Massive multi-element data intelligent collection system and collection method

Abstract

The application relates to a mass multi-element data intelligent collection system and a collection method, wherein the mass multi-element data intelligent collection system comprises a collection extraction module, a collection storage module, a collection selection module and a collection query module. In view of the characteristics of multi-element data query request elements in a large-scale user environment, such as high concurrency of query requests, large storage data volume of multi-element data of users and the like, the mass multi-element data intelligent collection system can meet the key problems of rapid response to online concurrent requests of large-scale users and rapid multi-element search and query of mass multi-element data. In the storage stage, the mass multi-element data intelligent collection system extracts according to different element characteristics of invoices, stores into a collection information table after collection and classification, and in the query stage, originally required multi-element joint query is simplified into once element identification value calculation and twice single-element query, so that all electronic invoice information meeting the query condition can be quickly obtained, and the query time is greatly optimized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a mass multi-element data intelligent collection system and a collection method. BACKGROUND

[0002] With the development of the information age, the use scale of mass multi-element data is also getting larger and larger. For example, after a user registers a new system, after a buyer places an order, and after a merchant issues an electronic invoice, the generated data will be stored in a database for storage and subsequent query.

[0003] At present, the industry usually uses a relational database to store multi-element data information. The relational database is a database that uses a relational model to organize data. It stores data in the form of rows and columns to facilitate user understanding. The series of rows and columns of the relational database are called tables, and a group of tables constitutes a database.

[0004] In the relational database, although the general storage and query invoice requirements can be met, with the increase of business volume, when storing and querying mass multi-source heterogeneous data under large-scale users, the traditional relational database query response speed is slow, and under high concurrency conditions, problems such as service downtime are increasingly serious.

[0005] Taking electronic invoice information as an example, the following problems exist in the data service platform query under a large-scale user environment: Since indexes need to be established for multiple fields, the existing method consumes a lot of resources when performing joint queries on mass multi-element data, and the time cost is large, and the query efficiency is low. The existing method for improving the query efficiency of multi-element data depends on specific fields and data types, and although it can improve the query efficiency of multi-element data in specific scenarios, it cannot improve the query rate of any combination of elements in scenarios with many query elements. The existing method for improving the query efficiency of multi-element data depends on a specific design structure or framework, has poor portability, and has a high use threshold. When introducing the existing optimization technology into an existing system, even if the existing system structure is compatible with the introduced optimization technology, a large amount of modification of the existing data may be required, and the configuration of the new method in the old system is relatively cumbersome. SUMMARY

[0006] In order to solve the above problems in the prior art, the present application provides a mass multi-element data intelligent collection system and a collection method. The technical problems to be solved by the present application are solved by the following technical solutions:

[0007] The present application provides a mass multi-element data intelligent collection system, comprising:

[0008] The aggregation extraction module is configured to extract key elements of the corresponding invoice according to the received invoice aggregation request, obtain a plurality of aggregation types according to the key elements, acquire identification information corresponding to each aggregation type, and generate aggregation information of the corresponding invoice according to the plurality of identification information.

[0009] The aggregation storage module is configured to store the aggregation information in an aggregation information table and set identification information in the aggregation information table as an index item.

[0010] The aggregation selection module is configured to determine an aggregation type corresponding to the invoice query request according to the received invoice query request and calculate an element identification value corresponding to the invoice query request.

[0011] The aggregation query module is configured to query the aggregation information table according to the aggregation type and the element identification value corresponding to the invoice query request to obtain invoice IDs meeting the conditions.

[0012] In an embodiment of the present application, the invoice aggregation request includes invoice information, and the invoice information includes key elements of the invoice.

[0013] In an embodiment of the present application, the key elements of the invoice include an invoice ID, a buyer name, a buyer taxpayer identification number, a buyer address, a buyer telephone number, a buyer bank of deposit, a buyer bank account number, a commodity name, a commodity unit price, a commodity quantity, a commodity total amount, a commodity tax rate, a commodity tax amount, a seller name, a seller taxpayer identification number, a seller address, a seller telephone number, a seller bank of deposit, a seller bank account number, a payee name, an invoicer name, an invoice code, an invoice date, a check code and a machine code.

