CN111124516B - Server parameter reduction method and device and computer readable storage medium - Google Patents
Server parameter reduction method and device and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a server parameter reduction method, a device and a medium, which construct a difference matrix according to a plurality of acquired server sample parameters. Adding target elements which only contain single attribute information in the difference matrix to a reduction set; and zero the target element in the difference matrix. Calculating the probability value of each attribute information in the difference matrix, selecting the attribute information with the probability value meeting the preset condition, and adding the attribute information to the reduction set; setting elements in the difference matrix, which are not empty with the intersection of the reduction set, to zero; the operation ends until the difference matrix is an empty set. The reduction set contains important parameters that affect the performance of the server. The parameter adjustment of the server is carried out depending on the attribute information in the reduction set, so that the efficiency of optimizing the system performance can be improved. Important attribute information is selected based on a mode of combining the difference matrix and attribute selection, the scale of logic operation and the loss of information in the calculation process are reduced to a certain extent, and the efficiency of attribute information screening is improved.
Description
Technical Field
The present invention relates to the field of server technologies, and in particular, to a method and an apparatus for reducing server parameters, and a computer-readable storage medium.
Background
In the informatization context, the performance of the enterprise application system is related to the informatization level of the enterprise. The application system with good performance can keep higher throughput under the condition of high load of the server. Achieving this goal requires that the application server maintain a high availability.
However, with the increase of enterprise application systems, the expansion of application range and the increase of application data and service time, the performance of the application systems is reduced, and system maintenance personnel need to optimize the application systems appropriately according to specific situations.
The traditional optimization method is to adjust server parameters, one way can be based on technical document analysis of the server, so as to adjust parameters of the server and the system application platform, and the other way can utilize a mature optimization tool to analyze system performance and then adjust server parameters. The types of server parameters are various, the influence degree of the server parameters on the operation performance of the server is different, the traditional server performance optimization mode depends on the experience of operation and maintenance personnel to a great extent, and the time is long.
Therefore, how to improve the efficiency of server performance optimization is a problem to be solved by those skilled in the art.
Disclosure of Invention
Embodiments of the present invention provide a method, an apparatus, and a computer-readable storage medium for server parameter reduction, which can improve efficiency of server performance optimization.
To solve the foregoing technical problem, an embodiment of the present invention provides a server parameter reduction method, including:
constructing a difference matrix according to the obtained multiple server sample parameters;
extracting target elements only containing single attribute information in the difference matrix, and adding the target elements to a reduction set; and zeroing the target element in the difference matrix;
calculating probability values of all attribute information in the difference matrix, and selecting the attribute information with the probability values meeting preset conditions to be added to the reduction set; and zeroing out elements of the difference matrix that are not empty of intersections with the reduced set;
judging whether the difference matrix is an empty set or not;
if not, returning to calculate the probability value of each attribute information in the difference matrix, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set; and zeroing out elements of the difference matrix that are not empty from the intersection of the reduction set;
if yes, the operation is ended.
Optionally, the constructing a difference matrix according to the obtained multiple server sample parameters includes:
processing the acquired parameters of the plurality of server samples according to a preset classification rule to obtain attribute information corresponding to the plurality of samples;
and constructing a difference matrix based on the distinguishing characteristics of the attribute information of any two samples.
Optionally, adding the attribute information with the probability value meeting a preset condition to the reduction set includes:
and selecting attribute information with the maximum probability value and adding the attribute information to the reduction set.
Optionally, adding the attribute information with the probability value meeting a preset condition to the reduction set includes:
sequencing the attribute information according to the descending order of the probability value;
and selecting the first N pieces of attribute information to be added to the reduction set.
Optionally, after the difference matrix is an empty set, the method further includes:
and saving the attribute information contained in the reduction set to a preset position.
