CN114443613A

CN114443613A - Configuration optimization method and device and electronic equipment

Info

Publication number: CN114443613A
Application number: CN202111574562.3A
Authority: CN
Inventors: 章锐; 叶小朋; 吴远昌; 陈阳关; 王丹; 廖裕兴; 李超亚; 谈志军
Original assignee: Tianyi Cloud Technology Co Ltd
Current assignee: Tianyi Cloud Technology Co Ltd
Priority date: 2021-12-21
Filing date: 2021-12-21
Publication date: 2022-05-06

Abstract

The invention relates to the field of computer science, in particular to a configuration optimization method, a configuration optimization device and electronic equipment. Through the random variation of the data, the configured options have diversity, the optimal configuration options can be kept through the subsequent screening process, the optimal configuration effect is obtained through multiple iterations, the configuration optimization is guaranteed to be automatically carried out in a high-efficiency and high-quality mode, and the working efficiency is greatly improved.

Description

Configuration optimization method and device and electronic equipment

Technical Field

The invention relates to the field of computer science, in particular to a configuration optimization method and device and electronic equipment.

Background

The cloud database is an extremely important product in the field of cloud computing, and the use performance of the cloud database is usually directly related to the configuration parameters of the database. In a cloud database, under the condition that a Central Processing Unit (CPU) and a memory are limited, the performance of the cloud database is mainly related to parameter configuration of the database. The performance of the cloud database can be better exerted by proper database configuration parameters, so that the use experience of the application service is improved. Currently, parameter configuration optimization of a cloud Database mainly depends on the practical experience of a Database Administrator (DBA). Therefore, the cloud database parameter configuration optimization has a higher industry threshold, and has higher requirements on the capability and experience of the DBA.

Therefore, a configuration optimization method, a configuration optimization device and an electronic device are needed to overcome the above drawbacks.

Disclosure of Invention

In view of this, embodiments of the present invention provide a configuration optimization method and apparatus, and an electronic device, so as to solve the problem that configuration optimization cannot be automatically performed on a database.

According to a first aspect, an embodiment of the present invention provides a configuration optimization method, including:

acquiring an initialization configuration information set of a target database;

performing mutation processing on each configuration information in the initialization configuration information set to obtain a mutated configuration information set;

calculating adaptive values corresponding to the initialized configuration information set and the mutated configuration;

selecting the maximum adaptive value in the adaptive values as a target adaptive value;

and when the target adaptive value reaches an optimization threshold value, determining a configuration information set corresponding to the target adaptive value as a target configuration information set.

According to the configuration optimization method provided by the embodiment of the invention, the configured options have diversity through random variation of data, the optimal configuration options can be kept through the subsequent screening process, the optimized configuration effect is obtained through multiple iterations, the automatic implementation of configuration optimization is guaranteed with high efficiency and high quality, and the working efficiency is greatly improved.

With reference to the first aspect, in a first implementation manner of the first aspect, the performing mutation processing on each configuration information in the initialization configuration information set to obtain a mutated configuration information set includes:

carrying out information mutation processing on the initialization configuration information set based on a first probability to obtain a mutated configuration information set;

and performing information exchange processing on the mutated configuration information set and the initialized configuration information set based on a second probability to obtain the mutated configuration information set.

The configuration optimization method provided by the embodiment of the invention ensures the smooth operation of the data mutation process by determining how to mutate the data and how to exchange the mutated data, provides a basis for the smooth operation of subsequent work, and further improves the work efficiency.

With reference to the first aspect or the first implementation manner, in a second implementation manner of the first aspect, the performing information mutation processing on the initialized configuration information set based on the first probability to obtain a mutated configuration information set includes:

converting the initialization configuration information set into corresponding binary information;

and modifying the data in the binary information based on the first probability, and determining a mutated configuration information set.

The configuration optimization method provided by the embodiment of the invention shows the randomness of data variation through a specific method for determining the data variation, and because of sufficient randomness, the quality of the optimized configuration result obtained through screening is higher, and the working efficiency is further improved.

With reference to the first implementation manner of the first aspect, in a third implementation manner of the first aspect, the performing, based on the second probability, information exchange processing on the mutated configuration information set and the initialized configuration information set to obtain the mutated configuration information set includes:

comparing the second probability with threshold data to obtain a comparison result;

and when the second probability is greater than the threshold data, performing information exchange processing on the mutated configuration information set and the initialized configuration information set to obtain the mutated configuration information set.