[0014] In an embodiment of the present application, the aggregation extraction module includes:

[0015] The key element extraction unit is configured to extract key elements of the corresponding invoice according to the invoice information.

[0016] The aggregation type division unit is configured to generate a plurality of aggregation types according to the key elements, wherein the aggregation types are combinations of one or more key elements.

[0017] The aggregation information generation unit is configured to perform a concatenation operation on the key elements in each aggregation type to obtain merged key elements, perform hash value calculation on the merged key elements by using a hash algorithm to obtain identification information corresponding to each aggregation type, and construct aggregation information of the invoice according to the invoice ID and the identification information corresponding to the plurality of aggregation types.

[0018] In one embodiment of the present application, the invoice query request comprises a query element of the invoice, and the query element comprises one or more key elements of the invoice.

[0019] In one embodiment of the present application, the aggregation selection module comprises:

[0020] An aggregation type determination unit is configured to determine an aggregation type corresponding to the invoice query request according to the query element;

[0021] An identification value calculation unit is configured to perform a concatenation operation on the query element to obtain a merged query element, and perform hash value calculation on the merged query element by using a hash algorithm to obtain an element identification value corresponding to the invoice query request.

[0022] In one embodiment of the present application, the aggregation storage module is further configured to send the invoice information to an electronic invoice storage system for storage, wherein, in the electronic invoice storage system, the invoice ID is set as an index item.

[0023] Correspondingly, the aggregation query module is further configured to send the invoice ID meeting the condition to the electronic invoice storage system for invoice ID query to obtain a query result, and the query result is the invoice information corresponding to the invoice ID.

[0024] The present application further provides a mass multi-element data intelligent aggregation method, comprising an aggregation storage method and an aggregation query method, wherein,

[0025] The aggregation storage method comprises:

[0026] According to the received invoice aggregation request, key elements of the corresponding invoice are extracted, a plurality of aggregation types are obtained according to the key elements, identification information corresponding to each aggregation type is obtained, and aggregation information of the corresponding invoice is generated according to the plurality of identification information;

[0027] The aggregation information is stored in an aggregation information table, and the identification information in the aggregation information table is set as an index item.

[0028] The aggregation query method comprises:

[0029] According to the received invoice query request, the aggregation type corresponding to the invoice query request is determined, and an element identification value corresponding to the invoice query request is calculated;

[0030] According to the aggregation type and the element identification value corresponding to the invoice query request, the aggregation information table is queried to obtain an invoice ID meeting the condition.

[0031] In one embodiment of the present application, the aggregation storage method further comprises:

[0032] send the invoice information to an electronic invoice storage system for storage, wherein the invoice ID is set as an index item in the electronic invoice storage system;

[0033] Correspondingly, the aggregation query method further comprises:

[0034] send the invoice ID meeting the condition to the electronic invoice storage system for invoice ID query to obtain a query result, the query result being invoice information corresponding to the invoice ID.

[0035] The application further provides an electronic invoice management system, comprising an electronic invoice billing system, an electronic invoice query system, an electronic invoice storage system and the mass multi-element data intelligent aggregation system according to any one of claims 1-7, wherein,

[0036] The electronic invoice billing system is configured to generate invoice information, generate an invoice aggregation request according to the invoice information and send the invoice aggregation request to the mass multi-element data intelligent aggregation system.

[0037] The electronic invoice query system is configured to generate an invoice query request and send the invoice query request to the mass multi-element data intelligent aggregation system, and further configured to parse and restore the query result.

[0038] The electronic invoice storage system is configured to store the invoice information.

