A method, system and related equipment for reconciliation

Abstract

The embodiment of the present invention provides a reconciliation method, system and related equipment for improving the efficiency of document reconciliation. The method of the embodiment of the present invention includes: according to the specified field in the preset matching rule, extracting the field value set corresponding to each specified field from the two data sets to be matched, each preset matching rule specifies a specified field in each of the two data sets as an associated field, each data set includes multiple documents, and each document contains the field values ​​of all fields in the corresponding data set; using the preset matching algorithm corresponding to the preset matching rule, matching the field value set corresponding to the associated field to obtain the matching result of the associated field; identifying the successfully matched target document according to the matching result of the associated field, and the associated fields of all fields in the target document exist in the same document of another data set.

Description

Technical Field

[0001] The present invention relates to the technical field of account reconciliation, and in particular to an account reconciliation method, system and related equipment. Background Art

[0002] Reconciliation is the process of checking accounts, which refers to the work of checking and verifying the relevant data in the account book to ensure that the book records are correct and reliable. The documents of both parties to be reconciled are matched according to the configured field mapping relationship and different matching rules, and finally the documents that meet all matching conditions are reconciled.

[0003] The currently known reconciliation method is to set multiple matching rules, each rule applies to one or more fields, take out the field value set corresponding to all fields of documents A and B, execute each matching rule in sequence, and the data that meets the conditions of the previous rule will continue to participate in the subsequent matching until all fields of the document are matched, and then the matching result can be obtained. The existing solution requires serial execution of each matching rule, which is inefficient. Summary of the invention

[0004] The embodiments of the present invention provide a reconciliation method, system and related equipment for improving the efficiency of document reconciliation.

[0005] A first aspect of an embodiment of the present invention provides a reconciliation method, which may include:

[0006] According to the specified fields in the preset matching rules, a field value set corresponding to each specified field is extracted from the two data sets to be matched. Each preset matching rule specifies a specified field in each of the two data sets as an associated field. Each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set.

[0007] Using a preset matching algorithm corresponding to a preset matching rule, matching the field value set corresponding to the associated field to obtain a matching result of the associated field;

[0008] A successfully matched target document is identified according to the matching result of the associated fields, wherein the associated fields of all fields in the target document exist in the same document in another data set.

[0009] Optionally, as a possible implementation manner, in the reconciliation method in the embodiment of the present invention, a preset matching algorithm corresponding to a preset matching rule is used to match a field value set corresponding to an associated field, including:

[0010] Use the field value in the associated field as the key, and the ID of the document where each field value is located as the value, and store the field value sets corresponding to the associated field in independent HashMap data structures;

[0011] When it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0012] Optionally, as a possible implementation manner, in the reconciliation method in the embodiment of the present invention, a preset matching algorithm corresponding to a preset matching rule is used to match a field value set corresponding to an associated field, and further includes:

[0013] Using the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, the field value sets corresponding to the associated field are stored in independent HashMap data structures.

[0014] When all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated fields corresponding to the target Value values ​​match successfully.

[0015] Optionally, as a possible implementation manner, in the reconciliation method in the embodiment of the present invention, a preset matching algorithm corresponding to a preset matching rule is used to match a field value set corresponding to an associated field, and further includes:

[0016] When the field value in the associated field is a date, the date is converted into a time period string as the key, and the ID of the document where each field value is located is used as the value. The field value sets corresponding to the associated field are stored in independent HashMap data structures respectively;

[0017] When it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0018] Optionally, as a possible implementation manner, the reconciliation method in the embodiment of the present invention uses a preset matching algorithm corresponding to a preset matching rule to match a field value set corresponding to an associated field, and further includes:

[0019] When the field value in the associated field is a numeric value, the difference range corresponding to the numeric value is used as the key, and the ID of the document where each field value is located is used as the value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure;

[0020] When it is found that the key of the difference range corresponding to the current value has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0021] A second aspect of an embodiment of the present invention provides an account reconciliation system, which may include:

[0022] The extraction module extracts a field value set corresponding to each specified field from two data sets to be matched according to the specified fields in the preset matching rules. Each preset matching rule specifies a specified field in each of the two data sets as a related field. Each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set.