The embodiment of the invention also provides a server parameter reduction device, which comprises a construction unit, an extraction unit, a zero setting unit, a selection unit and a judgment unit;
the construction unit is used for constructing a difference matrix according to the acquired multiple server sample parameters;
the extracting unit is configured to extract a target element that only includes single attribute information in the difference matrix, and add the target element to a reduction set;
the zero setting unit is used for setting the target element in the difference matrix to zero;
the selecting unit is used for calculating the probability value of each attribute information in the difference matrix, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set;
the zero setting unit is also used for setting zero to the elements of the difference matrix which are not empty with the intersection of the reduction set;
the judging unit is used for judging whether the difference matrix is an empty set or not; if not, returning to the selection unit; if yes, the operation is ended.
Optionally, the constructing unit is specifically configured to process the acquired parameters of the multiple server samples according to a preset classification rule, so as to obtain attribute information corresponding to the multiple samples; and constructing a difference matrix based on the distinguishing characteristics of the attribute information of any two samples.
Optionally, the selecting unit is specifically configured to select attribute information with the largest probability value and add the attribute information to the reduction set.
Optionally, the selecting unit is specifically configured to sort the attribute information according to a descending order of the probability values; and selecting the first N pieces of attribute information to be added to the reduction set.
Optionally, the system further comprises a storage unit;
and the storage unit is used for storing the attribute information contained in the reduction set to a preset position after the difference matrix is an empty set.
The embodiment of the invention also provides a server parameter reduction device, which comprises:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the server parameter reduction method as in any one of the above.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the server parameter reduction method according to any one of the above.
According to the technical scheme, the difference matrix is constructed according to the obtained multiple server sample parameters. When the target element only containing single attribute information exists in the difference matrix, the target element is the attribute information necessary for distinguishing the sample data, so that the target element can be added to the reduction set; and zero the target element in the difference matrix. Calculating probability values of all attribute information in the difference matrix, wherein the greater the probability value is, the more times the attribute information appears is, the higher the importance degree is, so that the attribute information with the probability value meeting the preset condition can be selected and added to the reduction set; and zeroes out the elements of the difference matrix that are not empty of intersections with the reduction set. And judging whether the difference matrix is an empty set. When the difference matrix is not an empty set, calculating the probability value of each attribute information in the difference matrix again, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set; and setting the non-empty intersection elements of the difference matrix and the reduction set to zero until the difference matrix is an empty set, and ending the operation. The reduction set contains screened attribute information which is an important parameter influencing the operation performance of the server. The parameter adjustment of the server is carried out depending on the attribute information in the reduction set, so that the efficiency of optimizing the system performance can be improved. Important attribute information is selected based on a mode of combining the difference matrix and attribute selection, the purpose of locking important data is achieved, the scale of logic operation and the loss of information in the calculation process are reduced to a certain extent, and the efficiency of attribute information screening is improved.
Drawings
In order to illustrate the embodiments of the present invention more clearly, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained by those skilled in the art without inventive effort.
Fig. 1 is a flowchart of a server parameter reduction method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a server parameter reduction apparatus according to an embodiment of the present invention;
fig. 3 is a schematic hardware structure diagram of a server parameter reduction apparatus according to an embodiment of the present invention.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without any creative work belong to the protection scope of the present invention.
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Next, a server parameter reduction method provided by an embodiment of the present invention is described in detail. Fig. 1 is a flowchart of a server parameter reduction method according to an embodiment of the present invention, where the method includes:
s101: and constructing a difference matrix according to the obtained multiple server sample parameters.
The server sample parameters include performance parameters of the server during operation, for example, temperature values of server devices, CPU utilization, disk utilization, and other information.
In a specific implementation, a plurality of server sample parameters can be obtained by collecting performance parameters of the server in different time periods.
Each server sample parameter may be regarded as a sample, and in order to select important data included in the sample, in the embodiment of the present invention, a difference matrix may be constructed based on a difference between any two samples.
In view of the fact that each server sample parameter contains a large amount of data and redundant information may exist, in the embodiment of the present invention, a plurality of acquired server sample parameters may be processed according to a preset classification rule, so as to obtain attribute information corresponding to each of a plurality of samples.
