阅读说明：本技术 工业数据库集群系统及其数据访问方法 (Industrial database cluster system and data access method thereof ) 是由 严翎通 方洪祥 王洪原 汪方方 于 2021-06-18 设计创作，主要内容包括：本公开实施例涉及一种工业数据库集群系统及其数据访问方法,其方法包括：S10、通过选主确定每个设备对象对应的节点数据库,建立设备对象和节点数据库的映射关系；其中,映射关系中每个设备对象对应的节点数据库是基于该设备对象的设备实例上线时间、设备实例延迟时间和设备实例所在集群节点健康值确定的；S20、集群系统获取用户端发送的访问请求；S30、集群系统基于目标设备对象,通过查找设备对象和节点数据库的映射关系,确定要访问的目标节点数据库；S40、集群系统将访问请求发送至目标节点数据库,访问目标设备对象的设备实例数据。通过本申请的访问方法,保证了要访问数据的可用性和数据的一致性。(The embodiment of the disclosure relates to an industrial database cluster system and a data access method thereof, wherein the method comprises the following steps: s10, determining a node database corresponding to each equipment object through a selection master, and establishing a mapping relation between the equipment objects and the node database; the node database corresponding to each equipment object in the mapping relation is determined based on the equipment instance online time, the equipment instance delay time and the cluster node health value of the equipment instance; s20, the cluster system acquires the access request sent by the user side; s30, the cluster system determines a target node database to be accessed by searching the mapping relation between the device object and the node database based on the target device object; and S40, the cluster system sends the access request to the target node database to access the device instance data of the target device object. By the access method, the availability of the data to be accessed and the consistency of the data are ensured.)

1. A data access method of an industrial database cluster system is characterized in that the database cluster system stores operation data acquired from all industrial field devices in real time, wherein the operation data of each industrial field device comprises a plurality of device instance data respectively stored on different cluster nodes; the method comprises the following steps:

s10, determining a node database corresponding to each equipment object through a selection master, and establishing a mapping relation between the equipment objects and the node database; the node database corresponding to each equipment object in the mapping relation is determined based on the equipment instance on-line time, the equipment instance delay time and the cluster node health value of the equipment instance;

s20, the cluster system acquires an access request sent by a user side, wherein the access request is used for accessing equipment instance data of a target equipment object;

s30, the cluster system determines a target node database to be accessed by searching the mapping relation between the device object and the node database based on the target device object;

s40, the cluster system sends the access request to the target node database to access the device instance data of the target device object.

2. The method of claim 1, wherein determining the node database corresponding to each device object by election comprises:

aiming at one equipment object, determining all equipment instances corresponding to the equipment object;

calculating the weight of each equipment instance, and synchronizing the weight of each equipment instance among all nodes of the cluster, wherein the weight is determined based on the on-line time of the equipment instance, the delay time of the equipment instance and the health value of the cluster node where the equipment instance is located;

and selecting the cluster node database where the equipment instance with the largest weight is located as the node database of the equipment object.

3. The method of claim 2, wherein the weights are calculated by the formula:

w＝t_on×70％+t_delay×30％+h×10％

where w represents the weight of the device instance, t_onRepresents the time of line on the device instance, t_delayThe delay time of the device instance is shown, and h represents the health value of the cluster node where the device instance is located.

4. The method of claim 2, wherein determining the node database for each device object further comprises:

and when the weight values of the equipment instances are the same, selecting the cluster node database with the minimum serial number of the node as the corresponding node database.

5. The method of claim 1, wherein the industrial database cluster system employs a database engine-based cluster architecture or a database gateway-based cluster architecture.

6. An industrial database cluster system, characterized in that it processes access requests sent by user terminals by means of the method of any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when being executed by a processor, carries out the steps of the data access method of an industrial database cluster system according to any one of the preceding claims 1 to 5.

8. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the data access method of an industrial database cluster system as claimed in any one of the preceding claims 1 to 5.

Technical Field

The application belongs to the technical field of computers, and particularly relates to an industrial database cluster system and a data access method thereof.

