reconciled; initialize the reconciliation task result table, and delete the last reconciliation result data, the last reconciliation detail data, and the last reconciliation detail history data.
[0052] Correspondingly, an embodiment of the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the reconciliation data processing method when executing the computer program.
[0053] Correspondingly, an embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the reconciliation data processing method.
[0054] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:
[0055] An embodiment of the present invention provides a reconciliation data processing method, apparatus, terminal device and computer-readable storage medium, the reconciliation data processing method comprising: obtaining a target reconciliation task and setting reconciliation information of the target reconciliation task; performing hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end; according to the target reconciliation task, respectively obtaining the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within a target reconciliation time interval; obtaining reconciliation data according to the reconciliation information; performing verification according to the reconciliation data, the merge identifier, the number of reconciliation items and the number of reconciliation amounts; summarizing the verification results and using the summarized processing results as the reconciliation processing results. By implementing the present invention, by setting reconciliation information, obtaining the number of reconciliation items and the number of reconciliation amounts at the source end and the clearing end within the target reconciliation time interval, performing verification, and summarizing the verification results as reconciliation processing results, compared with Java's native method, in the reconciliation process, factors such as the number of reconciliation items and the number of reconciliation amounts are taken into consideration, which can effectively improve the execution efficiency and accuracy of the reconciliation process. In addition, compared with the existing reconciliation methods, it embodies a higher degree of refinement. BRIEF DESCRIPTION OF THE DRAWINGS
[0056] Figure 1 : A flow chart of an embodiment of the reconciliation data processing method provided by the present invention.
[0057] Figure 2 : A schematic diagram of the architecture of an embodiment of the reconciliation data processing system provided by the present invention.
[0058] Figure 3 : A schematic diagram of the step flow of an embodiment of the reconciliation data processing system provided by the present invention.
[0059] Figure 4 : A schematic diagram of the execution flow of an embodiment of the Aviator engine provided by the present invention.
[0060] Figure 5 : A flow chart of an embodiment of the reconciliation data processing device provided by the present invention. DETAILED DESCRIPTION
[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0062] Embodiment 1
[0063] Please refer to Figure 1 , Figure 1 A method for processing reconciliation data provided in an embodiment of the present invention includes steps S1 to S3. In this embodiment, the method for processing reconciliation data can be applied to a reconciliation processing system. The reconciliation system can be applied to computer devices, including but not limited to smart phones, laptops, tablet computers, desktop computers, and physical servers and cloud servers connected to display units. The reconciliation processing method and the reconciliation processing system can be used in scenarios such as consumer finance.
[0064] For example, the system architecture diagram of the reconciliation processing system may be as follows: Figure 2 As shown. In the figure, BOSS is the reconciliation interface Vue. Vue is a JavaScript framework for building user interfaces. It is built on standard HTML, CSS, and JavaScript, and provides a set of declarative, componentized programming models that can efficiently develop user interfaces. In this embodiment, the general configuration of reconciliation parameters (tasks, reconciliation keys, reconciliation pre-settings, reconciliation field attribute parsing), rule configuration (such as Aviator), and reconciliation result display are mainly implemented.
[0065] The Utils shown in the figure are general tools, including SpringBean acquisition, general tool class, RebbitMQ configuration, Redis configuration, SFTP tool and database connection tool.
[0066] The CORE shown in the figure is the reconciliation processing core, which is mainly used to realize the comparison of reconciliation detail data, statistics of reconciliation results, etc.
[0067] The PREPOSE shown in the figure is used for pre-processing of reconciliation, and can obtain data according to pre-configured content, including obtaining various types of files and querying databases. The QUARTZ shown in the figure is a scheduling module, which can automatically trigger reconciliation. For example, the steps and processes implemented by the reconciliation processing system can be as follows: Figure 3 shown.
[0068] according to Figure 1 The reconciliation processing method shown, step S1 includes: obtaining a target reconciliation task and setting the reconciliation information of the target reconciliation task; performing hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end.
[0069] Step S2, according to the target reconciliation task, respectively obtain the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within the target reconciliation time interval.
[0070] Step S3, obtaining reconciliation data according to the reconciliation information; performing verification according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount; and summarizing the verification results and using the summarization results as the reconciliation results.
