CN114328032A

CN114328032A - Disaster recovery switching processing method and device based on big data double activities and computer equipment

Info

Publication number: CN114328032A
Application number: CN202210008457.1A
Authority: CN
Inventors: 杨荣霞
Original assignee: China Southern Power Grid Big Data Service Co ltd
Current assignee: China Southern Power Grid Big Data Service Co ltd
Priority date: 2022-01-05
Filing date: 2022-01-05
Publication date: 2022-04-12

Abstract

The application relates to a disaster recovery switching processing method and device based on big data double activities and computer equipment. The method comprises the following steps: acquiring data processing service states of a main data center and a standby data center of a service system; when the data processing service state is determined to be a normal state, acquiring a current operation mode of a service system; and when the current operation mode is determined to be the disaster recovery mode, controlling the main data center to be closed, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started. The method can achieve the dual activity of the main data and the standby data center of the business system, and the business system can be used by switching the main data and the standby data centers because the data between the main data and the standby data centers is not different, thereby effectively preventing the risk of data loss, minimizing the shutdown risk of the business system, ensuring the stable and safe operation of the business system, and improving the business continuity of the business system under the data failure.

Description

Disaster recovery switching processing method and device based on big data double activities and computer equipment

Technical Field

The present application relates to the field of computer technologies, and in particular, to a disaster recovery switching processing method and apparatus based on big data dual activities, and a computer device.

Background

With the development of computer technology and the popularization and application of big data analysis and artificial intelligence in different fields or business systems, big data becomes a data core of each business system and bears the function of a base of each business system, so that the requirements on the business continuity and the business data safety performance of each business system are increasingly improved.

Conventionally, when a data center of a service system fails or is damaged, service data needs to be stored or restored in time to ensure service continuity. The method specifically adopts a bottom layer copying technology based on the remote storage equipment, and a storage manufacturer provides a special bottom layer technology and software to realize data mirroring of the main center storage equipment and the remote standby center storage equipment, and copy data to a remote end in a synchronous or asynchronous mode so as to realize data storage and subsequent recovery.

However, the conventional bottom layer copy technology based on the remote storage device only has a simple data copy function, and when the master and the standby centers need to be switched, due to the data difference between the master and the standby centers, the service data cannot be directly linked over the existing data difference, that is, the service cannot be directly used between the master and the standby centers, and can be put into use again after a worker further handles the problem of data loss. Therefore, the conventional data disaster recovery switching method still has the problem that data is not consistent and the service cannot be directly used, and further the service continuity of the current service system under the data failure still needs to be improved.

Disclosure of Invention

Therefore, in order to solve the above technical problems, it is necessary to provide a disaster recovery switching processing method, device and computer equipment based on big data dual activities, which can improve the service continuity of a service system under a data failure.

In a first aspect, the present application provides a disaster recovery handover processing method based on big data dual activity. The method comprises the following steps:

acquiring data processing service states of a main data center and a standby data center of a service system;

when the data processing service state is determined to be a normal state, acquiring a current operation mode of the service system;

and when the current operation mode is determined to be a disaster recovery mode, controlling the main data center to be closed, synchronously switching a service access interface to the standby data center according to domain name data, and controlling the standby data center to be started.

In one embodiment, the current operating mode further comprises a normal mode; the method further comprises the following steps:

when the current operation mode is determined to be the normal mode, controlling the standby data center to be closed, and controlling the service access interface to be connected with the main data center according to the domain name data; the service access interface is used for providing a read-write channel for the service data of the service system for the application system.

In one embodiment, the acquiring data processing service states of a main data center and a standby data center of a business system includes:

acquiring current operation state data and application configuration data of a main data center and a standby data center of the service system;

determining data processing service states of a main data center and a standby data center of the business system according to the current operation state data and the application configuration data; the data processing service state is used for determining whether the service system is currently in a master-slave active state or not.

In one embodiment, the controlling the main data center to be turned off when it is determined that the current operation mode is the disaster recovery mode, synchronously switching service access to the backup data center according to domain name data, and controlling the backup data center to be turned on includes:

when the current operation mode is determined to be a disaster recovery mode, controlling the main data center to be closed, and configuring service access data according to domain name data;

and cutting off the service connection between the main data center and the application system according to the service access data, switching a service access interface to the standby data center, and controlling the standby data center to start.

