CN117171136A

CN117171136A - Data tandem method and related device

Info

Publication number: CN117171136A
Application number: CN202311168043.6A
Authority: CN
Inventors: 吴进
Original assignee: Honghua Shuzhi Energy Technology Shenzhen Co ltd
Current assignee: Honghua Shuzhi Energy Technology Shenzhen Co ltd
Priority date: 2023-09-11
Filing date: 2023-09-11
Publication date: 2023-12-05

Abstract

The invention provides a data tandem method and a related device, comprising the following steps: establishing connection with at least two data source devices; acquiring a table structure of a data table of each data source device, and generating a data model according to the table structure; creating a data flow direction relation between the data models; configuring a mapping relation of fields between a source data model and a target data model according to the data flow direction relation; transmitting data corresponding to the target field in the source data model to the target data model according to the mapping relation of the field, and performing data processing according to the data corresponding to the target field through data source equipment to which the target data model belongs to obtain a data processing result; the service interface is created according to the mapping relation of the fields and the data processing result, so that the user can flexibly connect and process the data of different energy suppliers according to the service demands and generate corresponding service interfaces, the customized design of the service interfaces is realized, and the change of the service demands of the user is met.

Description

Data tandem method and related device

Technical Field

The present invention relates to the field of energy technologies, and in particular, to a data tandem method and a related device.

Background

The energy industry always has the problems of numerous data sources, numerous information systems and the like. According to different market demands, comprehensive energy service providers often independently build application systems when dealing with each project, so that the problems of data island, data splitting, chimney type construction and incapability of uniform operation exist among energy applications. After the user adopts technical means such as interface calling and the like to realize the calling of the data between the systems, the calling method or interface design between the systems is lacking in flexibility, and the change of the user requirements cannot be met; and invocation of the system relies on specific vendors or technologies that limit the extensibility of the system if they cannot meet new requirements.

Disclosure of Invention

The embodiment of the invention provides a data tandem method and a related device, which can flexibly tandem and process data of different energy suppliers according to the service demands of users and generate corresponding service interfaces, thereby realizing the customized design of the service interfaces and meeting the change of the service demands of the users.

In a first aspect, an embodiment of the present invention provides a data tandem method, including: a server for use in a data tandem system, the method comprising:

Establishing connection with at least two data source devices;

acquiring a table structure of a data table of each data source device in the at least two data source devices, and generating a data model of the table structure according to a table name, a field, a data type and constraint information of the table structure;

creating a data flow direction relation of at least two data models corresponding to the at least two data source devices, wherein the data model with data flowing out is a source data model, and the data model with data flowing in is a target data model;

configuring a mapping relation of fields between the source data model and the target data model according to the data flow direction relation, wherein the mapping relation of the fields refers to a rule for associating fields with the same meaning between the source data model and the target data model;

transmitting data corresponding to a target field in the source data model to the target data model according to the mapping relation of the field, and performing data processing according to the data corresponding to the target field through the data source equipment to which the target data model belongs to obtain a data processing result, wherein the target field is a field which needs to be transmitted and has the same meaning and is determined between the source data model and the target model;

And creating a service interface according to the mapping relation of the fields and the data processing result, and outputting the data processing result by calling the service interface.

In a second aspect, an embodiment of the present invention provides a data tandem device, including:

the first connection unit is used for establishing connection with at least two data source devices; the table structure of the data table of each data source device in the at least two data source devices is obtained, and a data model of the table structure is generated according to the table name, the field, the data type and the constraint information of the table structure;

the first configuration unit is used for creating a data flow direction relation of at least two data models corresponding to the at least two data source devices, wherein the data model with data flowing out is a source data model, and the data model with data flowing in is a target data model;

the second configuration unit configures the mapping relation of the fields between the source data model and the target data model according to the data flow direction relation, wherein the mapping relation of the fields refers to a rule for associating the fields with the same meaning between the source data model and the target data model;

The first processing unit is used for transmitting data corresponding to a target field in the source data model to the target data model according to the mapping relation of the field, and performing data processing according to the data corresponding to the target field through the data source equipment to which the target data model belongs to obtain a data processing result, wherein the target field is a field which needs to be transmitted and has the same meaning and is determined between the source data model and the target model;

and the first output unit creates a service interface according to the mapping relation of the fields and the data processing result and outputs the data processing result by calling the service interface.