[0071] As a preferred implementation, before performing step S1, the user can click to trigger or configure the QUARTZ scheduling module through the BOSS interface Vue to automatically activate the reconciliation. Then, the pre-reconciliation verification is performed through CORE, including: checking whether the reconciliation task is configured; checking whether the reconciliation status is normal, determining whether it is "unreconciled" or "reconciled" (data in reconciliation is not allowed to be initiated repeatedly); judging whether reconciliation is supported (mainly checking parameter configuration); checking the last reconciliation date (some reconciliations support the same day, and some reconciliations only support the previous day).
[0072] Furthermore, before the reconciliation information of the target reconciliation task in step S1, it also includes: setting the status of the reconciliation task configuration table to being reconciled; initializing the reconciliation task result table, deleting the last reconciliation result data of the reconciliation task result table (which can be specifically the result data of the last reconciliation day, and the result data of this reconciliation day is added through the reconciliation data processing method), the last reconciliation detail data and the last reconciliation detail historical data.
[0073] Then, in step S1, the reconciliation information of the target reconciliation task is set: create a reconciliation context, that is, set the task number, reconciliation date, reconciliation type, reconciliation prefix code, amount unit, reconciliation data acquisition type, parser code, terminal code, field separator, ftp connection parameter, database connection string and string encoding type of the target reconciliation task. At the same time, hash processing can be performed according to the unique business serial number of the source end and the clearing end to obtain a merged identifier id, and the merged identifier is stored in the reconciliation detail table respectively to prepare for subsequent reconciliation.
[0074] Then, for step S2, according to the target reconciliation task, the number of reconciliation items and the amount of reconciliation at the source end within the target reconciliation time interval, and the number of reconciliation items and the amount of reconciliation at the clearing end within the target reconciliation time interval are obtained respectively. Preferably, the target reconciliation time interval may refer to a reconciliation day.
[0075] Further, in step S3, obtaining reconciliation data according to the reconciliation information includes:
[0076] Query the reconciliation pre-configuration table; wherein the reconciliation pre-configuration table configures the data acquisition method of the source end and the clearing end; obtain the initial data according to the acquisition method; use the preset configuration field parser and file parser to process the initial data (convert it into model data) to obtain the reconciliation data. Exemplarily, the acquisition method includes an FTP-based acquisition method and an SQL-based acquisition method. For example, FTP configures the IP username and password, file path, file matching expression and file parser; for SQL, the database connection string and SQL statement are configured.
[0077] Furthermore, the checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount includes:
[0078] Performing a general check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain the reconciliation consistent data; wherein the general check means that all the attributes to be checked on the source end and the clearing end are the same;
[0079] According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, a unilateral verification is performed to obtain unilateral verification data; wherein the unilateral verification refers to the fact that any one of the source end and the clearing end lacks the attribute to be verified;
[0080] Perform difference checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain difference checking data; wherein the difference checking refers to the same primary key attribute being the same and the attributes to be checked being different;
[0081] The verification result of step S3 is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0082] In this embodiment, the standard check key is equal to all checked attributes; the unilateral check key is the primary key of the business data, usually a serial number. For any of the above-mentioned general check, unilateral check and difference check, different methods can be implemented by configuring the reconciliation mode of the reconciliation task, that is, using the Aviator engine and / or redis for checking. When the amount of data is not large, the Aviator engine can be selected. When the amount of data is relatively large, such as millions of data, redis can be used to take the intersection of the data keys.
[0083] That is, according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, when the data volume is less than or equal to the preset threshold, the Aviator engine is used for verification; when the data volume is greater than the preset threshold, redis is used for verification.
[0084] In this embodiment, the merging identifier mainly plays the role of filtering out the data required for verification. Specifically, the verification based on the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount also includes:
[0085] When performing the general verification, the merge identifier is used to filter out the data required for the general verification from the reconciliation data of the source end and the clearing end, and the general verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the verification consistent data;
[0086] When the unilateral verification is adopted, the data required for the unilateral verification is filtered out from the reconciliation data of either the source end or the clearing end by using the merging identifier, and the unilateral verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the unilateral verification data;
[0087] When the difference check is adopted, the merge identifier is used to filter out the data required for the difference check from the reconciliation data of the source end and the clearing end, and the difference check is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the difference check data;
[0088] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0089] Furthermore, the execution process of the Aviator (account reconciliation) engine can be as follows: Figure 4 As shown. FACT refers to the fact object, that is, the object that carries the real thing or fact, and this embodiment represents the reconciliation data. The RULE shown in the figure is a specific rule, which is an inference statement composed of conditions and conclusions. The LHS shown in the figure is the left half of the rule, which generally refers to the specific left half factor. RHS is the right half of the rule, usually referring to the then and else parts of the rule. Generally refers to a specific action, because then and else often correspond to specific actions. Rule Engine refers to the executor of the rule expression. OutputResult refers to the execution result.
