CN116401090A - Abnormal data source determining method based on data updating - Google Patents
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Abstract
The invention relates to the field of data processing, in particular to an abnormal data source determining method based on data updating, which comprises the following steps: s100, in response to reaching the first time mom 1 Will be in mom 2 And mom (mom) 1 Each piece of failure information received by the server is used as target failure information; mom (mom) 2 Is a second time; s200, if the target failure information meeting the key conditions meets the preset abnormal conditions, entering step S300; s300, determining A 1 Whether first preset failure information with the same target failure information exists or not; if yes, determining the target data source as an abnormal data source; otherwise, performing data updating processing on each target failure identifier, and proceeding to step S200 after performing data updating processing on each target failure identifier. Thereby, the accuracy of the determination of the abnormal data source can be improved.
Description
Technical Field
The invention relates to the field of data processing, in particular to an abnormal data source determining method based on data updating.
Background
When determining an abnormal data source, the server generally determines whether each failure in acquiring data from the data source is caused by the abnormality of the data source in a preset time period according to the data acquisition failure information corresponding to the data source, and determines whether the data source is an abnormal data source according to the number of data acquisition failures caused by the abnormality of the data source in the preset time period. The data acquisition failure information is generated by a data source, and is generally pre-stored in the server in order to save the data transmission amount between the server and the data source as much as possible.
However, after the data acquisition failure information generated by the data source is updated in the data source, the data acquisition failure information pre-stored in the server cannot be updated completely and synchronously basically, so that the accuracy of determining whether the failure of acquiring the data from the data source is caused by the abnormality of the data source is reduced, and therefore, the accuracy of determining the abnormal data source is lower.
Disclosure of Invention
Aiming at the technical problems, the invention adopts the following technical scheme:
the invention provides an abnormal data source determining method based on data updating, which is applied to a server, wherein the server is connected with a target data source; the target data source is configured to return corresponding failure information to the server when the data acquisition according to the received data acquisition request sent by the server fails; the server stores a first preset failure information list A 1 ＝(a 1 1 ,a 2 1 ,...,a k 1 ,...,a z 1 )，a k 1 ＝(a k1 1 ,a k2 1 ,...,a kx 1 ,...,a ky(k) 1 )，a kx 1 ＝(bs kx 1 ,ms kx 1 ) K=1, 2,..z, x=1, 2,., y (k); wherein a is k 1 For the kth second preset failure flag c k The corresponding first set of preset failure information, z being the number of second preset failure identifiers, the second preset failure identifiers being generated by the server,each second preset failure identifier belongs to a key category or a non-key category; a, a kx 1 C is k Corresponding x-th first preset failure information, y (k) is c k The number of corresponding first preset failure information; bs kx 1 Is a as kx 1 Corresponding first preset failure identification, ms kx 1 For bs kx 1 Corresponding preset paraphrasing information; the first preset failure information is generated by a target data source; a is that 1 Any two first preset failure identifications in the test result are different; the determination method comprises the following steps:
s100, in response to reaching the first time mom 1 Will be in mom 2 And mom (mom) 1 Each piece of failure information received by the server is used as target failure information, and the target failure information comprises a target failure identifier and target paraphrasing information corresponding to the target failure identifier; mom (mom) 2 For the second time mom 2 ＜mom 1 。
S200, if the target failure information meeting the key conditions in the target failure information meets the preset abnormal conditions, entering step S200; the key condition is that the target failure identifier in the current target failure information is the same as any one of the first preset failure identifiers corresponding to the key categories.
S300, determining A 1 Whether first preset failure information with the same failure information of each target exists or not; if yes, determining the target data source as an abnormal data source; otherwise, the data updating process is performed on each target failure identifier, and the step S300 is performed after the data updating process is performed on each target failure identifier.
The data update process includes the steps of:
and S310, taking the target failure identifier which is currently subjected to data updating processing as the current failure identifier.
S320, determining A 1 Whether a first preset failure identifier which is the same as the current failure identifier exists or not; if not, the process proceeds to step S330.
