CN116340296A - Multi-source data fusion and unified information model construction method based on data probes - Google Patents
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Abstract
The application relates to the technical field of power data, in particular to a multisource data fusion and unified information model construction method based on a data probe. The method comprises the following steps: responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database; sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database; the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request. The method and the device can accurately collect corresponding data in the power model.
Description
Technical Field
The application relates to the technical field of power data, in particular to a multisource data fusion and unified information model construction method based on a data probe.
Background
The power grid system comprises a plurality of data models, wherein object information of each power equipment object is stored in each data model; when facing specific business scenes, the required data models are different.
When the number of data models is large, the schedulers are required to respectively call the object information of each object from each system, and the data calling process is complicated.
Disclosure of Invention
According to the above-mentioned technical problems, it is necessary to provide a method for constructing a multi-source data fusion and unified information model based on a data probe, which can accurately collect corresponding data in a power model.
In a first aspect, the present application provides a method for constructing a multi-source data fusion and unified information model based on a data probe, where the method includes:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
In one embodiment, the control data probe feeds object information back to the virtualization server, comprising:
The control executor feeds the object information back to the data center;
and sending the object information to the virtualization server in a timing forwarding mode.
In one embodiment, the method further comprises:
and carrying out visualization processing on the knowledge graph index library, and feeding back the visualized knowledge graph index library to the virtualization server so that the virtualization server marks the access object in the visualized knowledge graph index library and displays the access object to the sender.
In a second aspect, the present application further provides a device for multi-source data fusion and unified information model construction based on a data probe, where the device includes:
the request response module is used for responding to the search request, searching in the knowledge graph index library and obtaining an access object corresponding to the search request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
the scheduling module is used for sending an extraction instruction comprising an access object to an executor connected to the multi-source database so as to instruct the executor to extract object information corresponding to the access object in the multi-source database;
and the feedback module is used for controlling the data probe to feed back the object information to the virtualization server so that the virtualization server feeds back the object information to a sender of the retrieval request.
In a third aspect, the present application provides a method for constructing a multisource data fusion and unified information model based on a data probe, where the method includes:
responding to an extraction instruction comprising an access object sent by a dispatching center, and extracting object information corresponding to the access object from a multi-source database; the access object is obtained by searching in a knowledge graph index base by a scheduling center based on a search request;
and responding to the control operation of the dispatching center, and feeding back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the retrieval request.
In one embodiment, extracting object information corresponding to an access object in a multi-source database includes:
selecting a target read-write plug-in from the read-write plug-in set according to the data type of the access object;
determining the loading position of the target read-write plug-in the multi-source database according to the data source corresponding to the access object;
loading a target read-write plug-in at a loading position;
and extracting object information corresponding to the access object from the multi-source database through the loaded target read-write plug-in.
In one embodiment, in response to a control operation of the dispatch center, feeding back the object information to the virtualization server for the virtualization server to feed back the object information to a sender of the search request, including:
Responding to the control operation of the dispatching center, and determining a target conversion plug-in according to the data type of the virtualized server and the data type of the access object;
according to the target conversion plug-in, performing data type conversion on the object information;
and feeding back the converted object information to the virtualization server so that the virtualization server feeds back the converted object information to a sender of the search request.
In one embodiment, before feeding back the converted object information to the virtualization server for the virtualization server to feed back the converted object information to the sender of the search request, the method further includes:
and carrying out integrity check and validity check on the converted object information.
In one embodiment, the method further comprises:
storing object relation information in the object information in a relation database in the data probe;
object attribute information in the object information is stored in a text database in the data probe.
In a fourth aspect, the present application further provides a device for multi-source data fusion and unified information model construction based on a data probe, where the device includes:
the instruction response module is used for responding to the extraction instruction comprising the access object sent by the dispatching center and extracting object information corresponding to the access object from the multi-source database; the access object is obtained by searching in a knowledge graph index base by a scheduling center based on a search request;
And the information forwarding module is used for responding to the control operation of the dispatching center and feeding back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the retrieval request.