The configuration optimization method provided by the embodiment of the invention shows the randomness of the exchange after the data variation by determining the specific method of the exchange after the data variation, and because of having sufficient randomness, the quality of the optimized configuration result obtained by screening is higher, and the working efficiency is further improved.

With reference to the first aspect, in a fourth implementation manner of the first aspect, the obtaining an initialization configuration information set includes:

and acquiring the initialization configuration information set to determine the performance index and the resource utilization condition of the target database.

According to the configuration optimization method provided by the embodiment of the invention, through determining the configuration items, the related configuration data can be accurately mutated, the configuration failure caused by data error mutation in the mutation process is avoided, and the working efficiency is further improved.

With reference to the first aspect, in a fifth implementation manner of the first aspect, the calculating an adaptive value corresponding to the mutated configuration includes:

acquiring a first weight corresponding to each performance index and a second weight corresponding to each resource utilization condition, wherein the first weight is larger than zero, and the second weight is smaller than zero;

and calculating the weighted sum of the first weight and the second weight, the corresponding performance index and the resource utilization condition, and determining an adaptive value corresponding to the varied configuration.

According to the configuration optimization method provided by the embodiment of the invention, the variation result can be definitely judged through the calculation process of the definite adaptive value, a foundation is provided for subsequent screening of high-quality variation data, and the working efficiency is further improved.

With reference to the first aspect, in a sixth implementation manner of the first aspect, the method further includes:

and when the variation times reach a preset variation time threshold, determining the configuration information set corresponding to the target adaptive value as a target configuration information set.

According to the configuration optimization method provided by the embodiment of the invention, through determining the number of times of variation, the problem that meaningless variation continues under the condition that the optimal configuration cannot be obtained even after multiple times of variation is solved, and the working efficiency is further improved.

According to a second aspect, an embodiment of the present invention provides a configuration optimization apparatus, including:

the acquisition module is used for acquiring an initialization configuration information set of a target database;

the first processing unit is used for performing mutation processing on each configuration information in the initialization configuration information set to obtain a mutated configuration information set;

a second processing unit, configured to calculate adaptive values corresponding to the initialized configuration information set and the mutated configuration;

a third processing unit, configured to select a maximum adaptive value of the adaptive values as a target adaptive value;

and the fourth processing unit is configured to determine, when the target adaptation value reaches an optimization threshold, a configuration information set corresponding to the target adaptation value as a target configuration information set.

According to a third aspect, an embodiment of the present invention provides an electronic device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing therein computer instructions, and the processor executing the computer instructions to perform the configuration optimization method according to the first aspect or any one of the embodiments of the first aspect.

According to a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the configuration optimization method described in the first aspect or any one of the implementation manners of the first aspect.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a flow diagram of a configuration optimization method according to an embodiment of the invention;

FIG. 2 is a flow diagram of a configuration optimization method according to an embodiment of the present invention;

FIG. 3 is a flow diagram of a configuration optimization method according to an embodiment of the invention;

FIG. 4 is a block diagram of a configuration optimization apparatus according to an embodiment of the present invention;

fig. 5 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to 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., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In describing the present invention, it is noted that the term "and/or" as used in this specification and the appended claims refers to and includes any and all combinations of one or more of the associated listed items.

Furthermore, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

In accordance with an embodiment of the present invention, there is provided a configuration optimization method embodiment, it being noted that the steps illustrated in the flowchart of the figure may be performed in a computer system, such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.

In this embodiment, a configuration optimization method is provided, which may be used in an electronic device, such as a computer, a server, a tablet computer, and the like, fig. 1 is a flowchart of the configuration optimization method according to an embodiment of the present invention, and as shown in fig. 1, the flowchart includes the following steps:

s11, acquiring an initialization configuration information set of the target database;

specifically, the initialization configuration information set of the target database has a certain value range, and the value is required to be taken according to a preset range.

For example, in practical application, it is assumed that a database DB _ a exists, where a value of the initialization configuration information set msg1 needs to be taken, and assuming that the value range of msg1 is [20, 30], the value of msg1 may be 25, but the value of msg1 cannot be 10 or 40.

Details about this step will be described later.

S12, performing mutation processing on each configuration information in the initialization configuration information set to obtain a mutated configuration information set;

specifically, mutation information is initialized to perform mutation processing according to a preset mutation rule.

For example, assume that there is one set of initialization configuration information msg2, assume that msg2 has a value of 25, and after mutation, msg2 has a value of 52.

