CN114625554A

CN114625554A - Fault repairing method and device, electronic equipment and storage medium

Info

Publication number: CN114625554A
Application number: CN202110982076.9A
Authority: CN
Inventors: 王立冬; 王琛; 郭思曼; 欧阳晔; 赵一鸣
Original assignee: Guangzhou Yaxin Technology Co ltd
Current assignee: Guangzhou Yaxin Technology Co ltd
Priority date: 2021-08-25
Filing date: 2021-08-25
Publication date: 2022-06-14

Abstract

The embodiment of the application provides a fault repairing method, and relates to the technical field of fault repairing. The method comprises the following steps: acquiring fault data, wherein the fault data comprises at least one piece of target index information with a fault; determining associated index information corresponding to the target index information from a preset constructed frequent pattern FP tree; restoring the target index information and the associated index information; wherein, the FP tree comprises the incidence relation of at least two index information. The embodiment of the application can effectively mine the relevance between the faults, so that the potential fault information can be mined in time, and the stability of the system can be better guaranteed.

Description

Fault repairing method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of fault repairing technologies, and in particular, to a fault repairing method and apparatus, an electronic device, and a storage medium.

Background

The system stability refers to a certain stable state of a system element under external influence, and colloquially refers to the ability of providing continuous and reliable service even in the face of various extreme situations or emergencies in the process of operation, operation and maintenance of the system.

In the existing scheme, in order to ensure the stability of the system, a plurality of system stability monitoring systems are arranged to monitor the system and discover faults of the system, and the system stability monitoring systems mainly monitor index information such as hardware, the system, applications and networks and discover the abnormity or fault of each index information in time so as to repair the system.

Disclosure of Invention

Embodiments of the present invention provide a fault repairing method, apparatus, electronic device and storage medium that overcome the above problems or at least partially solve the above problems.

In a first aspect, a fault repairing method is provided, which includes:

acquiring fault data, wherein the fault data comprises at least one piece of target index information with a fault;

determining associated index information corresponding to the target index information from a preset constructed frequent pattern FP tree;

restoring the target index information and the associated index information;

the FP tree comprises an incidence relation of at least two index information.

In one possible implementation manner, the method for constructing the FP-tree includes: collecting a fault sample set, wherein the fault sample set comprises at least one fault sample; the fault sample comprises at least one fault index information;

scanning a fault sample set, counting the occurrence frequency of each faulted index information, eliminating the faulted index information of which the occurrence frequency is less than the preset occurrence frequency, and putting the rest faulted index information and the corresponding occurrence frequency into a head pointer table of the FP tree according to a descending order arrangement rule;

and creating a root node of the FP tree, scanning each fault sample in sequence, linking the index information with faults in the fault sample to the root node in sequence, if the node corresponding to the index information with faults in the path where the fault sample is located already exists, adding one to the count of the node, and if the node corresponding to the index information with faults does not exist, adding the node corresponding to the index information with faults in the path.

In a possible implementation manner, determining, from a preset constructed FP tree, associated index information having a correspondence with target index information includes:

traversing the FP tree, and mining a frequent item set containing target index information; the frequent item set comprises target index information and candidate index information;

and determining associated index information corresponding to the target index information from the candidate index information based on a preset rule.

In one possible implementation manner, determining, from the candidate index information, associated index information having a correspondence relationship with the target index information based on a preset rule includes:

calculating the confidence coefficient between the target index information and the candidate index information according to a preset confidence coefficient calculation method;

and determining associated index information corresponding to the target index information from the candidate target information according to the confidence degree.

In one possible implementation manner, determining, from the candidate index information, associated index information having a correspondence relationship with the target index information according to the confidence degree includes:

constructing a binary recursive segmentation cart tree based on the confidence coefficient, wherein the nodes of the cart tree are candidate index information, the non-leaf nodes of the cart tree represent judgment conditions, and the edges of the cart tree represent judgment results; the leaf nodes of the cart tree represent candidate index information belonging to the corresponding judgment result;

and traversing the cart tree, and determining candidate index information corresponding to the leaf node with the confidence coefficient greater than the preset confidence coefficient threshold value as associated index information having a corresponding relationship with the target index information.

In one possible implementation, the repairing the target index information and the associated index information includes:

and calling a preset repairing method corresponding to the target and the associated index information from a preset database, and repairing the target index information and the associated index information.

In one possible implementation manner, the repairing the target index information and the associated index information further includes:

and if the target index information and the associated index information are failed to be repaired, sending alarm information to prompt failure repair.

In a second aspect, there is provided a fault repair device, the device comprising:

the acquisition module is used for acquiring fault data, and the fault data comprises at least one piece of target index information with a fault;

the relevant index information determining module is used for determining relevant index information which has a corresponding relation with the target index information from a preset constructed frequent pattern FP tree;

the restoration module is used for restoring the target index information and the associated index information;

the FP tree comprises an incidence relation of at least two index information.

