CN114386509A - Data fusion method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of data processing, and discloses a data fusion method, a data fusion device, electronic equipment and a storage medium, wherein the method comprises the following steps: receiving a data fusion request sent by a data demand party, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field; constructing a data acquisition channel of a data source end, and searching service data of a data field from the data source end according to the data acquisition channel; according to a preset data code table, carrying out format standardization on the service data to obtain standard service data; defining a data loading node in a pre-constructed data fusion template, matching standard business data with the data loading node according to a preset matching rule, loading the standard business data to the data loading node successfully matched with the standard business data, and returning the standard business data to a data demand side. In addition, the invention also relates to a block chain technology, and the standard service data can be stored in the block chain. The invention can improve the efficiency of data fusion.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a data fusion method and apparatus, an electronic device, and a computer-readable storage medium.
Background
With the development of big data, business data generated in different business scenes can be scattered in different databases, message queues and file systems, when data fusion processing of cross-business applications is performed, data is collected and cleaned from different data sources by adopting a data warehouse technology and then collected into a data warehouse to realize data fusion of the cross-business applications, but different data collection and conversion rules need to be configured when data fusion is performed through the data warehouse technology due to different storage positions of different data sources, so that more time needs to be consumed in the data fusion process, and the efficiency of the data fusion is affected.
Disclosure of Invention
The invention provides a data fusion method, a data fusion device, electronic equipment and a computer readable storage medium, and mainly aims to improve the efficiency of data fusion.
In order to achieve the above object, the present invention provides a data fusion method, including:
receiving a data fusion request sent by a data demand party, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
constructing a data acquisition channel of the data source end, and searching the service data of the data field from the data source end according to the data acquisition channel;
according to a preset data code table, carrying out format standardization on the service data to obtain standard service data;
defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
Optionally, the identifying a fusion object of the data fusion request includes:
acquiring fusion information of the data fusion request, and identifying a data target and a data source of the data fusion request according to the fusion information;
converting the data target into a data field, and determining a data source end of the data fusion request according to the data source;
and generating a fusion object of the data fusion request according to the data field and the data source end.
Optionally, the constructing a data acquisition channel of the data source includes:
acquiring a database interface and an access path of the data source end, and identifying an access port of the data source end according to the database interface;
and generating a data acquisition channel of the data source end according to the access path and the access port.
Optionally, the searching, according to the data acquisition channel, the service data of the data field from the data source end includes:
configuring a query statement of the data field at the data source end, and identifying an access area of the data field at the data source end according to the data acquisition channel;
and inquiring the service data of the data field from the access area by using the inquiry statement.
Optionally, the standardizing the format of the service data according to a preset data code table to obtain standard service data includes:
acquiring a data field and a data format in the service data, and matching the data field with a code table field in the data code table;
when the data field is successfully matched with the code table field in the data code table, judging whether the code table format of the code table field is consistent with the data format;
if the data format is consistent with the standard service data, the data format is used as the final format of the service data to obtain the standard service data;
and if not, updating the data format according to the code table format to obtain the standard service data.
Optionally, the matching the data field with a code table field in the data code table includes:
converting the data field and the code table field into a data field vector and a code table field vector respectively;
calculating vector similarity of the data field vector and the code table field vector;
if the vector similarity is not greater than a preset threshold, the data field and the code table field fail to be matched;
if the vector similarity is greater than the preset threshold, the data field and the code table field are successfully matched;
wherein the vector similarity of the data field vector and the code table field vector is calculated using the following formula:
wherein R represents vector similarity, AxRepresenting the x-th data field vector, n representing the number of data field vectors, ByAnd m represents the number of field vectors of the code table.
Optionally, before the matching the standard service data with the data loading node according to a preset matching rule, the method further includes:
acquiring data attributes of the standard service data and node attributes of the data loading nodes;
configuring matching logic of the standard service data and the data loading node according to the data attribute and the node attribute, and determining a matching mode of the standard service data and the data loading node;
and generating the matching rule according to the matching logic and the matching mode.
In order to solve the above problem, the present invention further provides a data fusion apparatus, including:
the fusion object identification module is used for receiving a data fusion request sent by a data demand party and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
the service data extraction module is used for constructing a data acquisition channel of the data source end and searching the service data of the data field from the data source end according to the data acquisition channel;
the service data standardization module is used for carrying out format standardization on the service data according to a preset data code table to obtain standard service data;
and the service data fusion module is used for defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to implement the data fusion method described above.
In order to solve the above problem, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the data fusion method described above.