[0090] For example, for the Aviator (reconciliation) engine in general reconciliation: Aviator compiles the expression into java bytecode and hands it over to JVM for execution. It can support most operation operators, including arithmetic operators, relational operators, logical operators, and regular matching. It also supports custom functions and incoming parameters, with excellent performance. For the acquired data at both ends, the corresponding data at both ends are found through the above merged id, and the expression configured according to the rules (for example, data model A. attribute A == data model B. attribute B && data model A. attribute B == data model B. attribute B...), that is, the attributes that need to be compared are equal, and the Aviator expression is executed by the incoming data and returns true, indicating that the data at both ends are consistent. You can also configure the attributes to be unequal separately to obtain the reconciliation results of specific differences.
[0091] The implementation logic of the redis intersection method in general verification is as follows: by configuring the standard verification key, the model attributes a, b, c, d... are configured in the table, and they are connected by commas. For example, A10232432 (value of attribute a), 200 (value of attribute b), 100 (value of attribute c), 12 (value of attribute d)..., the data at both ends are set to the hash bucket of the context context respectively, the key is the string of attribute value concatenation, and the value is the corresponding model data. The data is set to the redis memory through the redis executePipeline pipeline method (this feature supports sending multiple commands at one time and returning the results at one time after execution. The pipeline reduces the round-trip delay time by reducing the number of client-redis communications, so that the performance can be improved by more than 100 times compared with the original set key method under large data volume), and the keys at both ends are uniformly set to prepare for subsequent comparison. The intersection of the data sets corresponding to the keys stored in the redis memory is taken, and the resulting set is the verified consistent data. Then, the corresponding source data is found according to the key through the hash buckets at both ends, and the reconciliation result identifier of the detailed data is updated.
[0092] For the Aviator (account reconciliation) engine, in the unilateral verification, usually one piece of data from each end is compared. If the data obtained through the merged ID only has data on one end, it can be judged as unilateral.
[0093] The implementation logic of the redis intersection method in unilateral verification is usually unilateral comparison under large data volumes. There are tens of thousands of data under the same batch number. At this time, they are uniformly compared through the unilateral key (usually configured as an attribute that can identify the uniqueness of the data). It is consistent with the above redis executePipeline method, except that the redis difference method is used to obtain the difference data at both ends and merge them. Then the corresponding source data is found, and the reconciliation result of the detailed data is updated to be marked as unilateral verification.
[0094] For the difference verification of Aviator (reconciliation) engine, you can refer to the above Aviator steps. The mismatch is the difference data. Update the reconciliation results of the detailed data at both ends to verify the difference.
[0095] The implementation logic of the redis intersection method in difference checking can refer to the above redis processing steps, and the comparison is unified through the difference key, and the difference data is still obtained through the redis difference method.
[0096] Then, the reconciliation results obtained above are summarized and processed to obtain the data that is consistent with the verification, the data that is unilaterally verified, and the data that is different from the verification, and the reconciliation processing results are obtained. Then the reconciliation processing results are saved to the reconciliation result table and returned to the front-end page for display. This embodiment is based on the technical characteristics of Java polymorphism, generics, etc., and has stronger versatility and applicability than the existing technology, and is suitable for a wider range of reconciliation scenarios; and the lightweight rule engine Aviator is introduced to achieve the isolation of logic and data, with higher scalability, maintainability, business flexibility and business transparency, reducing the risk of frequent iteration and upgrade of the system.
[0097] In addition, QUARTS automatically triggers reconciliation tasks to improve the work efficiency of business operators.
[0098] In addition, redis can be implemented through memory, reducing I / O operations and increasing the operation rate. Given the more efficient data structure of redis, the time complexity of data storage can be minimized. Reasonable data encoding is adopted, and different encoding formats are adapted according to the string length and the number of elements. In addition, a suitable thread model and I / O multiplexing model are adopted, so that context switching is not required during execution, reducing time consumption. The real-time efficiency of data comparison of large amounts of data can be efficiently achieved through the pipeline pipeline method.