[0039] Compared with the prior art, the application has the following beneficial effects:

[0040] 1. In the storage stage, the mass multi-element data intelligent aggregation system according to the application divides multiple aggregation types according to key elements of invoices, obtains identification information of the aggregation types corresponding to the invoices, creates an aggregation information table to realize storage of identification information of specific combined elements, sets the identification information in the aggregation information table as an index item and further provides support for subsequent accurate retrieval based on elements.

[0041] 2. In the query stage, the mass multi-element data intelligent aggregation system according to the application converts original joint query into aggregation information query constructed according to key elements, merges query elements in the mass multi-element data intelligent aggregation system to obtain corresponding element identification values, queries the aggregation information table according to the element identification values to obtain invoice IDs meeting the condition.

[0042] 3. The mass multi-element data intelligent collection system of the present application can store mass multi-element data and perform retrieval, and will not cause a large amount of resource consumption when retrieving mass multi-element data, and has less time consumption and high query efficiency.

[0043] 4. The mass multi-element data intelligent collection system and collection method of the present application extract according to different element characteristics of data during data storage, store in the collection information table after collection and classification, simplify the original joint query of multiple elements into once element identification value calculation and twice single element query, and greatly optimize the query time.

[0044] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the content of the specification can be implemented, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is a structural block diagram of a mass multi-element data intelligent collection system provided by an embodiment of the present application;

[0046] Figure 2 is a flowchart of a collection and storage method provided by an embodiment of the present application;

[0047] Figure 3 is a flowchart of a collection and query method provided by an embodiment of the present application;

[0048] Figure 4 is a structural block diagram of an electronic invoice management system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined purpose, the following will be described in detail in combination with the drawings and specific embodiments, and a mass multi-element data intelligent collection system and collection method according to the present application will be described in detail.

[0050] The foregoing and other technical contents, characteristics and effects of the present application can be clearly presented in the following specific embodiment description with the aid of the accompanying drawings. Through the description of the specific embodiments, the technical means and effects adopted by the present application to achieve the predetermined purpose can be more deeply and specifically understood. However, the accompanying drawings are provided for reference and description only, and are not used to limit the technical solutions of the present application.

[0051] Embodiment one

[0052] Please refer to Figure 1 , Figure 1The application provides a structure block diagram of a mass multi-element data intelligent collection system, as shown in the figure, the mass multi-element data intelligent collection system comprises a collection extraction module, a collection storage module, a collection selection module and a collection query module.

[0053] The collection extraction module is used for extracting key elements of the corresponding invoice according to the received invoice collection request, obtaining a plurality of collection types according to the key elements, acquiring identification information corresponding to each collection type, and generating collection information of the corresponding invoice according to the plurality of identification information.

[0054] In an optional embodiment, the invoice collection request comprises invoice information, and the invoice information comprises key elements of the invoice.

[0055] Optionally, any field in the electronic invoice information table can be used as the key element of the invoice, including an invoice ID, a purchaser name, a purchaser taxpayer identification number, a purchaser address,

[0056] a purchaser telephone number, a purchaser bank account, a purchaser account number, a commodity name, a commodity unit price, a commodity quantity, a commodity total amount, a commodity tax rate, a commodity tax amount, a seller name, a seller taxpayer identification number, a seller address, a seller telephone number, a seller bank account, a seller account number, a payee name, an invoicer name, an invoice code, an invoice date, a check code and a machine code.

[0057] For example, the purchaser name is a key element, and the commodity name is also a key element.

[0058] In an optional embodiment, the collection extraction module comprises a key element extraction unit, a collection type division unit and a collection information generation unit. The key element extraction unit is used for extracting key elements of the corresponding invoice according to the invoice information.

[0059] The collection type division unit is used for generating a plurality of collection types according to the key elements. Optionally, the collection type is a combination of one or more key elements.

[0060] It should be noted that each key element can be used as an independent collection type, or can be used as a key element in a plurality of other collection types. In this embodiment, the collection type comprising a plurality of key elements can be divided according to a commonly used joint query mode.