In a third aspect, an embodiment of the present application provides a server, including a processor and a memory storing execution instructions, where when the processor executes the execution instructions stored in the memory, the processor performs the method according to any one of the first aspects.

It can be seen that in the embodiment of the present application, a connection is first established with at least two data source devices; acquiring a table structure of a data table of each data source device in at least two data source devices, and generating a data model of the table structure according to table names, fields, data types and constraint information of the table structure; secondly, creating a data flow direction relation of at least two data models corresponding to at least two data source devices, wherein the data model with data flowing out is a source data model, and the data model with data flowing in is a target data model; configuring a mapping relation of fields between a source data model and a target data model according to the data flow direction relation; thirdly, transmitting data corresponding to the target field in the source data model to the target data model according to the mapping relation of the field, and carrying out data processing according to the data corresponding to the target field through data source equipment to which the target data model belongs to obtain a data processing result; finally, a service interface is established according to the mapping relation of the fields and the data processing result, and the data processing result is output by calling the service interface; in summary, through the technical scheme of the application, users can flexibly connect and process the data of different energy suppliers according to the service demands and generate corresponding service interfaces, thereby realizing the customized design of the service interfaces and meeting the change of the service demands of the users.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of a data tandem method according to an embodiment of the present application;

FIG. 2 is a data flow relationship diagram of at least two data models corresponding to at least two data source devices according to an embodiment of the present application;

FIG. 3 is an exemplary diagram of a mapping relationship of fields provided by an embodiment of the present application;

FIG. 4a is a user interface diagram of a service interface-front-end parameter configuration provided by an embodiment of the present application;

FIG. 4b is a user interface schematic diagram of a service interface-return parameter configuration provided by an embodiment of the present application;

FIG. 4c is a schematic diagram of a service interface provided by an embodiment of the present application;

FIG. 5 is another flow chart of a data tandem method according to an embodiment of the present application;

fig. 6 is a functional unit composition block diagram of a data tandem device according to an embodiment of the present application;

FIG. 7 is a block diagram of a server according to an embodiment of the present application;

FIG. 8 is an exemplary diagram of a business model provided by an embodiment of the present application;

fig. 9 is a view showing a data model level service connection according to an embodiment of the present application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

The following will describe in detail.

The terms "first," "second," "third," and "fourth" and the like in the description and in the claims and drawings are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The term "at least one" in the present application means one or more, and a plurality means two or more. In the present application and/or describing the association relationship of the association object, the representation may have three relationships, for example, a and/or B may represent: a alone, a and B together, and B alone, wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one (item) below" or the like, refers to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, a and b, a and c, b and c, or a, b and c, wherein each of a, b, c may itself be an element, or may be a collection comprising one or more elements.

It should be noted that, the equality in the embodiment of the present application may be used with a greater than or less than the technical scheme adopted when the equality is greater than or equal to the technical scheme adopted when the equality is less than the technical scheme, and it should be noted that the equality is not used when the equality is greater than the technical scheme adopted when the equality is greater than or equal to the technical scheme adopted when the equality is greater than the technical scheme; when the value is equal to or smaller than that used together, the value is not larger than that used together. "of", corresponding "and" corresponding "in the embodiments of the present application may be sometimes used in combination, and it should be noted that the meaning to be expressed is consistent when the distinction is not emphasized.

The application provides a data tandem method and a related device, and the embodiment of the application is described in detail below with reference to the accompanying drawings.

Referring to fig. 1, fig. 1 is a flow chart of a data tandem method according to an embodiment of the present application, which is applied to a server of a data tandem system, and the method includes:

s101, connection is established with at least two data source devices.

In a possible embodiment, the connection is established with at least two data source devices, and the connection mode includes service interface call or database exchange.

If the service interface calling mode is adopted, the user can fill in the data source name, description, belonging system, URL address and data provider information required by the interface calling to configure the HTTP form data source.

If the data tandem is performed by adopting a database exchange mode, a user can fill in a data source name, a description, a database IP host name, a port number, a user name password, a data provider and the like according to the type of the data source, and establish the data source.

After the connection of the data source device is established, the data source connection test can be performed, related data source information is recorded, and periodic maintenance and updating are performed, wherein the data source information comprises the name, the type, the connection address, the credential information, the description and the like of the data source. By recording and maintaining the data source information, the subsequent use and management can be facilitated.

S102, obtaining a table structure of a data table of each data source device in the at least two data source devices, and generating a data model of the table structure according to a table name, a field, a data type and constraint information of the table structure.