S330, a first preset failure information a is to be added 00 1 Added to A 1 Middle and pri max Corresponding to the first preset failure information group; a, a 00 1 ＝(bs 00 1 ,ms 00 1 )，bs 00 1 Ms for current failure identification 00 1 Target definition information corresponding to the current failure identification is provided; maximum priority pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Max () is a preset maximum value determination function, a k 1 Corresponding priority pri k ＝(∑ x＝1 y(k) d kx )/y(k)，d kx Identifying corresponding target paraphrasing information and ms for current failure kx 1 Degree of matching between the two.
The invention has at least the following beneficial effects:
in the present invention, when reaching the first time mom 1 When the target failure information meeting the key condition meets the preset abnormal condition, and A 1 If the first preset failure information which is the same as any target failure information does not exist in the data processing system, the data updating processing is carried out on each target failure identifier so as to update A 1 In update A 1 Then, whether the target failure information meeting the key conditions meets the preset abnormal conditions is determined again until the target data source is determined to be a normal data source or the target failure information meets the preset abnormal conditions due to A 1 The target data source is determined to be an abnormal data source by the first preset failure information with the same target failure information.
In comparison with the related art, when reaching the first time mom 1 When the target failure information meeting the key conditions meets the preset abnormal conditions, determining the target data source as an abnormal data source, and updating A after determining that the target failure information meeting the key conditions meets the preset abnormal conditions 1 Then determining whether the target data source is an abnormal data source, so that A stored in the server can be reduced 1 The possibility that the normal target data source is determined as an abnormal data source due to incomplete real-time update can be improved in accuracy of determination of the abnormal data source.
Further, in the present invention, update A 1 When a is to be a 00 1 Added to A 1 Middle and pri max In the corresponding first preset failure information set and pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Due to pri k The determination of (a) takes into account the target paraphrasing information corresponding to the current failure identification and a) k 1 The target paraphrasing information and the preset paraphrasing information used for determining the matching degree are generated by a target data source, namely the target paraphrasing information and the preset paraphrasing information used for determining the matching degree are generated by the same main body, and the a is determined according to the matching degree in the invention 00 1 The corresponding first preset failure information group is more accurate, and the accuracy of data updating can be improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for determining an abnormal data source based on data update according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The embodiment of the invention provides an abnormal data source determining method based on data updating, wherein the determining method is applied to a server, and the server is connected with a target data source.
The target data source is configured to return corresponding failure information to the server when data acquisition according to a received data acquisition request sent by the server fails.
Specifically, the failure information includes a corresponding failure identifier and paraphrase information of the failure identifier. The failure is identified as an error code and the paraphrase information is an error description text. For example, failure is identified as 0044 and the corresponding paraphrase information is "network status bad".
The server stores a first preset failure information list A 1 ＝(a 1 1 ,a 2 1 ,...,a k 1 ,...,a z 1 )，a k 1 ＝(a k1 1 ,a k2 1 ,...,a kx 1 ,...,a ky(k) 1 )，a kx 1 ＝(bs kx 1 ,ms kx 1 ) K=1, 2,..z, x=1, 2,., y (k); wherein a is k 1 For the kth second preset failure flag c k The corresponding first preset failure information group, z is the number of second preset failure identifiers, the second preset failure identifiers are generated by the server, and each second preset failure identifier belongs to a key category or a non-key category; a, a kx 1 C is k Corresponding x-th first preset failure information, y (k) is c k The number of corresponding first preset failure information; bs kx 1 Is a as kx 1 Corresponding first preset failure identification, ms kx 1 For bs kx 1 Corresponding preset paraphrasing information; the first preset failure information is generated by a target data source; a is that 1 Any two of the first preset failure identifications are different.
Specifically, the first preset failure identifier and the second preset failure identifier are error codes, and the preset paraphrasing information is an error description text of the corresponding first preset failure identifier.
Each second preset failure identifier has a corresponding failure grade, the second preset failure identifiers with the failure grade greater than or equal to the preset grade belong to a key category, the second preset failure identifiers with the failure grade smaller than the preset grade belong to a non-key category, and the specific failure grade and the preset grade are set in the field according to the application scenario, which is not limited in the embodiment of the invention.