In one possible implementation, the apparatus includes: an FP tree construction module; the FP tree construction module comprises:

the acquisition submodule is used for acquiring a fault sample set, and the fault sample set comprises at least one fault sample; the fault sample comprises at least one fault index information;

the scanning submodule is used for scanning the fault sample set, counting the occurrence frequency of each fault index information, eliminating the fault index information of which the occurrence frequency is less than the preset occurrence frequency, and putting the rest fault index information and the corresponding occurrence frequency into a head pointer table of the FP tree according to a descending order arrangement rule;

and the creating submodule is used for creating a root node of the FP tree, sequentially scanning each fault sample, sequentially linking the fault index information in the fault sample to the root node, if the node corresponding to the fault index information in the path where the fault sample is located already exists, adding one to the count of the node, and if the node corresponding to the fault index information does not exist, newly adding the node corresponding to the fault index information in the path.

In one possible implementation manner, the association index information determining module includes:

the frequent item set determining submodule is used for traversing the FP tree and mining a frequent item set containing target index information; the frequent item set comprises target index information and candidate index information;

and the associated index information determining submodule is used for determining associated index information which has a corresponding relation with the target index information from the candidate index information based on a preset rule.

In one possible implementation manner, the association index information determining sub-module further includes:

the confidence coefficient determining unit is used for calculating the confidence coefficient between the target index information and the candidate index information according to a preset confidence coefficient calculating method;

and the associated index information determining unit is used for determining the associated index information corresponding to the target index information from the candidate target information according to the confidence coefficient.

In one possible implementation manner, the correlation index information determining sub-module further includes:

a cart tree construction unit, configured to construct a binary recursive segmentation cart tree based on the confidence, where a node of the cart tree is candidate index information, a non-leaf node of the cart tree represents a determination condition, and an edge of the cart tree represents a determination result; the leaf nodes of the cart tree represent candidate index information belonging to the corresponding judgment result;

and the cart tree traversing unit is used for traversing the cart tree and determining candidate index information corresponding to the leaf node with the confidence coefficient greater than the preset confidence coefficient threshold value as the associated index information with the corresponding relation with the target index information.

In one possible implementation, the repair module includes:

and the repairing submodule is used for calling a preset repairing method corresponding to the target and the associated index information from a preset database and repairing the target index information and the associated index information.

In one possible implementation, the apparatus further includes:

and the warning module is used for sending warning information to prompt failure repair if the target index information and the associated index information are failed to repair.

In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method provided in the first aspect.

In a fourth aspect, embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the method as provided in the first aspect.

In a fifth aspect, an embodiment of the present invention provides a computer program, where the computer program includes computer instructions stored in a computer-readable storage medium, and when a processor of a computer device reads the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, so that the computer device executes the steps of implementing the method provided in the first aspect.

According to the fault repairing method, the fault repairing device, the electronic equipment and the storage medium provided by the embodiment of the invention, the fault data is obtained, and the fault data comprises at least one target index information with a fault; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relation of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between the faults can be effectively mined, so that the potential fault information can be timely mined, and the stability of the system can be better ensured.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.

Fig. 1 is a schematic flowchart of a fault repairing method according to an embodiment of the present application;

fig. 2 is a schematic diagram of a construction process of an FP-tree provided in an embodiment of the present application;

fig. 3a is a schematic diagram after a failure sample 1 is connected to a root node of a FP-tree according to the embodiment of the present application;

fig. 3b is a schematic diagram after a failure sample 2 is linked to a root node of a FP-tree according to the embodiment of the present application;

fig. 3c is a schematic diagram of an FP tree generated after

fault samples

3, 4, 5, 6, 7, 8, and 9 are sequentially connected to the FP tree according to an example provided by the embodiment of the present application;

fig. 4a is a conditional FP sub-tree corresponding to a conditional mode base of indicator information E that has a fault according to an embodiment of the present application

Fig. 4b1 is a FP sub-tree corresponding to the condition mode base of the indicator information C with fault according to the embodiment of the present application;

fig. 4b2 is another FP sub-tree corresponding to the conditional mode base of the indicator information C with failure according to the embodiment of the present application;

fig. 5 is a flowchart of determining associated index information from candidate index information according to an embodiment of the present application;

fig. 6 is a schematic diagram of a cart tree corresponding to index information B with a fault according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a fault repairing apparatus according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.

