CN114448843A - A kind of adaptive heartbeat detection method and device, electronic equipment - Google Patents

Abstract

The invention discloses a self-adaptive heartbeat detection method and device and electronic equipment, wherein the self-adaptive heartbeat detection method comprises the following steps: acquiring a heartbeat message queue at the current moment; determining a self-adaptive model algorithm equation according to the heartbeat message queue at the current moment; determining the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation; determining the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment; and performing heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message. According to the invention, the next heartbeat is predicted through the historical heartbeat information, the heartbeat timeout interval is dynamically adjusted, the flexibility and the accuracy of node detection are greatly improved, and the condition of node failure misjudgment caused by network jitter, communication delay, communication blockage and the like is greatly reduced.

Description

An adaptive heartbeat detection method and device, and electronic equipment

technical field

The invention relates to the technical field of cloud database cluster systems, in particular to an adaptive heartbeat detection method and device, and electronic equipment.

Background technique

With the advent of the era of mobile Internet and cloud computing, applications in various industries have higher and higher requirements for data storage. The traditional stand-alone database is not enough to meet the needs of applications in terms of performance, reliability, availability, etc., giving birth to high-availability databases. cluster system. A general high-availability database cluster adopts a centralized management of one master and multiple backups. Generally, three roles of coordination node, data node, and agent node are set in the cluster. The data node mainly stores data, and the agent node monitors and reports the health of the data node. Status, resource status, the coordinating node is responsible for cluster maintenance and task delivery based on the status information reported by the Agent, and the Agent handles tasks such as master-standby switchover, replication setup, data backup and recovery, and so on. Generally, the agent reports the heartbeat regularly, and the timeout time of the node is fixed. In a large-scale cluster, there are network jitter, communication delay, communication blockage, etc., especially in the cloud computing virtualization environment, which will cause the node to be mistaken for It is invalid, which leads to misjudgment of cluster status and triggers active/standby switchover, which greatly affects the read and write usage of applications.

SUMMARY OF THE INVENTION

Therefore, the technical problem to be solved by the present invention is that due to network jitter, communication delay, communication congestion and other conditions in the large-scale cloud database cluster system, the cluster state misjudgment triggers automatic switching problems, thereby providing an adaptive heartbeat detection. Method and device, electronic device.

According to a first aspect, an embodiment of the present invention discloses an adaptive heartbeat detection method. The method includes: acquiring a heartbeat message queue at the current moment; determining an adaptive model algorithm equation according to the heartbeat message queue at the current moment; The algorithm equation of the adaptive model determines the predicted arrival time of the next heartbeat message; according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment, the timeout interval of the next heartbeat message is determined; The heartbeat detection of the next heartbeat message is performed at the timeout interval of one heartbeat message.

Optionally, the obtaining the heartbeat message queue at the current moment includes: obtaining the arrival time of the heartbeat message; arranging according to the arrival time of the heartbeat message to form an original heartbeat message queue; when the heartbeat message at the current moment arrives, storing the The heartbeat message at the current moment is stored at the end of the original heartbeat message queue, and the heartbeat message at the head end of the original heartbeat message queue is eliminated to form a heartbeat message queue at the current moment.

Optionally, determining the adaptive model algorithm equation according to the heartbeat message queue at the current moment includes: according to the heartbeat message queue at the current moment, assigning the arrival time of the heartbeat message at each moment in the heartbeat message queue. Accumulate the arrival time of all heartbeat messages before this moment to obtain the cumulative heartbeat time at this moment; determine the first sequence based on the cumulative heartbeat time at each moment in the heartbeat message queue at the current moment; according to the first sequence , determine the adaptive model algorithm equation.

Optionally, determining the predicted arrival time of the heartbeat message at the next moment according to the adaptive model algorithm equation includes: solving the adaptive model algorithm equation to determine the predicted arrival time of the heartbeat message at the next moment; The predicted arrival time of the heartbeat message at the next moment is added to a preset correction value to determine the predicted arrival time of the heartbeat message at the next moment.