After establishing data connection with the data source equipment, the data tandem system automatically reads the name of a database table under each data source equipment, acquires the table structure of the data table of each data source equipment, and synchronizes the table structure into the data tandem system; the data tandem system automatically generates a data model according to the table structure.

The user can configure the automatic synchronization mode of the data table structure, namely, the mode that the data tandem system acquires the data table structure.

Further, the data model can be further perfected, associations among entities can be added, indexes can be established, views can be defined, and the like, as required.

It can be seen that in this embodiment, when a user performs a specific business process and creation of a tandem task, the user may directly use these automatically created data models, without manually creating a table structure.

S103, creating a data flow direction relation of at least two data models corresponding to the at least two data source devices, wherein the data model with data flowing out is a source data model, and the data model with data flowing in is a target data model.

The data flow relation is established in a visual dragging mode.

The data flow relation between the data source devices and the data flow relation between the data models can be defined macroscopically through the data flow relation.

For an example of this embodiment, please refer to fig. 2, fig. 2 is a data flow relationship diagram of at least two data models corresponding to at least two data source devices according to an embodiment of the present invention.

As shown in FIG. 2, there are four systems, which are equipment cloud management systems, energy consumption management systems, carbon emission calculation tools, and data visualization BI tools.

The equipment cloud management system is a data monitoring system and can monitor the data of facility equipment such as an air conditioner, a factory station, illumination, an elevator and the like in real time to obtain the air conditioner real-time monitoring data, the factory station real-time monitoring data, the illumination real-time monitoring data and the elevator real-time monitoring data.

The energy consumption management system can calculate corresponding energy consumption data according to real-time monitoring data of each area, equipment and system.

And a carbon emission calculation means capable of calculating the amount of carbon emission from the energy consumption data of the apparatus or system.

The data visualization BI tool can perform visual analysis and display on energy consumption data and carbon emission data.

According to the method steps of the invention, the data tandem process comprises four data source devices [ device cloud management system, energy consumption management system, carbon emission calculation tool and data visualization BI tool ];

establishing data connection between the four data source devices and a data tandem system; synchronizing the data table structure of each data source device to a data tandem system to generate a corresponding data model;

The equipment cloud management system comprises 4 data models, namely: air conditioner real-time monitoring data, factory station real-time monitoring data, illumination real-time monitoring data and elevator real-time monitoring data;

the energy consumption management system comprises 4 data models, namely: air conditioner energy consumption data, station energy consumption data, illumination energy consumption data and elevator energy consumption data;

the carbon emission calculation tool comprises 2 data models, namely, calculating carbon emission of a client and calculating carbon emission of a park;

the data visualization BI includes 2 data models, building energy consumption analysis, carbon emission analysis, respectively.

Data flow between the device cloud management system and the energy consumption management system:

connecting the air conditioner real-time monitoring data with the air conditioner energy consumption data, wherein the air conditioner real-time monitoring data is output, and the air conditioner energy consumption data is input;

the method comprises the steps that real-time monitoring data of a plant station are connected with energy consumption data of the plant station, the real-time monitoring data of the plant station are output, and the energy consumption data of the plant station are input;

connecting the illumination real-time monitoring data with the illumination energy consumption data, wherein the illumination real-time monitoring data is output and the illumination real-time monitoring data is input;

and connecting the elevator real-time monitoring data with the elevator energy consumption data, wherein the elevator real-time monitoring data is output, and the elevator energy consumption data is input.

Data flow between the equipment cloud management system and the carbon emission calculation tool:

in this example, the customer carbon emissions calculation is for lighting and elevators, and the campus carbon emissions calculation is for air conditioning and plant sites;

the method comprises the steps that air conditioner real-time monitoring data and plant station real-time monitoring data are respectively connected with park carbon emission calculation, the air conditioner real-time monitoring data and the plant station real-time monitoring data are output, and the park carbon emission calculation is input;

and respectively connecting the illumination real-time monitoring data and the elevator real-time monitoring data with the customer carbon emission calculation, wherein the illumination real-time monitoring data and the elevator real-time monitoring data are output, and the customer carbon emission calculation is output.

Data flow between the energy management system and the data visualization BI tool:

and respectively connecting the air conditioner energy consumption data, the station energy consumption data, the illumination energy consumption data and the elevator energy consumption data with building energy consumption analysis, wherein the air conditioner energy consumption data, the station energy consumption data, the illumination energy consumption data and the elevator energy consumption data are output, and the building energy consumption analysis is input.

