CN115220901A - Cloud data center, first edge side server and multi-source data management system - Google Patents

Abstract

The application provides a high in the clouds data center, first edge side server and multisource data management system, high in the clouds data center includes the task scheduling module, the intranet pierces through module and data collection module, the task scheduling module, the intranet pierces through module and data collection module and reads first house property data from first target product through first edge side server every first time of setting for, and gather the first house property data that will read, and write into the second target product through the first house property data of second edge side server after will gathering. The application provides a high in clouds data center can be automatically with the leading-in second target product of first house property data in the first target product, need not manual operation, has saved manpower resources to carry out first house property data introduction once every first length of time of setting for, the real-time is better, and the first target product all can be regarded as to all products of target object simultaneously, has realized the house property data sharing of all products of target object, and is more friendly to the target object.

Description

Cloud data center, first edge side server and multi-source data management system

Technical Field

The application relates to the technical field of data processing, in particular to a cloud data center, a first edge side server and a multi-source data management system.

Background

In the real estate field, the time period for selling rooms in a developer's playground is long, involving many business phases, such as, for example, the phases of acquiring customers, customer follow-up, customer visit, customer drafts, customer payments, etc. In order to implement the workflow process of the business phase online, each service provider develops a different application product for each business phase. Because the advantageous products of different service providers are different, developers can respectively select products at different stages according to the requirements of the developers, so that the situation that customers and businesses are bound by software service providers due to channel simplification is avoided.

However, the product data provided by each service provider are not intercommunicated, so that when a developer selects products of different service providers, export data needs to be manually imported between the products of different service providers, for example, when a product 1 provided by a service provider 1 is used for online activities to obtain a plurality of pieces of customer information, when a product 2 provided by a service provider 2 is used for customer follow-up and visit records, all the customer information needs to be manually exported from the product 1 and imported into the product 2 to continue the next work flow. On one hand, the manual import and export mode increases the workload of workers, which causes waste of human resources, and on the other hand, the non-intercommunication of the house data causes that developers can not see the data flow statistics of the whole flow, such as customer retention rate, which brings great influence on the normal decision of the developers.

Disclosure of Invention

In view of this, the present application provides a cloud data center, a first edge side server and a multi-source data management system, which are used to solve the above technical problems, and the technical scheme is as follows:

a cloud-based data center, comprising:

the system comprises a task scheduling module, a task execution module and a task execution module, wherein the task scheduling module is used for acquiring an automation task corresponding to a first target product of a target object, and generating a first data reading instruction corresponding to the automation task every other first set time length when an execution mode contained in the automation task is a Robot Process Automation (RPA) mode, and the first set time length is determined according to an execution frequency contained in the automation task;

the intranet penetration module is used for sending a first data reading instruction to the first edge side server by adopting an intranet penetration technology so that the first edge side server responds to the first data reading instruction, reading first property data from a first target product by adopting an RPA technology, and sending the first property data to the data summarizing module, wherein the first edge side server is an edge side server where the first target product is located;

the data summarization module is used for summarizing the first property data read within at least one first set time length and generating a first data write-in instruction based on the summarized first property data;

the intranet penetration module is further used for sending the first data writing instruction to the second edge side server by adopting an intranet penetration technology, so that the second edge side server responds to the first data writing instruction, the RPA technology is adopted to write the summarized first house data into a second target product, the second target product is a product except the first target product in all products of the target object, and the second edge side server is an edge side server where the second target product is located.

Optionally, the first property data is incremental property data or all property data, and the incremental property data refers to newly added property data in the first target product within a corresponding first set time length;

if the first property data is all the property data, the data summarizing module summarizes the first property data read within at least one first set time period, and when generating a first data writing instruction based on the summarized first property data, the data summarizing module is specifically configured to:

respectively determining incremental property data from the first property data read within at least one first set time length, and taking all the determined incremental property data as the summarized first property data;

and generating a first data writing instruction based on the summarized first property data.

Optionally, the method further includes:

and the task result reporting module is used for receiving a writing result of the summarized first property data fed back by the second edge side server, wherein the writing result is used for reflecting whether the edge side server successfully writes all the summarized first property data.

Optionally, the method further includes:

the cloud calling incremental data acquisition module is used for exposing the data reading and writing interface to the first target product when the execution mode included in the automation task is the interface calling mode so that the first target product can conveniently push the first property data to the cloud data center through the data reading and writing interface;

and the cloud calling incremental data writing module is used for writing the first property data received by the cloud data center into a second target product through the data reading and writing interface.