[0023] The matching module uses a preset matching algorithm corresponding to a preset matching rule to match a set of field values ​​corresponding to the associated field to obtain a matching result of the associated field;

[0024] The identification module identifies a successfully matched target document according to the matching result of the associated fields, wherein the associated fields of all fields in the target document exist in the same document of another data set.

[0025] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may include:

[0026] The first matching unit uses the field value in the associated field as the key and the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

[0027] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0028] The second matching unit uses the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when all keys of the same field value have matching target Value values ​​in two independent HashMaps respectively, it is determined that the associated field corresponding to the target Value value matches successfully.

[0029] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0030] The third matching unit, when the field value in the associated field is a date, converts the date into a time period string as the key, takes the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated fields in independent HashMap data structures respectively; when it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

[0031] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0032] The fourth matching unit, when the field value in the associated field is a numerical value, uses the difference range corresponding to the numerical value as the key, and the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when it is found that the key of the difference range corresponding to the current numerical value has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0033] A third aspect of an embodiment of the present invention provides a computer device, the computer device comprising a processor, the processor being configured to implement the steps in the first aspect and any possible implementation manner of the first aspect when executing a computer program stored in a memory.

[0034] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps in the first aspect and any possible implementation of the first aspect are implemented.

[0035] It can be seen from the above technical solutions that the embodiments of the present invention have the following advantages:

[0036] In an embodiment of the present invention, the reconciliation system can extract a field value set corresponding to each specified field from two data sets to be matched according to the specified fields in the preset matching rules, and then use a preset matching algorithm corresponding to the preset matching rules to match the field value set corresponding to the associated fields to obtain the matching results of the associated fields, and identify the successfully matched target document according to the matching results of the associated fields. Compared with the prior art, multiple fields in the same document can be matched in parallel, shortening the matching time and improving the reconciliation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of an embodiment of a reconciliation method in an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of a specific application embodiment of a reconciliation method in an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of an embodiment of a reconciliation system in an embodiment of the present invention;

[0040] Figure 4 FIG. 1 is a schematic diagram of an embodiment of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The embodiments of the present invention provide a reconciliation method, system and related equipment for improving the efficiency of document reconciliation.

[0042] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0043] The terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0044] In the existing reconciliation method, the matching rules of each field are executed serially in sequence, and the data that meets the conditions of the previous rule continues to participate in the subsequent matching until all the fields of the document are matched, and the matching result can be obtained, which is inefficient. The present invention matches the field value sets of each field in parallel, greatly shortening the matching time.

[0045] For ease of understanding, the specific process in the embodiment of the present invention is described below. Figure 1 , an embodiment of a reconciliation method in an embodiment of the present invention may include:

[0046] 101. According to the specified fields in the preset matching rules, a field value set corresponding to each specified field is extracted from the two data sets to be matched, wherein each preset matching rule specifies one specified field in each of the two data sets as an associated field, and each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set;

[0047] In actual use, multiple documents to be reconciled can form two data sets, each document contains multiple fields, each field can be set with the same or different matching rules, and each preset matching rule specifies a specified field in each of the two data sets as an associated field. In order to execute the matching rules of each field in parallel, the reconciliation system in the embodiment of the present invention can extract the field value set corresponding to each specified field from the two data sets to be matched according to the specified field in the preset matching rule.

[0048] For example, please refer to the data set A shown in Table 1 and the data set B shown in Table 2, where data set A includes document (number) 11 (including field values ​​a1, b1, c1, d1), document (number) 12 (including field values ​​a2, b2, c2, d2), and document (number) 13 (including field values ​​a3, b3, c3, d3); data set B includes document (number) 21 (including field values ​​A1, B1, C1, D1), document (number) 22 (including field values ​​A2, B2, C2, D2), and document (number) 23 (including field values ​​A3, B3, C3, D3). Four rules can be configured for the four fields (a, b, c, d) in the data set A: Rule 1, determine whether the field values ​​of the specified field a and the specified field A are equal; Rule 1, determine whether the field values ​​of field a and field A are equal; Rule 2, determine whether the date interval between field b and field B is within a preset period (for example, 30 days); Rule 3, determine whether the names (strings) of field c and field C are similar; Rule 4, determine whether the difference between the field values ​​of field d and field D is within a preset range. According to the rules, the field value set corresponding to the specified fields (a, b, c, d, A, B, C, D) can be extracted, for example, the field value set of the specified field a includes a1, a2, and a3.