[0061] For example, in a joint query mode using the purchaser name and the seller name, the purchaser name is a key element, and the seller name is a key element. Using the two key elements [purchaser name, seller name] as the condition of this joint query, the condition [purchaser name, seller name] can be recorded as a collection type.

[0062] Exemplarily, in the joint query mode using the commodity name, the commodity quantity and the biller name, the commodity name, the commodity quantity and the biller name are respectively used as the conditions of the joint query, and the condition [commodity name, commodity quantity, biller name] can be recorded as a collection type.

[0063] The collection information generation unit is configured to perform a concatenation operation on the key elements in each collection type to obtain merged key elements, perform hash value calculation on the merged key elements by using a hash algorithm, obtain the identification information corresponding to each collection type, and construct the collection information of the invoice according to the invoice ID and the identification information corresponding to the plurality of collection types.

[0064] In this embodiment, the hash value of the merged key elements calculated by using the hash algorithm is used as the identification information corresponding to the collection type.

[0065] Optionally, according to the defined collection type, the content of the corresponding field is extracted from the invoice information into the corresponding collection type, and the key elements are merged into a string of texts ElementCombine, and each collection type corresponds to one merged ElementCombine, wherein the ElementCombine is composed of the key elements concatenated in sequence. For each ElementCombine, a hash algorithm is used to calculate the ElementHash, that is, the identification information corresponding to the collection type. Then, the invoice ID of the invoice information and the hash values of all the collection types calculated are combined to form the collection information of the invoice.

[0066] The hash (Hash) algorithm, also known as the hash algorithm, is to transform the input of any length into the output of fixed length by using the hash algorithm, and the output is the hash value. In an optional embodiment, a common hash algorithm such as MD5, SHA (SHA can be further divided into SHA-1, SHA-224, SHA-256, SHA-384, and SHA-512, etc.), SM3, etc. can be used for hash value calculation.

[0067] It should be noted that in the embodiment, the identification information is mainly generated and spliced by the hash algorithm in the acquisition process of the identification information, and in other embodiments, a specific encoding algorithm, encryption algorithm, signature algorithm, etc. can be used instead of the hash algorithm. Alternatively, when acquiring the identification information, the base64 encoding of the concatenated operation of each key element or the conversion to a hexadecimal string can be calculated, and a specified length is intercepted as the identification information; or a specific key and signature algorithm can be used to calculate the signature value of the concatenated elements, as the identification information; or a specific encryption algorithm and encryption key can be used to calculate the ciphertext of the concatenated elements, and a specified length is intercepted as the identification information.

[0068] The aggregation storage module is configured to store the aggregation information in the aggregation information table, and set the identification information in the aggregation information table as an index item.

[0069] In an optional embodiment, the aggregation storage module maintains an aggregation information table (or divided into multiple according to the number of invoices). The aggregation information table includes an invoice ID field and a plurality of aggregation type fields. The invoice ID and the hash values corresponding to the plurality of aggregation types in the aggregation information are stored in the corresponding positions in the aggregation information table. The hash values in the aggregation information table are set as index items to support subsequent element-based accurate retrieval. The aggregation storage module inserts the new aggregation information into the aggregation information table after receiving the new aggregation information.

[0070] The aggregation selection module is configured to determine the aggregation type corresponding to the invoice query request according to the received invoice query request, and calculate the element identification value corresponding to the invoice query request.

[0071] In an optional embodiment, the invoice query request includes a query element of the invoice, and the query element includes one or more key elements of the invoice.

[0072] In an optional embodiment, the aggregation selection module includes an aggregation type determination unit and an identification value calculation unit. The aggregation type determination unit is configured to determine the aggregation type corresponding to the invoice query request according to the query element.

[0073] For example, if all invoice information of the purchase party name is Zhang San and the seller name is Li Si supermarket is queried, the query element of the invoice includes two key elements of the purchase party name and the seller name, and it is determined that the aggregation type of the invoice query request is [purchase party name, seller name].