As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

The terms referred to in this application will first be introduced and explained:

a Frequent Pattern tree (FP-tree) is a tree structure satisfying the following conditions: (1) it consists of a root node (null), item prefix subtrees (as children), and a frequent item header table. (2) Each node in the item prefix subtree includes three domains: item _ name, count, and node _ link, where: item _ name records the identification of the item represented by the node; the count records the number of transactions of the sub-path reaching the node; the node _ link is used to connect the next node with the same identifier in the tree, and if the next node with the same identifier does not exist, the value is "null". (3) The entries of the frequent entry header table include a frequent entry identification field: item _ name and a head pointer to the first frequent item node in the tree with the item identification: head of node _ link.

The general procedure for FP-growth is as follows:

1: firstly, scanning the data set once to obtain an item set with frequent items of 1, defining minimum support (the minimum number of times of occurrence of items), deleting the items smaller than the minimum support, and then arranging the items in the original data set according to the descending order of the item set.

2: the second scan, creates an entry header table (descending order from top to bottom), and a FP-tree.

A CART (Classification And Regression Tree), called a CART Tree for short, is formed by a binary recursive partitioning method, a current sample set is divided into two sub-sample sets, so that the generated non-leaf sub-nodes all have two branches, therefore, a decision Tree generated by the CART algorithm is a binary Tree with a simple structure, the non-leaf nodes of the CART Tree are generally attributes or judgment conditions, And the leaf nodes are item frequent item sets corresponding to (or not belonging to) the attributes

The system stability refers to a certain stable state of a system element under external influence, and colloquially refers to the ability of ensuring that the system can still provide continuous and reliable service in the process of operation, operation and maintenance, namely in the face of various extreme situations or emergencies. With the development of the internet, the requirements of each large internet company on the stability and reliability of the service are higher and higher. In the field of software systems, a common index is the service availability time ratio, the higher the ratio is, the higher the system stability is, if we take the data of a whole year, the common 4 9 (99.99%) means that the service provided by our system is only 52 minutes long in the unavailable time of the whole year! Therefore, the importance of the system stability analysis can be seen.

There is no reliable system in the world, and machines, programs and networks may have problems in operation, which leads to system abnormality and loss of money and reputation, so the objective of ensuring system stability is to reduce loss, and it is expected to shorten the MTTR (mean time to repair) when abnormality occurs by finding, locating and solving problems. At present, a plurality of relatively mature system stability monitoring systems exist, and the system stability monitoring systems mainly monitor index information such as hardware, systems, applications, networks and the like, constantly monitor the systems in real time, feed back the current states (normal, abnormal and fault) of the systems in real time, and ensure the reliability, safety and sustainable and stable operation of the systems.

The present application provides a fault repairing method, apparatus, electronic device and computer readable storage medium, which aim to solve the above technical problems in the prior art.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. These several specific embodiments may be combined with each other below, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

An embodiment of the present application provides a fault repairing method, as shown in fig. 1, the method includes:

step S101, obtaining fault data, wherein the fault data comprises at least one target index information with faults.

Index information in the embodiments of the present application refers to any data or data combination used for determining system stability, including but not limited to environment information, host information, system information, application information, and network information, and specifically, the index information may be CPU temperature, physical disk, motherboard temperature, disk array, memory usage, disk read-write throughput, process port, database data, network information, and the like.

The target index information in the embodiment of the present application refers to the index information that has a fault, that is, the index information is faulty and is abnormal. Each index information may be compared with preset index information (or a preset index information threshold), when the index information is not equal to the preset index information or the index information is higher than the preset index information threshold, it may be determined that the index information is target index information with a fault, for example, the CPU temperature at a certain time exceeds 60 degrees to determine that the CPU temperature is abnormal, that is, the CPU at the time is the target index information with a fault, for example, a network signal is abnormal at a certain time, that is, the network signal is the target index information with a fault, and other index information may determine whether the index information is the target index information with a fault by comparing with the preset index information threshold, which is not illustrated in detail herein.

The fault data in the embodiment of the present application includes at least one target index information where a fault occurs, and the fault data is a fault detected at any time point.

Step S102, determining associated index information corresponding to target index information from a preset and constructed frequent pattern FP tree, wherein the FP tree comprises the associated relation of at least two index information.

The associated index information of the embodiment of the application refers to index information which has a corresponding relation with target index information, the corresponding relation refers to the possibility that the associated index information fails after the target index information with the failure appears, and by finding out the index information which has the corresponding relation with the target index information, the potential risk can be effectively excavated, and the impending failure can be predicted.

The FP tree of the embodiment of the application is constructed in advance, the FP tree comprises the association relation of each index information, and the association index information corresponding to the target index information can be determined by traversing the FP tree.

And step S103, restoring the target index information and the associated index information.

After the associated index information corresponding to the target index information is determined, the target index information is repaired, and meanwhile, the associated index information is also repaired in advance, so that other faults are avoided, or the faults can be repaired in time.

According to the method and the device, fault data are obtained, wherein the fault data comprise at least one piece of target index information with faults; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relation of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between faults can be effectively mined, so that the potential fault information is timely mined, and the stability of the system is better ensured.