In a fifth aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
In a sixth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
Responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
In a seventh aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the steps of:
responding to an extraction instruction comprising an access object sent by a dispatching center, and extracting object information corresponding to the access object from a multi-source database; the access object is obtained by searching in a knowledge graph index base by a scheduling center based on a search request;
and responding to the control operation of the dispatching center, and feeding back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the retrieval request.
In an eighth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
responding to an extraction instruction comprising an access object sent by a dispatching center, and extracting object information corresponding to the access object from a multi-source database; the access object is obtained by searching in a knowledge graph index base by a scheduling center based on a search request;
and responding to the control operation of the dispatching center, and feeding back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the retrieval request.
According to the multisource data fusion and unified information model construction method based on the data probes, the dispatching center receives the retrieval request and retrieves the access object from the knowledge graph index library, and any object needing to be accessed in each power system model can be rapidly and accurately positioned by integrating the power system models through the knowledge graph index library; further, the dispatching center instructs the data probe to extract the object information corresponding to the access object in the multi-source database, so that the virtualization server feeds back the object information to the sender of the retrieval request, the step of extracting the whole data is completed through dispatching the data probe, the step of carrying out data virtualization display is completed through dispatching the virtualization server, the whole data retrieval process is formed through the retrieval step, the data extraction step and the data virtualization display step, any object needing to be accessed in each power system model is accurately positioned, and the accurate access to the required data in each data model in the power system is realized.
Drawings
FIG. 1 is an application environment diagram of a data probe-based multi-source data fusion and unified information model building method in one embodiment;
FIG. 2 is a flow chart of a method for data probe-based multi-source data fusion and unified information model construction in one embodiment;
FIG. 3 is a schematic diagram of an application layer, a virtualization layer, and a data layer in one embodiment;
FIG. 4 is a flow chart of information retrieval in another embodiment;
FIG. 5 is a schematic diagram of a probe engine in one embodiment;
FIG. 6 is a flow diagram of a load target read-write plug-in one embodiment;
FIG. 7 is a diagram of data type conversion based on a target conversion plugin in one embodiment;
FIG. 8 is a flowchart of a method for data probe-based multi-source data fusion and unified information model construction in another embodiment;
FIG. 9 is a block diagram of a data probe-based multi-source data fusion and unified information model building apparatus in one embodiment;
FIG. 10 is an internal block diagram of a computer device in one embodiment;
FIG. 11 is a block diagram of a multi-source data fusion and unified information model building device based on data probes in one embodiment;
fig. 12 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The power grid system comprises a plurality of data models, wherein object information of each power equipment object is stored in each data model; when facing specific business scenes, the required data models are different. When the number of data models is large, the schedulers are required to respectively call the object information of each object from each system, and the data calling process is complicated.
The embodiment provides a multisource data fusion and unified information model construction method based on a data probe, which adopts the data probe to accurately collect related data according to task information issued by a user and store the related data according to configuration information of the task, so as to support data requirements such as digital simulation, tide calculation and the like.
As shown in fig. 1, the data probe comprises two parts, a dispatch center 102 and an actuator 104, respectively. The data probe data acquisition operation process is that a user issues a task, and task information is set as follows: the location of the data source, the task type, and the execution time, etc. The dispatching center 102 correctly sets related parameters of data acquisition and storage according to the configuration information of the task, then invokes the executor 104 to execute the data acquisition and storage according to the time setting of the task, conforms to the instruction sent by the dispatching center 102, realizes the data acquisition and storage, and feeds back the execution information and the execution result to the dispatching center 102.
In one embodiment, as shown in fig. 2, a method for constructing a multi-source data fusion and unified information model based on a data probe is provided, and the method is applied to the dispatch center 102 in fig. 1 for illustration, and includes the following steps:
s201, searching is carried out in the knowledge graph index library in response to the search request, and an access object corresponding to the search request is obtained.