Details about this step will be described later.

S13, calculating adaptive values corresponding to the initialized configuration information set and the mutated configuration;

specifically, a formula is preset to calculate the adaptive value.

For example, assuming that the configuration information set 25 and the variant configuration 52 exist, the preset formulas are fed, and the adaptive values are calculated to be 0.7 and 0.9, respectively.

It should be noted that, in this embodiment, the correspondence relationship between 25 and 0.7, and the correspondence relationship between 52 and 0.9 are only schematic, and are not strictly calculated mathematically, and in practical application, calculating the corresponding adaptive value requires acquiring the related calculation parameters according to the practical application scenario, which is only an example here.

Details about this step will be described later.

S14, selecting the maximum adaptive value in the adaptive values as a target adaptive value;

specifically, still taking the above-described adaptive values 0.7 and 0.9 as examples, of these two adaptive values, 0.9 is selected as the target adaptive value.

And S15, when the target adaptive value reaches the optimization threshold value, determining the configuration information set corresponding to the target adaptive value as a target configuration information set.

Specifically, assuming that the optimization threshold is 0.8, taking the target adaptive value as 0.9 as an example, and determining the configuration information set corresponding to the target adaptive value as the target configuration information set when the target adaptive value is 0.9.

In this embodiment, a configuration optimization method is provided, which may be used in an electronic device, such as a computer, a server, a tablet computer, and the like, fig. 2 is a flowchart of the configuration optimization method according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:

s21, acquiring an initialization configuration information set of the target database;

specifically, S21 includes:

s211, acquiring the initialization configuration information set to determine the performance index and the resource utilization condition of the target database.

Specifically, for example, it is assumed that there are two performance indexes and two types of resource utilization conditions, and it is further assumed that configuration parameters corresponding to the two performance indexes and the two types of resource utilization conditions are A, B, C, D respectively, where the value ranges of the four parameters are as shown in table 1 below:

parameter(s)	Value range
		A	[2000,4000]
B	[1200,2400]
		C	[10M,30M]
D	[10G,40G]

TABLE 1

Taking values according to a preset range, assuming that 30 data are required, the parameters are stored in a form of four-dimensional data, for example, 11 th data may be recorded as:

s22, performing mutation processing on each configuration information in the initialization configuration information set to obtain a mutated configuration information set;

specifically, S22 includes:

s221, carrying out information mutation processing on the initialization configuration information set based on the first probability to obtain a mutated configuration information set;

in some optional implementations of this embodiment, the step S221 may include:

(1) converting the initialization configuration information set into corresponding binary information;

it is assumed that there is a set of configuration information,

can be converted into

(2) And modifying the data in the binary information based on the first probability, and determining a mutated configuration information set.

Assuming that the first probability is 0.6, it indicates that each bit has a probability of 0.6 negated, and when one bit is negated, the output information remains as described above

For example, assume that the second bit in 11 is inverted and obtained

And S222, performing information exchange processing on the mutated configuration information set and the initialized configuration information set based on a second probability to obtain the mutated configuration information set.

In some optional implementations of this embodiment, the step S222 may include:

(1) comparing the second probability with threshold data to obtain a comparison result;

specifically, the threshold data is a random number in the [0, 1] interval. And comparing the second probability with threshold data to obtain a comparison result.

(2) And when the second probability is greater than the threshold data, performing information exchange processing on the mutated configuration information set and the initialized configuration information set to obtain the mutated configuration information set.

In particular, it is assumed that the above is still true

And

for example, assuming that the threshold data is 0.6 and the second probability is 0.8, the mutated configuration information set and the initialized configuration information set are subjected to information exchange processing.

Further, the modified parameter is a second parameter, where a serial number of the parameter is J, in the above example, J is 2, a random number K is set, a value range of K is [1, D ], D is a dimension of the corresponding configuration information set, in the above example, D is 4, and when the random number K is J, the mutated configuration information set and the initialized configuration information set are also subjected to information exchange processing.

Further, the above example is summarized as the following formula:

s23, calculating adaptive values corresponding to the initialized configuration information set and the mutated configuration;

specifically, S23 includes:

s231, acquiring a first weight corresponding to each performance index and a second weight corresponding to each resource utilization condition, wherein the first weight is greater than zero, and the second weight is smaller than zero;

specifically, it is obvious that in practical application, the higher the weight is, the better the data is, and in the using process, the less the data is, the better the data is, so the first weight is greater than zero, the second weight is less than zero, and meanwhile, the first weight is more than one, and the second weight is more than one.