[0049] ID a b c d 11 a1 b1 c1 d1 12 a2 b2 c2 d2 13 a3 b3 c3 d3

[0050] Table 1

[0051] ID A B C D 21 A1 B1 C1 D1 22 A2 B2 C2 D2 23 A3 B3 C3 D3

[0052] Table 2

[0053] 102. Using a preset matching algorithm corresponding to a preset matching rule, match a field value set corresponding to the associated field to obtain a matching result of the associated field;

[0054] In the embodiment of the present invention, a preset matching algorithm can be configured in advance for each preset matching rule, and the field value set corresponding to the associated field is matched to obtain the matching result of the associated field. The specific preset matching algorithm can be reasonably set according to actual needs, and is not specifically limited here.

[0055] Using the example in step 101, see Figure 2 Based on rule 1, the matching results of the associated fields (field a and field A) can be obtained. For example, if the field values ​​a1 and A1 are equal, it means that documents 11 and 21 are successfully matched in the associated fields (field a and field A); if the field values ​​a2 and A2 are equal, it means that documents 12 and 22 are successfully matched in the associated fields (field a and field A). Based on rule 2, the matching results of the associated fields (field b and field B) can be obtained. For example, if the date intervals of field values ​​b1 and b3 and B1 are within the preset period, it means that documents 11 and 13 are successfully matched in the associated fields (field b and field B) of document 21; if the date intervals of field values ​​b2 and B2 are within the preset period, it means that documents 12 and 22 are successfully matched in the associated fields (field b and field B). Based on rule 3, the matching results of the associated fields (field c and field C) can be obtained. For example, if the string of field values ​​c1 and C2 is similar, it means that document 11 and document 22 are successfully matched in the associated field (field c and field C); if the string of field value c2 is similar to that of C1 and C2, it means that document 12 is successfully matched with document 21 and document 22 in the associated field (field c and field C). Based on rule 4, the matching results of the associated fields (field d and field D) can be obtained. For example, if the field values ​​d2 and D2 are equal, it means that document 12 and document 22 are successfully matched in the associated field (field d and field D); if the field value d3 and D1 are equal, it means that document 13 and document 21 are successfully matched in the associated field (field d and field D).

[0056] 103. The successfully matched target document is identified based on the matching result of the associated fields, and the associated fields of all fields in the target document exist in the same document in another data set.

[0057] In the embodiment of the present invention, the successfully matched target document can be identified according to the matching result of the associated fields, and the associated fields of all fields in the target document exist in the same document in another data set.

[0058] by Figure 2 The example shown is used to illustrate that only document 12 and document 22 are successfully matched in all associated fields (field a and field A, field b and field B, field c and field C, field d and field D), which means that only document 12 and document 22 are target documents.

[0059] In an embodiment of the present invention, the reconciliation system can extract a field value set corresponding to each specified field from two data sets to be matched according to the specified fields in the preset matching rules, and then use a preset matching algorithm corresponding to the preset matching rules to match the field value set corresponding to the associated fields to obtain the matching results of the associated fields, and identify the successfully matched target document according to the matching results of the associated fields. Compared with the prior art, multiple fields in the same document can be matched in parallel, shortening the matching time and improving the reconciliation efficiency.

[0060] In the above Figure 1 On the basis of the illustrated embodiment, for ease of understanding, a preset matching algorithm corresponding to a preset matching rule available in the embodiment of the present invention will be described.

[0061] Optionally, as a possible implementation, a preset matching algorithm corresponding to a preset matching rule is used to match the field value set corresponding to the associated field, which may include: using the field value in the associated field as the key, and the identity identification ID of the document where each field value is located as the Value, and storing the field value set corresponding to the associated field in an independent HashMap data structure; when it is queried that the same key has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

[0062] Specifically, you can use the HashMap.get method to obtain the IdList corresponding to the specified Key value (string value). If there is no document ID corresponding to the Key value, an empty list is generated, the document ID is put in, and the Key value (string value) and the document ID are put in using the HashMap.put method. If the document ID corresponds to the Key value, the Key value (string value) and the document ID are put in using the HashMap.put method. Among them, the document ID of data set A and the document ID of data set B are independent of each other. The two document IDs under the same Key are matching data. This process directly uses the hash structure to obtain the matching result set, with a time complexity of O(lgN), which is extremely efficient.