Background

In the practical application of large industrial real-time database, a large amount of data of collecting equipment needs to be accessed, and the providers of the data are usually some hardware devices, instruments and meters and the like scattered on an industrial field. In order to ensure the reliability and stability of device data, the same device generally needs to be accessed into different cluster nodes, and the purpose of doing so is to ensure that a single point of failure in a database cluster does not result in no data availability of a cluster data platform. But this results in systems that are typically fault tolerant by maintaining multiple copies and maintaining consistency of the multiple copies.

To maintain consistency of multiple copies, a Raft distributed consistency protocol is typically employed. In the method for selecting the master consistently by the Raft, each instance in the system confirms that the master instance is on line through a heartbeat packet, and when the heartbeat is overtime, each instance considers that the master instance is disconnected, and the master selection is started again. Each instance firstly elects itself as a main instance, broadcasts a vote to other instances in the cluster system, requests other instances of the system to cast a vote for itself, and if the acceptance of more than half of the instances is received, the main instance is elected. If more than half of the instances are not approved within the timeout, the current instance randomly waits for a period of time and then initiates a new round of election again until some instances are selected as the primary.

The method has the advantages that the main examples must be selected when data access is conducted on the cluster system each time due to the adoption of the Raft main selection algorithm, the Raft main selection algorithm requires that the number of the examples in the cluster is odd, double-example redundancy is a very common deployment mode in the field of large industrial real-time databases, and the main examples cannot be selected due to the adoption of the Raft main selection algorithm. If the main instance cannot be selected within a certain time, the cluster can continuously select the main instance until the main instance is selected, and finally, the user cannot access the system data in the period.

Disclosure of Invention

Technical problem to be solved

In view of the above disadvantages and shortcomings of the prior art, the present application provides an industrial database cluster system and a data access method thereof.

(II) technical scheme

In order to achieve the purpose, the technical scheme is as follows:

in a first aspect, the present application provides a data access method for an industrial database cluster system, where the database cluster system stores operation data acquired in real time from each industrial field device, and the operation data of each industrial field device includes multiple device instance data stored on different cluster nodes respectively; the method comprises the following steps:

s10, determining a node database corresponding to each equipment object through a selection master, and establishing a mapping relation between the equipment objects and the node database; the node database corresponding to each equipment object in the mapping relation is determined based on the equipment instance on-line time, the equipment instance delay time and the cluster node health value of the equipment instance;

s20, the cluster system acquires an access request sent by a user side, wherein the access request is used for accessing equipment instance data of a target equipment object;

s30, the cluster system determines a target node database to be accessed by searching the mapping relation between the device object and the node database based on the target device object;

s40, the cluster system sends the access request to the target node database to access the device instance data of the target device object.

Optionally, determining a node database corresponding to each device object by election includes:

aiming at one equipment object, determining all equipment instances corresponding to the equipment object;

calculating the weight of each equipment instance, and synchronizing the weight of each equipment instance among all nodes of the cluster, wherein the weight is determined based on the on-line time of the equipment instance, the delay time of the equipment instance and the health value of the cluster node where the equipment instance is located;

and selecting the cluster node database where the equipment instance with the largest weight is located as the node database of the equipment object.

Optionally, the calculation formula of the weight is:

w＝t_on×70％+t_delay×30％+h×10％

where w represents the weight of the device instance, t_onRepresents the time of line on the device instance, t_del_ayThe delay time of the device instance is shown, and h represents the health value of the cluster node where the device instance is located.

Optionally, determining a node database corresponding to each device object further includes:

and when the weight values of the equipment instances are the same, selecting the cluster node database with the minimum serial number of the node as the corresponding node database.

Optionally, the industrial database cluster system employs a database engine-based cluster architecture or a database gateway-based cluster architecture.

In a second aspect, the present application provides an industrial database cluster system, which processes an access request sent by a user terminal through the method according to any one of the above first aspects.

In a third aspect, the present application provides an electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the data access method of an industrial database cluster system as described in any of the above first aspects.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for data access of an industrial database cluster system as defined in any one of the first aspect above.