In one embodiment, the method further comprises:

when the data processing service state is determined to be an abnormal state, triggering an abnormal repairing instruction;

responding to the abnormal repairing instruction, and determining an abnormal data position corresponding to an abnormal state;

and performing abnormal restoration based on the abnormal data position until the data processing service state is a normal state.

In one embodiment, the current operating state data includes component state data, upstream and downstream dependency state data, and component difference data of the primary data center and the backup data center; the application configuration data comprises user authority configuration data of the main data center and the standby data center and service system application configuration data.

In a second aspect, the present application further provides a disaster recovery switching processing device based on big data dual activities. The device comprises:

the data processing service state acquisition module is used for acquiring data processing service states of a main data center and a standby data center of the service system;

the current operation mode acquisition module is used for acquiring the current operation mode of the service system when the data processing service state is determined to be a normal state;

and the switching module is used for controlling the main data center to be closed when the current operation mode is determined to be the disaster recovery mode, synchronously switching a service access interface to the standby data center according to domain name data, and controlling the standby data center to be started.

In one embodiment, the disaster recovery switching processing apparatus based on big data double-live further includes a connection control module, configured to:

In one embodiment, the data processing service status obtaining module is further configured to:

acquiring current operation state data and application configuration data of a main data center and a standby data center of the service system; determining data processing service states of a main data center and a standby data center of the business system according to the current operation state data and the application configuration data; the data processing service state is used for determining whether the service system is currently in a master-slave active state or not.

In one embodiment, the switching module is further configured to:

when the current operation mode is determined to be a disaster recovery mode, controlling the main data center to be closed, and configuring service access data according to domain name data; and cutting off the service connection between the main data center and the application system according to the service access data, switching a service access interface to the standby data center, and controlling the standby data center to start.

In one embodiment, the disaster recovery switching processing device based on big data double-live further includes:

the abnormal repair instruction triggering module is used for triggering an abnormal repair instruction when the data processing service state is determined to be an abnormal state;

the abnormal data position determining module is used for responding to the abnormal repairing instruction and determining an abnormal data position corresponding to an abnormal state;

and the abnormal repairing module is used for repairing the abnormality based on the abnormal data position until the data processing service state is a normal state.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

In the disaster recovery switching processing method, the disaster recovery switching processing device and the computer equipment based on big data double activities, the current operation mode of the business system is obtained by obtaining the data processing service states of the main data center and the standby data center of the business system and when the data processing service state is determined to be a normal state. And further controlling the main data center to be closed when the current operation mode is determined to be the disaster recovery mode, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started. The main data and standby data centers of the business system are normally used as the basis for starting the standby disaster mode, namely, the main data and standby data centers of the business system are dual-active.

Drawings

Fig. 1 is an application environment diagram of a disaster recovery handover processing method based on big data live in an embodiment;

fig. 2 is a schematic flow chart of a disaster recovery switching processing method based on big data double-active in an embodiment;

fig. 3 is a schematic flow chart of a disaster recovery handover processing method based on big data double-active in another embodiment;

fig. 4 is a schematic flow chart illustrating a disaster recovery handover processing method based on big data double liveness in yet another embodiment;

fig. 5 is a schematic flow chart illustrating a disaster recovery handover processing method based on big data double-active in yet another embodiment;

fig. 6 is a block diagram of a disaster recovery switching processing device based on big data double-live in an embodiment;

fig. 7 is a block diagram of a disaster recovery switching processing device based on big data double-live in another embodiment;

FIG. 8 is an architecture diagram of a big data double-active based disaster recovery switching processing system in one embodiment;

FIG. 9 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The disaster recovery switching processing method based on big data double activity provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104, or may be located on the cloud or other network server. The server 104 obtains the data processing service states of the main data center and the standby data center of the service system, and judges whether the data processing server states are normal. The service system may be installed in the terminal 102 or integrated in the server 104 itself, the service system may store the service data to the primary data center and the backup data center synchronously, and the application system may also read and write the service data to the primary data center or the backup data center through the service access interface. And when the data processing service state is determined to be a normal state, acquiring the current operation mode of the service system, and further judging whether the current operation mode is a disaster recovery mode. And when the current operation mode is determined to be the disaster recovery mode, controlling the main data center to be closed, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

In an embodiment, as shown in fig. 2, a disaster recovery handover processing method based on big data double-live is provided, which is described by taking the application of the method to the server in fig. 1 as an example, and includes the following steps:

step S202, acquiring data processing service states of a main data center and a standby data center of the business system.