An embodiment of the present application provides a possible implementation manner, and as shown in fig. 2, an exemplary diagram of a building process of a FP-tree is shown, where a building method of the FP-tree includes:

step S201, a fault sample set is collected, wherein the fault sample set comprises at least one fault sample, and the fault sample comprises at least one fault index information.

The fault sample set comprises a plurality of fault samples, and each fault sample comprises at least one fault index information.

The embodiment of the application does not limit how to acquire the sample data, for example, firstly, index information samples are acquired, each index information sample comprises a plurality of pieces of information, each index information is compared with preset index information, and if the index information is normal, the index information is removed from the sample, so that only the index information of a fault is left in the sample, and at this time, the index information sample set is a fault sample set.

Step S202, scanning a fault sample set, counting the occurrence frequency of each fault index information, eliminating fault index information with the occurrence frequency smaller than the preset occurrence frequency, and putting the residual fault index information and the corresponding occurrence frequency into an FP tree head pointer table according to a descending order arrangement rule.

The method comprises the steps of firstly scanning the whole fault sample set, determining the occurrence frequency of each fault in the fault sample set, wherein the occurrence frequency of the index information of the fault is also called the support degree of the index information of the fault, if the occurrence frequency of certain fault index information is less than the preset occurrence frequency, the fault index information is not frequently fault and not frequently fault, the fault index information can be removed from the fault sample set, and each fault sample does not comprise the fault index information.

Specifically, assume that there are 9 failure samples in the failure sample set, and each of the samples is:

failure sample 1: A. b, E, F, respectively;

failure sample 2: B. d;

failure sample 3: B. c;

failure sample 4: A. b, D, respectively;

failure sample 5: A. c;

failure sample 6: B. c;

failure sample 7: A. c;

failure sample 8: A. b, C, E, respectively;

failure sample 9: A. b, C, respectively;

wherein A, B, C, D, E and F are different types of index information of fault

Scanning the fault sample set for the first time, and counting the occurrence frequency of each faulted index information, wherein the occurrence frequency of each faulted index information is as follows:

a: 6 times; b: 7 times; c: 6 times; d:2 times; e:2 times; f: 1 time;

defining the minimum occurrence frequency of the index information with faults as 2, and reordering the index information with faults according to a descending order rule, wherein the ordering result is as follows: b: 7 times; a: 6 times; c: 6 times; d:2 times; e:2 times, based on the times, a head pointer table of the FP-tree can be created, the head pointer table is shown in table 1:

TABLE 1

Meanwhile, the arrangement sequence of the index information with faults in the fault sample can be sorted according to the occurrence frequency of each index information with faults, and the sorted fault sample is as follows:

failure sample 1: B. a, E, respectively;

failure sample 2: B. d;

failure sample 3: B. c;

failure sample 4: B. a, D, respectively;

failure sample 5: A. c;

failure sample 6: B. c;

failure sample 7: A. c;

failure sample 8: B. a, C, E, respectively;

failure sample 9: B. a, C, respectively;

according to the embodiment of the application, after the fault sample is scanned for the first time, the occurrence frequency of each piece of fault index information is obtained, and the head pointer table of the FP tree is established based on the occurrence frequency of each piece of fault index information.

Step S203, creating a root node of the FP tree, sequentially scanning each fault sample, sequentially linking the indicator information with the fault in the fault sample to the root node, if the node corresponding to the indicator information with the fault in the path where the fault sample is located already exists, adding one to the count of the node, and if the node corresponding to the indicator information with the fault does not exist, adding a node corresponding to the indicator information with the fault in the path.

In the above steps, after the faulty index information with the frequency less than the preset frequency is removed from the faulty samples, the arrangement sequence of the faulty index information in each faulty sample is sorted to obtain sorted faulty samples, and the arrangement sequence of the faulty index information in the sorted faulty samples is arranged according to the frequency of occurrence of each faulty index information in the whole faulty sample set.

In the embodiment of the application, after a head pointer table of an FP tree is created, the FP tree is created, a root node of the FP tree is created first, the root node of the FP tree is empty, each fault sample is scanned in sequence, the faulty index information in the fault sample is connected to the root node, if a node corresponding to the faulty index information in a path where the fault sample is located already exists, the count of the node where the node is located is added, if a node corresponding to the faulty index information does not exist, the node corresponding to the faulty index information is newly added in the path until the entire FP tree is created, the node corresponding to the node of the FP tree is the faulty index information and the count (frequency of occurrence) of the faulty index information in the path, if the fault sample is located in the path and the node corresponding to the faulty index information exists, when the faulty index information is scanned again, and if the node corresponding to the index information with the fault does not exist in the path where the fault sample is located, the node corresponding to the index information with the fault is newly added to the path.