(III) advantageous effects

The beneficial effect of this application is: according to the access method, the availability of the data in the cluster system is guaranteed, and the data subscribed by different clients in the cluster are data from the same equipment instance, so that the consistency of the data in the cluster system is guaranteed.

Drawings

The application is described with the aid of the following figures:

FIG. 1 is a schematic flow chart illustrating a data access method of an industrial database cluster system according to an embodiment of the present application;

FIG. 2 is a schematic diagram of an industrial database cluster system and an industrial site according to another embodiment of the present disclosure;

FIG. 3 is a schematic diagram of an industrial database cluster system election trigger condition according to another embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device according to another embodiment of the present application.

Detailed Description

For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings. It is to be understood that the following specific examples are illustrative of the invention only and are not to be construed as limiting the invention. In addition, it should be noted that, in the case of no conflict, the embodiments and features in the embodiments in the present application may be combined with each other; for convenience of description, only portions related to the invention are shown in the drawings.

In view of the disadvantages of the prior art, the present application provides a data access method for an industrial database cluster system, and the present invention is described in detail by embodiments below.

Fig. 1 is a schematic flow chart illustrating a data access method of an industrial database cluster system storing operation data acquired in real time from each industrial field device according to an embodiment of the present disclosure, where the operation data of each industrial field device includes a plurality of device instance data stored on different cluster nodes, respectively; as shown in fig. 1, the method includes:

s10, determining a node database corresponding to each equipment object through a selection master, and establishing a mapping relation between the equipment objects and the node database; the node database corresponding to each equipment object in the mapping relation is determined based on the equipment instance online time, the equipment instance delay time and the cluster node health value of the equipment instance;

s20, the cluster system acquires an access request sent by the user side, and the access request is used for accessing equipment instance data of the target equipment object;

s30, the cluster system determines a target node database to be accessed by searching the mapping relation between the device object and the node database based on the target device object;

and S40, the cluster system sends the access request to the target node database to access the device instance data of the target device object.

The data access method of the industrial database cluster system can be applied to the field of large industrial real-time databases, and by selecting the device instance data with highest reliability and availability from the multiple device instances for access, the problems of data availability and consistency in the cluster are solved, and the data subscribed by different clients in the cluster are ensured to be the data from the same device instance.

Before describing each step, the industrial field data collection related to the present embodiment is described.

The industrial data acquisition system acquires operation data from each industrial field device in real time, the acquirable data comprises data of DCS/PLC/SCADA/RFID/bar code/two-dimensional code, and the acquired data is stored in a database, wherein the database is various real-time databases.

In this embodiment, the device instance represents a device actually accessed in a cluster node, and one device object includes a plurality of different device instances on different nodes of the cluster. Furthermore, the device instances on a cluster node are different from each other. The device instance data on the cluster nodes represents the operation data of the industrial field devices which are acquired through the acquisition ports and stored on the preset cluster nodes.

It should be noted here that, in order to improve reliability and availability of device operation data acquisition, each industrial field device is connected to at least two cluster nodes, so that acquired data are stored in different database cluster nodes. This introduces a problem of how to ensure the consistency of the data in the cluster, i.e. the data of device 1 on the client subscription node 1 is consistent with the data of device 1 on the client subscription node 2. For this reason, the present embodiment provides a data access method for an industrial database cluster system, and the following is a description of each step of the method of the present embodiment.

In this embodiment, determining the node database corresponding to each device object by the owner may include:

s011, aiming at one equipment object, determining all equipment instances corresponding to the equipment object;

s012, calculating the weight of each equipment instance, and synchronizing the weight of each equipment instance among all the nodes of the cluster, wherein the weight is determined based on the on-line time of the equipment instance, the delay time of the equipment instance and the health value of the cluster node where the equipment instance is located;

the weight is calculated by the formula:

w＝t_on×70％+t_delay×30％+h×10％

where w represents the weight of the device instance, t_onRepresents the time of line on the device instance, t_delayRepresenting the delay time of the equipment instance, and h represents the health value of the cluster node where the equipment instance is located;

and S013, selecting the cluster node database where the equipment instance with the largest weight is located as the node database of the equipment object.