The knowledge graph index library is constructed based on object index structures corresponding to the objects in the multi-source database; and each object in the multi-source database is each object of each power equipment stored in each data model in the power grid.
Specifically, the index library is mainly constructed by a unified information model based on a knowledge graph, and a storage carrier is a Neo4j graph database.
It will be appreciated that a knowledge graph is a large-scale Semantic Network (Semantic Network) rich in entities (Entity), concepts (concepts), and various Semantic relationships (Semantic Relationship) between them. Specifically, the knowledge graph describes the objective world in the form of structured triples (binary relations) under the agreed framework. In fact, the form of triples is in the form of both a specific form of "head entity-relationship-tail entity" and a form of "entity-attribute value". From the view of the graph structure, the nodes represent entities or concepts in the knowledge graph, and the directed edges connecting two nodes are abstracted relations between the entities or concepts. The following figures show typical examples of knowledge maps.
In this embodiment, the knowledge graph index library uses a specific device of a novel power system as an object, describes metadata specifications containing multi-source system data in an entity, and uses a specific object beijiao.220m6 in a bus section class as an example: the intra-entity attributes include metadata specifications for metrology and state estimation in other data systems, such as E8000 and DF8003E, in addition to basic information describing physical devices and associations with other objects. Index information of source data of the object entity can be obtained through finding attribute names such as phase angle weight, AB line voltage and the like in the object entity, and then the dispatching center 102 dispatches the executor 104 to set corresponding data access strategies based on the index of the object entity to extract correct data.
In addition, the knowledge graph index library also provides a visual clear hierarchical relationship for a user, and the hierarchical relationship of the device objects is represented by a mode of 'company-sub control area-plant station-voltage level area-specific device' so as to facilitate the management of the device. Therefore, the knowledge graph index library in the embodiment can be used for organizing and managing all registered information objects, namely novel power system equipment, provides object discovery service for the cross-source data service of the probe engine, and helps the probe to quickly discover and acquire correct data objects.
S202, sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database.
The executor mainly comprises two parts, namely a data synchronizer and log service: 1) The main function of the data synchronizer is to call the appropriate Read and Write Read and dump data according to the parameters transferred by the scheduler. 2) The log service is mainly used for recording related information of the data synchronizer during data acquisition and data storage, including execution time, data type conversion during acquisition, filling mode during data loss and the like, and feeding the recorded information back to a log recording module of the dispatching center for unified storage and processing of the information.
Specifically, the process of executing the data synchronization function and the log service function number by the executor is realized by a data virtualization technology. It will be appreciated that data virtualization is a technique that can provide a unified, abstract to data-consuming users and can query and process data stored in a heterogeneous data store collection from an encapsulation standpoint. Data virtualization provides a unified view of data from multiple data stores that are not visible to users and are not known to the users from which they acquired data. Data virtualization hides the fact that data is integrated together to form a unified perspective; encapsulation is a technique of hiding technical details of acquiring data by a data virtualization technology; the storage location, storage structure, API used, access language, application storage technology, and all other technical details of the data use user should be transparent to the data.
In addition, the definition of data virtualization includes query (ing) and processing (Manipulating), which allows data to be queried in a storage area, while also allowing data to be deleted, inserted, and updated (as long as allowed in the data storage area). Blending and isomerism means that if data of multiple data stores need to be accessed, they may have different storage formats, database languages and APIs. For example, data store 1 may be an SQL database, data store 2 an XML file format database, data store 3 a NoSQL database, and data store 4 a spreadsheet file. The data virtualization layer should still be able to present data from multiple different data stores to a data-using user in a manner similar to depositing all data in one data store.
Thus, as shown in FIG. 3, in the present embodiment, the executives are configured within the virtualization layer, and the executives are connected to the application layer and the data layer (corresponding to the multi-element database) such that the data extraction process of the executives is not visible to the user.