The classification rule includes a classification for classifying the server sample parameters, and in a specific implementation, the data included in the server sample parameters may be classified into a corresponding classification. A category can be considered as a kind of attribute information. The attribute information corresponding to each sample is different.
In the embodiment of the invention, the classification is not carried out on the conventional data which basically does not influence the running performance of the server, such as information such as time stamps. Therefore, the server sample parameters are processed through the classification rules, redundant data and conventional data can be removed, and therefore each sample is more refined, simplified and normalized.
In order to ensure the diversity of the sample information, a difference matrix can be constructed based on the distinguishing characteristics of the attribute information of any two samples. The element in the ith row and the jth column in the difference matrix represents the distinguishing characteristic of the attribute information of the ith sample and the jth sample.
It is assumed that the sample 1 includes attribute information a, attribute information b, attribute information c, and attribute information e, and the sample 2 includes attribute information a, attribute information b, and attribute information d, where the distinguishing features of the sample 1 and the sample 2 are the attribute information c, the attribute information d, and the attribute information e.
For the same sample, there is no distinguishing feature, so the element is set to zero at the position where the number of rows and columns in the difference matrix is equal. The difference matrix is a symmetric matrix, and only the lower triangular matrix is needed to be calculated during calculation.
S102: extracting target elements only containing single attribute information in the difference matrix, and adding the target elements to the reduction set; and zero the target element in the difference matrix.
In the embodiment of the invention, an independent reduction set can be constructed and used for recording the screened attribute information.
If the difference matrix has an element containing only single attribute information, it indicates that the attribute information is the attribute information necessary for distinguishing sample data, and therefore the attribute information is a core attribute, and at this time, the attribute information may be added to the reduction set. To facilitate differentiation from other elements, an element containing only a single attribute information may be referred to as a target element.
For convenience of subsequent screening, after the target element only containing single attribute information is added to the reduction set, the value of the position of the target element in the difference matrix may be set to zero.
S103: calculating the probability value of each attribute information in the difference matrix, selecting the attribute information with the probability value meeting the preset condition, and adding the attribute information to the reduction set; and zeroes out the elements of the difference matrix that are not empty of intersections with the reduction set.
In the difference matrix, the number of times of occurrence of certain attribute information is larger, which indicates that the attribute information can distinguish more objects, and conversely, indicates that the attribute information can distinguish less objects, which has less influence on the operation state of the whole server.
In a specific implementation, the attribute information with the largest probability value can be selected and added to the reduction set.
Or sorting the attribute information according to the descending order of the probability value; and selecting the first N pieces of attribute information to be added to the reduction set.
The value of N may be set according to actual requirements, and may specifically be determined according to the number of categories of the attribute information, for example, a first category of the attribute information is 20, and N may be 2.
After the attribute information with the probability value meeting the preset condition is added to the reduction set, at this time, the attribute information contained in the reduction set may be compared with each element in the difference matrix, and when an intersection between the attribute information contained in the reduction set and an element in the difference matrix is not empty, it is indicated that the attribute information contained in the element and having an effect on the operating state of the server has been added to the reduction set, and at this time, a value of a position where the element is located may be set to zero.
S104: and judging whether the difference matrix is an empty set.
When the difference matrix is not an empty set, it indicates that the difference matrix still contains attribute information having a large influence on the operation performance of the server, and at this time, the process may return to S103 to continue the screening of the attribute information.
When the difference matrix is an empty set, it indicates that the screening of the attribute information is completed, and the operation may be ended.
The reduction set contains screened attribute information which is an important parameter influencing the operation performance of the server. When the difference matrix is an empty set, the attribute information contained in the reduction set can be stored to a preset position, so that the reduction set can be called when the system performance needs to be optimized subsequently.
Wherein the preset position may point to a non-volatile storage medium in the server. By storing the attribute information in the reduction set into the nonvolatile storage medium, the security of the attribute information in the reduction set can be ensured, and the subsequent calling and reading can be facilitated.