[0099] Accordingly, refer to Figure 5 The embodiment of the present invention further provides a reconciliation data processing device, including a setting module 101, an acquisition module 102 and a checking module 103; wherein,
[0100] The setting module 101 is used to obtain a target reconciliation task and set the reconciliation information of the target reconciliation task; perform hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end;
[0101] The acquisition module 102 is used to acquire the number of reconciliation items and the amount of reconciliation at the source end and the clearing end within the target reconciliation time interval according to the target reconciliation task;
[0102] The checking module 103 is used to obtain the reconciliation data according to the reconciliation information; perform checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount; and perform summary processing on the checking result, and use the summary processing result as the reconciliation processing result.
[0103] As a preferred solution, the checking module 103 performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, including:
[0104] The checking module 103 performs a general check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain the reconciliation consistent data; wherein the general check means that all the attributes to be checked on the source end and the clearing end are the same;
[0105] According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, a unilateral verification is performed to obtain unilateral verification data; wherein the unilateral verification refers to the fact that any one of the source end and the clearing end lacks the attribute to be verified;
[0106] Perform difference checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain difference checking data; wherein the difference checking refers to the same primary key attribute being the same and the attributes to be checked being different;
[0107] The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
[0108] As a preferred solution, the checking module 103 performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, and further includes:
[0109] When performing the general verification, the verification module 103 uses the merge identifier to filter out the data required for the general verification from the reconciliation data of the source end and the clearing end, and performs the general verification based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the verification consistent data;
[0110] When the unilateral verification is adopted, the verification module 103 uses the merge identifier to filter out the data required for the unilateral verification from the reconciliation data of either the source end or the clearing end, and performs the unilateral verification based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the unilateral verification data;
[0111] When the difference check is adopted, the checking module 103 uses the merge identifier to filter out the data required for the difference check from the reconciliation data of the source end and the clearing end, and performs the difference check according to the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the difference check data;
[0112] The checking module 103 obtains the checking result according to the checking consistent data, the unilateral checking data and the difference checking data.
[0113] As a preferred solution, the checking module 103 performs checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, including:
[0114] The checking module 103 uses the Aviator engine to check the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount when the data volume is less than or equal to a preset threshold; and uses redis to check when the data volume is greater than the preset threshold.
[0115] As a preferred solution, the setting module 101 sets the reconciliation information of the target reconciliation task, including:
[0116] The setting module 101 sets the task number, reconciliation date, reconciliation type, reconciliation prefix code, amount unit, reconciliation data acquisition type, parser code, terminal code, field delimiter, FTP connection parameters, database connection string and string encoding type of the target reconciliation task.
[0117] As a preferred solution, the checking module 103 obtains reconciliation data according to the reconciliation information, including:
[0118] The checking module 103 queries the pre-configuration table for reconciliation; wherein the pre-configuration table for reconciliation configures the data acquisition method of the source end and the clearing end;
[0119] According to the acquisition method, initial data is acquired;
[0120] The initial data is processed using a preset configuration field parser and file parser to obtain the reconciliation data.
[0121] As a preferred solution, the reconciliation data processing device further includes an initialization module, and the initialization module is used for, before the setting module 101 sets the reconciliation information of the target reconciliation task:
[0122] Set the status of the reconciliation task configuration table to being reconciled; initialize the reconciliation task result table, and delete the last reconciliation result data, the last reconciliation detail data, and the last reconciliation detail history data.
[0123] Correspondingly, an embodiment of the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the reconciliation data processing method when executing the computer program.
[0124] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal, and various interfaces and lines are used to connect various parts of the entire terminal.
[0125] The memory can be used to store the computer program, and the processor realizes various functions of the terminal by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.
[0126] Correspondingly, an embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the reconciliation data processing method.
[0127] Wherein, if the module integrated in the reconciliation data processing device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.
[0128] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:
[0129] An embodiment of the present invention provides a reconciliation data processing method, apparatus, terminal device and computer-readable storage medium, the reconciliation data processing method comprising: obtaining a target reconciliation task and setting reconciliation information of the target reconciliation task; performing hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end; according to the target reconciliation task, respectively obtaining the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within a target reconciliation time interval; obtaining reconciliation data according to the reconciliation information; performing verification according to the reconciliation data, the merge identifier, the number of reconciliation items and the number of reconciliation amounts; summarizing the verification results and using the summarized processing results as the reconciliation processing results. By implementing the present invention, by setting reconciliation information, obtaining the number of reconciliation items and the number of reconciliation amounts at the source end and the clearing end within the target reconciliation time interval, performing verification, and summarizing the verification results as reconciliation processing results, compared with Java's native method, in the reconciliation process, factors such as the number of reconciliation items and the number of reconciliation amounts are taken into consideration, which can effectively improve the execution efficiency and accuracy of the reconciliation process. In addition, compared with the existing reconciliation methods, it embodies a higher degree of refinement.