The higher the failure level, the greater the likelihood that the failure indicated by the second preset failure identifier is caused by the abnormality of the target data source. For example, the first failure cause is a network failure, the second failure cause is an interface failure on the target data source for transmitting acquired data corresponding to the data acquisition request to the server, and based on this, the failure level corresponding to the second preset failure identifier corresponding to the first failure cause is higher than the failure level corresponding to the second preset failure identifier corresponding to the second failure cause.
Each second preset failure identifier is provided with a plurality of corresponding paraphrasing text data, and the paraphrasing text data is an error description text of the corresponding second preset failure identifier. Based on the above, in all the first preset failure identifiers, if the semantic matching degree of at least one paraphrasing text data corresponding to any one first preset failure identifier and any one second preset failure identifier exceeds a preset matching degree threshold value, determining that the first preset failure identifier corresponds to the second preset failure identifier; in all the first preset failure identifications, if the semantic matching degree of the preset paraphrasing information corresponding to any one of the first preset failure identifications and at least one paraphrasing text data corresponding to a plurality of second preset failure identifications exceeds a preset matching degree threshold, determining the second preset failure identification corresponding to the paraphrasing text data with the largest semantic matching degree of the preset paraphrasing information corresponding to the first preset failure identification as corresponding to the first preset failure identification.
In a specific embodiment, the server is an airline server, and the server sends corresponding data acquisition requests to the target data source in response to a user performing a business operation. The business operation can be ticket buying, inquiring, ticket returning or changing, etc.
The abnormal data source determining method based on the data update will be described below with reference to a flowchart of the abnormal data source determining method based on the data update shown in fig. 1.
The determination method comprises the following steps:
s100, in response to reaching the first time mom 1 Will be in mom 2 And mom (mom) 1 Each piece of failure information received by the server is used as target failure information, and the target failure information comprises a target failure identifier and target paraphrasing information corresponding to the target failure identifier.
Wherein mom 2 For the second time mom 2 ＜mom 1 。
In a specific embodiment, the end time of each of a plurality of preset sliding time windows is taken as mom 1 For any mom 1 The determination method of the embodiment of the present invention can be performed.
S200, if the target failure information meeting the key conditions in the target failure information meets the preset abnormal conditions, entering step S300.
The key condition is that the target failure identifier in the current target failure information is the same as any one of the first preset failure identifiers corresponding to the key categories.
In a specific embodiment of the step S200, if the target failure information meeting the key condition satisfies the preset abnormal condition in the plurality of target failure information, step S300 is entered, otherwise, the target data source is determined as the normal data source.
S300, determining A 1 Whether first preset failure information with the same failure information of each target exists or not; if yes, determining the target data source as an abnormal data source; otherwise, the data updating process is performed on each target failure identifier, and the step S200 is performed after the data updating process is performed on each target failure identifier.
The data update process includes the steps of:
s310, taking a target failure identifier which is currently subjected to data updating processing as a current failure identifier;
s320, determining A 1 Whether a first preset failure identifier which is the same as the current failure identifier exists or not; if not, go to step S330;
s330, a first preset failure information a is to be added 00 1 Added to A 1 Middle and pri max Corresponding to the first preset failure information group; a, a 00 1 ＝(bs 00 1 ,ms 00 1 )，bs 00 1 Ms for current failure identification 00 1 Target definition information corresponding to the current failure identification is provided; maximum priority pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Max () is a preset maximum value determination function, a k 1 Corresponding priority pri k ＝(∑ x＝1 y(k) d kx )/y(k)，d kx Identifying corresponding target paraphrasing information and ms for current failure kx 1 Degree of matching between the two.
It can be seen that in the present invention, when the first time mom is reached 1 When the target failure information meeting the key condition meets the preset abnormal condition, and A 1 If the first preset failure information which is the same as any target failure information does not exist in the data processing system, the data updating processing is carried out on each target failure identifier so as to update A 1 In update A 1 Then, whether the target failure information meeting the key conditions meets the preset abnormal conditions is determined again until the target data source is determined to be a normal data source or the target failure information meets the preset abnormal conditions due to A 1 The target data source is determined to be an abnormal data source by the first preset failure information with the same target failure information.
