CN112463564A - Method and device for determining correlation index influencing host state - Google Patents
Method and device for determining correlation index influencing host state Download PDFInfo
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Abstract
The invention discloses a method and a device for determining correlation indexes influencing a host state, which can be used in the financial field or other technical fields, and the method comprises the following steps: acquiring a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state; determining a Euclidean distance between the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index; and if the Euclidean distance is smaller than a preset threshold value, determining the target index as a correlation index influencing the state of the host. The invention realizes more accurate and rapid confirmation whether the host index is the correlation index of the host state, and is beneficial to improving the effect of abnormal attribution of the host.
Description
Technical Field
The invention relates to the technical field of host anomaly analysis, in particular to a method and a device for determining correlation indexes influencing a host state.
Background
The exception checking of the large host is important work of system operation and maintenance personnel, and the key for effectively solving the problem is how to quickly and accurately locate the source of the exception. The host has various host indexes during the operation, and the host abnormity attribution efficiency can be effectively improved by determining which host indexes have larger influence on the host operation state. At present, how to determine whether a host index has a great influence on the running state of a host depends on manual experience mostly, and the accuracy and the reliability are not high.
Disclosure of Invention
In order to solve the technical problems in the background art, the present invention provides a method and an apparatus for determining a correlation index affecting a host state.
To achieve the above object, according to one aspect of the present invention, there is provided a method for determining a correlation index affecting a state of a host, the method comprising:
acquiring a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state;
determining a Euclidean distance between the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index;
and if the Euclidean distance is smaller than a preset threshold value, determining the target index as a correlation index influencing the state of the host.
Optionally, before determining the euclidean distance between the time-series serialized vector of the host state and the time-series serialized vector of the index state of the target index, the method further includes:
adding a preset offset to all second values in the time-series serialized vector of the indicator state of the target indicator.
Optionally, the determining the euclidean distance between the time-series serialized vector of the host state and the time-series serialized vector of the index state of the target index includes:
respectively performing dimensionality reduction on the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index;
and calculating the Euclidean distance between the time sequence serialized vector of the host state after the dimension reduction processing and the time sequence serialized vector of the index state of the target index after the dimension reduction processing.
Optionally, the method for determining the correlation index affecting the host state further includes:
serializing host state data in a preset time period to obtain a time sequence serialized vector of the host state;
and carrying out serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialization vector of the index state of the target index.
In order to achieve the above object, according to another aspect of the present invention, there is provided an apparatus for determining a correlation index affecting a state of a host, the apparatus comprising:
the time sequence serialization vector acquisition unit is used for acquiring a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state;
the Euclidean distance calculating unit is used for determining the Euclidean distance between the time sequence serialization vector of the host machine state and the time sequence serialization vector of the index state of the target index;
and the determining unit is used for determining the target index as a correlation index influencing the state of the host when the Euclidean distance is smaller than a preset threshold.
Optionally, the apparatus for determining a correlation index affecting a state of a host further includes:
and the offset processing unit is used for adding a preset offset to all second numerical values in the time sequence serialization vector of the index state of the target index.
Optionally, the euclidean distance calculating unit includes:
the dimension reduction processing module is used for respectively carrying out dimension reduction processing on the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index;
and the calculation module is used for calculating the Euclidean distance between the time sequence serialized vector of the host state after the dimension reduction processing and the time sequence serialized vector of the index state of the target index after the dimension reduction processing.
Optionally, the apparatus for determining a correlation index affecting a state of a host further includes:
the first time sequence serialization vector generation unit is used for carrying out serialization processing on host state data in a preset time period to obtain a time sequence serialization vector of the host state;
and the second time sequence serialized vector generation unit is used for carrying out serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialized vector of the index state of the target index.
In order to achieve the above object, according to another aspect of the present invention, there is also provided a computer device, including a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the method for determining a correlation index affecting a state of a host when executing the computer program.
In order to achieve the above object, according to another aspect of the present invention, there is also provided a computer readable storage medium storing a computer program which, when executed in a computer processor, implements the steps in the above method of determining a correlation index affecting a state of a host.
The invention has the beneficial effects that: the embodiment of the invention determines whether the target index is the correlation index influencing the host state by calculating the Euclidean distance between the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index, realizes more accurate and rapid determination of whether one host index has larger influence on the host running state, and is beneficial to improving the effect of abnormal attribution of the host.