Data flow between the carbon emission calculation tool and the data visualization BI tool:

and connecting the customer carbon emission calculation and the park carbon emission calculation with the carbon emission analysis respectively, wherein the customer carbon emission calculation and the park carbon emission calculation are output, and the carbon emission analysis is input.

After the above steps are completed, a complete data flow relationship is established, wherein each data flow relationship will be subjected to the subsequent steps of the method.

Therefore, in this embodiment, by creating the data flow between the application systems in a visualized manner, the architecture, the components and the data dependency relationship of the whole system can be clearly known, and the connection relationship between the data models can be accurately adjusted based on the service requirements.

S104, configuring a mapping relation of fields between the source data model and the target data model according to the data flow direction relation, wherein the mapping relation of the fields refers to a rule for associating fields with the same meaning between the source data model and the target data model.

The mapping relation of the fields can be configured in a visual dragging mode.

An example is listed for the present embodiment, in the data flow direction between the device cloud management system and the energy consumption management system in fig. 2, "connect the air conditioner real-time monitoring data with the air conditioner energy consumption data, the air conditioner real-time monitoring data is output, and the air conditioner energy consumption data is input; for example, please refer to fig. 3, fig. 3 is an exemplary diagram of mapping relationships between fields according to an embodiment of the present invention.

As shown in fig. 3: on the basis of the creation of the data flow relation, the configuration of the mapping relation of the fields is carried out:

the real-time monitoring data of the air conditioner is assumed to comprise the following field names: ID. The capability, operation time, corresponding fields are described as: numbering, power, run time;

the following field names are included in the air conditioner energy consumption data: ID. The capability, operation time, energy consumption, corresponding fields are described as: numbering, power, run time, energy consumption;

the determination target field is: ID. capability and operation time;

and connecting the target field in the air conditioner real-time monitoring data with the target field in the air conditioner energy consumption data to form a mapping relation of the fields.

The mapping relation of the fields can be configured for each link with a data flow relation.

It can be seen that, in this embodiment, through visual operation, a user may intuitively configure a mapping relationship of a field, and adjust and modify the mapping relationship at any time to adapt to a change of a service flow and a change of a requirement, so that maintenance cost may be reduced, service changes may be quickly corresponding, and meanwhile, a mapping rule of each field may have traceability, so that data may be monitored conveniently.

In one possible embodiment, in configuring the mapping relation of the fields between the source data model and the target data model, the method further comprises configuring an operation period and a usage engine between the source data model and the target data model.

Wherein, the operation period configuration is: the operation period of the data mapping is specified, and the data mapping task can be configured to be executed at a certain time interval, at a fixed time point or based on event triggering, such as being executed according to a heartbeat time stamp, an increment time stamp and the like.

Wherein the usage engine configuration is: the selection of an appropriate engine to implement the mapping may choose to use different engines or tools to accomplish the data mapping operations, such as using ETL (extraction, transformation, loading) tools, data integration platforms, middleware, etc., to handle the data mapping, depending on the particular needs and system architecture.

It can be seen that in this embodiment, by configuring the operation cycle and using the engine, the data mapping can be automatically performed at a specific time point or time interval, and the mapping process can be implemented using appropriate tools and techniques. Therefore, the automation degree, accuracy and efficiency of data mapping can be improved, and the requirements of human intervention and manual operation are reduced. Meanwhile, the operation period and the use engine can be flexibly adjusted according to service requirements so as to adapt to different data management requirements and service scenes.

S105, transmitting data corresponding to a target field in the source data model to the target data model according to the mapping relation of the field, and performing data processing according to the data corresponding to the target field through the data source equipment to which the target data model belongs to obtain a data processing result, wherein the target field is a field which needs to be transmitted and has the same meaning and is determined between the source data model and the target model.

The specific steps of this embodiment are as follows: after the data flow direction relation and the mapping relation of the fields are configured, a server of the data tandem system transmits the data flow direction relation and the mapping relation of the fields to data source equipment where a source data model is located, and controls the data source equipment to transmit data corresponding to a target field to the target data model, and after the data source equipment which the target data model belongs to receives the data corresponding to the target field, the data corresponding to the target field is processed according to the function of the data source equipment, so that a data processing result is obtained; and then the data source equipment to which the target data model belongs transmits the data processing result to the server of the data tandem system.