In comparison with the related art, when reaching the first time mom 1 When the target failure information meeting the key conditions meets the preset abnormal conditions, determining the target data source as an abnormal data source, and updating A after determining that the target failure information meeting the key conditions meets the preset abnormal conditions 1 Then determining whether the target data source is an abnormal data source, so that A stored in the server can be reduced 1 The possibility that the normal target data source is determined as an abnormal data source due to incomplete real-time update can be improved in accuracy of determination of the abnormal data source.
Further, in the present invention, update A 1 When a is to be a 00 1 Added to A 1 Middle and pri max In the corresponding first preset failure information set and pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Due to pri k The determination of (a) takes into account the target paraphrasing information corresponding to the current failure identification and a) k 1 The target paraphrasing information and the preset paraphrasing information used for determining the matching degree are generated by a target data source, namely the target paraphrasing information and the preset paraphrasing information used for determining the matching degree are generated by the same main body, and the a is determined according to the matching degree in the invention 00 1 The corresponding first preset failure information group is more accurate, and the accuracy of data updating can be improved.
In addition, in the invention, the data updating process is performed when the target failure information meeting the key condition meets the preset abnormal condition, compared with the process when the first time mom is reached 1 And then, carrying out data updating processing, wherein the data updating processing can not be carried out when the target failure information meeting the key conditions does not meet the preset abnormal conditions, so that the calculated amount of the server can be reduced, and the calculation resources are saved.
Optionally, step S320 includes the steps of:
s321, determining A 1 Whether a first preset failure identifier which is the same as the current failure identifier exists or not; if yes, go to step S340; otherwise, step S330 is entered.
The data update process further includes the steps of:
s340, determining whether preset paraphrasing information of a first preset failure identifier which is the same as the current failure identifier is the same as target paraphrasing information corresponding to the current failure identifier; if not, the process proceeds to step S350.
S350, determining A 1 Whether the preset paraphrasing information which is the same as the target paraphrasing information corresponding to the current failure identification exists or not; if yes, go to step S360.
S360, from A 1 Deleting the first preset failure information where the first preset failure identifier identical to the current failure identifier is located.
S370, will A 1 The first preset failure identifier corresponding to the preset paraphrase information which is the same as the target paraphrase information corresponding to the current failure identifier is replaced by the current failure identifier.
Optionally, step S350 includes the steps of:
s351, determining A 1 Whether the preset paraphrasing information which is the same as the target paraphrasing information corresponding to the current failure identification exists or not; if yes, go to step S360; otherwise, step S380 is entered.
The data update process further includes the steps of:
s380, adding the first preset failure information a 00 1 Added to A 1 Middle and pri max And the corresponding first preset failure information group.
Wherein a is 00 1 ＝(bs 00 1 ,ms 00 1 )，bs 00 1 Ms for current failure identification 00 1 Target definition information corresponding to the current failure identification is provided; maximum priority pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Max () is a preset maximum value determination function, a k 1 Corresponding priority pri k ＝(∑ x＝1 y(k) d kx )/y(k)，d kx Identifying corresponding target paraphrasing information and ms for current failure kx 1 Degree of matching between the two.
S390, mix A 1 In a 00 1 Each piece of first preset failure information is taken as candidate preset failure information, and is shown in A 1 And deleting candidate preset failure information of the first preset failure identifier identical to the current failure identifier.
Optionally, the server is connected with the target data source through a plurality of data interfaces of the server; the server is used for sending a corresponding data acquisition request to the target data source through each data interface; the target data source is configured to, for each data acquisition request sent by the server, if the data acquisition according to the data acquisition request fails, return failure information corresponding to the data acquisition request to the server through a data interface corresponding to the data acquisition request.
Specifically, the data interface is an API (Application Programming Interface ) interface.
