CN114020572A - Distributed alarm method and device - Google Patents
Distributed alarm method and device Download PDFInfo
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- CN114020572A CN114020572A CN202111308781.7A CN202111308781A CN114020572A CN 114020572 A CN114020572 A CN 114020572A CN 202111308781 A CN202111308781 A CN 202111308781A CN 114020572 A CN114020572 A CN 114020572A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Abstract
The embodiment of the invention provides a distributed alarm method and a distributed alarm device. The method comprises the following steps: distributing the event to a corresponding application module for business processing; and the application module stores the alarm data in the event into a distributed memory database. By the invention, different events are distributed to corresponding application modules for processing, the alarm data obtained after preprocessing is stored in the distributed memory database, and the secondary service processing can be carried out by self-defining processing logic on the alarm processing engine. Under the condition of ensuring high-efficiency reading and writing, the memory space can be expanded in parallel. The problems that in the related technology, due to the adoption of a multilayer framework and a single thread, the data synchronization efficiency is low, the alarm processing speed is influenced, and the parallel expansion capability is lacked are solved, and the effect of keeping the high-efficiency event acquisition efficiency and the processing efficiency is achieved.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a distributed alarm method and a distributed alarm device.
Background
In the related art, the centralized monitoring solution may unify and inherit monitoring of managing various events including system, application, network monitoring, and the like. By way of example, Tivoli Netcool/ONMIbus enables data collection from network management consoles, transmission infrastructure, telephony devices, data networks, LANs and WANs and various classes of applications and non-IT devices, which play a key role in integration and management throughout the IT service architecture.
The existing commercial suite Tivoli Netcool/ONMIbus mainly comprises ObjectServer, Probes, Gateways, Desktop tools, Administration tools, Netcool MIB Manager and The Web GUI seven modules. The event processing flow comprises the steps of firstly obtaining an event and simply logically processing equipment data through a probe, then carrying out field conversion on the corresponding event, inserting the event into a memory database of an ObjectServer, carrying out related automatic logical processing on the event by the ObjectServer, and finally displaying the event on a front-end page of a user through data visualization processing.
The existing business suite completes the processing of events through the coordinated operation of all modules, the coupling of each module is high, a multiple architecture design is adopted, each module belongs to black box operation for users, the processing freedom degree of post-addition to special business scenes is not high, and specifically, the business suite at least comprises the following defects: the system is of a multilayer structure, the data synchronization efficiency is low, and the alarm processing speed is influenced; single-thread processing: the acquisition and processing are single-threaded and have no parallel expansion capability.
Disclosure of Invention
The embodiment of the invention provides a distributed alarm method and a distributed alarm device, which are used for at least solving the problems of low data synchronization efficiency, influence on alarm processing speed and lack of parallel expansion capability caused by the adoption of a multi-layer architecture and a single thread in the related technology.
According to an embodiment of the present invention, a distributed alarm method is provided, including: distributing the event to a corresponding application module for business processing; and the application module stores the alarm data in the event into a distributed memory database and carries out secondary service processing.
In an exemplary embodiment, before distributing the event to the corresponding application module for business processing, the method further includes: acquiring original data in a corresponding acquisition mode according to the type of a data source; wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
In one exemplary embodiment, the business process includes: the method comprises the steps of stream processing and batch processing, wherein each application module runs the same stream processing, and the batch processing is carried out by the application modules according to events.
In one exemplary embodiment, the stream processing includes: the method comprises the steps of event preprocessing, event enrichment, maintenance period processing, maintenance period setting and event compression, wherein the batch processing comprises the following steps: event upgrading and downgrading, event recovery, maintenance period, alarm secondary processing, alarm notification and Root Cause Analysis (RCA).
In one exemplary embodiment, distributing the event to the corresponding application module for business processing comprises: and packaging and managing and arranging the alarm processing function by the business processing in a mode of an application store.
In an exemplary embodiment, performing the secondary service processing on the alarm data stored in the distributed memory database further includes: and inquiring alarm data from the distributed memory database and carrying out corresponding operation on the alarm data according to the requirement.