And S203, controlling the data probe to feed back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the search request.
The virtualization server is used for providing an output result page and feeding back object information to a sender of the search request. Alternatively, the output results page may be a visual interface, or a two-dimensional tabular view in a specified format.
According to the multisource data fusion and unified information model construction method based on the data probes, the dispatching center receives the retrieval request and retrieves the access object from the knowledge graph index library, and any object needing to be accessed in each power system model can be rapidly and accurately positioned by integrating the power system models through the knowledge graph index library; further, the dispatching center instructs the data probe to extract the object information corresponding to the access object in the multi-source database, so that the virtualization server feeds back the object information to the sender of the retrieval request, the step of extracting the whole data is completed through dispatching the data probe, the step of carrying out data virtualization display is completed through dispatching the virtualization server, the whole data retrieval process is formed through the retrieval step, the data extraction step and the data virtualization display step, any object needing to be accessed in each power system model is accurately positioned, and the accurate access to the required data in each data model in the power system is realized.
The present embodiment provides an alternative way to control the data probe to feed back the object information to the virtualization server, i.e. a way to refine S203. The specific implementation process can comprise the following steps: the control executor feeds the object information back to the data center; and sending the object information to the virtualization server in a timing forwarding mode.
Specifically, the executor realizes data virtualization (i.e. a virtualized server) by deploying an independent server, the original data bus is kept unchanged, the stable operation of the existing data architecture is ensured, and data flows (object information) are stored in the virtualized server for using the multi-source heterogeneous data virtualized service in a mode of forwarding from a data center table at regular time.
Further, the method for constructing the multisource data fusion and unified information model based on the data probes further comprises the following steps: and carrying out visualization processing on the knowledge graph index library, and feeding back the visualized knowledge graph index library to the virtualization server so that the virtualization server marks the access object in the visualized knowledge graph index library and displays the access object to the sender.
Wherein, for the operators in the power system, if the operators directly access the unordered object information, a great deal of time is required to design complex programs to integrate the source system data, so that the design of a self-service use view based on the service is necessary.
In the visual processed knowledge graph index library interface design, the entity object inquiry function is realized, when a sub-control area drop-down menu is clicked, a command sentence in KG_search.py is executed to search for an entity existing in the neo4j graph database, and the entity is returned and displayed in the menu. When a certain sub-control area is selected, executing the corresponding function in the file KG_search.py obtains the sentence of the station under the sub-control area. And executing the sentence search map database entity when the factory station item drop-down menu is clicked, returning, and executing the same process for the subsequent query condition. And finally, the entity information of the specific equipment to be queried is returned to the map display and the corresponding attribute information table is displayed at the same time. And the information model maintenance function can import the neo4j graph database only by selecting the file type, the affiliated system and other conditions on the interface and clicking to import and execute KG_import.
Further, in the data virtualization probe function implementation, the knowledge graph index library queries the returned equipment entity and the attribute information contained in the equipment entity, returns the equipment entity name and the attribute name corresponding to the query to the two selection boxes, and the user generates an empty header by checking the corresponding equipment and attribute. The empty header returned after header set up is used as input for the probe. And executing data_integration.py to analyze header information, judging the corresponding Data source files, executing Data acquisition, merging to generate a dataframe, selecting the types of the files everywhere, and clicking to derive to generate an xls table file. The preview window allows the probe to be viewed and the data results returned after execution.
In the embodiment, the service view of the object information is provided through the virtualization server, so that service personnel can conveniently and rapidly search the extracted object information, and a rapid and convenient information display mode is provided.
In one embodiment, as shown in fig. 4, a method for constructing a multi-source data fusion and unified information model based on a data probe is provided, and the method is applied to the executor 104 in fig. 1 for illustration, and includes the following steps:
s401, extracting object information corresponding to the access object in the multi-source database in response to an extraction instruction comprising the access object sent by the dispatching center.
The access object is obtained by searching in a knowledge graph index base by the scheduling center based on a search request.