Specifically, the data processing service states of the main data center and the standby data center of the service system are determined by acquiring the current operation state data and the application configuration data of the main data center and the standby data center of the service system and according to the current operation state data and the application configuration data.

Further, the current operating state data includes component state data, upstream and downstream dependency state data, and component difference data of the primary data center and the standby data center, and the application configuration data includes user authority configuration data of the primary data center and the standby data center and service system application configuration data. Specifically, the data processing service states of the main data center and the standby data center of the service system need to be determined according to component state data, upstream and downstream dependency state data, component difference data of the main data center and the standby data center, user authority configuration data and service system application configuration data.

The data processing service state is used for determining whether the business system is currently in a main active/standby active state. Specifically, when the data processing service state is a normal state, it may be determined that the service system is in a primary and secondary active state, and based on the disaster recovery deployment mode of the primary and secondary centers, the primary and secondary data centers perform data incremental warehousing simultaneously, the warehoused data volumes of the primary and secondary data centers are basically consistent, and the states belong to the primary and secondary active states.

Similarly, when the data processing service state is an abnormal state, the main data center and the standby data center of the service system do not meet the active-standby dual-active state at present, and after the abnormal data needs to be further repaired, the data processing service states of the main data center and the standby data center of the service system are obtained again, and whether the data processing service state is a normal state or not is judged again.

And step S204, when the data processing service state is determined to be a normal state, acquiring the current operation mode of the service system.

Specifically, when it is determined that the data processing service state is a normal state, the primary data center and the standby data center of the business system are in a primary-standby dual-active state, and the current operation mode of the business system is further acquired on the basis that the primary-standby dual-active state is met.

The current operation mode of the service system comprises a normal mode and a disaster recovery mode, under the normal mode, the service system simultaneously performs data increment warehousing to the main data center and the standby data center, but when the configuration is performed through the domain name data of the domain name system, a service access interface needs to be connected with the main data center, so that the read-write processing of the service data between the application system and the main data center is realized.

Similarly, in the disaster recovery mode, the service system performs data incremental warehousing to the main data center and the standby data center simultaneously, but when the configuration is performed through the domain name data of the domain name system, the service access interface needs to be connected with the standby data center, so as to realize the read-write processing of the service data between the application system and the standby data center.

Step S206, when the current operation mode is determined to be the disaster recovery mode, the main data center is controlled to be closed, the service access interface is synchronously switched to the standby data center according to the domain name data, and the standby data center is controlled to be started.

Specifically, when the current operation mode is determined to be the disaster recovery mode, the main data center is controlled to be closed, service access data are configured according to the domain name data, further, according to the service access data, service connection between the main data center and the application system is cut off, a service access interface is switched to the standby data center, and the standby data center is controlled to be started.

Further, when the current operation mode is determined to be the disaster recovery mode, it indicates that the current main data center has a fault or needs to be maintained, and the service in the main data and the service between the application systems need to be connected, and the service data read-write processing between the application systems and the main data center cannot be executed. The service access interface is switched to the standby data center through the service access data configured by the domain name data, and the standby data center is controlled to be started, so that second-level switching between the main data center and the standby data center is realized, the risk of data loss is effectively prevented, the risk of shutdown of a service system is minimized, and stable and safe operation of the service is guaranteed.

In the disaster recovery switching processing method based on big data double activities, the current operation mode of the business system is obtained by obtaining the data processing service states of the main data center and the standby data center of the business system and when the data processing service state is determined to be a normal state. And further controlling the main data center to be closed when the current operation mode is determined to be the disaster recovery mode, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started. The main data and standby data centers of the business system are normally used as the basis for starting the standby disaster mode, namely, the main data and standby data centers of the business system are dual-active.

In one embodiment, as shown in fig. 3, a disaster recovery handover processing method based on big data double liveness is provided, where the method includes:

step S302, acquiring data processing service states of a main data center and a standby data center of the business system.