[0074] Exemplarily, if the query commodity name is A mobile phone, the commodity quantity is 1, and the invoicer name is Wang Wu, all the invoice information, the query elements of the invoice include the commodity name, the commodity quantity, and the invoicer name, and the aggregation type of the invoice query request is determined as [commodity name, commodity quantity, invoicer name].

[0075] The identification value calculation unit is configured to perform a concatenation operation on the query elements to obtain merged query elements, and perform hash value calculation on the merged query elements by using a hash algorithm to obtain the element identification value corresponding to the invoice query request.

[0076] In this embodiment, the hash value of the merged query elements calculated by using the hash algorithm is taken as the element identification value corresponding to the invoice query request.

[0077] Optionally, the specific steps of obtaining the element identification value are similar to the steps of obtaining the hash value of the aggregation type in the aggregation information generation unit, and thus are not described herein again.

[0078] It should be noted that in other embodiments in which specific encoding algorithms, encryption algorithms, signature algorithms, etc. are used instead of the hash algorithm to obtain the identification information, the corresponding method is used to obtain the element identification value corresponding to the invoice query request.

[0079] The aggregation query module is configured to query the aggregation information table according to the aggregation type and the element identification value corresponding to the invoice query request to obtain the invoice ID meeting the condition.

[0080] Further, in other embodiments, the aggregation storage module is further configured to send the invoice information to an electronic invoice storage system for storage, wherein the invoice ID is set as an index item in the electronic invoice storage system. Correspondingly, the aggregation query module is further configured to send the invoice ID meeting the condition to the electronic invoice storage system for invoice ID query to obtain a query result, and the query result is the invoice information corresponding to the invoice ID.

[0081] Optionally, the electronic invoice storage system can be an external storage system independent of the massive multi-element data intelligent aggregation system, or can be a storage unit located in the massive multi-element data intelligent aggregation system.

[0082] The mass multi-element data intelligent collection system of the embodiment divides multiple collection types according to key elements of invoices in the storage stage, obtains identification information of the collection type corresponding to the invoices, and creates a collection information table to realize storage of identification information of specific combined elements, and sets the identification information in the collection information table as an index item, thereby further providing support for subsequent implementation of element-based accurate retrieval. In the query stage, the original joint query is converted into a collection information query constructed according to key elements, the query elements are combined in the mass multi-element data intelligent collection system, and the corresponding element identification value is calculated, and the element identification value is used to query the collection information table to obtain the invoice ID meeting the condition. Thereafter, the mass multi-element data intelligent collection system sends all the invoice IDs meeting the condition to the electronic invoice storage system for query based on the invoice ID, and all the electronic invoice information meeting the query condition can be quickly obtained.

[0083] Embodiment Two

[0084] The embodiment provides a mass multi-element data intelligent collection method, which comprises a collection storage method and a collection query method. Please refer to the flowchart of the collection storage method shown in Figure 2 As shown in the figure, the collection storage method of the embodiment comprises the following steps:

[0085] Step 201: According to the received invoice collection request, the key elements of the corresponding invoice are extracted, multiple collection types are obtained according to the key elements, the identification information corresponding to each collection type is obtained, and the collection information of the corresponding invoice is generated according to the multiple identification information.

[0086] Step 202: Store the collection information in the collection information table, and set the identification information in the collection information table as an index item.

[0087] In an optional embodiment, the collection storage method further comprises:

[0088] Step 203: Send the invoice information to the electronic invoice storage system for storage, wherein the invoice ID is set as an index item in the electronic invoice storage system.

[0089] Please refer to the flowchart of the collection query method shown in Figure 3 As shown in the figure, the collection query method of the embodiment comprises the following steps:

[0090] Step 301: According to the received invoice query request, determine the collection type corresponding to the invoice query request, and calculate the element identification value corresponding to the invoice query request;

[0091] Step 302: According to the collection type and the element identification value corresponding to the invoice query request, query the collection information table to obtain the invoice ID meeting the condition.