Further, the actuator in this embodiment includes a probe engine and an extraction module. As shown in fig. 5, the probe engine is a part for receiving a user application request and delivering a corresponding data result, and mainly comprises a service request analysis sub-module, an object discovery sub-module, an access policy sub-module, an extraction module and the like, wherein the part is a core module of a data virtualization layer, and the actual embodiment in the whole data virtualization is a program written at the bottom layer.
After receiving an extraction instruction comprising an access object sent by a dispatching center, the probe engine analyzes the sub-module, the object discovery sub-module, the access strategy sub-module and the extraction module according to the service request, and connects a corresponding data source storage area and extracts object instance data based on the target object information position and the access mode provided by the object index library.
Specifically, when an extraction instruction including an access object sent by a dispatching center is received, the service request analysis submodule analyzes the extraction instruction, the access object is determined after analysis is completed, then the object discovery submodule locates the position of the access object, the access policy submodule formulates a corresponding multi-source data access policy, the policy is delivered to the extraction module, and the extraction module is used for extracting object information corresponding to the access object in a multi-source database.
And S402, feeding back the object information to the virtualization server in response to the control operation of the dispatching center so that the virtualization server feeds back the object information to the sender of the retrieval request.
In one implementation, the control operation of the dispatch center may be to directly forward the extracted data; in another implementation, the control operation of the dispatch center may be to pre-process the extracted data and then forward the pre-processed data.
Specifically, after object information corresponding to the access object is extracted from the multi-source database, the control operation of the dispatching center feeds the object information back to the virtualization server, so that the virtualization server feeds the object information back to the sender of the retrieval request.
Further, at the virtualization base layer, the implementation of two tasks is mainly focused. First, consider a data source system importing into a virtualization server. The part does not need to pay attention to that the source system is based on SQL or NoSQL, the file format is CIM/E or XML, and a piece of independent storage area receives real-time data distributed by the existing data bus at regular time. Second, if there is an incorrect data stored in the source system, a certain preprocessing operation is performed. At the data specification management level, the specification data model is presented in a view form, so that the integration of the multi-source system data model is ensured as much as possible. The Neo4j graph database is deployed in a server, stores the unified information models, and provides a visual view of query management for the user at a front-end interface.
According to the multisource data fusion and unified information model construction method based on the data probes, the executor responds to the extraction instruction to obtain the object information corresponding to the access object, and based on the control operation of the dispatching center, the object information is fed back to the virtualization server to accurately extract required data in each heterogeneous data model in the power system.
As shown in fig. 6, this embodiment provides an alternative way to extract object information corresponding to the access object in the multi-source database, that is, a way to refine S301. The specific implementation process can comprise the following steps:
s601, selecting a target read-write plug-in from the read-write plug-in set according to the data type of the access object.
The data synchronization in this embodiment synchronizes various data sources, thereby realizing data synchronization. The data synchronizer (read-write plug-in set) comprises three main types, namely a read-write plug-in and an intermediate component, and the data types of each type are respectively corresponding to the read-write plug-in and the intermediate component. It can be understood that the read-write plug-ins respectively comprise various plug-ins suitable for reading and writing different data types, and can be integrated to corresponding positions in the form of plug-ins when a new data source needs to be read and written. The main function of the intermediate component is the conversion of data, which mainly includes the conversion of data types and the conversion of data missing values.
The function of the data synchronizer is extracted and assembled, the original complex network structure is changed into a bus type mainly comprising plug-ins, so that various data sources of data types can be conveniently adapted, when new data types of data sources are added, the data sources can be quickly and accurately adapted, and the application range and the robustness of the data reading and storing module are greatly increased.
Specifically, when extracting data from the multivariate database, there may be a difference in data types of the objects, and the read-write plug-in set in this embodiment can implement extraction of different types of data.
S602, determining the loading position of the target read-write plug-in the multi-source database according to the data source corresponding to the access object.