A first edge-side server, comprising:

the system comprises a trigger module and an RPA data acquisition module, wherein the trigger module is used for informing the RPA data acquisition module to acquire data after receiving a first data reading instruction corresponding to an automation task corresponding to a first target product of a target object, wherein the first data reading instruction refers to a data reading instruction generated by a cloud data center at intervals of a first set time length when an execution mode contained in the automation task is an RPA mode, and the first set time length is determined according to an execution frequency contained in the automation task corresponding to the first target product;

the RPA data acquisition module is used for reading all property data from the first target product by adopting an RPA technology;

the data reporting module is used for sending all the property data to the cloud data center so that the cloud data center can write the first property data into a second target product through a second edge side server, wherein the second target product refers to a product except the first target product in all products of a target object, the first property data is all the property data or incremental property data in all the property data, and the incremental property data refers to newly increased property data in the first target product within a corresponding first set time length;

the trigger module is further configured to notify the RPA data writing module to write data after receiving a second data writing instruction corresponding to an automation task corresponding to a second target product, where the second data writing instruction is a data writing instruction generated based on summarized second house data after the cloud data center aggregates the second house data read within at least one second set time period, the second house data is house data in the second target product, and the second set time period is determined according to an execution frequency included in the automation task corresponding to the second target product;

and the RPA data writing module is used for writing the summarized second house product data into the first target product by adopting an RPA technology.

Optionally, the method further includes:

the data comparison and conversion module is used for determining incremental property data from all property data;

and the data reporting module is also used for sending the incremental property data to the cloud data center.

Optionally, the method further includes:

and the encryption and decryption login module is used for decrypting the locally acquired encryption login information based on the decryption key after the trigger module receives the first data reading instruction and before the RPA data acquisition module reads all the property data to obtain decryption login information, and logging in the first target product based on the decryption login information, wherein the encryption login information is a ciphertext of login information preset in the first target product by the target object.

Optionally, when the RPA data collection module reads all the property data from the first target product by using the RPA technology, the RPA data collection module is specifically configured to:

acquiring a first target product from a preset page element position by adopting an RPA technology, and reading all property data from the first target product;

the first edge-side server, further comprising:

the case server stability module is used for scanning front-end page elements when preset page element positions fail, sending the newly scanned page element positions to the RPA data acquisition module if the page elements of a first target product are scanned, so that the RPA data acquisition module can acquire the first target product from the newly scanned page element positions, and sending alarm information to an administrator of the first edge side server if the page elements of the first target product are not scanned for multiple times.

Optionally, the case server stability module is further configured to:

and when the first edge side server is disconnected or the automatic task fails to be executed, reconnecting the first edge side server with the cloud data center, and caching the real estate data read in the automatic task execution process in a message queue during reconnection.

A multi-source data management system comprises the cloud data center, the first edge side server and the second edge side server.

According to the technical scheme, the cloud data center comprises a task scheduling module, an intranet penetration module and a data summarization module, wherein the task scheduling module is used for acquiring an automation task corresponding to a first target product of a target object, and when an execution mode included in the automation task is a robot process automation RPA mode, a first data reading instruction corresponding to the automation task is generated at intervals of a first set time length, the intranet penetration module is used for sending the first data reading instruction to a first edge side server by adopting an intranet penetration technology, so that the first edge side server responds to the first data reading instruction, reading first property data from the first target product by adopting an RPA technology, and sending the first property data to the data summarization module, the data summarization module is used for summarizing the first property data read in at least one first set time length, generating a first data writing instruction based on the summarized first property data, the intranet penetration module is further used for sending the first data writing instruction to a second edge side server by adopting an intranet penetration technology, so that the second edge side responds to the summarized first property data, and writing the second property data into the target product by adopting an intranet penetration technology. The utility model provides a high in clouds data center can be automatically with the leading-in second target product of first real estate data in the first target product, need not manual operation, human resources have been saved, and carry out first real estate data once and lead-in every first length of time of setting for, the real-time is better, simultaneously all products of target object all can regard as first target product, the real estate data sharing of all products of target object has been realized, thereby the target object can see the data flow statistics of full flow, it is more friendly to the target object.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a schematic structural diagram of a cloud data center provided in an embodiment of the present application;

fig. 2 is a schematic structural diagram of another cloud data center provided in the embodiment of the present application;

fig. 3 is a schematic structural diagram of another cloud data center provided in the embodiment of the present application;

fig. 4 is an overall architecture diagram of a cloud data center and a single product according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a first edge-side server according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of another first edge-side server according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of another first edge-side server according to an embodiment of the present disclosure;

fig. 8 is a schematic structural diagram of another first edge-side server according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The application provides a cloud data center, a first edge server and a multi-source data management system, which are applied to the field of real estate. For convenience of description of the cloud data center, the first edge server and the multi-source data management system, related terms applied in the present application are now explained.