Optionally, determining the time-out interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment includes: comparing the predicted arrival time of the next heartbeat message with all the heartbeat messages. The arrival time of the terminal heartbeat message in the heartbeat message queue at the current moment is subtracted to obtain the timeout interval of the next heartbeat message.

Optionally, performing the heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message includes: adjusting the expected arrival time of the next heartbeat message according to the timeout interval of the next heartbeat message; After the next heartbeat message arrives, the arrival time of the next heartbeat message is obtained; when the arrival time of the next heartbeat message is different from the expected arrival time of the next heartbeat message, it is determined that the node is invalid.

Optionally, performing the heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message further includes: when the arrival time of the next heartbeat message is the same as the expected arrival time of the next heartbeat message , determine that the node is a valid node and update the heartbeat message queue.

According to a second aspect, an embodiment of the present invention further discloses an adaptive heartbeat detection device, the device includes: an acquisition module for acquiring the heartbeat message queue at the current moment; an algorithm equation determination module for according to the current moment The heartbeat message queue, determine the adaptive model algorithm equation;

A time-of-arrival determination module for determining the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation;

A timeout interval determination module is used to determine the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment; the detection module is used to determine the timeout interval of the next heartbeat message based on the timeout interval of the next heartbeat message Perform heartbeat detection for the next heartbeat message.

According to a third aspect, an embodiment of the present invention further discloses an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores data that can be used by the at least one processor. Instructions executed by the processor, the instructions being executed by the at least one processor to cause the at least one processor to execute the adaptive heartbeat according to the first aspect or any of the optional embodiments of the first aspect The steps of the detection method.

According to a fourth aspect, an embodiment of the present invention further discloses a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the first aspect or any optional implementation of the first aspect The steps of the adaptive heartbeat detection method described in the method.

The technical scheme of the present invention has the following advantages:

1. The self-adaptive heartbeat detection method provided by the present invention, by obtaining the heartbeat message queue at the current moment, and according to the heartbeat message queue at the current moment, determine the adaptive model algorithm equation, then according to the adaptive model algorithm equation, determine the next heartbeat The predicted arrival time of the message, according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment, determine the timeout interval of the next heartbeat message, and perform the heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message. The present invention predicts the next heartbeat through the historical heartbeat information, and corrects it through the correction value, dynamically adjusts the heartbeat timeout interval, greatly improves the flexibility and accuracy of node detection, and greatly reduces network jitter and communication delay. , communication congestion, etc., the situation of node failure and misjudgment occurs.

2. The present invention uses the heartbeat message queue to ensure that the latest heartbeat information is used as a sample for prediction and correction in the form of a sliding window, which greatly reduces the prediction error and improves the real-time and accuracy of node detection.

Description of drawings

In order to illustrate the specific embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the specific embodiments or the prior art. Obviously, the accompanying drawings in the following description The drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

1 is a schematic flowchart of an adaptive heartbeat detection method in an embodiment of the present invention;

2 is a specific flowchart of an adaptive heartbeat detection method in an embodiment of the present invention;

3 is a schematic structural diagram of an adaptive heartbeat detection device in an embodiment of the present invention;

FIG. 4 is a diagram of a specific example of an electronic device in an embodiment of the present invention.

Detailed ways

The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the indicated device or element must have a specific orientation or a specific orientation. construction and operation, and therefore should not be construed as limiting the invention. Furthermore, the terms "first", "second", and "third" are used for descriptive purposes only and should not be construed to indicate or imply relative importance.

In the description of the present invention, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense, unless otherwise expressly specified and limited, for example, it may be a fixed connection or a detachable connection connection, or integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal connection of two components, which can be a wireless connection or a wired connection connect. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood in specific situations.

In the description of the invention, it is to be understood that, as used in this specification and the appended claims, the term "and/and/or" refers to any combination of one or more of the associated listed items and all possible combinations, and including those combinations. In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

An embodiment of the present invention discloses an adaptive heartbeat detection method. As shown in FIG. 1 , the method includes the following steps:

Step 101: Obtain the heartbeat message queue at the current moment.