S603, loading the target read-write plug-in at the loading position.
S604, extracting object information corresponding to the access object from the multi-source database through the loaded target read-write plug-in.
Further, after the data extraction operation is completed, the object relationship information in the object information is stored in a relational database in the data probe. Object attribute information in the object information is stored in a text database in the data probe. Thus, the step of extracting the data in each data model into the multivariate database is realized.
Specifically, the memory architecture used by the probe engine is composed of two parts, the core logic is abstracted, and the connection is respectively a relational database and a text through various plug-ins. In the process of extracting data by using a probe engine, the WritePlugin of the data synchronizer can realize conversion and cleaning of the data, two-dimensional data and corresponding model information thereof are stored in a relational database, and text data such as a log is stored in a text form.
In this embodiment, the step of extracting the data from each data model to the multivariate database is implemented by automatically matching the corresponding target read-write plug-ins and automatically loading the target read-write plug-ins.
It can be appreciated that, in the end-to-end data synchronization process of the conventional data synchronizer, due to various types of data involved, a complex network structure is usually formed in the synchronization process, and the network structure is complex, which is not beneficial to data synchronization. As shown in fig. 7, this embodiment provides an alternative way to feed back the object information to the virtualization server in response to the control operation of the dispatch center, so that the virtualization server feeds back the object information to the sender of the search request, that is, provides a way to refine S302. The specific implementation process can comprise the following steps:
s701, in response to control operation of the dispatching center, determining a target conversion plug-in according to the data type of the virtualized server and the data type of the access object.
After receiving the control operation sent by the data probe engine, the module actually accesses the source data file and collects the corresponding data information to preprocess the source data file so as to form a unified standard format, so that the integration of multi-source data is facilitated, and the collected multi-source data is preprocessed and then sent to the data probe engine for data integration to finally complete a complete and correct data service.
S702, performing data type conversion on the object information according to the target conversion plugin.
Further, integrity check and validity check are carried out on the converted object information.
S703, feeding back the converted object information to the virtualization server for the virtualization server to feed back the converted object information to the sender of the search request.
In this embodiment, the extracted data stream is subjected to preliminary operations such as cleaning pretreatment, and then the result is delivered to the executor to complete the final integration work.
In one embodiment, a method for constructing a multi-source data fusion and unified information model based on a data probe is provided, as shown in fig. 8, including: a dispatcher inputs a retrieval request containing an access object on a computer interface, wherein the access object can be equipment such as a main transformer, a line and the like; retrieving the access object information in the knowledge graph index base according to the retrieval request; generating an access request (corresponding to the extraction instruction) according to the access object information, analyzing the extraction instruction by a probe engine in an executor to obtain metadata information of the access object, performing header encapsulation on the metadata information, extracting source data from a multi-element database (namely a measurement database) based on an attribute name and a position index, preprocessing the source data, and returning the preprocessed data to a virtual server; the virtual server generates a virtual form based on the preprocessed result, and displays the virtual form on a software interface for receiving by a dispatcher.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
According to the same inventive concept, the embodiment of the present application further provides a data probe-based multi-source data fusion and unified information model construction device 1 for implementing the above-mentioned data probe-based multi-source data fusion and unified information model construction method. The implementation scheme of the device for solving the problem is similar to that described in the above method, so the specific limitation in the embodiments of the device 1 for constructing the multi-source data fusion and unified information model based on the data probe provided below can be referred to the limitation of the method for constructing the multi-source data fusion and unified information model based on the data probe hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 9, there is provided a multi-source data fusion and unified information model building apparatus 1 based on a data probe, including: a request response module 11, a scheduling module 12 and a feedback module 13, wherein:
the request response module 11 is configured to respond to a search request, and perform a search in the knowledge-graph index library to obtain an access object corresponding to the search request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
a scheduling module 12, configured to send an extraction instruction including an access object to an executor connected to the multi-source database, so as to instruct the executor to extract object information corresponding to the access object in the multi-source database;
and the feedback module 13 is used for controlling the data probe to feed back the object information to the virtualization server so that the virtualization server feeds back the object information to the sender of the retrieval request.