[0092] In an alternative embodiment, the method of aggregating queries further comprises:

[0093] Step 303: send the qualified invoice ID to the electronic invoice storage system for invoice ID query, and obtain the query result, which is the invoice information corresponding to the invoice ID.

[0094] The mass multi-element data intelligent aggregation method provided in this embodiment is applicable to the mass multi-element data intelligent aggregation system described in Embodiment One, and has similar implementation principles and technical effects, which will not be described here.

[0095] The mass multi-element data intelligent aggregation method of this embodiment extracts different elements of invoices during electronic invoice storage, stores the classified and aggregated information in the aggregation information table, simplifies the original multi-element joint query into one element identification value calculation and twice single-element query, and greatly optimizes the query time.

[0096] It should be noted that the above description is only one specific example of the mass multi-element data intelligent aggregation system and aggregation method of the present application, and does not constitute any limitation on the present application. Obviously, for those skilled in the art, after understanding the content and principles of the present application, various modifications and changes in form and details can be made without departing from the principles and structures of the present application. However, these modifications and changes based on the idea of the present application are still within the protection scope of the claims of the present application.

[0097] The mass multi-element data intelligent aggregation system and aggregation method of the present application is not limited to the electronic invoice scenario, and is still applicable in scenarios with mass data and similar needs for joint query. Among them, the primary key or unique field in the data table can be used as the object to be searched, any field in the data table can be used as the key element described in the present application, and any field combination that needs to be queried jointly can be used as the aggregation type, thereby constructing the aggregation information table, realizing aggregation storage and aggregation query.

[0098] For example, the mass multi-element data intelligent collection system and method of the present application is applied in a book management system, and a book information intelligent collection system and book information intelligent collection can be realized. There can be a book information table, which can have the following fields: book number, book ISBN, book name, author, publisher, publication date, introduction, book number, library location, and library code. Among them, the book number is the primary key of the table and can be used as the object of collection query and set as an index item in the database. Each field can be used as a key element in the book information intelligent collection system. Any key element can construct a collection type, such as in a joint query, finding all book numbers with the author as Zhang San and the publication date as 2023, then [author, publication date] can be recorded as a collection type. In the collection information table, the book number is the primary key of the collection information table, and each collection type is another field of the table and is marked as an index item. In the collection query, according to the key elements used in the joint query, the collection type is determined, and the element identification value corresponding to the collection type is calculated, and then the record containing the element identification value is searched in the collection information table to obtain the corresponding book number, and the collection query operation is completed.

[0099] Such various modifications and changes in form and details based on different application scenarios do not deviate from the idea of the present application and are still within the protection scope of the claims of the present application.

[0100] The mass multi-element data intelligent collection system and method of the present application extracts data according to different element characteristics during data storage, stores the classified data in the collection information table, simplifies the original multi-element joint query into once element identification value calculation and twice single-element query, and greatly optimizes the query time.

[0101] Embodiment three

[0102] This embodiment provides an electronic invoice management system, please see Figure 4 The structure block diagram of the electronic invoice management system is shown in the figure, the electronic invoice management system of the present application comprises: an electronic invoice billing system, an electronic invoice query system, an electronic invoice storage system and a mass multi-element data intelligent collection system.

[0103] Among them, the mass multi-element data intelligent collection system provides a calling interface for the electronic invoice billing system and the electronic invoice query system.

[0104] In this embodiment, the electronic invoice billing system is used to generate invoice information, generate an invoice collection request according to the invoice information, and send the invoice collection request to the mass multi-element data intelligent collection system.

[0105] In the embodiment, the mass multi-element data intelligent collection system includes a collection extraction module, a collection storage module, a collection query module and a collection selection module as described in Embodiment One, and can execute the mass multi-element data intelligent collection method and perform persistent storage of the collection information.