[0063] Optionally, as a possible implementation, a preset matching algorithm corresponding to a preset matching rule is used to match the field value set corresponding to the associated field, which may include: using the character of each byte of the field value in the associated field as the key, and using the character information in the previous byte as the Value, and storing the field value set corresponding to the associated field in an independent HashMap data structure; when all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0064] Specifically, the characters in the field value are used as the key, the value is the index information of the previous character, and the HashMap is used as the index storage structure. At the beginning of the operation, the index level N is determined according to the character types of the input original string and the target string, that is, there are N HashMaps as index containers. Take the matching process of the original string "accagx" and the target string "cag" as an example: 1. Create an index for each character of the original string "accagx" in turn, add a as the key to the map, and the value is the character information before a. If there is no character, it is empty. Then create the first two character information of a, which is also not empty, until the index information of the first N characters is created, and the N-level index creation of the character a is ended. Then create the index of c, the key is c, the value is the character information that records the previous character a, and the same as the first character a, and the index of the first N characters is created... Repeatedly until all characters are created. Finally, create the index of character x, record the index information of the first N characters, and record the index information of the last character in the backtracking list. When all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully. For example, when the strings "cag" and "accagx" exist in two data sets respectively, all keys of the string "cag" have matching target Value values ​​in two independent HashMaps, then it can be determined that the corresponding associated fields match successfully. This process uses a multi-level hash algorithm to establish an index with a time complexity of O(nlgN), which is much more efficient than traditional algorithms.

[0065] Optionally, as a possible implementation, a preset matching algorithm corresponding to a preset matching rule is used to match the field value set corresponding to the associated field, which may include: when the field value in the associated field is a date, the date is converted into a time period string as a key, the identity ID of the document where each field value is located is used as a Value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure; when it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0066] Specifically, the date value, such as 2020-01-01, 2020-01-02, is formatted as a string and stored in the HashMap as a Key, and the Value value is the corresponding document ID. The date difference can be specified to be no more than 30 days, so according to the specified difference N, key = 2020-01-01, 2020-01-02...2020-01-N (01 <= N <= 30), the Value value is equal, and the string is inserted into the HashMap in sequence. Finally, the IDList of data set A and the IDList value of data set B corresponding to each Key are taken out to directly obtain the matching date difference data. This process directly uses the hash structure to obtain the matching result set, with a time complexity of O(lgN), which is extremely efficient.

[0067] Optionally, as a possible implementation, a preset matching algorithm corresponding to a preset matching rule is used to match the field value set corresponding to the associated field, which may include: when the field value in the associated field is a numeric value, the difference range corresponding to the numeric value is used as the key, and the identity identification ID of the document where each field value is located is used as the Value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure; when it is queried that the key of the difference range corresponding to the current numeric value has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0068] See also Figure 3 The embodiment of the present invention further provides a reconciliation system, which may include:

[0069] The extraction module 301 extracts a field value set corresponding to each specified field from two data sets to be matched according to the specified fields in the preset matching rules. Each preset matching rule specifies one specified field in each of the two data sets as an associated field. Each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set.

[0070] The matching module 302 uses a preset matching algorithm corresponding to a preset matching rule to match a field value set corresponding to the associated field to obtain a matching result of the associated field;

[0071] The identification module 303 identifies the successfully matched target document according to the matching result of the associated fields, and the associated fields of all the fields in the target document exist in the same document in another data set.

[0072] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may include:

[0073] The first matching unit uses the field value in the associated field as the key and the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

[0074] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0075] The second matching unit uses the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when all keys of the same field value have matching target Value values ​​in two independent HashMaps respectively, it is determined that the associated field corresponding to the target Value value matches successfully.

[0076] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0077] The third matching unit, when the field value in the associated field is a date, converts the date into a time period string as the key, takes the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated fields in independent HashMap data structures respectively; when it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

[0078] Optionally, as a possible implementation manner, the matching module in the embodiment of the present invention may further include:

[0079] The fourth matching unit, when the field value in the associated field is a numerical value, uses the difference range corresponding to the numerical value as the key, and the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when it is found that the key of the difference range corresponding to the current numerical value has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0081] The network diagram editor in the embodiment of the present invention is described above from the perspective of modular functional entities. Figure 4 , the computer device in the embodiment of the present invention is described below from the perspective of hardware processing:

[0082] The computer device 1 may include a memory 10, a processor 12 and an input / output bus 13. The processor 11 implements the above Figure 1 The steps in the embodiment of the reconciliation method shown are, for example, Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules or units in the above-mentioned device embodiments are realized.