Specifically, by obtaining the arrival time of a certain number of heartbeat messages in history, sorting them according to the arrival time of the heartbeat messages, and placing the heartbeat messages closest to the current moment at the end of the heartbeat message queue in order to form the original heartbeat message queue. When the heartbeat message arrives, the heartbeat message at the current moment is stored at the end of the original heartbeat message queue, and the heartbeat message at the head end of the original heartbeat message queue is eliminated to form a heartbeat message queue at the current moment.

Exemplarily, as an optional implementation of the present invention, for example, the latest k heartbeats are taken from the heartbeat message record queue, assuming m ₁ , m ₂ , ..., m _k , and the arrival times are respectively t ⁰ (1),t ⁰ (2),…,t ⁰ (k), arranged according to the arrival time to form the original sequence t ⁰ =(t ⁰ (1),t ⁰ (2),…,t ⁰ (k) ).

The invention stores the heartbeat message queue by the sliding window method, ensures that the latest heartbeat information is used as a sample for prediction and correction, greatly reduces the prediction error, and improves the real-time performance and accuracy of node detection.

Step 102: Determine an adaptive model algorithm equation according to the heartbeat message queue at the current moment.

Step 103: Determine the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation.

Step 104: Determine the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment.

Specifically, according to the heartbeat message queue at the current moment, the arrival time of the heartbeat message at each moment in the heartbeat message queue at the current moment and the arrival times of all the heartbeat messages before the moment are cumulatively calculated to obtain the cumulative heartbeat time at the moment, and based on The accumulated heartbeat time results at each moment in the heartbeat message queue at the current moment form a first sequence according to the original sequence, and then determine the adaptive model algorithm equation according to the first sequence. And solve the algorithm equation of the adaptive model, obtain the predicted time of the arrival of the heartbeat message at the next moment, and finally add the predicted time of the arrival of the heartbeat message at the next moment with the preset correction value to obtain the next moment of the heartbeat message. Predicted arrival time. Finally, the predicted arrival time of the heartbeat message at the next moment is subtracted from the arrival time of the heartbeat message at the end of the heartbeat message queue at the current moment to obtain the timeout interval of the next heartbeat message.

Exemplarily, as an optional embodiment of the present invention, as shown in FIG. 2 , first, a certain number of recent historical heartbeat data are taken to construct an initial sequence t ₀ , and then the first sequence t 0 is generated from the initial sequence t ₀ by an accumulation generation method. A sequence t ₁ , and then the differential equation GM(1,1) of the adaptive model algorithm is established for the sequence t ₁ , and then the differential equation GM(1,1) of the adaptive model algorithm is solved to obtain the heartbeat prediction arrival time. In the first sequence, a preset fixed correction value is added to each arrival time value in the first sequence to obtain the final heartbeat message arrival time prediction sequence tn, and then the sequence _{tn is} subtracted from the initial sequence t ₀ , and then The timeout interval sequence is obtained, and the predicted timeout interval at the end of the timeout interval sequence is the timeout interval of the next heartbeat of the node.

For example, construct the initial sequence first: take the nearest p heartbeats, and use these heartbeat moral practices as the initial sequence t ⁰ , i.e.

t ⁰ =(t ⁰ (1),t ⁰ (2),…,t ⁰ (p))

Then, the method of cumulative generation is used to accumulate the arrival time of the heartbeat message at each time in the initial sequence and the arrival time of all previous heartbeat messages, and the cumulative time of the heartbeat messages at each moment can be obtained.