[0130] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.
Claims
1. A method for processing reconciliation data, It is characterized in that include: Obtaining a target reconciliation task and setting reconciliation information for the target reconciliation task; Perform hash processing on the business serial numbers of at least two to-be-reconciled terminals of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled terminals include at least one source terminal and at least one clearing terminal; According to the target reconciliation task, respectively obtain the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within the target reconciliation time interval; According to the reconciliation information, reconciliation data is obtained; according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, verification is performed; and the verification result is summarized and processed, and the summary processing result is used as the reconciliation processing result.
2. A method for processing reconciliation data according to claim 1, It is characterized in that The checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount includes: Performing a general check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain the reconciliation consistent data; wherein the general check means that all the attributes to be checked on the source end and the clearing end are the same; According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, a unilateral verification is performed to obtain unilateral verification data; wherein the unilateral verification refers to the fact that any one of the source end and the clearing end lacks the attribute to be verified; Perform difference checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount to obtain difference checking data; wherein the difference checking refers to the same primary key attribute being the same and the attributes to be checked being different; The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
3. A method for processing reconciliation data according to claim 2, It is characterized in that The checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount also includes: When performing the general verification, the merge identifier is used to filter out the data required for the general verification from the reconciliation data of the source end and the clearing end, and the general verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the verification consistent data; When the unilateral verification is adopted, the data required for the unilateral verification is filtered out from the reconciliation data of either the source end or the clearing end by using the merging identifier, and the unilateral verification is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the unilateral verification data; When the difference check is adopted, the merge identifier is used to filter out the data required for the difference check from the reconciliation data of the source end and the clearing end, and the difference check is performed based on the filtered data combined with the number of reconciliation items and the reconciliation amount to obtain the difference check data; The verification result is obtained according to the verification consistent data, the unilateral verification data and the difference verification data.
4. A method for processing reconciliation data according to claim 1, It is characterized in that The checking according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount includes: According to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount, when the data volume is less than or equal to the preset threshold, the Aviator engine is used for verification; when the data volume is greater than the preset threshold, redis is used for verification.
5. A method for processing reconciliation data according to claim 1, It is characterized in that The setting of the reconciliation information of the target reconciliation task includes: Set the task number, reconciliation date, reconciliation type, reconciliation prefix code, amount unit, reconciliation data acquisition type, parser code, terminal code, field delimiter, ftp connection parameters, database connection string and string encoding type of the target reconciliation task.
6. A method for processing reconciliation data according to claim 1, It is characterized in that The acquiring reconciliation data according to the reconciliation information includes: Querying a pre-configuration table for reconciliation; wherein the pre-configuration table for reconciliation configures the data acquisition method of the source end and the clearing end; According to the acquisition method, initial data is acquired; The initial data is processed using a preset configuration field parser and file parser to obtain the reconciliation data.
7. A method for processing reconciliation data according to claim 1, It is characterized in that Before setting the reconciliation information of the target reconciliation task, the method further includes: Set the status of the reconciliation task configuration table to being reconciled; initialize the reconciliation task result table, and delete the last reconciliation result data, the last reconciliation detail data, and the last reconciliation detail history data.
8. A reconciliation data processing device, It is characterized in that It includes a setting module, an acquisition module and a verification module; among which, The setting module is used to obtain a target reconciliation task and set the reconciliation information of the target reconciliation task; perform hash processing on the business serial numbers of at least two to-be-reconciled ends of the target reconciliation task to obtain a merge identifier; wherein the at least two to-be-reconciled ends include at least one source end and at least one clearing end; The acquisition module is used to acquire the number of reconciliation items and the number of reconciliation amounts of the source end and the clearing end within the target reconciliation time interval according to the target reconciliation task; The checking module is used to obtain the reconciliation data according to the reconciliation information; to check according to the reconciliation data, the merging identifier, the number of reconciliation items and the reconciliation amount; to summarize the checking results and use the summary results as the reconciliation results.
9. A terminal device, It is characterized in that The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for processing reconciliation data as claimed in any one of claims 1 to 7 is implemented.
10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the reconciliation data processing method according to any one of claims 1 to 7.