RPA: the RPA is called robot Process Automation (robot Process Automation), and the main function is to perform the interaction between the working information and the service through the robot according to the designed Process. Therefore, when the interaction between the working information and the service is more, the RPA can efficiently solve the complex processes, and the labor cost is saved.

And (3) edge calculation: the method is characterized in that an open platform integrating network, calculation, storage and application core capabilities is adopted at one side close to an object or a data source to provide nearest-end service nearby. The application program is initiated at the edge side, so that a faster network service response is generated, and the basic requirements of the industry in the aspects of real-time business, application intelligence, safety, privacy protection and the like are met.

Individual products: inside the workflow of real estate project, there are several different sales links, such as customer acquisition, customer visit, customer contract, house source issue, etc. Because the business emphasis of each link is different, developers in each link can use application program products of different service providers to carry out online work. The application products of different software providers used at various points are referred to herein as "individual products".

The data center comprises: the intermediate tool and platform are used for uniformly reading, sorting and writing the data of each single product.

Next, the cloud data center provided by the present application is first described in detail through the following embodiments.

Referring to fig. 1, a schematic structural diagram of a cloud data center provided in an embodiment of the present application is shown, where the cloud data center may include: task scheduling module 11, intranet penetration module 12 and data summarization module 13.

The task scheduling module 11 is configured to obtain an automation task corresponding to a first target product of a target object, and generate a first data reading instruction corresponding to the automation task every first set time length when an execution mode included in the automation task is a Robot Process Automation (RPA) mode, where the first set time length is determined according to an execution frequency included in the automation task.

The intranet penetrates the module 12 for adopt the intranet to penetrate the technology and send the first data reading instruction to first edge side server response first data reading instruction adopts RPA technique to read first property data from first target product, and sends first property data to the data summarization module, and wherein, first edge side server is the edge side server at first target product place.

The data summarizing module 13 is configured to summarize the first property data read within at least one first set duration, and generate a first data writing instruction based on the summarized first property data.

The intranet penetration module 12 is further configured to send the first data write-in instruction to the second edge side server by using an intranet penetration technology, so that the second edge side server responds to the first data write-in instruction, and writes the summarized first property data into the second target product by using an RPA technology, where the second target product is a product of all products of the target object except the first target product, and the second edge side server is an edge side server where the second target product is located.

Specifically, the user may configure the data center at the task scheduling module 11 to read in the automation task of the first target product, and then the task scheduling module may obtain the automation task corresponding to the first target product of the target object.

Optionally, the target object is a developer, and the first target product refers to a single product selected by the developer, and the single product may specifically be any one of all products selected by the developer.

Optionally, the automation task includes an execution frequency, an execution mode, and a product identifier, where the product identifier refers to an identifier of the first target product, and the execution mode includes an RPA mode and an interface calling mode.

When the execution mode is the RPA mode, the execution frequency is used to instruct the task scheduling module 11 to generate the frequency of the first data reading instruction, for example, the first set time length determined according to the execution frequency is 10 minutes, and when the execution mode included in the automation task is the RPA mode, the task scheduling module 11 generates one first data reading instruction every 10 minutes.

Here, the first data reading instruction is used to read property data from a first target product, and in order to distinguish the property data from property data in a second target product, the property data read from the first target product is referred to as first property data, and the property data read from the second target product is referred to as second property data, where the second target product refers to a product other than the first target product among all products of the target object. Optionally, the first target product and the second target product are products of different service providers or products of the same service provider.

Optionally, the property data in each product may be classified into six data categories, which are clients, consultants, channels, sources, orders and money, that is, the embodiment may classify the property data interactions in the field working process into the six types of property data, and implement synchronization of the six types of property data through programs.

In order to respond to the synchronization processing more quickly and safely, the edge side local scenario server where the product is located may be adopted in the present embodiment, and for convenience of the following description, the edge side local scenario server is simply referred to as the edge side server. In this embodiment, the edge side server is deployed in the local area network of the case, so the edge side server belongs to an intranet server without a public network IP, the cloud data center is deployed on the cloud server, and the cloud server belongs to a server with a public network IP, therefore, the cloud data center needs to include the intranet penetration module 12, and the intranet penetration module 12 can adopt an intranet penetration technology to send the first data reading instruction to the first edge side server. Here, the intranet penetration technology is to call an intranet server without the public network IP from a server with the public network IP, and the common software is FRP (a cross-platform intranet penetration tool).

The first edge side server can respond to the first data reading instruction, read the first property data from the first target product by adopting an RPA technology, and send the first property data to the data summarizing module.