In addition, pointers corresponding to each failed index information in the head pointer table are required to point to nodes corresponding to the failed index information in the FP tree.

Specifically, continuing with the example, as shown in fig. 3a, which exemplarily shows a schematic diagram after connecting the fault sample 1 to the root node of the FP-tree, the order of the failed indicator information in the head pointer table is ordered according to the frequency of occurrence of each failed indicator information, the failed indicator information in the fault sample 1 has B, A and E, the failed indicator information B in the head pointer table points to the node B in the FP-tree, the failed indicator information a in the head pointer table points to the node a in the FP-tree, and the failed indicator information E in the head pointer table points to the node E in the FP-tree.

Continuing the above example, as shown in fig. 3B, the schematic diagram after the fault sample 2 is linked to the root node of the FP tree is exemplarily shown, where the index information with the fault in the fault sample 2 has B and D, and is also the first in the row of the index information with the fault B, the count of the node B is directly increased by one, and the node corresponding to the index information D with the fault does not exist in the generated FP tree, and the node corresponding to the index information D with the fault needs to be newly added in sequence.

Continuing the above example, as shown in fig. 3c, the FP tree is generated after the

fault samples

3, 4, 5, 6, 7, 8, and 9 are sequentially connected to the FP tree, each path of the FP tree is a sample, as can be seen from the FP tree, 7 fault samples include the indicator information B that a fault occurs, and the first place of the indicator information a that a fault occurs in 2 fault samples is the first place of the indicator information B that a fault occurs in 7 fault samples.

The embodiment of the present application provides a possible implementation manner, in which association index information having a correspondence with target index information is determined from a preset constructed FP tree, including:

traversing the FP tree, and mining a frequent item set corresponding to target index information; the frequent item set comprises at least one candidate index information which has a corresponding relation with the target index information;

The candidate index information exists in the frequent item set, and other index information except the target index information in the frequent item set is the candidate index information.

In the embodiment of the application, the FP trees corresponding to the fault sample set are constructed to determine the association relationship between each piece of faulty index information, and after the fault data is obtained, the association index information corresponding to the target index information where the fault occurs in the fault data is determined by traversing the FP trees, and the specific method is as follows:

the conditional mode is based on a path set taking the searched element item as the end, each path is actually a prefix path, and the frequent item set refers to frequent items: frequently occurring elements/items in multiple collections are frequent items

Frequent item set: there are a series of sets, these sets have some identical elements, the elements with high frequency of occurrence in the set at the same time form a subset, satisfy certain threshold condition, it is a frequent item set.

A very large frequent itemset: the frequent item set with the most elements, i.e. any superset of the frequent item set, is a non-frequent item set. Frequent items, also called frequent 1 item set, with 1 element in the subset, frequent 2 item set, with 2 elements in the subset, … …, frequent n item set, with n elements in the subset, n being a positive integer.

Assuming that target index information with a fault is E, starting with a node where the node E is located, traversing the whole FP tree from bottom to top to obtain a conditional pattern base { (B A:1), (B A C:1) }, constructing a conditional FP sub-tree corresponding to the conditional pattern base of the index information E with the fault as shown in FIG. 4a, then recursively calling the conditional FP sub-tree, enumerating all combinations of { B:2, A:2, C:1}, and then merging the conditional FP sub-tree with E to obtain a frequent item set { BE:2}, { AE:2} and { BAE:2} with a support degree corresponding to the index information E with the fault larger than 2, wherein { B E:2} and { A E:2} are frequent 2 sets of E, and { B A E:2} is frequent 3 sets of E.

Assuming that the target index information with a fault is C, starting with the node where the node C is located, traversing the entire FP sub-tree from bottom to top to obtain a conditional schema base { (BA:2), (B:2), (a:2) }, and constructing the FP sub-tree corresponding to the conditional schema base of C, as shown in fig. 4B1, where the FP sub-tree corresponding to the conditional schema base of the index information with a fault C is still a multi-path tree, and a set of frequent item sets { B C:4} and { A C:4} is obtained by merging each item in the head pointers of the conditional FP sub-trees corresponding to the conditional schema bases of C and C, but this set of frequent item sets is not all frequent item sets with C suffixes, and further requires to recursively invoke the conditional FP of C, the frequent item sets are { a, B }, and the conditional schema bases of { a, C } are { B:2, which generates a conditional FP sub-tree as shown in fig. 4b 2. This is a one-path conditional FP subtree in which B is merged with the pattern suffix { a, C } to obtain the pattern { ABC: 2}. Theoretically, a mode set with { B, C } as the mode suffix should also be calculated, but the conditional mode base of { B, C } is null, the recursive call ends, and all the frequent item sets with the final mode suffix I3 with a support degree greater than 2 are: { B C:4}, { A C:4}, and { AB C:2}, where { B C:4} and { A C:4} are frequent 2-item sets, and { AB C:2} is a frequent 3-item set.