In a specific embodiment, the server is an airline server, and any two data interfaces correspond to different service types, and the server is configured to send, in response to a user performing an operation corresponding to each data interface, a corresponding data acquisition request to a target data source through the data interface. For example, the number of the data interfaces is 4, the 4 data interfaces are respectively a first data interface, a second data interface, a third data interface and a fourth data interface, the first data interface is a data interface corresponding to ticket selling service, the second data interface is a data interface corresponding to inquiry service, the third data interface is a data interface corresponding to ticket refunding service, and the fourth data interface is a data interface corresponding to change signing service. Correspondingly, the server responds to the ticket purchasing operation of the user and sends a corresponding data acquisition request to the target data source through the first data interface, the server responds to the query operation of the user and sends the corresponding data acquisition request to the target data source through the second data interface, the server responds to the ticket returning operation of the user and sends the corresponding data acquisition request to the target data source through the third data interface, and the server responds to the change operation of the user and sends the corresponding data acquisition request to the target data source through the fourth data interface.
Step S200 includes the steps of:
s201, A is as follows 1 Each first preset failure identifier corresponding to the key category is used as a target preset failure identifier.
Specifically, A 1 Each first preset failure identifier in the first preset failure information group corresponding to each second preset failure information belonging to the key category is the first preset failure identifier corresponding to the key category.
S202, acquiring a TIME list TIME= (TIME 1 ,time 2 ,...,time i ,...,time n )，time i ＝(time i1 ,time i2 ,...,time iu ,...,time iv(i) ) U=1, 2,. -%, v (i); wherein, time is i For the time group corresponding to the ith data interface, n is the number of data interfaces, time iu For the server at mom 2 And mom (mom) 1 Time between sending the ith data acquisition request to the target data source through the ith data interface, time i1 ≤time i2 ≤...≤time iu ≤...≤time iv(i) ，mom 2 ＜time iu ＜mom 1 The method comprises the steps of carrying out a first treatment on the surface of the v (i) is the server at mom 2 And mom (mom) 1 The number of data acquisition requests sent to the target data source through the ith data interface.
S203, according to TIME, obtaining a TIME difference list DeltaT= (Deltat) 1 ,Δt 2 ,...,Δt Q ,...,Δt n )，Δt i ＝(Δt i1 ,Δt i2 ,...,Δt iu ,...,Δt iv(i) )。
Wherein Δt is i For time of i Corresponding time difference group, Δt iu For time of iu A corresponding time difference; Δt (delta t) iu The following conditions are satisfied:
if u=1, Δt i1 ＝[(time i1 -mom 2 )+(time i2 -time i1 )]/2；
If u=q, Δt iq ＝[(time iq -time i(q-1) )+(time i(q+1) -time iq )]/2,q＝2,3,...,v(i)-1；
If u=v (i), Δt iv(i) ＝[(time iv(i) -time i(v(i)-1) )+(mom 1 -time iv(i) )]/2。
S204, according to the delta T, acquiring a first reliability parameter par delta sigma of the target data source i＝1 n [w i *s(i)/v(i)]。
S (i) is the number of target failure identifiers which are the same as any target preset failure identifier in all target failure identifiers corresponding to the ith data interface; w (w) i Is the ithWeights, w, corresponding to the data interfaces i ＝α*v(i)+β/F i Alpha is a first preset coefficient, beta is a second preset coefficient, F i For the time difference fluctuation parameter corresponding to the ith data interface, F i ＝[∑ u＝1 v(i) (Δt iu -Δt ave i ) 2 ]/v(i)，Δt ave i For the reference time difference corresponding to the ith data interface, deltat ave i ＝(∑ u＝1 v(i) Δt iu )/v(i)。
S205, determining whether par meets par not less than pre1; if yes, the target failure information meeting the key conditions meets the preset abnormal conditions, and the step S300 is carried out; otherwise, the target failure information meeting the key conditions does not meet the preset abnormal conditions, and the target data source is determined to be a normal data source.
Wherein pre1 is a preset first target threshold.