For example, after the air conditioner energy consumption data is received by the air conditioner real-time monitoring data, the energy consumption management system calculates energy consumption according to the received air conditioner real-time monitoring data to obtain energy consumption data of each or all air conditioners, and transmits the energy consumption data of the air conditioners to a server of the data tandem system.

In one possible embodiment, the transmitting the data corresponding to the target field in the source data model to the target data model includes:

and converting the data corresponding to the target field by referring to a preset data mapping rule so that the data corresponding to the target field meets the data requirement of the target data model.

The mapping rule can be customized and managed by a user, and is uploaded to the data tandem system, and can be used when data corresponding to a target field in the source data model is transferred to the target data model.

The mapping rule is a rule or logic for data conversion and processing, defines a mapping relation and conversion logic between input data and output data, can perform various data operations, can perform simple mapping, for example, extract or splice certain fields of the input data, such as removing spaces before and after a character string, intercepting the character string-designating a table below, intercepting the character string-designating a length, and the like, can perform conversion of a data format, such as performing character string date processing, initial transcription, and the like, and can also perform complex data conversion and calculation, such as data screening and grouping based on condition judgment.

Therefore, in this embodiment, the data to be transmitted is automatically converted through the visualized mapping rule, so that the possibility of manual processing and human errors is reduced, and the data in the source data model can be correctly and accurately mapped to the corresponding fields of the target data model, so as to avoid data errors or losses caused by inconsistent field configuration.

S106, creating a service interface according to the mapping relation of the fields and the data processing result, and outputting the data processing result by calling the service interface.

In one possible embodiment, the outputting the data processing result by calling the service interface includes:

acquiring front-end parameters of the service interface, wherein the front-end parameters at least comprise a URL address, a request mode and a request parameter, and the request parameter comprises part or all of the target field;

and outputting the data processing result.

The user can set the front-section parameters uniformly by adopting an interface configuration template.

And the created service interfaces are uniformly managed in the interface list.

After the user fills the front-section parameters, the service interface automatically outputs the return parameters according to the request parameters, and the user can configure the return parameters, for example, only select the data to be displayed.

As an example, referring to fig. 4a, fig. 4a is a schematic diagram of a user interface of a service interface-front-end parameter configuration according to an embodiment of the present application, where the front-end parameter configuration mainly includes a service address (URL address), a request mode (such as a POST request), and a request parameter, and the request parameter may also be specifically configured, for example, a configuration parameter name, a parameter location, a parameter type, a default value, and so on.

Referring to fig. 4b, fig. 4b is a schematic diagram of a user interface of a service interface-return parameter configuration according to an embodiment of the present application, where the parameter name, the return field, and the example value are automatically filled back according to the front-end parameter.

The user can also specifically configure which specific return parameters need to be displayed, and select parameters needing to be returned through the visualization of the return parameter starting or not.

Referring to fig. 4c with reference to fig. 4a and fig. 4b, fig. 4c is a schematic diagram of a service interface according to an embodiment of the present application.

User call interface 1, input front-end parameters:

if the front-end parameter is null, outputting the whole business process data contained in the interface 1 by default, and finally displaying as: and outputting the energy consumption analysis of the whole building, including the energy consumption display of equipment and systems such as air conditioners, stations, illumination, elevators and the like, and outputting the carbon emission analysis of the whole building, including the carbon emission display of the equipment and systems such as the air conditioners, the stations, the illumination, the elevators and the like.

If the user inputs the air conditioner ID in the request parameter configuration, the parameter position is Body, the parameter type is Str, and the parameter name ID, EER, COP, the parameter of the AC CO2 version and the corresponding return field are automatically returned to the parameter configuration interface: the air conditioner number, the air conditioner energy efficiency ratio, the air conditioner cooling conversion efficiency and the air conditioner carbon emission, and a user can select which of the parameters need to be specifically displayed, so that flexible and efficient processing result output is achieved.

It can be seen that in this embodiment, the interface configuration template and the unified management interface list can improve development efficiency, reduce maintenance cost, and eliminate some unnecessary fields or reorganize the structure of the returned data by automatically outputting the returned parameters and flexible configuration. Therefore, flexible data display and interface use modes can be provided according to different front-end requirements and service scenes, and better use experience is provided for front-end developers.

In one possible embodiment, after said configuring the mapping relation of fields between said source data model and said target data model, said method further comprises:

and generating a service model and a visualized service model map according to the data flow direction relation corresponding to the source data model and the target data model and the mapping relation of the fields, wherein the service model map is used for checking the data flow direction relation and the mapping relation of the fields.