According to another embodiment of the present invention, there is provided a distributed alarm apparatus including:
the distribution module is used for distributing the events to the corresponding application modules for business processing; and the storage module is used for storing the alarm data in the event into a distributed memory database through the application module and carrying out secondary service processing.
In an exemplary embodiment, the obtaining module is configured to obtain original data in a corresponding collecting manner according to a type of a data source; wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
In an exemplary embodiment, the query module is configured to query the alarm data from the distributed memory database and perform corresponding operation on the alarm data according to a requirement.
According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, different events are distributed to the corresponding application modules for processing, and the alarm data obtained in the processing is stored in the distributed memory database, so that the memory space can be expanded in parallel under the condition of ensuring high-efficiency reading and writing. Therefore, the problems of low data synchronization efficiency, influence on alarm processing speed and lack of parallel expansion capability caused by the adoption of a multilayer architecture and a single thread in the related technology can be solved, and the effect of keeping high-efficiency event acquisition efficiency and processing efficiency can be achieved.
Drawings
Fig. 1 is a block diagram of a hardware structure of a computer terminal that operates a distributed alarm method according to an embodiment of the present invention;
FIG. 2 is a flow diagram of a distributed alarm method according to an embodiment of the present invention;
FIG. 3 is a block diagram of a distributed alerting device according to an embodiment of the present invention;
FIG. 4 is a block diagram of a distributed alerting device according to another embodiment of the present invention;
FIG. 5 is a diagram of a network architecture for operating a distributed alarm method and apparatus according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a processing engine functional module implementing a distributed alarm method according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided in the embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the operation on a computer terminal as an example, fig. 1 is a hardware structure block diagram of a computer terminal for operating a distributed alarm method according to an embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a Processing device such as a Microprocessor (MCU) or a Programmable logic device (FPGA)) and a memory 104 for storing data, wherein the computer terminal may further include a transmission device 106 for communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the computer terminal. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the distributed alarm method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to a computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
Fig. 2 is a flowchart of a distributed alarm method according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:
step S202, distributing the event to a corresponding application module for business processing;
and step S204, the application module stores the alarm data in the event into a distributed memory database and carries out secondary service processing.
Before step S202 in this embodiment, the method may further include: acquiring original data in a corresponding acquisition mode according to the type of a data source;
wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
In step S202 of this embodiment, the service processing includes: the method comprises the steps of stream processing and batch processing, wherein each application module runs the same stream processing, and the batch processing is carried out by the application modules according to events.
In this embodiment, the stream processing includes: the method comprises the steps of event preprocessing, event enrichment, maintenance period processing, maintenance period setting and event compression, wherein the batch processing comprises the following steps: event upgrading and downgrading, event recovery, maintenance period, secondary alarm processing, alarm notification and RCA root cause analysis.
In step S202 of this embodiment, the method may further include: and packaging and managing and arranging the alarm processing function by the business processing in a mode of an application store.
In step S204 of this embodiment, the method may further include: inquiring alarm data from the distributed memory database and carrying out corresponding operation on the alarm data according to the requirement
Through the steps, a distributed system structure is adopted, different events are distributed to corresponding application modules for processing, alarm data obtained in the processing are stored in a distributed memory database, and the storage capacity can be expanded in parallel under the condition of ensuring high-efficiency reading and writing. The problems that in the related technology, due to the adoption of a multilayer architecture and a single thread, the data synchronization efficiency is low, the alarm processing speed is influenced, and the parallel expansion capability is lacked are solved, and the event acquisition efficiency and the event processing efficiency are improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a Read-Only Memory/Random Access Memory (ROM/RAM), a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, a distributed alarm device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, which have already been described and are not described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 3 is a block diagram of a distributed alarm apparatus according to an embodiment of the present invention, and as shown in fig. 3, the apparatus includes a distribution module 10 and a storage module 20.