According to the technical scheme, the difference matrix is constructed according to the obtained multiple server sample parameters. When the target element only containing single attribute information exists in the difference matrix, the target element is the attribute information necessary for distinguishing the sample data, so that the target element can be added to the reduction set; and zero the target element in the difference matrix. Calculating probability values of all attribute information in the difference matrix, wherein the greater the probability value is, the more times the attribute information appears is, the higher the importance degree is, so that the attribute information with the probability value meeting the preset condition can be selected and added to the reduction set; and zeroes out the elements of the difference matrix that are not empty of intersections with the reduction set. And judging whether the difference matrix is an empty set. When the difference matrix is not an empty set, calculating the probability value of each attribute information in the difference matrix again, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set; and setting the non-empty intersection elements of the difference matrix and the reduction set to zero until the difference matrix is an empty set, and ending the operation. The reduction set contains screened attribute information which is an important parameter influencing the operation performance of the server. The parameter adjustment of the server is carried out depending on the attribute information in the reduction set, so that the efficiency of optimizing the system performance can be improved. Important attribute information is selected based on a mode of combining the difference matrix and attribute selection, the purpose of locking important data is achieved, the scale of logic operation and the loss of information in the calculation process are reduced to a certain extent, and the efficiency of attribute information screening is improved.
Fig. 2 is a schematic structural diagram of a server parameter reduction apparatus according to an embodiment of the present invention, which includes a constructing unit 21, an extracting unit 22, a zeroing unit 23, a selecting unit 24, and a determining unit 25;
the construction unit 21 is configured to construct a difference matrix according to the obtained multiple server sample parameters;
the extracting unit 22 is configured to extract a target element that only includes single attribute information in the difference matrix, and add the target element to the reduction set;
a zero setting unit 23, configured to zero out a target element in the difference matrix;
the selecting unit 24 is configured to calculate a probability value of each attribute information in the difference matrix, select an attribute information with a probability value meeting a preset condition, and add the attribute information to the reduction set;
the zero-setting unit 23 is further configured to zero out elements in the difference matrix that are not empty from the intersection with the reduction set;
a judging unit 25, configured to judge whether the difference matrix is an empty set; if not, returning to the selection unit 24; if yes, the operation is ended.
Optionally, the constructing unit is specifically configured to process the acquired parameters of the multiple server samples according to a preset classification rule, so as to obtain attribute information corresponding to the multiple samples; and constructing a difference matrix based on the distinguishing characteristics of the attribute information of any two samples.
Optionally, the selecting unit is specifically configured to select the attribute information with the largest probability value and add the attribute information to the reduction set.
Optionally, the selecting unit is specifically configured to sort the attribute information according to a descending order of the probability values; and selecting the first N pieces of attribute information to be added to the reduction set.
Optionally, the system further comprises a storage unit;
and the storage unit is used for storing the attribute information contained in the reduction set to a preset position after the difference matrix is an empty set.
The description of the features in the embodiment corresponding to fig. 2 may refer to the related description of the embodiment corresponding to fig. 1, and is not repeated here.
According to the technical scheme, the difference matrix is constructed according to the obtained multiple server sample parameters. When the target element only containing single attribute information exists in the difference matrix, the target element is the attribute information necessary for distinguishing the sample data, so that the target element can be added to the reduction set; and zero the target element in the difference matrix. Calculating probability values of all attribute information in the difference matrix, wherein the greater the probability value is, the more times the attribute information appears is, the higher the importance degree is, so that the attribute information with the probability value meeting the preset condition can be selected and added to the reduction set; and zeroes out the elements of the difference matrix that are not empty of intersections with the reduction set. And judging whether the difference matrix is an empty set. When the difference matrix is not an empty set, calculating the probability value of each attribute information in the difference matrix again, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set; and setting the non-empty intersection elements of the difference matrix and the reduction set to zero until the difference matrix is an empty set, and ending the operation. The reduction set contains screened attribute information which is an important parameter influencing the operation performance of the server. The parameter adjustment of the server is carried out depending on the attribute information in the reduction set, so that the efficiency of optimizing the system performance can be improved. Important attribute information is selected based on a mode of combining the difference matrix and attribute selection, the purpose of locking important data is achieved, the scale of logic operation and the loss of information in the calculation process are reduced to a certain extent, and the efficiency of attribute information screening is improved.