It can be seen that, in the embodiment of the present invention, by first identifying a fusion object of a data fusion request sent by the data demander, where the fusion object includes a data source end and a data field, a data type and a data source required by the data demander can be obtained, so as to guarantee the premise of subsequent data fusion; secondly, the embodiment of the invention searches the service data of the data field from the data source end by constructing the data acquisition channel of the data source end, can realize the uniform configuration of the acquisition rule of the service data, improve the efficiency of the subsequent data fusion, and combine the preset data code table to carry out the format standardization on the service data to obtain the standard service data, can realize the unification of the service data in the conversion process, and improve the processing speed of the subsequent service data; furthermore, in the embodiment of the present invention, a data loading node is defined in a pre-constructed data fusion template, the standard service data is matched with the data loading node according to a preset matching rule, and the standard service data is loaded to the data loading node successfully matched with the standard service data and then returned to the data requiring party, so that a fusion mode of the standard service data can be determined, excessive manual participation actions during data fusion are avoided, and the efficiency of data fusion is further improved. Therefore, the data fusion method, the data fusion device, the electronic device and the computer-readable storage medium provided by the embodiment of the invention can improve the efficiency of data fusion.
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Fig. 1 is a schematic flow chart of a data fusion method according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a data fusion apparatus according to an embodiment of the present invention;
fig. 3 is a schematic internal structural diagram of an electronic device implementing the data fusion method according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a data fusion method. The execution subject of the data fusion method includes, but is not limited to, at least one of electronic devices that can be configured to execute the method provided by the embodiments of the present application, such as a server, a terminal, and the like. In other words, the data fusion method may be performed by software or hardware installed in the terminal device or the server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Fig. 1 is a schematic flow chart of a data fusion method according to an embodiment of the present invention. In an embodiment of the present invention, the data fusion method includes:
s1, receiving a data fusion request sent by a data demand side, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field.
In the embodiment of the present invention, the data demander may be understood as a platform that needs to obtain data from different service systems, such as a data fusion platform, which is used to integrate service data in different service scenarios, where the data fusion request is generated based on different user requirements, for example, a user requirement is to fuse order data generated in different mall systems, a user requirement is to fuse search data generated in different search engines, and a user requirement is to fuse browse data of users in different front-end pages. Further, the embodiment of the present invention obtains the data type and the data source required by the data demander by identifying the fusion object of the data fusion request.
As an embodiment of the present invention, the identifying a fusion object of the data fusion request includes: acquiring fusion information of the data fusion request, identifying a data target and a data source of the data fusion request according to the fusion information, converting the data target into a data field, determining a data source end of the data fusion request according to the data source, and generating a fusion object of the data fusion request according to the data field and the data source end.
The fusion information may be understood as request data in the data fusion request, the data target may be understood as target data required by the data fusion request, and the data source may be understood as a source of the fusion data required by the data fusion request, such as a relational database or a non-relational database.
S2, constructing a data acquisition channel of the data source end, and searching the service data of the data field from the data source end according to the data acquisition channel.
According to the embodiment of the invention, the data acquisition channel of the data source end is constructed to guarantee the premise of extracting the subsequent service data, wherein the data acquisition channel can be understood as a data connection interface of the data source end. As an embodiment of the present invention, the constructing a data acquisition channel of the data source includes: and acquiring a database interface and an access path of the data source end, identifying an access port of the data source end according to the database interface, and generating a data acquisition channel of the data source end according to the access path and the access port.
The database interface may be understood as a data call entry provided by data in the data source to an external system, such as an API interface, and the access path refers to an address, such as a URL address, connected to the data source.
Further in an optional embodiment of the present invention, the searching, according to the data acquisition channel, the service data of the data field from the data source includes: and configuring a query statement of the data field at the data source end, identifying an access area of the data field at the data source end according to the data acquisition channel, and querying the service data of the data field in the access area by using the query statement.
The query statement can be compiled through SQL language, and the access area comprises a background database, a local cache and the like.
And S3, carrying out format standardization on the service data according to a preset data code table to obtain standard service data.
It should be understood that, since the service data is extracted based on the data source end, and the data formats stored by different data source ends are different, for example, for data of a time type, the a data source end stores in a year/month/day format, the B data source end stores in a day/month/year format, and for data of a gender type, the a data source end stores in a male/female format, and the B data source end stores in a man/wman format, in order to improve the fusion speed of subsequent service data, in the embodiment of the present invention, the format of the service data is standardized by using a preset data code table, so as to unify the formats of the service data, and ensure the processing speed of the subsequent service data.
The data code table can be understood as a standardized field table for specifying the format of the data field, such as specifying the format of the time field as year/month/day and the format of the gender field as male/female.
Further, as an embodiment of the present invention, the standardizing the format of the service data according to a preset data code table to obtain standard service data includes: and acquiring a data field and a data format in the service data, matching the data field with a code table field in the data code table, judging whether the code table format of the code table field is consistent with the data format when the data field is successfully matched with the code table field in the data code table, if so, taking the data format as the final format of the service data to obtain the standard service data, and if not, updating the data format according to the code table format to obtain the standard service data.