The distribution module 10 is used for distributing the events to the corresponding application modules for business processing;
and the storage module 20 is configured to store the alarm data in the event into a distributed memory database through the application module, and perform secondary service processing.
Fig. 4 is a block diagram of a distributed alarm device according to another embodiment of the present invention, and as shown in fig. 4, the device includes, in addition to all the modules shown in fig. 3, an acquisition module 30 and an inquiry module 40.
The acquisition module 30 is configured to acquire original data in a corresponding acquisition manner according to the type of the data source; wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
And the query module 40 is configured to query the alarm data from the distributed memory database and perform corresponding operations on the alarm data according to requirements.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
In order to facilitate understanding of the technical solutions provided by the present invention, the following detailed description will be made with reference to embodiments of specific scenarios.
The distributed alarm method and apparatus in the embodiment of the present application may be operated on the network architecture shown in fig. 5, as shown in fig. 5, the network architecture includes: zookeeper cluster, event collector, Dubbo distributed cluster, Ignite distributed memory database, and distributed memory database (Portal).
The technologies used in the embodiment include zookeeper distributed application program coordination service, a Dubbo lightweight service registration and call framework, an ignition memory database and a distributed memory database. The distributed memory database can store activity alarms, history alarms, configuration information and the like, and also supports persistence to a disk, so that data loss is prevented, and mass data can be stored; meanwhile, the resource data required in the event processing process can be stored in a distributed cache, and specifically, the resource data is stored in a Key-Value mode.
In this embodiment, the data area is configured as a master node synchronization mode, providing the final consistency of one data operation.
In this embodiment, in the event processing portion in the Dubbo distributed cluster, the adopted software framework is Springboot + Spring, and the conversion of different SQL grammars can be realized by combining ANTLR open-source syntax parsing software. The programming language is converted into bytecodes by using Java Tools, and the loaded bytecodes are run on the JVM through the dynamic loading capability of Spring. The communication between the nodes adopts Java native RMI communication protocol to complete the communication function between the cluster nodes.
Fig. 6 is a schematic diagram of a processing engine functional module for implementing a distributed alarm method according to an embodiment of the present invention, where, as shown in fig. 6, the functional module includes: the device comprises a service access layer, a processing layer, an APP management layer, a data management layer and an interface layer.
Specifically, firstly, the event processing engine needs a perfect service access layer, and in this embodiment, the processing engine designs data access supporting SQL syntax, and accesses the event information preprocessed by EPP to the event service entry of the engine. And (3) forming a distributed service registration and subscription center in a Dubbo + Zookeeper mode by using an open source distributed management tool Zookeeper as event service management, so as to meet the distributed service call of event logic processing. The service access layer functionally includes the functions of the acquisition module in the above embodiments.
After receiving the collected event information, a corresponding service processing link, namely a processing layer of an event processing engine, is to be performed, wherein the processing layer comprises corresponding service logic processing such as event enrichment, maintenance period setting, event compression, secondary processing, RCA root cause analysis and the like, the service logic is compiled by using a Scale or Java language and is defined as an APP processing module, and each service is independent APP operation and is divided into stream processing and batch processing. The processing layer functionally includes the functions of the distribution module in the above embodiments.
When business scenes are enriched day by day, scenes needing logic processing are increased gradually, an APP management layer is designed to manage the APPs of each business scene, the APPs compiled by Scala or Java are converted into byte codes through syntax analysis, the processing engine is directly and thermally deployed, business collaboration among some APPs is achieved, and management of APP versions can be achieved through the APP management layer.
For each data import and export and data backup, corresponding functions need to be completed through a designed data management layer, the data importer can analyze SQL syntax to realize automatic import of the Ignite memory database, the exporter can export the data to a local disk in a file form, and if the operation fails, the data can be returned to a state before the operation through operation rollback management. The data management layer can also complete the synchronization of the data of the double-center cluster, ensure the data completeness of the standby cluster and prevent the downtime risk. The data management layer functionally includes the functions of the storage module in the above embodiments.