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 introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts. In the drawings:
FIG. 1 is a first flowchart of a method for determining correlation indicators affecting a state of a host according to an embodiment of the present invention;
FIG. 2 is a flow chart of determining Euclidean distance according to an embodiment of the present invention;
FIG. 3 is a second flowchart of a method of determining correlation indicators affecting host state according to an embodiment of the present invention;
FIG. 4 is a block diagram of an apparatus for determining correlation indicators affecting a state of a host according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention and the above-described drawings, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the method and apparatus for determining the correlation index that affects the state of the host according to the present invention can be used in the financial field, or other technical fields.
Fig. 1 is a first flowchart of a method for determining a correlation indicator affecting a host status according to an embodiment of the present invention, and as shown in fig. 1, the method for determining a correlation indicator affecting a host status according to the embodiment includes steps S101 to S103.
Step S101, a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index are obtained, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state.
In the embodiment of the present invention, the time sequence serialization vector of the host state is obtained by performing serialization processing on host state data in a preset time period. The host state includes an abnormal state and a normal state. In the embodiment of the present invention, the serialization processing is specifically that the abnormal state is represented by a first numerical value, and the normal state is represented by a second numerical value. In an alternative embodiment of the invention, the firstOne value may be 1 and the second value may be 0. For example, at time T, if the host state S is defined as an abnormal state as 1 and a normal state as 0, the host state S is at T1～TNThe time interval can be serialized into a vector S consisting of 0 and 11，S2，......,SN}。
In the embodiment of the present invention, similar to the time sequence serialization vector of the host state, the time sequence serialization vector of the index state of the target index is obtained by performing serialization processing on the index state data of the target index in the preset time period. The index state also includes an abnormal state and a normal state. For example, database state indexes are collected, the rule is that the database state indexes are normally started and are serialized into 0, the database state indexes are abnormally stopped and are serialized into 1; and (4) collecting a copy delay index, wherein the rule is that the copy delay index is normal when the delay does not exceed 1 hour, and the serialization is 0, otherwise, the serialization is 1. The database index, the replication delay index K is at T1～TNThe time intervals can be serialized into vectors K consisting of 0 and 11，K2，......,KN}。
In alternative embodiments of the present invention, the target index may be a plurality of indexes that the host runs, such as a database index, a replication delay index, and the like.
Step S102, determining Euclidean distance between the time sequence serialization vector of the host machine state and the time sequence serialization vector of the index state of the target index.
Step S103, if the Euclidean distance is smaller than a preset threshold value, determining the target index as a correlation index influencing the state of the host.
In the embodiment of the present invention, if the euclidean distance is greater than or equal to the preset threshold, it is determined that the target indicator is not related to the host status.
Therefore, the Euclidean distance between the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index is calculated, so that whether the target index is the associated index influencing the host state is determined. Compared with the existing manual experience judgment, the method can accurately and quickly confirm whether a host index has a larger influence on the running state of the host, and is favorable for improving the effect of abnormal attribution of the host.
In an embodiment of the present invention, before determining the euclidean distance between the time-series serialized vector of the host state and the time-series serialized vector of the index state of the target index in step S102, the method of the present invention further includes:
adding a preset offset to all second values in the time-series serialized vector of the indicator state of the target indicator.
The invention defines the correlation between the host state and the index, and concretely comprises the following table 1. The abnormal index is strongly correlated when the host state is abnormal, the abnormal index is irrelevant when the host state is normal, and the normal index is weakly correlated when the host state is abnormal/normal.
TABLE 1
The influence indexes of the host state in the real scene may be multiple, that is, under the condition that a single index is normal, the associated state may be normal or abnormal, that is, a weak correlation scene of 0- >1\0- > 0. In order to distinguish the differences between strong correlation 1- >1 and weak correlation 0- >0, and between uncorrelated 1- >0 and weak correlation 0- >1, the present invention also corrects the index normal scenario, i.e. the index value is increased by the offset of δ, where δ ∈ (0, 1), as shown in table 2 below. Specifically, the present invention adds a preset offset δ to all second values in the time-series serialized vector of the indicator state of the target indicator.
| Index (I) | 1 | 1 | 0+δ | 0+ |
| Host state | ||||
| 1 | 0 | 1 | 0 | |
| Correlation | Strong correlation | Is not related | Weak correlation | Weak correlation |
TABLE 2
Fig. 2 is a flowchart of determining the euclidean distance according to the embodiment of the present invention, and as shown in fig. 2, the determining the euclidean distance between the time-series serialized vector of the host state and the time-series serialized vector of the index state of the target index in step S102 specifically includes step S201 and step S202.