According to the data flow direction relation and the field mapping relation, the system can automatically conduct service model carding, can summarize service models of all links, output the service model of the integrated energy platform, and form the service model map of the integrated energy platform. Through the map, the tandem situation and the tandem mode among the data source devices can be known macroscopically. In addition, the user can also view Schema information (i.e., data model information) of each data source device, such as field names, data types, constraint conditions, and the like, and the data objects and attribute information thereof in the service model through the service model map.

Referring to fig. 8, fig. 8 is an exemplary diagram of a service model according to an embodiment of the present application.

It should be noted that the example of fig. 8 is a part of the business flow illustrated in fig. 2.

As can be seen from fig. 8, the data flow relationships between the equipment cloud management system 81, the energy consumption analysis management system 82, and the carbon emission calculation management system 83 are as follows: the equipment cloud management system 81 is an output, and the energy consumption analysis management system 82 and the carbon emission calculation management system 83 are inputs. In this data flow relationship:

Specifically, the device cloud management system 81 obtains device energy consumption basic data according to the real-time monitoring data of the air conditioner and the illumination and the device basic data, where the energy consumption basic data includes the energy consumption basic data of the air conditioner and the energy consumption basic data of the illumination.

The air conditioner, the real-time monitoring data of illumination and the equipment basic data come from the air conditioner monitoring system 811 and the illumination monitoring system 812 respectively, the data provided by the air conditioner monitoring system 811 comprise air conditioner real-time monitoring data 8111 and air conditioner basic data 8112, and the data provided by the illumination monitoring system 812 comprise illumination real-time monitoring data 8121 and illumination basic data 8122.

The air conditioner real-time monitoring data 8111 and the lighting real-time monitoring data 8121 can be obtained according to the heartbeat packet time stamp, and the air conditioner basic data 8112 and the lighting basic data 8122 can be obtained according to the incremental data time stamp.

Mapping the energy consumption base data of the air conditioner to the energy consumption analysis management system 82: the energy consumption analysis management system 82 performs data processing on the energy consumption basic data of the air conditioner to obtain an energy efficiency ratio 821 of the air conditioner and a cooling conversion efficiency 822 of the air conditioner; mapping the energy consumption basic data of the air conditioner to the carbon emission calculation management system 83: the carbon emission calculation management system 83 performs data processing on the energy consumption base data to obtain the air-conditioning carbon emission amount 831.

Mapping the energy consumption base data of the lighting to an energy consumption analysis management system 82: the energy consumption analysis management system 82 performs data processing on the energy consumption basic data of illumination to obtain illumination power density 823; mapping the energy consumption basis data of the illumination to the carbon emission calculation management system 83: the carbon emission calculation management system 83 performs data processing on the energy consumption base data of the illumination to obtain an illumination apparatus carbon emission 832.

The data flow relationships of the energy consumption analysis management system 82, the carbon emission calculation management system 83 and the BI visualization platform 84 are as follows: the energy consumption analysis management system 82 and the carbon emission calculation management system 83 are output, and the BI visualization platform 84 is input. In this data flow relationship:

specific:

the energy consumption analysis management system 82 maps the energy efficiency ratio 821 of the air conditioner, the air conditioner cooling conversion efficiency 822 and the illumination power density 823 to the BI visualization platform 84, and the BI visualization platform 84 displays the energy efficiency ratio 821 of the air conditioner, the air conditioner cooling conversion efficiency 822 and the illumination power density 823.

The carbon emission calculation management system 83 maps the air-conditioning carbon emissions 831, the lighting device carbon emissions 832 to the BI visualization platform 84, and the BI visualization platform 84 displays according to the air-conditioning carbon emissions 831, the lighting device carbon emissions 832.

When a user invokes a corresponding interface to display, the parameters of the energy efficiency ratio 821 of the air conditioner, the cold supply conversion efficiency 822 of the air conditioner, the lighting power density 823, the air conditioner carbon emission 831 and the lighting equipment carbon emission 832 can be displayed at will singly or in a combined mode through the setting of the request parameters. For example, the ID of the air conditioner can be input, the return parameters automatically fill the energy efficiency ratio 821 of the air conditioner, the cold supply conversion efficiency 822 of the air conditioner and the carbon emission of the air conditioner, and the user can configure which of the parameters needs to be specifically displayed, so that flexible and efficient processing result output is achieved.