Optionally, the first property data is all property data or incremental property data in the first target product, where all property data refers to all property data included in the first target product until the current time, and the incremental property data refers to newly added property data in the first target product within a corresponding first set time length. For example, in this embodiment, the time when the target object, that is, the developer starts to use the first target product, is defined as 0 th minute, it is assumed that data reading instructions are generated in 10 th minute, 20 th minute, 30 th minute and 40 th minute, and it is assumed that the current time is 40 th minute, then all the property data refers to all the property data in the first target product within 0 to 40 th minute, and the incremental property data refers to newly added property data in the first target product within 31 to 40 minutes.

That is to say, after receiving the first data reading instruction, the first edge-side server may read all the property data before the current time from the first target product, or may read the incremental property data within the corresponding first set time length from the first target product.

In this embodiment, the data summarization module 13 may receive the read first property data in each first set duration, and then the data summarization module 13 may generate a first data write-in instruction based on the received first property data every time it receives the first property data read in one first set duration, or may summarize the first property data read in a plurality of first set durations after receiving the first property data read in a plurality of first set durations to obtain the summarized first property data, and then generate a first data write-in instruction based on the summarized first property data. Here, the first data writing instruction is used to cause the second edge side server to write the aggregated first property data into the second target product.

As described above, if the first property data is incremental property data, the data summarization module 13 may not perform any processing other than summarization on the incremental property data, and directly generate a first data write instruction; optionally, if the first property data is all the property data, the data summarization module 13 may also directly generate the first data write-in instruction without performing any processing other than summarization on the incremental property data (subsequently, the first data write-in instruction may be based on the overwrite writing).

Preferably, if the first property data is all property data, the process of the data summarization module 13 "summarizing the first property data read within at least one first set time period, and generating the first data write-in instruction based on the summarized first property data" may include: the method comprises the steps of respectively determining incremental property data from first property data read within at least one first set time length, taking all the determined incremental property data as summarized first property data, and generating a first data writing instruction based on the summarized first property data.

That is, after receiving the first property data, the data summarization module 13 needs to determine incremental property data from the first property data, and then generates a first data write command based on all incremental property data within at least one first set time duration.

For example, if the first set time is 10 minutes, the data summarization module 13 may extract, when the current time is 30 minutes, the new property data from 21 to 30 minutes as incremental property data within the first set time, and extract, when the current time is 40 minutes, the new property data from 31 to 40 minutes as incremental property data within another first set time, and so on, to obtain at least one incremental property data within the first set time, that is, the summarized first property data.

Similar to the first data reading instruction, after the first data writing instruction is generated, in this embodiment, the intranet penetration module 12 needs to send the first data writing instruction to the second edge side server by using an intranet penetration technology, and then the second edge side server can respond to the first data writing instruction and write the summarized first property data into the second target product by using an RPA technology. If the second target product includes a plurality of products, the second edge side server may write the aggregated first property data into the plurality of products, respectively.

By the embodiment, the cloud data center provided by the application can automatically lead first house property data in a first target product into a second target product without manual operation, manpower resources are saved, the first house property data are led in once every first set time, the real-time performance is better, all products of a target object can be used as the first target product, house property data sharing of all products of the target object is achieved, the target object can see data flow statistics of the whole process, and the target object is friendly.

That is, the embodiment can place all synchronous operations under a unified task scheduling module, and efficiently register and execute tasks. And the task scheduling module allocates the data to carry out intensive and uninterrupted bidirectional synchronization without manual triggering, so that quasi-real-time synchronization is realized.

In an optional embodiment, considering that at least part of the data writing may fail when the second edge side server writes the summarized first property data into the second target server, the second edge side server may feed back the writing result of the summarized first property data to the cloud data center after writing the summarized first property data into the second target server.

Then, referring to the schematic structural diagram of the cloud data center shown in fig. 2, the cloud data center may further include a task result reporting module 14, where the task result reporting module 14 is configured to receive a writing result of the summarized first property data fed back by the second edge-side server, where the writing result is used to reflect whether the edge-side server successfully writes all the summarized first property data.

For example, the write result is: the first property data after the summary contains 100 pieces of data, wherein 99 pieces of data are successfully written, the writing success rate is 99%, and the data which are not successfully written are xx data.

Of course, the above writing results are only examples and are not intended to limit the present application.

In summary, the embodiments of the present application provide a cloud data center, and an RPA manner is adopted to help a target object to use a single product of multiple service providers and conveniently get through all data of a full flow, so as to implement bidirectional and complete data sharing among multiple independent different service provider systems; and the cloud data center can perform a quasi-real-time level data synchronization task in 24 hours all day long without human intervention, so that the real-time performance is better.