Step S201, performing dimension reduction processing on the time-sequence serialized vector of the host state and the time-sequence serialized vector of the index state of the target index, respectively.
Host state SiAt T1～TNSerialization into
Wherein
Index KiAt T1～TNSerialization into
Wherein
The value of N is often large, so the host state SiAnd index KiIs a high-dimensional vector. In order to improve the calculation efficiency and the calculation result accuracy, the method also needs to project the high-dimensional vector into the low-dimensional vector.
In this embodiment of the present invention, in this step, a Principal component analysis (Principal components analysis) may be used to perform a dimension reduction process on the time-series serialized vector of the host state to obtain a feature vector of the host state, and a Principal component analysis (Principal components analysis) may be used to perform a dimension reduction process on the time-series serialized vector of the index state of the target index to obtain a feature vector of the target index. The feature vector of the obtained host state and the feature vector of the target index are both low-dimensional vectors.
Step S202, calculating Euclidean distances between the time sequence serialization vector of the host state after the dimension reduction processing and the time sequence serialization vector of the index state of the target index after the dimension reduction processing.
In the embodiment of the present invention, the time sequence serialized vector of the host state after the dimension reduction processing is the feature vector of the host state, and the index state of the target index after the dimension reduction processing is the feature vector of the target index. Calculating Euclidean distance between the characteristic vector of the host state and the characteristic vector of the target index, wherein the result is the Euclidean distance between the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index
Fig. 3 is a second flowchart of a method for determining a correlation index affecting a host status according to an embodiment of the present invention, and as shown in fig. 3, in an embodiment of the present invention, the method for determining a correlation index affecting a host status according to the present invention further includes step S301 and step S302.
Step S301, serializing host state data in a preset time period to obtain a time sequence serialized vector of the host state.
Step S302, performing serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialization vector of the index state of the target index.
As can be seen from the above embodiments, the method for determining the correlation index affecting the host status provided by the present invention has at least the following advantages:
1. the invention realizes the correlation analysis of the abnormal state of the host by using a machine learning method, and has better expansibility compared with the traditional mode which depends on manual experience.
2. The invention carries out binary serialization on the indexes according to normal and abnormal rules, quantifies key factors influencing abnormal states and ensures key information.
3. The method is based on multi-factor influence hypothesis after index serialization, corrects a normal index quantization value, and fits a real application scene.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Based on the same inventive concept, the embodiment of the present invention further provides an apparatus for determining a correlation index affecting a host status, which can be used to implement the method for determining a correlation index affecting a host status described in the above embodiment, as described in the following embodiment. Since the principle of solving the problem of the apparatus for determining the correlation index affecting the host state is similar to the method for determining the correlation index affecting the host state, the embodiment of the apparatus for determining the correlation index affecting the host state may refer to the embodiment of the method for determining the correlation index affecting the host state, and repeated details are omitted. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of a structure of an apparatus for determining a correlation indicator affecting a host state according to an embodiment of the present invention, and as shown in fig. 4, the apparatus for determining a correlation indicator affecting a host state according to an embodiment of the present invention includes: the device comprises a time sequence serialization vector acquisition unit 1, a Euclidean distance calculation unit 2 and a determination unit 3.
The time sequence serialization vector obtaining unit 1 is configured to obtain a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, where the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index include a first numerical value and a second numerical value, the first numerical value is used to represent an abnormal state, and the second numerical value is used to represent a normal state.
And the Euclidean distance calculating unit 2 is used for determining the Euclidean distance between the time sequence serialization vector of the host machine state and the time sequence serialization vector of the index state of the target index.
And the determining unit 3 is configured to determine the target index as a correlation index affecting a host state when the euclidean distance is smaller than a preset threshold.
In an embodiment of the present invention, the apparatus for determining a correlation index that influences a state of a host according to the present invention further includes:
and the offset processing unit is used for adding a preset offset to all second numerical values in the time sequence serialization vector of the index state of the target index.
In one embodiment of the present invention, the euclidean distance calculating unit includes:
the dimension reduction processing module is used for respectively carrying out dimension reduction processing on the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index;
and the calculation module is used for calculating the Euclidean distance between the time sequence serialized vector of the host state after the dimension reduction processing and the time sequence serialized vector of the index state of the target index after the dimension reduction processing.