Step S304, when the data processing service state is determined to be a normal state, the current operation mode of the service system is obtained.

And step S306, when the current operation mode is determined to be the normal mode, controlling the standby data center to be closed, and controlling the service access interface to be connected with the main data center according to the domain name data, wherein the service access interface is used for providing a read-write channel for the service data of the service system for the application system.

Specifically, when the current operation mode is determined to be the normal mode, the standby data center is controlled to be closed, service access data are configured according to the domain name data, and then the service access interface is controlled to be connected with the main data center according to the service access data. The service access interface is used for providing a read-write channel for the service data of the service system for the application system, when the service access interface is connected with the main data center, the application system performs data read-write on the service data in the main data center through the service access interface, and conversely, when the service access interface is connected with the standby data center, the application system performs data read-write on the service data in the standby data center through the service access interface.

Step S308, when the current operation mode is determined to be the disaster recovery mode, the main data center is controlled to be closed, the service access interface is synchronously switched to the standby data center according to the domain name data, and the standby data center is controlled to be started.

Further, when the current operation mode is determined to be the disaster recovery mode, it indicates that the current main data center has a fault or needs to be maintained, and the service in the main data and the service between the application systems need to be connected, and the service data read-write processing between the application systems and the main data center cannot be executed. And switching the service access interface to the standby data center through the service access data configured by the domain name data, and controlling the standby data center to start.

In the disaster recovery switching processing method based on big data double activities, the data processing service states of the main data center and the standby data center of the service system are obtained, and when the data processing service states are determined to be normal states, the current operation mode of the service system is obtained. And when the current operation mode is determined to be the normal mode, controlling the standby data center to be closed, and controlling the service access interface to be connected with the main data center according to the domain name data. And when the current operation mode is determined to be the disaster recovery mode, the main data center is controlled to be closed, the service access interface is synchronously switched to the standby data center according to the domain name data, and the standby data center is controlled to be started. The second-level switching between the main data center and the standby data center is realized, the risk of data loss is effectively prevented, the risk of shutdown of a service system is minimized, and the stable and safe operation of the service is guaranteed.

In an embodiment, as shown in fig. 4, a disaster recovery handover processing method based on big data dual activity is provided, where the method specifically includes:

step S402, acquiring data processing service states of a main data center and a standby data center of the business system.

Step S404, when the data processing service state is determined to be an abnormal state, an abnormal repair instruction is triggered.

Specifically, the data processing service states include a normal state and an abnormal state, wherein when the data processing service state is the abnormal state, the main data center and the standby data center of the service system do not meet the active-standby dual-active state at present, and after the abnormal data needs to be further repaired, the data processing service states of the main data center and the standby data center of the service system are obtained again, and whether the data processing service state is the normal state or not is judged again.

Further, when the data processing service state is determined to be an abnormal state, an abnormal repair instruction is triggered for further repairing the abnormal data until the data processing service state acquired again after repair is a normal state.

Step S406, determining an abnormal data position corresponding to the abnormal state in response to the abnormal repairing instruction.

Specifically, a triggered exception recovery instruction is responded, and a specific position of exception data corresponding to an exception state is acquired. The abnormal data types of the abnormal state may include component state abnormal data, upstream and downstream dependency state abnormal data, and component difference abnormal data of the main data center and the standby data center, and may further include user authority configuration abnormal data of the main data center and the standby data center, and service system application configuration abnormal data.

Further, after the abnormal data type of the abnormal state is determined, the specific position of the abnormal data of different abnormal data types can be further determined.

And step S408, performing exception repair based on the exception data position until the data processing service state is a normal state.

Specifically, the exception is repaired based on the location of the exception data, for example, the exception is repaired for the component state exception data, the upstream and downstream dependency state exception data, the component difference exception data, the user authority configuration exception data, the business system application configuration exception data, and the like of the main data center and the standby data center, so as to achieve the effect that the data processing service state is the normal state.

Further, the data center determining method can determine whether abnormal data occurs in the main data center or the standby data center, and further determine the type of the abnormal data after determining the data center with the abnormal data. For example, when it is determined that abnormal data occurs in the main data center and the type of the abnormal data is determined to be component state abnormal data, the states of different components of the main data center need to be further analyzed to determine a specific component which has a fault, a fault processing scheme corresponding to the faulty component is matched, a corresponding fault processing scheme is executed, and abnormal repair is completed.