[0106] In the embodiment, the electronic invoice query system is responsible for element-based query of invoice information, generates an invoice query request, sends the invoice query request to the mass multi-element data intelligent collection system, and is also used for analyzing and restoring the query result.

[0107] In the embodiment, the electronic invoice storage system is used for storing invoice information. The electronic invoice storage system is a typical database system, maintains a group of database server clusters, and stores the invoice information in the system in a database and table separation and read-write separation manner.

[0108] In the collection storage stage, the electronic invoice issuing system transmits an invoice collection request to the mass multi-element data intelligent collection system in the form of interface calling, the mass multi-element data intelligent collection system extracts key elements through the collection extraction module, generates collection information, and performs persistent storage in the mass multi-element data intelligent collection system after processing by the collection storage module, and the invoice information is connected to the electronic invoice storage system for persistent storage in the form of interface calling.

[0109] In the collection query stage, in the electronic invoice query system, the user selects the query type to be executed according to the interface prompt and inputs the query elements of the electronic invoice such as name and unit name. After receiving the request of the user, the electronic invoice query system sends the query request containing the query elements to the mass multi-element data intelligent collection system. The electronic invoice intelligent system merges the query elements through the collection selection module to calculate the corresponding element identification value, and then queries the collection information table according to the element identification value through the collection query module to obtain the invoice ID meeting the condition. Then, the mass multi-element data intelligent collection system sends all the invoice IDs meeting the condition to the electronic invoice storage system for query based on the invoice ID in the form of interface calling, so that all the electronic invoice information meeting the query condition can be quickly obtained. Then, the mass multi-element data intelligent collection system sends the query result to the electronic invoice query system after obtaining all the electronic invoice information meeting the query condition, and the electronic invoice query system analyzes and restores the invoice information record to obtain complete invoice information.

[0110] The electronic invoice management system of the application can store and search mass multi-element data, does not cause large resource consumption when searching the mass multi-element data, has less time consumption and high query efficiency.

[0111] It has to be understood that, in the present text, the terms "comprising", "including", or any other variant thereof, are intended to cover non-exclusive inclusions, such that the item or the entity comprising a list of elements does not include only those elements, but also other elements not explicitly listed. Without further limitations, an element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the item or the entity comprising the element. The terms "connected" or "coupled" or similar terms are not limited to a physical or mechanical connection, but can include an electrical connection, whether direct or indirect.

[0112] The above description is further detailed in connection with specific preferred embodiments of the application, and it is not to be construed that the specific implementation of the application is limited to these descriptions. For those skilled in the art, without departing from the concept of the application, a number of simple deductions or substitutions can be made, which should be considered as falling within the protection scope of the application.

Claims

1. A massive, multi-source intelligent data collection system, characterized in that, include: The collection and extraction module is used to extract the key elements of the corresponding invoice based on the received invoice collection request, obtain multiple collection types based on the key elements, obtain the identification information corresponding to each collection type, and generate the collection information of the corresponding invoice based on the multiple identification information. The invoice collection request includes invoice information, which includes key elements of the invoice; the collection and extraction module includes: The key element extraction unit is used to extract the key elements of the corresponding invoice based on the invoice information; the aggregation type division unit is used to generate multiple aggregation types based on the key elements, wherein the aggregation type is a combination including one or more key elements; the aggregation information generation unit is used to perform a cascading operation on the key elements in each aggregation type to obtain a merged key element, calculate the hash value of the merged key element using a hash algorithm to obtain the identification information corresponding to each aggregation type, and construct the aggregation information of the invoice based on the invoice ID and the identification information corresponding to multiple aggregation types. The collection and storage module is used to store the collection information in a collection information table and set the identification information in the collection information table as an index item; The aggregation selection module is used to determine the aggregation type corresponding to the received invoice query request and calculate the element identifier value corresponding to the invoice query request; the invoice query request includes query elements of the invoice, and the query elements include one or more key elements of the invoice; the aggregation selection module includes: The aggregation type determination unit is used to determine the aggregation type corresponding to the invoice query request based on the query elements; the identifier value calculation unit is used to perform a concatenation operation on the query elements to obtain a merged query element, and use a hash algorithm to calculate the hash value of the merged query element to obtain the element identifier value corresponding to the invoice query request. The collection and query module is used to query the collection information table according to the collection type and element identifier value corresponding to the invoice query request, and obtain the invoice ID that meets the conditions.