The business models can be clicked to drill down to check data exchange among specific data models, drill down to field levels aiming at the data models, and check mapping relations of fields among tables.

For example, referring to fig. 9, fig. 9 is a data model level service connection display diagram according to an embodiment of the present application. As shown in the figure 9 of the drawings,

the equipment cloud management system 91 (data source equipment) includes an air conditioner monitoring data table 911 and a lighting system monitoring data table 912, the energy consumption analysis management system 92 (data source equipment) includes an energy consumption data table 921 and an energy consumption topic index table 922, and the carbon emission calculation management system 93 (data source equipment) includes a carbon emission index table 931 and an energy consumption carbon emission analysis index table 932.

The air conditioner monitoring data table 911 and the lighting system monitoring data table 912 are respectively connected with the energy consumption data table 921, so that the energy consumption of the air conditioner and the lighting equipment can be respectively obtained, the energy consumption data table 921 is connected with the carbon emission index table 931, the carbon emission of the air conditioner and the lighting equipment can be obtained, the carbon emission index table 931 is connected with the energy consumption carbon emission analysis index table 932, the relation and the influence between the energy consumption and the carbon emission can be analyzed and evaluated, finally, the energy consumption carbon emission analysis index table 932 is connected with the energy consumption theme index table 922, a series of indexes and statistical data are provided through collecting and arranging the energy consumption data, and the organization or the system can be helped to perform energy management, energy conservation and emission reduction.

It can be seen that, in this embodiment, establishing an energy service model and viewing a service model map can help a user to comprehensively understand the junction situation and the junction mode between systems, and provide benefits of data exchange analysis, service flow management, and data preview and prediction.

In one possible embodiment, after the generating a service model and a visualized service model map according to the data flow direction relationship corresponding to the source data model and the target data model and the mapping relationship of the fields, the method further includes:

And establishing a business analysis library, wherein the business analysis library is used for automatically storing the business model and the data model.

After the tandem task configuration is finished, the data tandem system automatically stores the service model and the data model through a service analysis library, so that the key data are ensured to be completely stored, and necessary support is provided for subsequent analysis and inquiry.

In one possible embodiment, after the service interface is created according to the mapping relation of the fields and the data processing result, the method further includes, after the data processing result is obtained by calling the service interface:

and carrying out call monitoring and call statistics on the service interface, wherein the call monitoring at least comprises monitoring call abnormality, call time and call result, and the call statistics at least comprises statistics call frequency distribution, call success rate and hot call ranking.

It can be seen that, in this embodiment, call monitoring and call statistics on the service interface can ensure stability and reliability of the interface, help optimize system performance, evaluate service quality, provide good user experience, and provide data support for capacity planning and resource allocation. These benefits help to improve usability of the system, to improve user satisfaction, and to improve overall business efficiency and competitiveness.

Referring to fig. 5, fig. 5 is another flow chart of a data tandem method according to an embodiment of the present invention, which is applied to a server of a data tandem system, and the method includes:

s501, accessing a data source.

A connection is established with at least two data source devices.

S502, acquiring a data table structure and generating a data model.

And obtaining the table structure of the data table of each data source device in the at least two data source devices, and generating a data model of the table structure according to the table name, the field, the data type and the constraint information of the table structure.

S503, configuring a data flow relation.

And creating a data flow direction relation of at least two data models corresponding to the at least two data source devices, wherein the data model with data flowing out is a source data model, and the data model with data flowing in is a target data model.

S504, configuring the mapping relation of the fields.

And configuring the mapping relation of the fields between the source data model and the target data model according to the data flow direction relation, wherein the mapping relation of the fields refers to a rule for associating the fields with the same meaning between the source data model and the target data model.

S505, establishing a service model.

S506, establishing a business analysis library.

The business analysis library is used for automatically storing the business model and the data model.

S507, data processing.

Transmitting data corresponding to a target field in the source data model to the target data model according to the mapping relation of the field, and performing data processing according to the data corresponding to the target field through the data source equipment to which the target data model belongs to obtain a data processing result, wherein the target field is a field which needs to be transmitted and has the same meaning and is determined between the source data model and the target model.

S508, creating a service interface.

S509, interface monitoring and statistics.

It should be noted that, the specific implementation process of this embodiment may refer to the specific implementation process described in the foregoing method embodiment, which is not described herein.