And determining the specific fault position according to other abnormal data types of the main data center, and further matching the fault processing scheme until the repair is completed. Similarly, for different abnormal data types of the backup data center, similar abnormal repair processing flows can be adopted until the repair is completed.

Step S410, when the data processing service state is determined to be a normal state, acquiring the current operation mode of the service system.

Step S412, when the current operation mode is determined to be the normal mode, the standby data center is controlled to be closed, and the service access interface is controlled to be connected with the main data center according to the domain name data; the service access interface is used for providing a read-write channel for the service data of the service system for the application system.

Step S414, when it is determined that the current operation mode is the disaster recovery mode, controlling the main data center to close, synchronously switching the service access interface to the backup data center according to the domain name data, and controlling the backup data center to start.

In the disaster recovery mode, the service system performs data incremental warehousing to the main data center and the standby data center at the same time, but when the domain name data of the domain name system is configured, the service access interface needs to be connected with the standby data center, so that the service data reading and writing processing between the application system and the standby data center is realized.

And when the current operation mode is determined to be a disaster recovery mode, controlling the main data center to be closed, configuring service access data according to the domain name data, further cutting off service connection between the main data center and the application system according to the service access data, switching the service access interface to the standby data center, and controlling the standby data center to be started.

In the disaster recovery switching processing method based on big data double activities, the data processing service states of the main data center and the standby data center of the service system are obtained, when the data processing service states are determined to be abnormal states, an abnormal repair instruction is triggered, the abnormal repair instruction is responded, and the abnormal data position corresponding to the abnormal states is determined. And then carrying out abnormal repair based on the abnormal data position until the data processing service state is a normal state, and acquiring the current operation mode of the service system when the data processing service state is determined to be the normal state. And when the current operation mode is determined to be the disaster recovery mode, the main data center is controlled to be closed, the service access interface is synchronously switched to the standby data center according to the domain name data, and the standby data center is controlled to be started. The main data and standby data centers of the business system are normally used as the basis for starting the standby disaster mode, namely, the main data and standby data centers of the business system are dual-active.

In an embodiment, as shown in fig. 5, a disaster recovery handover processing method based on big data dual activity is provided, where the method specifically includes:

step S501, current operation state data and application configuration data of a main data center and a standby data center of a service system are obtained.

Step S502, determining the data processing service states of the main data center and the standby data center of the business system according to the current operation state data and the application configuration data, wherein the data processing service states are used for determining whether the business system is in a main active/standby active state or not currently.

In step S503, it is determined whether the data processing service state is normal.

Step S504, when the data processing service state is determined to be an abnormal state, an abnormal repair instruction is triggered.

Step S505, responding to the abnormal recovery instruction, and determining an abnormal data location corresponding to the abnormal state.

Step S506, performing exception repair based on the exception data position until the data processing service state is a normal state.

Step S507, when it is determined that the data processing service state is the normal state, acquiring a current operation mode of the service system.

Step S508, determine whether the current operation mode is the normal mode.

Step S509, when it is determined that the current operation mode is the normal mode, controlling the standby data center to be closed, and controlling the service access interface to be connected with the primary data center according to the domain name data.

Step S510, when it is determined that the current operation mode is the disaster recovery mode, controlling the main data center to close, and configuring service access data according to the domain name data.

And step S511, according to the service access data, cutting off the service connection between the main data center and the application system, switching the service access interface to the standby data center, and controlling the standby data center to start.

It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the present application further provides a disaster recovery switching processing device based on big data double-active for implementing the above disaster recovery switching processing method based on big data double-active. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the above method, so that specific limitations in one or more embodiments of the disaster recovery switching processing apparatus based on big data double activity provided below may refer to the limitations in the above disaster recovery switching processing method based on big data double activity, and are not described herein again.

In one embodiment, as shown in fig. 6, a disaster recovery switching processing apparatus based on big data double liveness is provided, including: a data processing service state obtaining module 602, a current operation mode obtaining module 604, and a switching module 606, wherein:

a data processing service state obtaining module 602, configured to obtain data processing service states of a primary data center and a backup data center of a business system.