In one embodiment, the feedback module 13 is further configured to: the control executor feeds the object information back to the data center; and sending the object information to the virtualization server in a timing forwarding mode.
In one embodiment, the apparatus for multi-source data fusion and unified information model construction based on the data probe further comprises a visualization processing module, wherein the visualization processing module is used for: and carrying out visualization processing on the knowledge graph index library, and feeding back the visualized knowledge graph index library to the virtualization server so that the virtualization server marks the access object in the visualized knowledge graph index library and displays the access object to the sender.
The modules in the multi-source data fusion and unified information model construction device based on the data probes can be all or partially realized by software, hardware and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 10. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store XX data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a method for multi-source data fusion and unified information model construction based on data probes.
It will be appreciated by those skilled in the art that the structure shown in fig. 10 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
According to the same inventive concept, the embodiment of the present application further provides a data probe-based multi-source data fusion and unified information model construction device 2 for implementing the above-mentioned data probe-based multi-source data fusion and unified information model construction method. The implementation scheme of the device for solving the problem is similar to that described in the above method, so the specific limitation in the embodiments of the device for constructing a multi-source data fusion and unified information model based on data probes 2 provided below can be referred to the limitation of the method for constructing a multi-source data fusion and unified information model based on data probes hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 11, there is provided a multi-source data fusion and unified information model construction device 2 based on a data probe, including: instruction response module 21 and information forwarding module 22, wherein:
an instruction response module 21, configured to respond to an extraction instruction sent by the dispatch center and including an access object, and extract object information corresponding to the access object in the multi-source database; the access object is obtained by searching in a knowledge graph index base by a scheduling center based on a search request;
the information forwarding module 22 is configured to, in response to a control operation of the dispatch center, feed back the object information to the virtualization server, so that the virtualization server feeds back the object information to a sender of the search request.
In one embodiment, instruction response module 21 includes:
the extraction execution sub-module is used for: selecting a target read-write plug-in from the read-write plug-in set according to the data type of the access object;
determining the loading position of the target read-write plug-in the multi-source database according to the data source corresponding to the access object;
loading a target read-write plug-in at a loading position;
and extracting object information corresponding to the access object from the multi-source database through the loaded target read-write plug-in.
In one embodiment, the information forwarding module 22 further includes a forwarding sub-module, specifically configured to: responding to the control operation of the dispatching center, and determining a target conversion plug-in according to the data type of the virtualized server and the data type of the access object;
according to the target conversion plug-in, performing data type conversion on the object information;
and feeding back the converted object information to the virtualization server so that the virtualization server feeds back the converted object information to a sender of the search request.
In one embodiment, the information forwarding module 22 further includes a verification sub-module for: and carrying out integrity check and validity check on the converted object information.
In one embodiment, the information forwarding module 22 further includes a storage sub-module for: storing object relation information in the object information in a relation database in the data probe;
object attribute information in the object information is stored in a text database in the data probe.
The modules in the multi-source data fusion and unified information model construction device based on the data probes can be all or partially realized by software, hardware and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 12. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program, when executed by the processor, implements a method for multi-source data fusion and unified information model construction based on data probes. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
responding to the retrieval request, and retrieving in a knowledge graph index library to obtain an access object corresponding to the retrieval request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
sending an extraction instruction comprising an access object to an executor connected to the multi-source database to instruct the executor to extract object information corresponding to the access object in the multi-source database;
the control data probe feeds the object information back to the virtualization server for the virtualization server to feed back the object information to the sender of the retrieval request.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as Static Random access memory (Static Random access memory AccessMemory, SRAM) or dynamic Random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include a distributed database according to a blockchain, etc., without being limited thereto. The processors referred to in the embodiments provided herein may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic, data processing logic based on quantum computing, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (12)
1. The method for constructing the multisource data fusion and unified information model based on the data probes is performed by a dispatching center in the data probes and is characterized by comprising the following steps of:
responding to a search request, and searching in a knowledge graph index library to obtain an access object corresponding to the search request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
Sending an extraction instruction comprising the access object to an executor connected to the multi-source database so as to instruct the executor to extract object information corresponding to the access object in the multi-source database;
and controlling the data probe to feed back the object information to a virtualization server so that the virtualization server feeds back the object information to a sender of the retrieval request.