S232, calculating a weighted sum of the first weight and the second weight, the corresponding performance index, and the resource utilization, and determining an adaptive value corresponding to the mutated configuration.

Specifically, the adaptation value may be calculated according to the following formula.

Wherein h is the number of the collected index types, A_hIs a value for the corresponding weight value,

the function is evaluated.

S24, selecting the maximum adaptive value in the adaptive values as a target adaptive value;

please refer to S14 in fig. 1, which is not described herein again.

And S25, when the target adaptive value reaches the optimization threshold value, determining the configuration information set corresponding to the target adaptive value as a target configuration information set.

Please refer to S15 in fig. 1, which is not described herein again.

As a specific application example of the present embodiment. As shown in fig. 3, the configuration optimization method includes:

s1, acquiring an initialization configuration information set of the target database;

s2, carrying out mutation operation on the configuration information set;

s3, exchanging the configuration information set based on the variation result;

s4, calculating the adaptive value of the configuration information set;

s5, judging whether the adaptive value reaches the optimization threshold value, if yes, executing a step S6, otherwise, executing a step S2;

s6, determining a target configuration information set.

In this embodiment, a configuration optimization apparatus is further provided, and the apparatus 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.

The present embodiment provides a configuration optimization apparatus, as shown in fig. 4, including:

an obtaining module 41, configured to obtain an initialization configuration information set of a target database;

a first processing unit 42, configured to perform mutation processing on each configuration information in the initialized configuration information set, so as to obtain a mutated configuration information set;

a second processing unit 43, configured to calculate adaptive values corresponding to the initialized configuration information set and the mutated configuration;

a third processing unit 44, configured to select a maximum adaptive value of the adaptive values as a target adaptive value;

a fourth processing unit 45, configured to determine, when the target adaptation value reaches an optimization threshold, a configuration information set corresponding to the target adaptation value as a target configuration information set.

The firmware refresh apparatus in this embodiment is presented in the form of functional units, where a unit refers to an ASIC circuit, a processor and a memory executing one or more software or fixed programs, and/or other devices that may provide the above-described functionality.

Further functional descriptions of the modules are the same as those of the corresponding embodiments, and are not repeated herein.

An embodiment of the present invention further provides an electronic device, which has the configuration optimization apparatus shown in fig. 5.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an alternative embodiment of the present invention, and as shown in fig. 5, the electronic device may include: at least one processor 51, such as a CPU (Central Processing Unit), at least one communication interface 53, memory 54, at least one communication bus 52. Wherein a communication bus 52 is used to enable the connection communication between these components. The communication interface 53 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 53 may also include a standard wired interface and a standard wireless interface. The Memory 54 may be a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 54 may alternatively be at least one memory device located remotely from the processor 51. Wherein the processor 51 may be in connection with the apparatus described in fig. 5, the memory 54 stores an application program, and the processor 51 calls the program code stored in the memory 54 for performing any of the above-mentioned method steps.

The communication bus 52 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 52 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.

The memory 54 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated: HDD) or a solid-state drive (english: SSD); the memory 54 may also comprise a combination of the above types of memories.

The processor 51 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.

The processor 51 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.

Optionally, the memory 54 is also used to store program instructions. The processor 51 may call program instructions to implement the configuration optimization method as shown in any of the embodiments of the present application.

Embodiments of the present invention further provide a non-transitory computer storage medium, where a computer-executable instruction is stored in the computer storage medium, and the computer-executable instruction may execute the configuration optimization method in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.

Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for configuration optimization, comprising:

acquiring an initialization configuration information set of a target database;

2. The method according to claim 1, wherein the performing mutation processing on each configuration information in the initialized configuration information set to obtain a mutated configuration information set includes:

3. The method of claim 2, wherein performing information mutation processing on the initialization configuration information set based on the first probability to obtain a mutated configuration information set comprises:

4. The method according to claim 2, wherein the performing information exchange processing on the mutated configuration information set and the initialized configuration information set based on the second probability to obtain the mutated configuration information set comprises:

5. The method of claim 1, wherein obtaining the initialization configuration information set comprises:

6. The method of claim 1, wherein the calculating an adaptation value corresponding to the mutated configuration comprises:

7. The method of claim 1, further comprising:

8. A configuration optimization apparatus, comprising:

9. An electronic device, 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 to cause the at least one processor to perform the steps of the method of any one of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1-7.