The interface layer provides corresponding interface functions for the outside of the system, and comprises an external interface for APP hot deployment and management, an interface for operating an ignition database, and an interface for inquiring batch processing and stream processing running information, wherein the functional interfaces are all called and realized on a matched front-end Web page. The interface layer functionally includes the functionality of the query module in the embodiments described above.
In this embodiment, the data stream operation mode based on the processing engine includes: a Universal management interface (UMP) platform may complete interfacing with an event processing engine through an Application Programming Interface (API) of Restful, deploy an application, and may also implement data query and operation on an event processing engine ignate database through a data manipulation interface of the event processing engine. The event collector is used as a producer to provide a service interface for the event processing engine through a Dubbo registration center, and the processing logic of the event processing engine completes the processing of the event in two modes of stream processing and batch processing, namely an application module. The processing cluster can realize leader node election and coordinated application node distribution through the Zookeeper, and each client finishes node communication through an RMI communication protocol.
In this embodiment, the processing engine is based on an Akka concurrent framework, the core of the Akka framework principle is an Actor, and different modules of the Actor have different functions, and the function roles of the Actor in the present invention are as follows:
the data acquisition Actor is used for acquiring original data, actively acquiring or passively receiving the original data, acquiring data of different types by one Actor, and acquiring the data regularly by adopting a polling mode for the actively acquired Actor;
all the collected original data are sent to the original data distribution Actor, and are distributed to the data analysis Actor by the original data distribution Actor, and meanwhile, the Actor can carry out overall scheduling control on the original data;
the data analysis actors are a group of actors, are main components for service processing and resource consumption, and can flexibly configure the concurrency number of the actors;
the persistence data distribution Actor sends all the data needing to be persisted to the Actor, distributes the data needing to be persisted to the persistence Actor, and simultaneously performs integral control on the persistence data, for example, the persistence cannot be performed or is slow due to the problems of a database or a network, so that the backpressure control can be realized;
the data persistence actors are a group of actors and are used for persisting data, the number of the actors can be configured, and the predominant IO consumers are provided.
In this embodiment, the business scene is converted into APP store mode, the APP mode is used to package, manage and arrange the alarm processing function, and the APP development can use the scripting language provided by the system and can also use Java or Scala development by defining the customized development of multiple APP types to support the processing function. The APP mode has the following characteristics and differences:
the dynamic property: can be dynamically arranged, deployed, modified or removed;
stream processing APP, namely, the APP operated on each node is operated, and if an event meets the condition of the APP, the APP logic is operated;
scheduling type batch processing APP: the scheduling engine of the event processing engine distributes the APPs on different nodes to run, each APP has only one instance, and a batch of events are taken from the event library at regular time to be processed;
subscription-type batch APP: the method comprises the steps that a scheduling engine of an event processing engine distributes APPs on different nodes to run, each APP only has one instance, and data are subscribed from streaming APPs or scheduling batch APPs to be processed in a unified and centralized mode;
broadcast type batch processing APP: the method comprises the steps that batch processing APPs run at each node, and an event source is data distributed by a certain scheduling type APP, so that the effect of distributed processing is achieved;
restful APP: dynamically generating an APP of a Restful interface so as to access internal data of the APP; graceful start-stop: when an APP is updated, the data being processed by the APP is automatically stopped after being processed, and the data needing to be processed immediately is processed by the new APP, namely, the new APP and the old APP can have an overlapped time to run simultaneously.
In this embodiment, the distributed alarm method based on the processing engine has the following characteristics:
distributed processing, high availability of clusters: a cluster is built by adopting a Dubbo + Zookeeper frame, distributed calling and load balancing functions are provided, and the processing capacity can be horizontally expanded; the processing nodes are still available in the cluster in the event that they are down by a certain amount.
And (3) alarm link tracking: each alarm processing key path has tracking information, and performance indexes of alarm processing can be checked and counted.
App hot plug: for large and complex processing logic, the processing logic can be developed by Scala or Java language in development environments such as Idea and Eclipse, and is packaged into a Jar package to be hot deployed in an alarm processing engine, and the App can be unloaded at any time.