For B, the corresponding conditional mode base is null, mining is not needed, the mining method for frequent item sets of other nodes is the same as the above method, the embodiments of the present application are not described one by one, and finally the frequent item sets corresponding to each target index information are shown in table 2:

node (index information of fault)	Frequent item set (frequent mode)
		E	{B E:2}，{A E:2}，{B A E:2}
D	{B D:2}
		C	{B C:4}，{AC:4}，{AC:2}
A	{B A:4}

TABLE 2

According to the method and the device, the frequent item sets corresponding to the target index information are determined by traversing the pre-constructed FP tree, the frequent item sets comprise the frequent item set 2, the frequent item set 3, the frequent item set n, wherein n is a positive integer greater than 1, the elements in the frequent item sets have an incidence relation, and the candidate index information corresponding to the target index information can be determined by determining the frequent item sets corresponding to the target index information.

In the embodiment of the application, the candidate index information and the target index information in the frequent item set have a corresponding relationship, the corresponding relationship is an association relationship, and the occurrence of the target index information may cause the occurrence of the candidate index information, that is, one fault may cause the occurrence of another fault, and does not necessarily cause the occurrence of another fault, and the association index information needs to be further determined from the candidate index information based on a preset rule, so that the subsequent content is detailed.

The embodiment of the present application provides a possible implementation manner, in which association index information having a correspondence with target index information is determined from candidate index information based on a preset rule, including:

The confidence level, also called reliability, or confidence level, confidence coefficient, i.e. when the sampling estimates the overall parameter, the conclusion is always uncertain due to the randomness of the sample, the span of the confidence interval is a positive function of the confidence level, i.e. the greater the confidence level required, the wider the confidence interval must be obtained, which correspondingly reduces the accuracy of the estimation.

In the embodiment of the present application, the confidence between the target index information and the candidate index information indicates the possibility of occurrence of the candidate index information due to the target index event, and the preset confidence calculation method corresponds to a calculation formula:

it should be noted that the target index information herein does not refer to a single index information, but may refer to a combination of a plurality of index information, the support degree of the frequent item set refers to the number of occurrences (frequency) of the frequent item set in the failure sample set, and the support degree of the target index information refers to the number of occurrences of the target index information in the failure sample set.

Specifically, continuing the above example, if the combination of the target index information a and B includes a frequent item set of a and B having { B a E:2}, where the degree of support of { B a E:2} is 2 and the degree of support of the combination of a and B is 3, the confidence between the target index information and the candidate index information is 2/3, that is, when the target index information is a combination of a and B (the combination of a and B is subsequently represented by AE), the probability of causing the index information E to malfunction is 2/3.

Continuing the example, if the target index information is B, the frequent 2 item set of B has { B E:2}, { B D:2}, { B C:4} and { B A:4}, and the support degree of B is 7, it is sequentially calculated that when the target index information B fails, the probability of causing failure of A, C, D and E is 2/7, 2/7, 4/7 and 4/7, respectively, and the frequent 3 item set of B has { B a E:2}, and it can be calculated that after the target index information B fails, the probability of causing failure of a and E at the same time is 2/7.

According to the method and the device, after the confidence degree between the target index information and the candidate index information is calculated, the associated index information corresponding to the target index information is determined from the candidate index information according to the confidence degree between the target index information and the candidate index information.

An embodiment of the present application provides a possible implementation manner, as shown in fig. 5, which exemplarily shows a flowchart for determining associated index information from candidate index information, and determining associated index information having a correspondence with target index information from the candidate index information according to a confidence degree, where the method includes:

step S501, a binary recursive segmentation cart tree is constructed based on the confidence coefficient, the nodes of the cart tree are candidate index information, the non-leaf nodes of the cart tree represent judgment conditions, and the edges of the cart tree represent judgment results.

According to the embodiment of the application, a cart tree is constructed according to the confidence degree between the target index information and the candidate index information, the cart tree is a binary tree, namely a cart hypothesis decision tree, the values of the internal node characteristics are yes and no, the left branch is a branch with the value of yes, and the right branch is a branch with the value of no. Such a decision tree is equivalent to recursively bisecting each feature, dividing the input space, i.e., the feature space, into a finite number of cells, and determining a predicted probability distribution over the cells, i.e., the conditional probability distribution that is output under the given conditions of the input.

In the embodiment of the present application, a non-leaf node of a cart tree is a determination condition, an edge of the cart tree indicates a determination result, a leaf node indicates candidate index information belonging to the determination result, and the leaf node also corresponds to one category.