A current operation mode obtaining module 604, configured to obtain a current operation mode of the service system when it is determined that the data processing service state is a normal state.

And a switching module 606, configured to control the main data center to be closed when it is determined that the current operation mode is the disaster recovery mode, and synchronously switch the service access interface to the backup data center according to the domain name data, and control the backup data center to be started.

In the disaster recovery switching processing device based on big data double activities, the current operation mode of the business system is obtained by obtaining the data processing service states of the main data center and the standby data center of the business system and when the data processing service state is determined to be a normal state. And further controlling the main data center to be closed when the current operation mode is determined to be the disaster recovery mode, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started. The main data and standby data centers of the business system are normally used as the basis for starting the standby disaster mode, namely, the main data and standby data centers of the business system are dual-active.

In an embodiment, as shown in fig. 7, a disaster recovery switching processing apparatus based on big data double-live is provided, and the apparatus specifically includes a data processing service state obtaining module 702, an exception repair instruction triggering module 704, an exception data position determining module 706, an exception repair module 708, a current operation mode obtaining module 710, a connection control module 712, and a switching module 714, where:

a data processing service state obtaining module 702, configured to obtain data processing service states of a primary data center and a standby data center of a business system.

And an exception recovery instruction triggering module 704, configured to trigger an exception recovery instruction when it is determined that the data processing service state is an exception state.

And an abnormal data position determining module 706, configured to determine, in response to the abnormal repairing instruction, an abnormal data position corresponding to the abnormal state.

And an exception recovery module 708, configured to perform exception recovery based on the location of the abnormal data until the data processing service state is a normal state.

The current operation mode obtaining module 710 is configured to obtain a current operation mode of the service system when it is determined that the data processing service state is a normal state.

And a connection control module 712, configured to control the standby data center to be closed when it is determined that the current operation mode is the normal mode, and control the service access interface to be connected with the primary data center according to the domain name data, where the service access interface is used to provide a read-write channel for the application system to the service data of the service system.

And a switching module 714, configured to control the main data center to be turned off when it is determined that the current operation mode is the disaster recovery mode, and synchronously switch the service access interface to the backup data center according to the domain name data, and control the backup data center to be turned on.

The disaster recovery switching processing device based on big data dual activity realizes that the data processing service state of the main data and the standby data center of the business system is normally used as the basis for starting the standby disaster mode, namely, the main data and the standby data center of the business system are dual-active, and the business system can be switched and used due to the fact that data between the main data and the standby data center are not different, so that the risk of data loss can be effectively prevented, the shutdown risk of the business system is minimized, the stable and safe operation of the business system is guaranteed, and the business continuity of the business system under the data failure is improved.

acquiring current operation state data and application configuration data of a main data center and a standby data center of a service system; determining data processing service states of a main data center and a standby data center of a service system according to the current operation state data and the application configuration data; the data processing service state is used for determining whether the business system is currently in a main active/standby active state.

In one embodiment, the switching module is further configured to:

when the current operation mode is determined to be a disaster recovery mode, controlling the main data center to be closed, and configuring service access data according to domain name data; and according to the service access data, cutting off the service connection between the main data center and the application system, switching the service access interface to the standby data center, and controlling the standby data center to start.

All or part of each module in the disaster recovery switching processing device based on big data double activity can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In an embodiment, as shown in fig. 8, a disaster recovery switching processing system based on big data double-active is provided, and as can be seen from fig. 8, the disaster recovery switching processing system based on big data double-active belongs to a double-active architecture, which specifically includes: business system 802, primary data center 804, backup data center 806, DNS (domain name system) 808, and application system 810, wherein:

the service system 802 performs incremental data storage on the primary data center 804 and the standby data center 806 simultaneously, that is, service data is synchronously written into the primary data center 804 and the standby data center 806, the storage data amount of the primary data center 804 and the standby data center 806 is basically consistent, and the status of the storage data amounts belongs to both active and standby.

The application system 810 performs routing configuration through a DNS (domain name system) 808, configures service access data, and determines an accessible data center according to the service access data.