Then, according to the heartbeat message accumulation time at all times in the heartbeat message queue, a sequence t ¹ is generated, that is,

t ¹ =(t ¹ (1),t ¹ (2),...,t ¹ (p))

Then integrate the sequence t ¹ ,

dt ¹ (k)=t ⁰ (k1)=t ¹ (k)-t ¹ (k-1)

Then the differential equation of the adaptive model algorithm is established,

dt ¹ (k)+az ¹ (k)=b,

in,

Then, the differential equation of the adaptive model algorithm is solved to calculate the heartbeat arrival time prediction sequence. The specific calculation process is as follows:

First, substitute k=2,...,p into the differential equation to obtain the differential equation system of the adaptive model algorithm,

By transforming this formula into the form y=Bu, where,

Solve for a and b to get

get the predicted value

Add a fixed correction value c to get the arrival time of the next heartbeat,

Finally, by subtracting the value of the initial sequence t ⁰ from the calculated heartbeat arrival time prediction sequence, the timeout interval sequence is obtained, where the last value of the timeout interval sequence is the timeout interval Δt of the next heartbeat of the node.

Among them, a and b are adaptive algorithm model parameters, which are determined by the arrival time of historical heartbeat messages.

Step 105 , heartbeat detection of the next heartbeat message is performed based on the timeout interval of the next heartbeat message.

Specifically, according to the timeout interval of the next heartbeat message, the expected arrival time of the next heartbeat message is adjusted, and after the next heartbeat message arrives, the actual arrival time of the next heartbeat message is obtained, and the actual arrival time is compared with the expected arrival time, When the actual arrival time of the next heartbeat message is different from the expected arrival time of the next heartbeat message, it is determined that the node is a failed node. When the actual arrival time of the next heartbeat message is the same as the expected arrival time of the next heartbeat message, the actual arrival time of the heartbeat message is stored at the end of the current heartbeat message queue, and the next heartbeat message is predicted through the new heartbeat message queue. Arrival time, by continuously continuing this calculation method, can dynamically detect whether the node fails at any time.

Among them, the present invention can not only be applied to node failure detection in a cloud database cluster system, such as the high-availability database system TELEDB, it can reduce the misjudgment of node failure due to network jitter, communication delay, communication congestion, etc., and improve the cluster performance. Availability can also be extended to other cluster systems or distributed systems to detect whether nodes fail.

The present invention predicts the next heartbeat through the historical heartbeat information, and corrects it through the correction value, dynamically adjusts the heartbeat timeout interval, greatly improves the flexibility and accuracy of node detection, and greatly reduces network jitter and communication delay. , communication congestion, etc., the node failure and misjudgment occur, which improves the availability of the cluster.

The embodiment of the present invention also discloses an adaptive heartbeat detection device, as shown in FIG. 3 , the device includes:

The obtaining module 31 is used to obtain the heartbeat message queue at the current moment, and for details, refer to step 101;

The algorithm equation determination module 32 is configured to determine the algorithm equation of the adaptive model according to the heartbeat message queue at the current moment. For details, refer to step 102;

The arrival time determination module 33 is used to determine the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation, for details, refer to step 103;

The timeout interval determination module 34 is used to determine the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment, and the details refer to the description in step 104;

The detection module 35 is configured to perform heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message. For details, refer to step 105 .

An embodiment of the present invention also provides an electronic device. As shown in FIG. 4 , the electronic device includes: a processor 401 and a memory 402, where the processor 401 and the memory 402 may be connected by a bus or in other ways. Take bus connection as an example; the processor 401 may be a central processing unit (Central Processing Unit, CPU). The processor 401 can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or Other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components and other chips, or a combination of the above types of chips.

As a non-transitory computer-readable storage medium, the memory 402 can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions corresponding to the adaptive heartbeat detection method in the embodiment of the present invention /modules. The processor 401 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 402, ie, implements the adaptive heartbeat detection method in the above method embodiments.

The memory 402 may include a storage program area and a storage data area, wherein the storage program area may store an operating system and an application program required by at least one function; the storage data area may store data created by the processor 401 and the like. Additionally, memory 402 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 402 may optionally include memory located remotely from processor 401, which may be connected to processor 401 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The one or more modules are stored in the memory 402, and when executed by the processor 401, execute the adaptive heartbeat detection method in the embodiment shown in FIG. 1-2.