Fig. 3 is a schematic hardware structure diagram of a server parameter reduction apparatus 30 according to an embodiment of the present invention, including:
a memory 31 for storing a computer program;
a processor 32 for executing a computer program for carrying out the steps of any of the server parameter reduction methods described above.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of any of the server parameter reduction methods described above.
The above description details a server parameter reduction method, apparatus, and computer-readable storage medium according to embodiments of the present invention. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Claims (10)
1. A method for server parameter reduction, comprising:
constructing a difference matrix according to the obtained multiple server sample parameters;
extracting target elements only containing single attribute information in the difference matrix, and adding the target elements to a reduction set; and zeroing the target element in the difference matrix;
calculating probability values of all attribute information in the difference matrix, and selecting the attribute information with the probability values meeting preset conditions to be added to the reduction set; and zeroing out elements of the difference matrix that are not empty of intersections with the reduced set;
judging whether the difference matrix is an empty set or not;
if not, returning to calculate the probability value of each attribute information in the difference matrix, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set; and zeroing out elements of the difference matrix that are not empty from the intersection of the reduction set;
if yes, the operation is ended.
2. The method of claim 1, wherein constructing the difference matrix according to the obtained plurality of server sample parameters comprises:
processing the acquired parameters of the plurality of server samples according to a preset classification rule to obtain attribute information corresponding to the plurality of samples;
and constructing a difference matrix based on the distinguishing characteristics of the attribute information of any two samples.
3. The method of claim 1, wherein adding attribute information to the reduction set, the extracted probability value of which satisfies a preset condition, comprises:
and selecting attribute information with the maximum probability value and adding the attribute information to the reduction set.
4. The method of claim 1, wherein adding attribute information to the reduction set, the extracted probability value of which satisfies a preset condition, comprises:
sequencing the attribute information according to the descending order of the probability value;
and selecting the first N pieces of attribute information to be added to the reduction set.
5. The method according to any one of claims 1-4, further comprising, after the difference matrix is an empty set:
and saving the attribute information contained in the reduction set to a preset position.
6. A server parameter reduction device is characterized by comprising a construction unit, an extraction unit, a zero setting unit, a selection unit and a judgment unit;
the construction unit is used for constructing a difference matrix according to the acquired multiple server sample parameters;
the extracting unit is configured to extract a target element that only includes single attribute information in the difference matrix, and add the target element to a reduction set;
the zero setting unit is used for setting the target element in the difference matrix to zero;
the selecting unit is used for calculating the probability value of each attribute information in the difference matrix, and selecting the attribute information with the probability value meeting the preset condition to be added to the reduction set;
the zero setting unit is also used for setting zero to the elements of the difference matrix which are not empty with the intersection of the reduction set;
the judging unit is used for judging whether the difference matrix is an empty set or not; if not, returning to the selection unit; if yes, the operation is ended.
7. The apparatus according to claim 6, wherein the constructing unit is specifically configured to process the obtained parameters of the plurality of server samples according to a preset classification rule, so as to obtain attribute information corresponding to each of the plurality of samples; and constructing a difference matrix based on the distinguishing characteristics of the attribute information of any two samples.
8. The apparatus according to claim 6 or 7, further comprising a saving unit;
and the storage unit is used for storing the attribute information contained in the reduction set to a preset position after the difference matrix is an empty set.
9. A server parameter reduction apparatus, comprising:
a memory for storing a computer program;
a processor for executing the computer program for carrying out the steps of the server parameter reduction method according to any of claims 1 to 5.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the server parameter reduction method according to any one of claims 1 to 5.
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