App can be programmed, scheduled and cooperated: the stream APP can be arranged in a chain mode, batch APPs can be scheduled to run on different nodes, and complex services such as summary processing and distribution processing can be completed jointly through cooperation among the APPs.
High concurrency, high performance: alarm processing and warehousing capacity: 10000 strips/s; active alert inventory reserves: 1000 ten thousand levels;
historical warning stock reserves: class hundred million;
compatibility: the method is fully compatible with the processing rule of the business suite Omnibus; the alarm processing logic can make quick and smooth transition;
disaster recovery and multi-data center deployment: the data is automatically backed up at regular time, and the data is ensured not to be lost in a mode of full amount plus incremental backup; supporting the deployment of a master-standby mode of multiple data centers and automatically synchronizing data among the data centers;
expansibility: supporting custom App development and deployment; supporting the operation of converting SQL-like App into Java byte code, and expanding SQL functions and syntax;
and (3) self-construction: the event processing platform is independently constructed on the basis of open source software, so that the construction speed can be increased, and the functional requirements and the business requirements can be met to the greatest extent.
Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above-mentioned method embodiments when executed.
In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details of this embodiment are not repeated herein.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. A distributed alarm method, comprising:
distributing the event to a corresponding application module for business processing;
and the application module stores the alarm data in the event into a distributed memory database and carries out secondary service processing.
2. The method of claim 1, wherein before distributing the event to the corresponding application module for service processing, the method further comprises:
acquiring original data in a corresponding acquisition mode according to the type of a data source;
wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
3. The method of claim 1, wherein the traffic processing comprises:
the method comprises the steps of stream processing and batch processing, wherein each application module runs the same stream processing, and the batch processing is carried out by the application modules according to events.
4. The method of claim 3, wherein the stream processing comprises: the method comprises the steps of event preprocessing, event enrichment, maintenance period processing, maintenance period setting and event compression, wherein the batch processing comprises the following steps: event upgrading and downgrading, event recovery, maintenance period, secondary alarm processing, alarm notification and RCA root cause analysis.
5. The method of claim 1, wherein distributing the events to corresponding application modules for business processing comprises:
and packaging and managing and arranging the alarm processing function by the business processing in a mode of an application store.
6. The method of claim 1, wherein performing secondary business processing on the alarm data stored in the distributed memory database comprises:
and inquiring alarm data from the distributed memory database and carrying out corresponding operation on the alarm data according to the requirement.
7. A distributed alarm device, comprising:
the distribution module is used for distributing the events to the corresponding application modules for business processing;
and the storage module is used for storing the alarm data in the event into a distributed memory database through the application module and carrying out secondary service processing.
8. The apparatus of claim 7, further comprising,
the acquisition module is used for acquiring original data in a corresponding acquisition mode according to the type of the data source;
wherein, the collection mode includes: and actively collecting or passively receiving, wherein the data is collected regularly by adopting a polling mode in the active collection.
9. The apparatus of claim 7, further comprising:
and the query module is used for querying the alarm data from the distributed memory database and carrying out corresponding operation on the alarm according to the requirement.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 6 when executed.
11. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114840219A (en) * | 2022-07-06 | 2022-08-02 | 湖南傲思软件股份有限公司 | Distributed event processing system |
| CN115437823A (en) * | 2022-08-31 | 2022-12-06 | 北京云脉芯联科技有限公司 | Overtime traversal method and chip |
-
2021
- 2021-11-05 CN CN202111308781.7A patent/CN114020572A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114840219A (en) * | 2022-07-06 | 2022-08-02 | 湖南傲思软件股份有限公司 | Distributed event processing system |
| CN115437823A (en) * | 2022-08-31 | 2022-12-06 | 北京云脉芯联科技有限公司 | Overtime traversal method and chip |
| CN115437823B (en) * | 2022-08-31 | 2024-02-06 | 北京云脉芯联科技有限公司 | Timeout traversing method and chip |
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