It should be noted that the time when the device instance is online refers to the time when the driver is connected to the device; the device instance delay is realized by a heartbeat packet, namely, the device sends a heartbeat packet to the device, the device replies a response, and the difference between the reply time and the sending time is the device delay time; the health value of the node refers to the value results of comprehensive evaluations such as the current cpu utilization rate, the disk writing io, the memory utilization rate, the disk space size and the like.

In this embodiment, determining the node database corresponding to each device object further includes:

and when the weight values of the equipment instances are the same, selecting the cluster node database with the minimum serial number of the node as the corresponding node database.

For step S10, the on-line time of the device instance, the delay time of the device instance, and the health value of the cluster node where the device instance is located for calculating the weight may be statistics of various indexes over a period of time. Accordingly, the cluster system may also update the mapping relationship periodically according to the statistical result each time.

In step S20, the access request sent by the user end may be that the client end subscribes real-time data through the real-time data subscription and distribution system, and the real-time data subscription and distribution system sends the access request to the cluster system.

In step S30, the cluster system determines a target node database to be accessed by searching a mapping relationship between a device object and a node database, which is established in advance, based on the target device object.

In step S40, the cluster system sends the access request to the target node database, and the real-time data subscription and distribution system accesses the device instance data of the target device object and pushes the device instance data to the user side.

It should be noted that, in the embodiment, the industrial database cluster system may adopt a cluster architecture based on a database engine or a cluster architecture based on a database gateway, which is not limited in this embodiment.

The embodiment provides a data access method for an industrial database cluster system, which solves the problems of data availability and consistency in a cluster by a multi-device instance master selection mode, and ensures that data subscribed by different clients in the cluster are data from the same device instance.

Example two

Fig. 2 is a schematic diagram illustrating a relationship between an industrial database cluster system and an industrial field in another embodiment of the present application, as shown in fig. 2, in this embodiment, data of a device 1, a device 2, and a device 3 in the industrial field is collected and stored in a real-time database cluster, the real-time database cluster includes 3 nodes, and dual-instance collection is performed on the industrial field devices, that is, the device 1 collects on the node 1 and the node 2, the device 2 collects on the node 1 and the node 3, and the device 3 collects on the node 2 and the node 3. Finally, the operation data of each industrial field device is respectively stored in two different cluster node databases, namely, the industrial real-time database cluster system adopts a dual-instance redundancy deployment mode.

The following description is made for the process of establishing the mapping relationship in the industrial database cluster system shown in fig. 2.

Step one, calculating the weight of the current equipment instance. Fig. 3 is a schematic diagram of a trigger condition for selecting a master of an industrial database cluster system in another embodiment of the present application, and as shown in fig. 3, after a real-time database cluster is successfully connected to a device, it is considered that a device instance is online at a current node in the cluster. And after the equipment instance is online, calculating the weight of the current equipment instance at the current node, and after the weight calculation is finished, synchronizing the weight of the equipment instance in each node of the cluster.

The weight of the device instance consists of three parts, namely the online time (70 percent) of the device instance, the delay time (20 percent) of the device instance and the health value (10 percent) of the node where the device instance is located. The 70% of the online time of the equipment instance is to ensure that the frequent online and offline of the equipment instance in the cluster does not influence the result of the main selection, reduce the switching of the equipment instance in the cluster and improve the stability of data. Meanwhile, the delay time of the equipment instance and the health value of the node where the equipment instance is located are increased by 2 weighted items, so that the equipment instance with the lowest delay and healthier node can be selected as the main equipment instance.

Step two, please continue to refer to fig. 3, after all nodes receive the weight of the online device instance, the device instance election logic of each node is triggered, wherein the larger the weight is, the better the device instance is, and the main idea of election is to select the optimal device instance.

And step three, after synchronization is finished, at the moment, each node has weight information of all the equipment instances of the equipment in the cluster, the weights of all the equipment instances of the current equipment are sorted from large to small, and the equipment instance with the largest weight is the main equipment instance. And when the scenes with the same weight value appear, selecting the equipment instance with the minimum serial number of the node as the main equipment instance.