If the target index information is B, the probability that the combination of candidate index information A, C, D, E and AE fails is as follows, as shown in fig. 6, for the cart tree corresponding to the index information B in which the failure occurs, if the target index information is B: 2/7, 2/7, 4/7, 2/7 and 2/7, where the probability of failure resulting in A, C and AE is less than 30% and the probability of failure resulting in C and E is greater than 50%, so A, C and AE are located on the left leaf node and C and E are located on the right leaf node.

Step S502, traversing the cart tree, and determining candidate index information corresponding to the leaf node with the confidence coefficient greater than the preset confidence coefficient threshold value as the associated index information having the corresponding relation with the target index information.

After the cart tree is constructed, traversing the cart tree, and determining candidate index information corresponding to a node with a confidence level greater than a preset confidence level threshold as associated index information having a corresponding relationship with target index information, where the preset confidence level threshold may be any preset threshold, for example, set 50%, indicating that a failure of the target index information is likely to cause a failure of the candidate index information, and set 70%, indicating that a failure of the target index information is likely to cause a failure of the candidate index information.

And continuing to the above example, setting the preset confidence threshold to be 50%, and if the target index information with the fault is B, determining that the associated index information corresponding to the target index information is D and E after traversing the cart tree.

According to the embodiment of the application, the cart tree corresponding to the confidence degrees of the target index information and the candidate index information is constructed, and the associated index information corresponding to the target index information can be quickly determined through the cart tree.

The embodiment of the present application provides a possible implementation manner, which repairs target index information and associated index information, and includes:

According to the method and the device for repairing the target index, the preset repairing method corresponding to the index information with the fault is stored in the preset database in advance, the target index information with the fault and the preset repairing method corresponding to the associated index information are called from the preset database through the mapping relation between the index information with the fault and the preset repairing method, so that the target index is repaired, the associated index information is repaired in advance, and the associated index information is prevented from being faulty.

The embodiment of the present application provides a possible implementation manner, which repairs target index information and associated index information, and then further includes:

According to the method and the device, after any one of the target index information and the associated index information is repaired in a failure mode, the warning information is sent to the user, so that the failure repair of the user is prompted, the user can determine the reason of the repair failure through checking the log, the repair failure is repaired by adopting a manual repair method, and the repair method is recorded to the preset database, so that the method can be directly called when the failure occurs next time, and manual reprocessing is not needed.

The embodiment of the present application provides a fault repairing apparatus 700, as shown in fig. 7, the apparatus may include:

an obtaining module 710, configured to obtain fault data, where the fault data includes at least one target indicator information that has a fault;

the associated index information determining module 720 is configured to determine associated index information having a corresponding relationship with the target index information from a preset constructed frequent pattern FP tree;

a repairing module 730, configured to repair the target index information and the associated index information;

the FP tree comprises an incidence relation of at least two index information.

The embodiment of the present application provides a possible implementation manner, and the apparatus includes: an FP tree construction module; the FP tree construction module comprises:

the acquisition submodule is used for acquiring a fault sample set, and the fault sample set comprises at least one fault sample; the fault sample comprises at least one index information of the fault;

the scanning submodule is used for scanning the fault sample set, counting the occurrence frequency of each faulted index information, eliminating the faulted index information with the occurrence frequency smaller than the preset occurrence frequency, and putting the residual faulted index information and the corresponding occurrence frequency into a head pointer table of the FP tree according to a descending order arrangement rule;

and the creating submodule is used for creating a root node of the FP tree, scanning each fault sample in sequence, linking the fault index information in the fault sample to the root node in sequence, if the node corresponding to the fault index information in the path where the fault sample is located already exists, adding one to the count of the node, and if the node corresponding to the fault index information does not exist, adding the node corresponding to the fault index information in the path.

The embodiment of the present application provides a possible implementation manner, and the associated index information determining module includes:

The embodiment of the present application provides a possible implementation manner, and the association index information determining sub-module further includes:

and the associated index information determining unit is used for determining the associated index information which has a corresponding relation with the target index information from the candidate target information according to the confidence coefficient.

The embodiment of the present application provides a possible implementation manner, and the correlation index information determining sub-module further includes:

The embodiment of the application provides a possible implementation manner, and the repair module comprises:

The embodiment of the present application provides a possible implementation manner, and the apparatus further includes:

The fault repairing apparatus provided in the embodiment of the present invention specifically executes the processes of the above method embodiments, and please refer to the contents of the above fault repairing method embodiments in detail, which are not described herein again. According to the fault repairing device provided by the embodiment of the invention, fault data are obtained, and the fault data comprise at least one piece of target index information with faults; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relation of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between faults can be effectively mined, so that the potential fault information is timely mined, and the stability of the system is better ensured.

An embodiment of the present application provides an electronic device, including: a memory and a processor; at least one program stored in the memory for execution by the processor, which when executed by the processor, implements: acquiring fault data, wherein the fault data comprises at least one piece of target index information with a fault; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relationship of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between faults can be effectively excavated, so that the potential fault information is excavated in time, and the stability of the system is better ensured.