2. The method of claim 1, wherein the controlling the data probe to feed back the object information to a virtualization server comprises:
controlling the executor to feed back the object information to the data center;
and sending the object information to a virtualization server in a timing forwarding mode.
3. The method according to claim 1, wherein the method further comprises:
and carrying out visualization processing on the knowledge graph index library, and feeding back the knowledge graph index library after the visualization processing to the virtualization server so that the virtualization server marks the access object in the knowledge graph index library after the visualization processing and displays the access object to the sender.
4. A method for constructing a multisource data fusion and unified information model based on a data probe, which is executed by an executor in the data probe, the method comprising the following steps:
Responding to an extraction instruction comprising an access object sent by a dispatching center, and extracting object information corresponding to the access object from a multi-source database; the access object is obtained by searching in a knowledge graph index base by the scheduling center based on a search request;
and responding to the control operation of the dispatching center, and feeding back the object information to a virtualization server so that the virtualization server feeds back the object information to a sender of the retrieval request.
5. The method according to claim 4, wherein extracting object information corresponding to the access object in the multi-source database comprises:
selecting a target read-write plug-in from the read-write plug-in set according to the data type of the access object;
determining the loading position of the target read-write plug-in the multi-source database according to the data source corresponding to the access object;
loading the target read-write plug-in at the loading position;
and extracting object information corresponding to the access object from the multi-source database through the loaded target read-write plug-in.
6. The method of claim 4, wherein said feeding back said object information to a virtualization server for said virtualization server to feed back said object information to a sender of said retrieval request in response to a control operation of said dispatch center, comprising:
Responding to the control operation of the dispatching center, and determining a target conversion plug-in according to the data type of the virtualized server and the data type of the access object;
according to the target conversion plug-in, carrying out data type conversion on the object information;
and feeding back the converted object information to a virtualization server so that the virtualization server feeds back the converted object information to a sender of the search request.
7. The method of claim 6, wherein before feeding back the converted object information to a virtualization server for the virtualization server to feed back the converted object information to the sender of the search request, the method further comprises:
and carrying out integrity check and validity check on the converted object information.
8. The method according to claim 4, wherein the method further comprises:
storing object relation information in the object information in a relation database in the data probe;
and storing object attribute information in the object information in a text database in the data probe.
9. A multi-source data fusion and unified information model construction device based on a data probe, the device comprising:
The request response module is used for responding to the search request, searching in the knowledge graph index library and obtaining an access object corresponding to the search request; the knowledge graph index library is constructed based on object indexes corresponding to the objects in the multi-source database;
the scheduling module is used for sending an extraction instruction comprising the access object to an executor connected with the multi-source database so as to instruct the executor to extract object information corresponding to the access object in the multi-source database;
and the feedback module is used for controlling the data probe to feed back the object information to a virtualization server so that the virtualization server feeds back the object information to a sender of the search request.
10. A multi-source data fusion and unified information model construction device based on a data probe, the device comprising:
the instruction response module is used for responding to an extraction instruction comprising an access object sent by the dispatching center and extracting object information corresponding to the access object from the multi-source database; the access object is obtained by searching in a knowledge graph index base by the scheduling center based on a search request;
And the information forwarding module is used for responding to the control operation of the dispatching center and feeding the object information back to the virtualization server so that the virtualization server feeds the object information back to the sender of the search request.
11. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 8 when the computer program is executed.
12. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.
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