In another embodiment of the application, in consideration of a single scheme for achieving data synchronization among multiple products only by using an RPA method, in order to enable the cloud data center to support more data synchronization methods and provide more perfect and better services for a target object as much as possible, the cloud data center provided in this embodiment may further use an interface calling method to perform data synchronization among different products.

Based on this, referring to a schematic structural diagram of another cloud data center shown in fig. 3, the cloud data center includes a cloud-call incremental data acquisition module 15 and a cloud-call incremental data writing module 16.

The cloud calling incremental data acquisition module 15 is configured to expose the data read-write interface to the first target product when the execution mode included in the automation task is the interface calling mode, so that the first target product pushes the first property data to the cloud data center through the data read-write interface.

Correspondingly, the cloud calling incremental data writing module 16 is configured to write the first property data received by the cloud data center into the second target product through the data reading and writing interface.

That is to say, the cloud data center can expose the data read-write channel to the outside, and a single product (a first target product) can initiatively push first property data to the cloud data center through the mode that the interface was called, and the cloud data center also can write first property data of a first target product into a second target product through the mode that the interface was called.

Optionally, the first target product may push the first property data to the cloud data center in a manner of calling the first property data through the interface every third set time, and the cloud data center writes the first property data of the first target product into the second target product in a manner of calling the first property data through the interface.

It should be noted that the interface calling mode requires that a single product and the cloud data center perform early-stage interface matching development, and a single product performing only interface development can perform data synchronization with the cloud data center through the interface calling mode.

In this embodiment, an interface calling mode is set, so that the data synchronization mode that the cloud data center provided by the present application can support is not single, and the cloud data center is more friendly to a target object.

Referring to the overall architecture diagram of the cloud data center and the single product shown in fig. 4, the cloud data center (i.e., the data center in fig. 4) is used as a center, data of each single product (i.e., the first target product, which may be the single product a, the single product B, the single product C, or the like in fig. 4) is synchronized to the data center, and the data center is transferred to each other single product (i.e., the second target product). Synchronization is bi-directional, with each individual product including both read and write operations, ultimately ensuring that the data center has all the data, and each individual product has all the data that is compatible with its system itself.

The specific synchronization mode includes an interface call mode and an RPA mode. In the interface calling mode, a single product initiates interface calling to synchronize data to a data center, and the data center calls each single product interface to write data; in the RPA mode, a data center initiates an RPA call to read single product data and initiates the RPA call to write data into a single product.

Fig. 4 only shows a schematic diagram of data exchange between a data center and a single product, and specific data exchange processes may refer to descriptions in the foregoing embodiments and are not described herein again.

Corresponding to the cloud data center provided in the foregoing embodiment, the present application further provides a first edge-side server, and then, the first edge-side server provided in the present application is first described in detail through the following embodiments.

Referring to fig. 5, a schematic structural diagram of a first edge-side server provided in the embodiment of the present application is shown, where the first edge-side server may include: the device comprises a trigger module 21, an RPA data acquisition module 22, a data reporting module 23 and an RPA data writing module 24.

The trigger module 21 is configured to notify the RPA data acquisition module to perform data acquisition after receiving a first data reading instruction corresponding to an automation task corresponding to a first target product of a target object, where the first data reading instruction refers to a data reading instruction generated by the cloud data center every first set time when an execution mode included in the automation task is an RPA mode, and the first set time is determined according to an execution frequency included in the automation task corresponding to the first target product.

And the RPA data acquisition module 22 is used for reading all the property data from the first target product by adopting the RPA technology.

The data reporting module 23 is configured to send all property data to the cloud data center, so that the cloud data center writes the first property data into the second target product through the second edge side server, where the second target product refers to a product other than the first target product in all products of the target object, the first property data is all property data, or incremental property data in all property data, and the incremental property data refers to newly added property data in the first target product within a corresponding first set time period.

The trigger module 21 is further configured to notify the RPA data writing module to write data after receiving a second data writing instruction corresponding to the automation task corresponding to a second target product, where the second data writing instruction is a data writing instruction generated based on summarized second house data after the cloud data center aggregates the second house data read within at least one second set duration, the second house data is house data in the second target product, and the second set duration is determined according to an execution frequency included in the automation task corresponding to the second target product.

And the RPA data writing module 24 is configured to write the summarized second house product data into the first target product by using an RPA technique.

Specifically, after the cloud data center sends the first data reading instruction to the first edge-side server, the trigger module 21 may receive the first data reading instruction. The trigger module 21 may notify the RPA data collection module 22 to collect data after receiving the first data reading instruction.

It should be noted that after the trigger module 21 receives the first data reading instruction, the RPA data acquisition module 22 is not directly notified to perform data acquisition, but the first target product needs to be logged in through the login information, and the RPA data acquisition module 22 may be notified to perform data acquisition only after the login is successful.