In an alternative embodiment, an electronic device is provided, as shown in fig. 8, the electronic device 4000 shown in fig. 8 comprising: a processor 4001 and a memory 4003. Processor 4001 is coupled to memory 4003, such as via bus 4002. Optionally, the electronic device 4000 may further comprise a transceiver 4004. In addition, the transceiver 4004 is not limited to one in practical applications, and the structure of the electronic device 4000 is not limited to the embodiment of the present application.

The Processor 4001 may be a CPU (Central Processing Unit), a general purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (field programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 4001 may also be a combination that performs a computational function, including, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, or the like.

Bus 4002 may include a path that carries information between the aforementioned components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 4002 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. 8, but this is not intended to represent only one bus or type of bus.

The Memory 4003 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.

The memory 4003 is used for storing application codes for executing the scheme of the present application, and the execution is controlled by the processor 4001. Processor 4001 is configured to execute application code stored in memory 4003 to implement what is shown in the foregoing method embodiments.

The present application provides a computer-readable storage medium, on which a computer program is stored, which, when running on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments. Compared with the prior art, the fault data is acquired, and the fault data comprises at least one piece of target index information with a fault; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relation of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between faults can be effectively mined, so that the potential fault information is timely mined, and the stability of the system is better ensured.

The embodiment of the present application provides a computer program, which includes computer instructions stored in a computer-readable storage medium, and when a processor of a computer device reads the computer instructions from the computer-readable storage medium, the processor executes the computer instructions, so that the computer device executes the contents as shown in the foregoing method embodiment. Compared with the prior art, the fault data is acquired, and the fault data comprises at least one piece of target index information with a fault; determining associated index information corresponding to target index information from a preset constructed frequent pattern FP tree, wherein the FP tree comprises the associated relationship of at least two pieces of index information; the target index information and the associated index information are repaired, and the association between faults can be effectively mined, so that the potential fault information is timely mined, and the stability of the system is better ensured.

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims

1. A method of fault remediation, comprising:

restoring the target index information and the associated index information;

wherein, the FP tree comprises the incidence relation of at least two index information.

2. The fault repairing method according to claim 1, wherein the building method of the FP tree comprises the following steps:

collecting a fault sample set, wherein the fault sample set comprises at least one fault sample; the fault sample comprises at least one fault index information;

scanning the fault sample set, counting the occurrence frequency of each faulted index information, eliminating the faulted index information with the occurrence frequency less than the preset occurrence frequency, and placing the residual faulted index information and the corresponding occurrence frequency into a head pointer table of the FP tree according to a descending order arrangement rule;

creating a root node of the FP tree, scanning each fault sample in sequence, linking the index information with faults in the fault sample to the root node in sequence, if the node corresponding to the index information with faults in the path where the fault sample is located already exists, adding one to the count of the node, and if the node corresponding to the index information with faults does not exist, adding the node corresponding to the index information with faults in the path.

3. The method according to claim 1, wherein the determining, from a preset-constructed FP tree, associated index information having a correspondence relationship with the target index information includes:

traversing the FP tree and mining a frequent item set containing the target index information; the frequent item set comprises target index information and candidate index information;

4. The fault repairing method according to claim 3, wherein determining associated index information corresponding to the target index information from the candidate index information based on a preset rule includes:

calculating the confidence degree between the target index information and the candidate index information according to a preset confidence degree calculation method;

5. The fault repairing method according to claim 4, wherein the determining, from the candidate index information, associated index information corresponding to the target index information according to the confidence degree includes:

constructing a binary recursive segmentation cart tree based on the confidence coefficient, wherein nodes of the cart tree are candidate index information, non-leaf nodes of the cart tree represent judgment conditions, and edges of the cart tree represent judgment results; the leaf nodes of the cart tree represent candidate index information belonging to a corresponding judgment result;

and traversing the cart tree, and determining candidate index information corresponding to the leaf node with the confidence coefficient greater than a preset confidence coefficient threshold value as associated index information having a corresponding relationship with the target index information.

6. The fault repairing method according to claim 1, wherein the repairing the target index information and the associated index information includes:

7. The fault repairing method according to claim 1, wherein the repairing the target index information and the associated index information further comprises:

8. A fault repair device, comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring fault data, and the fault data comprises at least one piece of target index information with a fault;

the associated index information determining module is used for determining associated index information which has a corresponding relation with the target index information from a preset constructed frequent pattern FP tree;

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the fault recovery method according to any of claims 1 to 7 are implemented when the processor executes the program.

10. A computer-readable storage medium storing computer instructions for causing a computer to perform the steps of the fault recovery method according to any one of claims 1 to 7.