[0083] In some embodiments of the present invention, the processor is specifically configured to implement the following steps:

[0084] According to the specified fields in the preset matching rules, a field value set corresponding to each specified field is extracted from the two data sets to be matched. Each preset matching rule specifies a specified field in each of the two data sets as an associated field. Each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set.

[0085] Using a preset matching algorithm corresponding to a preset matching rule, matching the field value set corresponding to the associated field to obtain a matching result of the associated field;

[0086] The successfully matched target document is identified based on the matching results of the associated fields, and the associated fields of all fields in the target document exist in the same document in another data set.

[0087] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0088] Use the field value in the associated field as the key, and the ID of the document where each field value is located as the value, and store the field value sets corresponding to the associated field in independent HashMap data structures;

[0089] When it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0090] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0091] Using the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, the field value sets corresponding to the associated field are stored in independent HashMap data structures.

[0092] When all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated fields corresponding to the target Value values ​​match successfully.

[0093] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0094] When the field value in the associated field is a date, the date is converted into a time period string as the key, and the ID of the document where each field value is located is used as the value. The field value sets corresponding to the associated field are stored in independent HashMap data structures respectively;

[0095] When it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0096] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0097] When the field value in the associated field is a numeric value, the difference range corresponding to the numeric value is used as the key, and the ID of the document where each field value is located is used as the value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure;

[0098] When it is found that the key of the difference range corresponding to the current value has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0099] The memory 10 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 10 may be an internal storage unit of the computer device 1, such as a hard disk of the computer device 1. In other embodiments, the memory 10 may also be an external storage device of the computer device 1, such as a plug-in hard disk equipped on the computer device 1, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. Further, the memory 10 may also include both an internal storage unit of the computer device 1 and an external storage device. The memory 10 may not only be used to store application software and various types of data installed in the computer device 1, such as the code of the computer program 01, etc., but may also be used to temporarily store data that has been output or is to be output.

[0100] In some embodiments, the processor 12 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 10, such as executing the computer program 01.

[0101] The input / output bus 13 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.

[0102] Furthermore, the computer device may also include a wired or wireless network interface 14. The network interface 14 may optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the computer device 1 and other electronic devices.

[0103] Optionally, the computer device 1 may also include a user interface, which may include a display (Display), an input unit such as a keyboard (Keyboard), and optionally, the user interface may also include a standard wired interface and a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the computer device 1 and to display a visual user interface.

[0104] Figure 4 Only the computer device 1 having components 11-14 and the computer program 01 is shown. It can be understood by those skilled in the art that Figure 4 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0105] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps can be implemented:

[0106] According to the specified fields in the preset matching rules, a field value set corresponding to each specified field is extracted from the two data sets to be matched. Each preset matching rule specifies a specified field in each of the two data sets as an associated field. Each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set.

[0107] Using a preset matching algorithm corresponding to a preset matching rule, matching the field value set corresponding to the associated field to obtain a matching result of the associated field;

[0108] The successfully matched target document is identified based on the matching results of the associated fields, and the associated fields of all fields in the target document exist in the same document in another data set.

[0109] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0110] Use the field value in the associated field as the key, and the ID of the document where each field value is located as the value, and store the field value sets corresponding to the associated field in independent HashMap data structures;

[0111] When it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0112] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0113] Using the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, the field value sets corresponding to the associated field are stored in independent HashMap data structures.

[0114] When all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated fields corresponding to the target Value values ​​match successfully.