In this embodiment, the first edge-side server may log in the first target product through the login information in the same manner as in the prior art, that is, the login information is stored in the cloud data center in advance, and when the cloud data center sends the first data reading instruction to the first edge-side server, the login information is sent to the first edge-side server at the same time, so that the trigger module 21 may log in the first target product through the login information after receiving the first data reading instruction and the login information, and then notify the RPA data acquisition module 22 to perform data acquisition.

Preferably, the login information is pre-stored in the cloud data center, and when the cloud data center is attacked, the login information of the first target product may be leaked. In order to prevent the login information from leaking in the case that the data interaction flow is smooth, referring to fig. 6, the first edge-side server provided in this embodiment may further include an encryption/decryption login module 25.

In this embodiment, the encryption and decryption login module 25 is configured to, after the trigger module 21 receives the first data reading instruction and before the RPA data acquisition module 22 reads all the property data, decrypt, based on the decryption key, the encrypted login information obtained locally to obtain decryption login information, and log in the first target product based on the decryption login information, where the encrypted login information is a ciphertext of login information preset by the target object in the first target product.

Specifically, when the initial project is opened, the administrator may input login information, encrypt and store the login information to the first edge side server locally, and manage the encryption key and the corresponding decryption key by the staff in the case. After the project is opened, the encryption and decryption login module 25 may obtain the encrypted login information locally from the first edge-side server after the trigger module 21 receives the first data reading instruction, then decrypt the encrypted login information based on the decryption key, and log in the first target product based on the decrypted login information after decryption.

Alternatively, the login information may be a user name and a password.

The embodiment can ensure that the login information of each single product is not leaked out by arranging the encryption and decryption login module 25, and the security is higher.

After successfully logging on the first target product, the RPA data collection module 22 may use the RPA technique to read all the property data from the first target product.

Specifically, the process of reading the first property data from the first target product by using the RPA technology includes: and acquiring a first target product from a preset page element position by adopting an RPA (resilient packet access) technology, and reading all property data from the first target product. Alternatively, the page element may be an application icon displayed on the front page for the first target product.

Considering that the RPA mode carries out a large amount of collection operation by simulating the click frequency of a human, a long time is needed under the condition that the data volume of all the property data is large, and if the operation of extracting the incremental property data is carried out on the cloud server, the delay is high. In order to avoid slow synchronization efficiency due to high latency, it is preferable that the RPA operation of the scenario itself and the incremental data extraction operation be performed by the computationally idle first edge-side server.

Based on this, referring to fig. 7, the first edge-side server provided in this embodiment of the present application may further include a data comparison and conversion module 26.

The data contrast conversion module 26 may be used to determine incremental property data from the total property data.

For example, all the property data read by the RPA data acquisition module 22 are property data in 0 to 40 minutes, and assuming that the current first data reading instruction is a data reading instruction generated in 31 to 40 minutes, the data comparison and conversion module 26 may determine, from the property data in 0 to 40 minutes, property data newly increased in 31 to 40 minutes, that is, incremental property data.

Under the condition that the first edge-side server includes the data comparing and converting module 26, the data reporting module 23 is further configured to send the incremental property data to the cloud data center.

In summary, the first edge-side server provided in the embodiment of the present application may not include the data comparison and conversion module 26, and in this case, the first edge-side server may send all the property data in the first target product to the cloud data center, and the cloud data center performs incremental property data extraction or non-extraction according to actual needs; in a preferable case, the first edge-side server may include the data comparing and converting module 26, so that the first edge-side server may send the incremental property data to the cloud data center, and at this time, the cloud data center may write the aggregated incremental property data into the second target product through the second edge-side server after aggregating the incremental property data within at least one first set time period. In the embodiment, the RPA operation and the data comparison and conversion operation are carried out at the edge side, so that the high efficiency of data synchronization is ensured.

After the cloud data center receives the first property data (optionally, all property data or incremental property data in the first target product) reported by the data reporting module 23, the first property data may be written into the second target product through the second edge side server. Regarding the process of the cloud data center writing the first property data into the second target product through the second edge side server, reference may be made to the above description of the cloud data center, which is not described herein again.

The foregoing embodiments describe in detail how first property data in a first target product can be written into a second target product in an incremental (or total) manner, and similarly, second property data in the second target product can be written into the first target product.

Specifically, the process of writing the second property data in the second target product into the first target product includes the following stages.

First, the task scheduling module 11 in the cloud data center obtains an automation task corresponding to a second target product of a target object, and generates a second data reading instruction every second set time when an execution mode included in the automation task is an RPA mode.