Further, in an optional embodiment of the present invention, the matching the data field with a code table field in the data code table includes: converting the data field and the code table field into a data field vector and a code table field vector respectively; calculating vector similarity of the data field vector and the code table field vector; if the vector similarity is not greater than a preset threshold, the data field and the code table field fail to be matched; if the vector similarity is greater than the preset threshold, the data field and the code table field are successfully matched;
wherein the vector similarity of the data field vector and the code table field vector is calculated using the following formula:
wherein R represents vector similarity, AxRepresenting the x-th data field vector, n representing the number of data field vectors, ByAnd m represents the number of field vectors of the code table.
Illustratively, the service data is 2021 years, the data field of the service data is identified as time, and the data format is date/month/year, the data field of the service data is matched with the code table field in the data code table, so that the data field of the service data is successfully matched with the time code table field in the data code table, and the code table format of the time code table field is year/month/day, so that the data format of the date/month/year of the service data is updated to the data format of year/month/day.
Further, in order to ensure privacy and security of the standard service data, the standard service data may also be stored in a blockchain node.
S4, defining a data loading node in the pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
It should be understood that, since a data source end generates a large amount of service data in an actual service scene, and service types of each service data are different, if the searched service data is directly stored, a phenomenon that the data is confused during fusion occurs, so that the efficiency of subsequent data fusion is affected, in the embodiment of the present invention, a data loading node is defined in a pre-constructed data fusion template to fuse the standard service data and then return the standard service data to the data requiring party, so as to ensure the fusion efficiency of the service data.
The data fusion template refers to a bottom template engine of the standard business data, and is used for fusing the business data found from the data source, such as a data table, the data loading node refers to a position node of the standard business data in the data fusion template, and the definition of the data loading node may be implemented by a character placeholder algorithm, such as a java placeholder algorithm.
In one embodiment of the present invention, before matching the standard service data with the data loading node according to a preset matching rule, the method further includes: acquiring data attributes of the standard service data and node attributes of the data loading nodes; configuring matching logic of the standard service data and the data loading node according to the data attribute and the node attribute, and determining a matching mode of the standard service data and the data loading node; and generating the matching rule according to the matching logic and the matching mode.
Further, in yet another optional embodiment of the present invention, the matching logic includes field ID matching logic, that is, matching the data ID of the standard service data with the ID of the data loading node. The matching mode comprises the following steps: in the first mode, the matching of subsequent data is stopped immediately when an error occurs; and in the second mode, the operation is not stopped when an error is encountered until all the data are matched, and all the data with the error are summarized and returned.
In one embodiment of the present invention, the standard service data is loaded at the data loading node by a get () method.
Further, in the embodiment of the present invention, after the data loading node loads the standard service data, the standard service data is returned to the data demanding party, so as to implement a data fusion request of the data demanding party.
It can be seen that, in the embodiment of the present invention, by first identifying a fusion object of a data fusion request sent by the data demander, where the fusion object includes a data source end and a data field, a data type and a data source required by the data demander can be obtained, so as to guarantee the premise of subsequent data fusion; secondly, the embodiment of the invention searches the service data of the data field from the data source end by constructing the data acquisition channel of the data source end, can realize the uniform configuration of the acquisition rule of the service data, improve the efficiency of the subsequent data fusion, and combine the preset data code table to carry out the format standardization on the service data to obtain the standard service data, can realize the unification of the service data in the conversion process, and improve the processing speed of the subsequent service data; furthermore, in the embodiment of the present invention, a data loading node is defined in a pre-constructed data fusion template, the standard service data is matched with the data loading node according to a preset matching rule, and the standard service data is loaded to the data loading node successfully matched with the standard service data and then returned to the data requiring party, so that a fusion mode of the standard service data can be determined, excessive manual participation actions during data fusion are avoided, and the efficiency of data fusion is further improved. Therefore, the data fusion method provided by the embodiment of the invention can improve the efficiency of data fusion.
FIG. 2 is a functional block diagram of the data fusion device according to the present invention.
The data fusion device 100 of the present invention may be installed in an electronic device. According to the realized functions, the data fusion device may include a fusion object identification module 101, a business data extraction module 102, a business data standardization module 103, and a business data fusion module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and can perform a fixed function, and is stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the fusion object identification module 101 is configured to receive a data fusion request sent by a data demander, and identify a fusion object of the data fusion request, where the fusion object includes a data source end and a data field;
the service data extraction module 102 is configured to construct a data acquisition channel of the data source, and search the service data of the data field from the data source according to the data acquisition channel;
the service data standardization module 103 is configured to standardize a format of the service data according to a preset data code table to obtain standard service data;
the service data fusion module 104 is configured to define a data loading node in a pre-constructed data fusion template, match the standard service data with the data loading node according to a preset matching rule, load the standard service data to the data loading node successfully matched with the standard service data, and return the standard service data to the data requiring party.