[0115] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0116] When the field value in the associated field is a date, the date is converted into a time period string as the key, and the ID of the document where each field value is located is used as the value. The field value sets corresponding to the associated field are stored in independent HashMap data structures respectively;

[0117] When it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0118] Optionally, as a possible implementation, the processor may also be used to implement the following steps:

[0119] When the field value in the associated field is a numeric value, the difference range corresponding to the numeric value is used as the key, and the ID of the document where each field value is located is used as the value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure;

[0120] When it is found that the key of the difference range corresponding to the current value has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

[0121] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0124] If the integrated unit 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 this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0125] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A reconciliation method, characterized in that: include: According to the fields contained in multiple documents, the multiple documents to be reconciled are combined into two data sets to be matched; According to the specified fields in the preset matching rules, a field value set corresponding to each specified field is extracted from the two data sets, wherein each preset matching rule specifies one specified field in each of the two data sets as an associated field, and each data set includes multiple documents, and each document includes field values ​​of all fields in the corresponding data set; Using a preset matching algorithm corresponding to a preset matching rule, matching the field value sets corresponding to the associated fields in parallel to obtain matching results for the associated fields; A successfully matched target document is identified according to the matching result of the associated fields, wherein the associated fields of all fields in the target document exist in the same document in another data set.

2. The method according to claim 1, characterized in that The method of using a preset matching algorithm corresponding to a preset matching rule to match a set of field values ​​corresponding to the associated fields in parallel to obtain a matching result of the associated fields includes: Use the field value in the associated field as the key, and the ID of the document where each field value is located as the value, and store the field value sets corresponding to the associated field in independent HashMap data structures; When it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

3. The method according to claim 2, characterized in that The method adopts a preset matching algorithm corresponding to a preset matching rule to match the field value set corresponding to the associated field and the field value set corresponding to the associated field in parallel to obtain a matching result of the associated field, and further includes: Using the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, the field value sets corresponding to the associated field are stored in independent HashMap data structures. When all keys of the same field value have matching target Value values ​​in two independent HashMaps, it is determined that the associated fields corresponding to the target Value values ​​match successfully.

4. The method according to claim 3, characterized in that The method adopts a preset matching algorithm corresponding to a preset matching rule to match the field value set corresponding to the associated field in parallel to obtain a matching result of the associated field, and further includes: When the field value in the associated field is a date, the date is converted into a time period string as the key, and the ID of the document where each field value is located is used as the value. The field value sets corresponding to the associated field are stored in independent HashMap data structures respectively; When it is found that the key of the time period string corresponding to the current date has a matching target Value value in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

5. The method according to claim 4, characterized in that The method adopts a preset matching algorithm corresponding to a preset matching rule to match the field value set corresponding to the associated field in parallel to obtain a matching result of the associated field, and further includes: When the field value in the associated field is a numeric value, the difference range corresponding to the numeric value is used as the key, and the ID of the document where each field value is located is used as the value, and the field value set corresponding to the associated field is stored in an independent HashMap data structure; When it is found that the key of the difference range corresponding to the current value has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value matches successfully.

6. A reconciliation system, characterized in that: include: An extraction module, used to group the multiple documents to be reconciled into two data sets to be matched according to the fields contained in the multiple documents; The extraction module is further used to extract a field value set corresponding to each specified field from the two data sets according to the specified field in the preset matching rule, each preset matching rule specifies a specified field in each of the two data sets as an associated field, each data set includes multiple documents, and each document contains field values ​​of all fields in the corresponding data set; A matching module, using a preset matching algorithm corresponding to a preset matching rule, matches a set of field values ​​corresponding to the associated fields in parallel, and obtains a matching result of the associated fields; The identification module identifies a successfully matched target document according to the matching result of the associated fields, wherein the associated fields of all fields in the target document exist in the same document of another data set.

7. The system according to claim 6, characterized in that The matching module comprises: The first matching unit uses the field value in the associated field as the key and the identity ID of the document where each field value is located as the Value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when it is found that the same key has matching target Value values ​​in two independent HashMaps, it is determined that the associated field corresponding to the target Value value is matched successfully.

8. The system according to claim 7, characterized in that The matching module also includes: The second matching unit uses the characters of each byte of the field value in the associated field as the key and the character information in the previous byte as the value, and stores the field value sets corresponding to the associated field in independent HashMap data structures respectively; when all keys of the same field value have matching target Value values ​​in two independent HashMaps respectively, it is determined that the associated field corresponding to the target Value value matches successfully.

9. A computer device, characterized in that: The computer device comprises a processor, and the processor is configured to implement the steps of the method according to any one of claims 1 to 5 when executing a computer program stored in a memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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