Then, the intranet penetration module 12 sends the second data reading instruction to the second edge side server by using an intranet penetration technology, so that the second edge side server responds to the second data reading instruction, reads the second property data from the second target product by using an RPA technology, and sends the second property data to the data summarization module 13, where the second property data refers to all property data in the second target product or newly added property data in the second target product within a corresponding second set time duration.

Then, the data summarization module 13 summarizes the second production data read in at least one second set read length, and generates a second data write-in instruction based on the summarized second production data.

Then, the intranet penetration module 12 sends a second data write instruction to the first edge-side server by using the intranet penetration technology.

Next, the trigger module 21 in the first edge-side server notifies the RPA data writing module 24 to write data after receiving the second data writing instruction.

Finally, the RPA data writing module 24 writes the summarized second house product data into the first target product by using an RPA technique.

The implementation processes of the above stages correspond to the process of writing the first property data in the first target product into the second target product one by one, and reference may be made to the description in the foregoing embodiments for details, which are not repeated herein.

In an optional embodiment, the data reporting module may be further configured to feed back the write-in result of the aggregated second-property data to the cloud data center, and specifically, to the task result reporting module 14.

Here, the writing result of the summarized second property data corresponds to the writing result of the summarized first property data, and details can refer to the description in the foregoing embodiments, and are not repeated herein.

In another embodiment of the present application, in order to cope with the situation that system update is possible for each single product and the first edge-side server may be crashed or disconnected during the daily synchronization process, the first edge-side server may be designed to be stable.

Based on this, the first edge side server may also include a case server stability module 27, see fig. 8.

Optionally, the scenario server stability module 27 may be configured to perform front-end page element scanning when a preset page element position is invalid, and if a page element of a first target product is scanned, send a newly scanned page element position to the RPA data acquisition module, so that the RPA data acquisition module acquires the first target product from the newly scanned page element position, and if the page element of the first target product is not scanned after multiple scans, send alarm information to an administrator of the first edge side server.

Specifically, the position of the page element of the first target product on the front-end page is preset in the RPA mode, and the click action of a human is simulated in the RPA mode to click on the preset page element position, so that all house property data can be acquired after the first target product is opened. However, after the system of the first target product is updated, the preset page element position may move, so that the preset page element position is invalid, and at this time, when the page element of the first target product is clicked at the original position in an RPA manner, a situation that the first target product cannot be opened occurs. In order to avoid this, the scenario server stability module 27 may perform front-end page element scanning when the preset page element position is invalid, and if the page element of the first target product is scanned, send the newly scanned page element position to the RPA data acquisition module 22, and in subsequent acquisition, the RPA data acquisition module 22 may perform data acquisition according to the newly scanned page element position.

Of course, there may be a case where the page element of the first target product is not scanned, and at this time, an alarm message may be sent to the administrator when the page element of the first target product is not scanned in an attempt of scanning for a plurality of times.

Optionally, the scenario server stability module 27 may be further configured to reconnect to the cloud data center when the first edge-side server is disconnected from the network or the automation task fails to be executed, and cache the property data read in the execution process of the automation task in the message queue during reconnection.

Specifically, for the case that the first edge side server is abnormal (for example, crashes, breaks the network, etc.), the first edge side server may be monitored in real time through the case server stability module 27, and when the task execution fails due to the abnormality of the first edge side server, the first edge side server is reconnected to the cloud data center in time, and the property data collected by the message queue cache is established during the reconnection, so that the data loss caused under the extreme condition is avoided.

In summary, considering that events such as system update may occur during the use of different products, and the first edge side server may also be affected by abnormal restart or network disconnection, and in the past, only methods such as manual redeployment and the like are relied on, and normal synchronization of data is disturbed.

In this embodiment, the structure of the second edge side server is the same as that of the first edge side server, and the description of the structure of the second edge side server is omitted here.

The embodiment of the application further provides a multi-source data management system, which comprises the cloud data center in any one of the embodiments, and the first edge side server and the second edge side server in any one of the embodiments.

For the interaction process of the cloud data center, the first edge side server and the second edge side server, reference may be made to the description in the foregoing embodiments, and details are not described here.

Finally, it is further noted that, herein, relational terms such as, for example, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.

In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A cloud data center, comprising:

the system comprises a task scheduling module, a task execution module and a task execution module, wherein the task scheduling module is used for acquiring an automation task corresponding to a first target product of a target object, and generating a first data reading instruction corresponding to the automation task at intervals of a first set time length when an execution mode contained in the automation task is a Robot Process Automation (RPA) mode, and the first set time length is determined according to an execution frequency contained in the automation task;

the intranet penetration module is used for sending the first data reading instruction to a first edge side server by adopting an intranet penetration technology, so that the first edge side server responds to the first data reading instruction, reading first property data from the first target product by adopting an RPA technology, and sending the first property data to the data summarization module, wherein the first edge side server is an edge side server where the first target product is located;

the data summarizing module is used for summarizing the first property data read within at least one first set time length and generating a first data writing instruction based on the summarized first property data;

the intranet penetration module is further configured to send the first data write-in instruction to a second edge side server by using the intranet penetration technology, so that the second edge side server responds to the first data write-in instruction, and writes the summarized first property data into a second target product by using the RPA technology, where the second target product is a product of all products of the target object except the first target product, and the second edge side server is an edge side server where the second target product is located.