In an embodiment of the present invention, the apparatus for determining a correlation index that influences a state of a host according to the present invention further includes:
the first time sequence serialization vector generation unit is used for carrying out serialization processing on host state data in a preset time period to obtain a time sequence serialization vector of the host state;
and the second time sequence serialized vector generation unit is used for carrying out serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialized vector of the index state of the target index.
To achieve the above object, according to another aspect of the present application, there is also provided a computer apparatus. As shown in fig. 5, the computer device comprises a memory, a processor, a communication interface and a communication bus, wherein a computer program that can be run on the processor is stored in the memory, and the steps of the method of the above embodiment are realized when the processor executes the computer program.
The processor may be a Central Processing Unit (CPU). The Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and units, such as the corresponding program units in the above-described method embodiments of the present invention. The processor executes various functional applications of the processor and the processing of the work data by executing the non-transitory software programs, instructions and modules stored in the memory, that is, the method in the above method embodiment is realized.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and such remote memory may be coupled to the processor via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more units are stored in the memory and when executed by the processor perform the method of the above embodiments.
The specific details of the computer device may be understood by referring to the corresponding related descriptions and effects in the above embodiments, and are not described herein again.
In order to achieve the above object, according to another aspect of the present application, there is also provided a computer readable storage medium storing a computer program which, when executed in a computer processor, implements the steps in the above method of determining a correlation index affecting a state of a host. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. 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) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for determining a correlation indicator that affects a state of a host, comprising:
acquiring a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state;
determining a Euclidean distance between the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index;
and if the Euclidean distance is smaller than a preset threshold value, determining the target index as a correlation index influencing the state of the host.
2. The method of claim 1, wherein before determining the euclidean distance between the time-ordered sequence of vectors of the host states and the time-ordered sequence of vectors of the target states, the method further comprises:
adding a preset offset to all second values in the time-series serialized vector of the indicator state of the target indicator.
3. The method according to claim 1 or 2, wherein the determining the euclidean distance between the time-series serialized vector of the host state and the time-series serialized vector of the target metric state comprises:
respectively performing dimensionality reduction on the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index;
and calculating the Euclidean distance between the time sequence serialized vector of the host state after the dimension reduction processing and the time sequence serialized vector of the index state of the target index after the dimension reduction processing.
4. The method of claim 1, further comprising:
serializing host state data in a preset time period to obtain a time sequence serialized vector of the host state;
and carrying out serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialization vector of the index state of the target index.
5. An apparatus for determining a correlation indicator that affects a state of a host, comprising:
the time sequence serialization vector acquisition unit is used for acquiring a time sequence serialization vector of a host state and a time sequence serialization vector of an index state of a target index, wherein the time sequence serialization vector of the host state and the time sequence serialization vector of the index state of the target index comprise a first numerical value and a second numerical value, the first numerical value is used for representing an abnormal state, and the second numerical value is used for representing a normal state;
the Euclidean distance calculating unit is used for determining the Euclidean distance between the time sequence serialization vector of the host machine state and the time sequence serialization vector of the index state of the target index;
and the determining unit is used for determining the target index as a correlation index influencing the state of the host when the Euclidean distance is smaller than a preset threshold.
6. The apparatus of claim 5, further comprising:
and the offset processing unit is used for adding a preset offset to all second numerical values in the time sequence serialization vector of the index state of the target index.
7. The apparatus according to claim 5 or 6, wherein the Euclidean distance calculating unit comprises:
the dimension reduction processing module is used for respectively carrying out dimension reduction processing on the time sequence serialized vector of the host state and the time sequence serialized vector of the index state of the target index;
and the calculation module is used for calculating the Euclidean distance between the time sequence serialized vector of the host state after the dimension reduction processing and the time sequence serialized vector of the index state of the target index after the dimension reduction processing.
8. The apparatus of claim 5, further comprising:
the first time sequence serialization vector generation unit is used for carrying out serialization processing on host state data in a preset time period to obtain a time sequence serialization vector of the host state;
and the second time sequence serialized vector generation unit is used for carrying out serialization processing on the index state data of the target index in the preset time period to obtain a time sequence serialized vector of the index state of the target index.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when executed in a computer processor, implements the method of any one of claims 1 to 4.
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