2. The massive multi-source intelligent data collection system according to claim 1, characterized in that, The key elements of the invoice include: invoice ID, buyer's name, buyer's taxpayer identification number, buyer's address, buyer's telephone number, buyer's bank, buyer's account number, product name, product unit price, product quantity, total product amount, product tax rate, product tax amount, seller's name, seller's taxpayer identification number, seller's address, seller's telephone number, seller's bank, seller's account number, payee's name, invoice issuer's name, invoice code, invoice date, verification code, and machine code.

3. The massive multi-source intelligent data collection system according to claim 1, characterized in that, The collection and storage module is also used to send the invoice information to the electronic invoice storage system for storage, wherein the invoice ID is set as an index item in the electronic invoice storage system; Accordingly, the collection and query module is also used to send the qualified invoice IDs to the electronic invoice storage system for invoice ID query to obtain query results, wherein the query results are the invoice information corresponding to the invoice ID.

4. A method for intelligent aggregation of massive multi-source data, characterized in that, include: Collection storage methods and collection query methods, among which, The aggregation and storage method includes: Based on the received invoice collection request, the key elements of the corresponding invoice are extracted. Based on the key elements, multiple collection types are obtained, and the identification information corresponding to each collection type is acquired. Based on the multiple identification information, the collection information of the corresponding invoice is generated. The invoice collection request includes invoice information, and the invoice information includes the key elements of the invoice. The collection type is a combination of one or more key elements. The process of obtaining the identification information corresponding to each collection type and generating collection information for the corresponding invoice based on the multiple identification information includes: performing a concatenation operation on the key elements in each collection type to obtain a merged key element; using a hash algorithm to calculate the hash value of the merged key element to obtain the identification information corresponding to each collection type; and constructing the collection information for the invoice based on the invoice ID and the identification information corresponding to multiple collection types. The collected information is stored in a collection information table, and the identification information in the collection information table is set as an index item; The aggregation query method includes: Based on the received invoice query request, determine the aggregation type corresponding to the invoice query request, and calculate the element identifier value corresponding to the invoice query request; wherein, the invoice query request includes query elements of the invoice, and the query elements include one or more key elements of the invoice; The calculation of the element identifier value corresponding to the invoice query request includes: performing a concatenation operation on the query elements to obtain a merged query element, and using a hash algorithm to calculate the hash value of the merged query element to obtain the element identifier value corresponding to the invoice query request. Based on the collection type and element identifier value corresponding to the invoice query request, the collection information table is queried to obtain the invoice ID that meets the conditions.

5. The intelligent aggregation method for massive multi-source data according to claim 4, characterized in that, The aggregation and storage method further includes: The invoice information is sent to an electronic invoice storage system for storage, wherein the invoice ID is set as an index item in the electronic invoice storage system; Accordingly, the aggregation query method further includes: The qualified invoice IDs are sent to the electronic invoice storage system for invoice ID lookup, and the lookup results are the invoice information corresponding to the invoice IDs.

6. An electronic invoice management system, characterized in that, include: The system includes an electronic invoice issuance system, an electronic invoice query system, an electronic invoice storage system, and a massive multi-source data intelligent collection system as described in any one of claims 1-3, wherein... The electronic invoice issuing system is used to generate invoice information, generate an invoice collection request based on the invoice information, and send the invoice collection request to the massive multi-source data intelligent collection system. The electronic invoice query system is used to generate an invoice query request and send the invoice query request to the massive multi-source data intelligent collection system. It is also used to parse and recover the query results. The electronic invoice storage system is used to store the invoice information.

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