2. The cloud data center of claim 1, wherein the first property data is incremental property data or all property data, and the incremental property data refers to newly added property data in the first target product within a corresponding first set duration;

if the first property data is the whole property data, the data summarization module is specifically configured to, when summarizing the first property data read within at least one first set time period and generating a first data write-in instruction based on the summarized first property data:

respectively determining incremental property data from the first property data read within the at least one first set time length, and taking all the determined incremental property data as the summarized first property data;

and generating the first data writing instruction based on the summarized first property data.

3. The cloud data center of claim 1, further comprising:

and the task result reporting module is used for receiving a writing result of the summarized first property data fed back by the second edge side server, wherein the writing result is used for reflecting whether the edge side server successfully writes all the summarized first property data.

4. The cloud data center of claim 1, further comprising:

the cloud calling incremental data acquisition module is used for exposing a data reading and writing interface to the first target product when an execution mode included in the automation task is an interface calling mode, so that the first target product can conveniently push the first property data to the cloud data center through the data reading and writing interface;

and the cloud calling incremental data writing module is used for writing the first property data received by the cloud data center into the second target product through the data reading and writing interface.

5. A first edge-side server, comprising:

the system comprises a trigger module and an RPA data acquisition module, wherein the trigger module is used for informing the RPA data acquisition module to acquire data after receiving a first data reading instruction corresponding to an automation task corresponding to a first target product of a target object, wherein the first data reading instruction refers to a data reading instruction generated by a cloud data center at intervals of a first set time length when an execution mode contained in the automation task is an RPA mode, and the first set time length is determined according to an execution frequency contained in the automation task corresponding to the first target product;

the RPA data acquisition module is used for reading all the property data from the first target product by adopting an RPA technology;

a data reporting module, configured to send all the property data to the cloud data center, so that the cloud data center writes first property data into a second target product through a second edge side server, where the second target product is a product of all products of the target object except the first target product, the first property data is all the property data or incremental property data in all the property data, and the incremental property data is newly added to the first target product within a corresponding first set duration;

the trigger module is further configured to notify an RPA data writing module to write data after receiving a second data writing instruction corresponding to the automation task corresponding to the second target product, where the second data writing instruction is a data writing instruction generated based on summarized second house data after the cloud data center aggregates the second house data read within at least one second set time period, the second house data is house data in the second target product, and the second set time period is determined according to an execution frequency included in the automation task corresponding to the second target product;

and the RPA data writing module is used for writing the summarized second house property data into the first target product by adopting the RPA technology.

6. The first edge-side server of claim 5, further comprising:

the data comparison and conversion module is used for determining the incremental property data from all the property data;

and the data reporting module is further used for sending the incremental property data to the cloud data center.

7. The first edge-side server of claim 5, further comprising:

and the encryption and decryption login module is used for decrypting the locally acquired encryption login information based on a decryption key after the trigger module receives the first data reading instruction and before the RPA data acquisition module reads all the property data to obtain decryption login information, and logging in the first target product based on the decryption login information, wherein the encryption login information is ciphertext of login information preset by the target object in the first target product.

8. The first edge-side server of claim 5, wherein the RPA data collection module, when using RPA technology to read all property data from the first target product, is specifically configured to:

acquiring the first target product from a preset page element position by adopting the RPA technology, and reading all the property data from the first target product;

the first edge-side server further comprises:

and the case server stability module is used for scanning front-end page elements when the preset page element position fails, sending the newly scanned page element position to the RPA data acquisition module if the page element of the first target product is scanned, so that the RPA data acquisition module can acquire the first target product from the newly scanned page element position, and sending alarm information to an administrator of the first edge side server if the page element of the first target product is not scanned after multiple scans.

9. The first edge-side server of claim 8, wherein the scenario server stability module is further configured to:

and when the first edge side server is disconnected or the automatic task fails to be executed, reconnecting the first edge side server with the cloud data center, and caching the real estate data read in the automatic task execution process in a message queue during reconnection.

10. A multi-source data management system is characterized by comprising the cloud data center of any one of claims 1 to 4, the first edge side server of any one of claims 5 to 9 and the second edge side server.

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