The above embodiment describes the intelligent processing method of the elevator information from the aspect of the method flow, and the embodiment of the application can divide the functional units of the electronic device according to the method example, for example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated in one processing unit. The integrated units may be implemented in hardware or in software functional units. It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice.

The following is an embodiment of the apparatus according to the present application, which is configured to execute the method implemented by the embodiment of the method according to the present application. Referring to fig. 6, fig. 6 is a functional unit block diagram of a data tandem device according to an embodiment of the present application, where the device specifically includes:

A first connection unit 601, configured to establish a connection with at least two data source devices; the table structure of the data table of each data source device in the at least two data source devices is obtained, and a data model of the table structure is generated according to the table name, the field, the data type and the constraint information of the table structure;

a first configuration unit 602, configured to create a data flow direction relationship of at least two data models corresponding to the at least two data source devices, where a data model from which data flows out is a source data model, and a data model from which data flows in is a target data model;

a second configuration unit 603, configured to configure a mapping relationship of fields between the source data model and the target data model according to the data flow direction relationship, where the mapping relationship of fields refers to a rule for associating fields having the same meaning between the source data model and the target data model;

a first processing unit 604, configured to transmit data corresponding to a target field in the source data model to the target data model according to a mapping relationship of the field, and perform data processing according to the data corresponding to the target field through the data source device to which the target data model belongs, so as to obtain a data processing result, where the target field is a field that needs to be transmitted and has the same meaning and is determined between the source data model and the target model;

The first output unit 605 creates a service interface according to the mapping relation of the fields and the data processing result, and outputs the data processing result by calling the service interface.

and outputting the data processing result.

Fig. 7 is a block diagram of a server according to an embodiment of the present application. As shown in fig. 7, the server 70 may include one or more of the following components: a processor 701, a memory 702, wherein the memory 702 may store one or more computer programs that may be configured to implement the methods as described in the embodiments above when executed by the one or more processors 701.

It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.

In the several embodiments provided in the present application, it should be understood that the disclosed method, apparatus and system may be implemented in other manners. For example, the device embodiments described above are merely illustrative; for example, the division of the unit is just one logic function division, and there may be another division manner when actually implementing the unit; for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may be physically included separately, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, or may be embodied in software instructions executed by a processor. The software instructions may be comprised of corresponding software modules that may be stored in random access Memory (Random Access Memory, RAM), flash Memory, read Only Memory (ROM), erasable programmable Read Only Memory (Erasable Programmable ROM), electrically Erasable Programmable Read Only Memory (EEPROM), registers, hard disk, a removable disk, a compact disc Read Only Memory (CD ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. In addition, the ASIC may reside in an access network device, a target network device, or a core network device. It is of course also possible that the processor and the storage medium reside as discrete components in an access network device, a target network device, or a core network device.

Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the embodiments of the present application may be implemented, in whole or in part, in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy Disk, a hard Disk, a magnetic tape), an optical medium (e.g., a digital video disc (Digital Video Disc, DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.

The foregoing detailed description of the embodiments of the present application further illustrates the purposes, technical solutions and advantageous effects of the embodiments of the present application, and it should be understood that the foregoing description is only a specific implementation of the embodiments of the present application, and is not intended to limit the scope of the embodiments of the present application, and any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the scope of the embodiments of the present application.

Claims

1. A data tandem method, applied to a server of a data tandem system, the method comprising:

establishing connection with at least two data source devices;

2. The method of claim 1, wherein the establishing a connection with at least two data source devices includes a service interface call or a database exchange.

3. The method according to claim 1, wherein said transmitting data corresponding to a target field in said source data model to said target data model comprises:

4. The method of claim 1, wherein outputting the data processing result by invoking the service interface comprises:

and outputting the data processing result.

5. The method of claim 1, wherein after said configuring the mapping of fields between the source data model and the target data model, the method further comprises:

6. The method of claim 5, wherein after the generating a business model and a visualized business model map from the data flow direction relationships and the field mappings corresponding to the source data model and the target data model, the method further comprises:

7. The method according to claim 1, wherein after said creating a service interface from the mapping relation of the fields and the data processing result, the method further comprises, after obtaining the data processing result by calling the service interface:

8. The method of claim 1, further comprising configuring an operational period and usage engine between the source data model and the target data model when configuring a mapping of fields between the source data model and the target data model.

9. A data tandem device, the device comprising:

10. A server comprising a processor and a memory storing execution instructions, wherein the processor performs the method of any one of claims 1 to 8 when the processor executes the execution instructions stored in the memory.