And step four, selecting the cluster node database where the main equipment instance is located as the node database of the equipment object.

The system can realize quick owner selection of multiple equipment instances in the cluster system, the main instance can be quickly selected in the owner selection process without the support of most nodes, the main equipment instance can be ensured to be selected inevitably in each owner selection process, the conditions of owner selection failure and no owner availability of the cluster can be avoided, and the stability of data is not influenced. Because the weights of the device instances in the cluster are synchronized, the information of different nodes in the cluster is consistent, and the condition that the master nodes selected by different nodes in the cluster are consistent and the master nodes selected by different nodes are inconsistent can be avoided. In addition, the main selection method described in the invention does not need more than half of the examples in the cluster to support, so that the number of the examples in the cluster is not limited, and the method is more flexible. The whole process has less interaction and high speed, and ensures the stability and consistency of industrial data.

EXAMPLE III

In a second aspect, the present application provides an industrial database cluster system, which processes an access request sent by a user terminal through the method according to any one of the above first aspects.

Example four

A third aspect of the present application provides an electronic device by another embodiment, including: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the data access method of the industrial database cluster system as described in any of the above embodiments.

Fig. 4 is a schematic structural diagram of an electronic device according to another embodiment of the present application.

The electronic device shown in fig. 4 may include: at least one processor 101, at least one memory 102, at least one network interface 104, and other user interfaces 103. The various components in the electronic device are coupled together by a bus system 105. It is understood that the bus system 105 is used to enable communications among the components. The bus system 105 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 105 in fig. 4.

The user interface 103 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, trackball, or touch pad, among others.

It will be appreciated that the memory 102 in this embodiment may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a programmable Read-only memory (PROM), an erasable programmable Read-only memory (erasabprom, EPROM), an electrically erasable programmable Read-only memory (EEPROM), or a flash memory. The volatile memory may be a Random Access Memory (RAM) which functions as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (staticiram, SRAM), dynamic random access memory (dynamic RAM, DRAM), synchronous dynamic random access memory (syncronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM ), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and direct memory bus RAM (DRRAM). The memory 62 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

In some embodiments, memory 102 stores elements, executable units or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system 1021 and application programs 1022.

The operating system 1021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application 622 includes various applications for implementing various application services. Programs that implement methods in accordance with embodiments of the invention can be included in application 1022.

In the embodiment of the present invention, the processor 101 is configured to execute the method steps provided in the first aspect by calling a program or an instruction stored in the memory 102, specifically, a program or an instruction stored in the application 1022, for example, including the following steps:

s10, determining a node database corresponding to each equipment object through a selection master, and establishing a mapping relation between the equipment objects and the node database; the node database corresponding to each equipment object in the mapping relation is determined based on the equipment instance online time, the equipment instance delay time and the cluster node health value of the equipment instance;

s20, the cluster system acquires an access request sent by the user side, and the access request is used for accessing equipment instance data of the target equipment object;

s30, the cluster system determines a target node database to be accessed by searching the mapping relation between the device object and the node database based on the target device object;

and S40, the cluster system sends the access request to the target node database to access the device instance data of the target device object.

The method disclosed by the above embodiment of the present invention can be applied to the processor 101, or implemented by the processor 101. The processor 101 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 101. The processor 101 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software elements in the decoding processor. The software elements may be located in ram, flash, rom, prom, or eprom, registers, among other storage media that are well known in the art. The storage medium is located in the memory 102, and the processor 101 reads the information in the memory 102 and completes the steps of the method in combination with the hardware thereof.

In addition, in combination with the data access method of the industrial database cluster system in the above embodiments, an embodiment of the present invention may provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the data access method of the industrial database cluster system in any one of the above embodiments is implemented.

It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.

For a software implementation, the techniques described herein may be implemented by means of units performing the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.

In the above embodiments disclosed in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods, apparatus, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Furthermore, it should be noted that in the description of the present specification, the description of the term "one embodiment", "some embodiments", "examples", "specific examples" or "some examples", etc., means that a specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, the claims should be construed to include preferred embodiments and all changes and modifications that fall within the scope of the invention.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include such modifications and variations.