The specific details of the above-mentioned adaptive heartbeat detection system can be understood by referring to the corresponding descriptions and effects in the embodiments shown in FIGS. 1-2 , and details are not repeated here.

Those skilled in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. During execution, the processes of the embodiments of the above-mentioned methods may be included. Wherein, the storage medium can be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive) , abbreviation: HDD) or solid-state drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memories.

Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, various modifications and variations can be made by those skilled in the art without departing from the spirit and scope of the present invention, such modifications and variations falling within the scope of the appended claims within the limited range.

Claims (10)

1. an adaptive heartbeat detection method, is characterized in that, comprises: Get the heartbeat message queue at the current moment; Determine the adaptive model algorithm equation according to the heartbeat message queue at the current moment; Determine the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation; Determine the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment; The heartbeat detection of the next heartbeat message is performed based on the timeout interval of the next heartbeat message. 2. The method according to claim 1, wherein the acquiring the heartbeat message queue at the current moment comprises: Get the arrival time of the heartbeat message; Arrange according to the arrival time of the heartbeat messages to form an original heartbeat message queue; When the heartbeat message at the current moment arrives, the heartbeat message at the current moment is stored at the end of the original heartbeat message queue, and the heartbeat message at the head of the original heartbeat message queue is removed to form a heartbeat message queue at the current moment. 3. The method according to claim 1, wherein, determining the adaptive model algorithm equation according to the heartbeat message queue at the current moment, comprising: According to the heartbeat message queue at the current moment, the cumulative heartbeat time at this moment is obtained by accumulatively calculating the arrival time of the heartbeat message at each moment in the heartbeat message queue and the arrival time of all the heartbeat messages before the moment; Determine the first sequence based on the accumulated heartbeat time at each moment in the heartbeat message queue at the current moment; According to the first sequence, the adaptive model algorithm equation is determined. 4. The method according to claim 1, wherein, determining the predicted arrival time of the heartbeat message at the next moment according to the adaptive model algorithm equation, comprising: Solving the adaptive model algorithm equation to determine the predicted time of arrival of the heartbeat message at the next moment; The predicted arrival time of the heartbeat message at the next moment is added to a preset correction value to determine the predicted arrival time of the heartbeat message at the next moment. 5. method according to claim 1, is characterized in that, described according to the predicted arrival time of described next heartbeat message and the heartbeat message queue of current moment, determine the timeout interval of next heartbeat message, comprising: The predicted arrival time of the heartbeat message at the next moment is subtracted from the arrival time of the terminal heartbeat message in the heartbeat message queue at the current moment to obtain the timeout interval of the next heartbeat message. 6. The method according to claim 1, wherein the heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message comprises: Adjust the expected arrival time of the next heartbeat message according to the timeout interval of the next heartbeat message; After the next heartbeat message arrives, obtain the arrival time of the next heartbeat message; When the arrival time of the next heartbeat message is different from the expected arrival time of the next heartbeat message, it is determined that the node fails. 7. The method of claim 6, further comprising: When the arrival time of the next heartbeat message is the same as the expected arrival time of the next heartbeat message, the node is determined to be a valid node, the heartbeat message queue is updated, and an iterative calculation is performed according to the heartbeat message queue. 8. An adaptive heartbeat detection device, comprising: The acquisition module is used to acquire the heartbeat message queue at the current moment; an algorithm equation determination module for determining an adaptive model algorithm equation according to the heartbeat message queue at the current moment; A time-of-arrival determination module for determining the predicted arrival time of the next heartbeat message according to the adaptive model algorithm equation; A timeout interval determination module, for determining the timeout interval of the next heartbeat message according to the predicted arrival time of the next heartbeat message and the heartbeat message queue at the current moment; A detection module, configured to perform heartbeat detection of the next heartbeat message based on the timeout interval of the next heartbeat message. 9. An electronic device, characterized in that, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to The at least one processor is caused to perform the steps of an adaptive heartbeat detection method according to any of claims 1-7. 10. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the steps of the adaptive heartbeat detection method according to any one of claims 1-7 are implemented.

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