In detail, when the modules in the data fusion device 100 in the embodiment of the present invention are used, the same technical means as the data fusion method described in fig. 1 above are adopted, and the same technical effects can be produced, which is not described herein again.
Fig. 3 is a schematic structural diagram of an electronic device 1 for implementing the data fusion method according to the present invention.
The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as a data fusion program, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device 1, connects various components of the electronic device 1 by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules (for example, executing a data fusion program, etc.) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as codes of a data fusion program, but also to temporarily store data that has been output or is to be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device 1 and other devices, and includes a network interface and an employee interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices 1. The employee interface may be a Display (Display), an input unit, such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visual staff interface.
Fig. 3 shows only the electronic device 1 with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The data fusion program stored in the memory 11 of the electronic device 1 is a combination of a plurality of computer programs, and when running in the processor 10, can realize:
receiving a data fusion request sent by a data demand party, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
constructing a data acquisition channel of the data source end, and searching the service data of the data field from the data source end according to the data acquisition channel;
according to a preset data code table, carrying out format standardization on the service data to obtain standard service data;
defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a non-volatile computer-readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device 1, may implement:
receiving a data fusion request sent by a data demand party, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
constructing a data acquisition channel of the data source end, and searching the service data of the data field from the data source end according to the data acquisition channel;
according to a preset data code table, carrying out format standardization on the service data to obtain standard service data;
defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method of data fusion, the method comprising:
receiving a data fusion request sent by a data demand party, and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
constructing a data acquisition channel of the data source end, and searching the service data of the data field from the data source end according to the data acquisition channel;
according to a preset data code table, carrying out format standardization on the service data to obtain standard service data;
defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
2. The data fusion method of claim 1, wherein the identifying the fusion object of the data fusion request comprises:
acquiring fusion information of the data fusion request, and identifying a data target and a data source of the data fusion request according to the fusion information;
converting the data target into a data field, and determining a data source end of the data fusion request according to the data source;
and generating a fusion object of the data fusion request according to the data field and the data source end.
3. The data fusion method of claim 1, wherein the constructing the data acquisition channel of the data source comprises:
acquiring a database interface and an access path of the data source end, and identifying an access port of the data source end according to the database interface;
and generating a data acquisition channel of the data source end according to the access path and the access port.
4. The data fusion method of claim 3, wherein the searching the service data of the data field from the data source end according to the data acquisition channel comprises:
configuring a query statement of the data field at the data source end, and identifying an access area of the data field at the data source end according to the data acquisition channel;
and inquiring the service data of the data field from the access area by using the inquiry statement.
5. The data fusion method according to any one of claims 1 to 4, wherein the standardizing the format of the service data according to a preset data code table to obtain standard service data comprises:
acquiring a data field and a data format in the service data, and matching the data field with a code table field in the data code table;
when the data field is successfully matched with the code table field in the data code table, judging whether the code table format of the code table field is consistent with the data format;
if the data format is consistent with the standard service data, the data format is used as the final format of the service data to obtain the standard service data;
and if not, updating the data format according to the code table format to obtain the standard service data.
6. The data fusion method of claim 5, wherein said matching the data field to a code table field in the data code table comprises:
converting the data field and the code table field into a data field vector and a code table field vector respectively;
calculating vector similarity of the data field vector and the code table field vector;
if the vector similarity is not greater than a preset threshold, the data field and the code table field fail to be matched;
if the vector similarity is greater than the preset threshold, the data field and the code table field are successfully matched;
wherein the vector similarity of the data field vector and the code table field vector is calculated using the following formula:
wherein R represents vector similarity, AxRepresenting the x-th data field vector, n representing the number of data field vectors, ByAnd m represents the number of field vectors of the code table.
7. The data fusion method of claim 1, wherein before matching the standard service data with the data loading node according to a preset matching rule, the method further comprises:
acquiring data attributes of the standard service data and node attributes of the data loading nodes;
configuring matching logic of the standard service data and the data loading node according to the data attribute and the node attribute, and determining a matching mode of the standard service data and the data loading node;
and generating the matching rule according to the matching logic and the matching mode.
8. A data fusion apparatus, the apparatus comprising:
the fusion object identification module is used for receiving a data fusion request sent by a data demand party and identifying a fusion object of the data fusion request, wherein the fusion object comprises a data source end and a data field;
the service data extraction module is used for constructing a data acquisition channel of the data source end and searching the service data of the data field from the data source end according to the data acquisition channel;
the service data standardization module is used for carrying out format standardization on the service data according to a preset data code table to obtain standard service data;
and the service data fusion module is used for defining a data loading node in a pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the data loading node successfully matched with the standard service data, and returning the standard service data to the data demand side.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the data fusion method of any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out a data fusion method according to any one of claims 1 to 7.
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