The current operation mode of the service system includes a normal mode and a backup mode, in the normal mode, after the application system 810 performs routing configuration through a Domain Name System (DNS) 808, it is determined that only the primary data center 804 can be accessed, and at this time, the backup data center 806 is not responsible for reading and writing service data of the application system 810, and only the backup data center 806 performs disaster recovery switching to allow the application system 810 to read and write the service data.

Similarly, in the disaster recovery mode, after the application system 810 performs routing configuration through a DNS (domain name system) 808, it is determined that only the backup data center 806 can be accessed, and at this time, the main data center 804 is not responsible for reading and writing the service data of the application system 810.

Further, as can be seen from fig. 8 (a), before the disaster recovery switching is performed, that is, when the current service system 802 is in the normal mode, the service system 802 performs data incremental warehousing on the primary data center 804 and the standby data center 806 at the same time, the warehoused data volumes of the primary data center 804 and the standby data center 806 are substantially consistent, and the statuses of the warehoused data volumes are both active and standby. After the application system 810 performs routing configuration through a Domain Name System (DNS) 808, it is determined that only the primary data center 804 can be accessed, and at this time, the backup data center 806 is not responsible for reading and writing the service data of the application system 810, and only the backup data center 806 that performs disaster recovery switching allows the application system 810 to read and write the service data.

Similarly, as can be seen from fig. 8 (b), after the disaster recovery switching is performed, that is, when the current service system 802 is in the disaster recovery mode, the service system 802 still performs incremental warehousing on the primary data center 804 and the backup data center 806 at the same time, the warehoused data volumes of the primary data center 804 and the backup data center 806 are substantially the same, and the statuses of the warehoused data volumes are both active and standby. After the application system 810 performs routing configuration through a DNS (domain name system) 808, it is determined that only the standby data center 806 can be accessed, and at this time, the primary data center 804 is not responsible for reading and writing the service data of the application system 810.

The disaster recovery switching processing system based on big data dual activity realizes that the data processing service state of the main data and the standby data center of the business system is normally used as the basis for starting the standby disaster mode, namely, the main data and the standby data center of the business system are dual-active, and the business system can be switched and used due to the fact that data between the main data and the standby data center are not different, so that the risk of data loss can be effectively prevented, the shutdown risk of the business system is minimized, the stable and safe operation of the business system is guaranteed, and the business continuity of the business system under the data failure is improved.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing the data processing service states of the main data center and the standby data center of the service system, the current operation mode of the service system and domain name data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize a disaster recovery switching processing method based on big data double activities.

Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:

when the data processing service state is determined to be a normal state, acquiring a current operation mode of a service system;

and when the current operation mode is determined to be the disaster recovery mode, controlling the main data center to be closed, synchronously switching the service access interface to the standby data center according to the domain name data, and controlling the standby data center to be started.

In one embodiment, the processor, when executing the computer program, further performs the steps of:

when the data processing service state is determined to be an abnormal state, triggering an abnormal repairing instruction; responding to the abnormal repairing instruction, and determining an abnormal data position corresponding to the abnormal state; and performing abnormal restoration based on the abnormal data position until the data processing service state is a normal state.

the current running state data comprises component state data, upstream and downstream dependency state data and component difference data of the main data center and the standby data center; the application configuration data comprises user authority configuration data of the main data center and the standby data center and service system application configuration data.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by the processor further performs the steps of:

In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A disaster recovery switching processing method based on big data double activities is characterized by comprising the following steps:

2. The method of claim 1, wherein the current operating mode further comprises a normal mode; the method further comprises the following steps:

3. The method of claim 1, wherein the obtaining the data processing service status of the primary data center and the backup data center of the business system comprises:

4. The method according to any one of claims 1 to 3, wherein the controlling the main data center to be turned off when the current operation mode is determined to be a disaster recovery mode, synchronously switching service access to the backup data center according to domain name data, and controlling the backup data center to be turned on includes:

5. A method according to any one of claims 1 to 3, characterized in that the method further comprises:

6. The method of claim 3, wherein the current operating state data includes component state data, upstream and downstream dependency state data, and component difference data for the primary and backup data centers; the application configuration data comprises user authority configuration data of the main data center and the standby data center and service system application configuration data.

7. A disaster recovery switching processing device based on big data double activities is characterized in that the device comprises:

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.