From this, it can be seen that, compared with the related art in which the target data source is determined as the abnormal data source when the failure rate of acquiring data from the target data source within the preset time period is high, w in the present invention i Consider that the server is in mom 2 And mom (mom) 1 The number v (i) of data acquisition requests sent to the target data source through the ith data interface, and the smaller v (i), the weight w corresponding to the ith data interface i The smaller, and in turn the smaller the effect s (i)/v (i) has on par, i.e., the smaller v (i), the server is at mom 2 And mom (mom) 1 The smaller the effect of the failure rate of acquiring data from the target data source through the ith data interface on determining whether the target data source is an abnormal data source, therefore, the target data source is an abnormal data source, and the smaller v (i) causes the problem of mom 2 And mom (mom) 1 When the failure rate of acquiring data from the target data source through the ith data interface is low, the possibility that the failure rate is low, so that the par is small and the target data source is not determined as an abnormal data source can be reduced, and therefore the accuracy of determining the abnormal data source can be improved.
Further, F in the present invention i The larger, w i Smaller, and s (i)/v #i) The smaller the effect on par, again due to F i ＝[∑ u＝1 v(i) (Δt iu -Δt ave i ) 2 ]V (i), thus in mom 2 And mom (mom) 1 The larger the time difference fluctuation of the data acquisition request sent by the server to the target data source through the ith data interface, the smaller the influence of s (i)/v (i) on par, namely mom 2 And mom (mom) 1 The more concentrated the data acquisition requests sent by the server to the target data source through the ith data interface, the smaller the influence of s (i)/v (i) on par, and then in mom 2 And mom (mom) 1 The time of the data acquisition request sent by the server to the target data source through the ith data interface is mostly concentrated in the time when s (i)/v (i) is smaller before the target server starts to be abnormal, so that the possibility that the target server is not determined as an abnormal server can be reduced, and the accuracy of determining the abnormal data source can be further improved.
Alternatively, alpha is more than or equal to 1 and less than or equal to 5, beta is more than or equal to 100 and less than or equal to 10000.
Alternatively, pre 1= (Σ) i＝1 n w i ) Coe, coe are preset target coefficients, 0.5 < coe is less than or equal to 0.9.
Optionally, step S300 includes the steps of:
s301, determining A 1 Whether first preset failure information with the same failure information of each target exists or not; if yes, determining the target data source as an abnormal data source, and proceeding to step S400; otherwise, the data updating process is performed on each target failure identifier, and the step S300 is performed after the data updating process is performed on each target failure identifier.
The determination method further comprises the following steps:
s400, disconnecting the connection between the server and the target data source.
S500, connecting the server with the standby data source corresponding to the target data source.
For example, if the server is an airline server, the target data source and the corresponding standby data source are data sources corresponding to different online ticketing platforms.
Optionally, step S340 includes the steps of:
s341, determining whether preset paraphrasing information of a first preset failure identifier which is the same as the current failure identifier is the same as target paraphrasing information corresponding to the current failure identifier; if yes, finishing the data updating processing of the current failure identifier; otherwise, step S350 is entered.
Optionally, the matching degree is a matching degree between a feature value of the corresponding target paraphrasing information and a feature value of the corresponding preset paraphrasing information, or the matching degree is a semantic matching degree between the corresponding target paraphrasing information and the corresponding preset paraphrasing information.
Specifically, the characteristic value is a hash value. In a specific embodiment, the matching degree is a difference between the hash value of the corresponding target paraphrase information and the hash value of the corresponding preset paraphrase information. For example, if the hash value of any target paraphrasing information is 0110 and the hash value of any preset paraphrasing information is 0111, it can be known that the matching degree of the target paraphrasing information and the preset paraphrasing information is 0001 according to 0111-0110=0001.
Optionally, part of the data interfaces are reserved interfaces and another part of the data interfaces are unreserved interfaces.
In a specific embodiment, if the service corresponding to any one of the data interfaces belongs to the after-sales service class, the data interface is determined to be a reserved interface, for example, for the first data interface, the second data interface, the third data interface and the fourth data interface, the first data interface and the second data interface are set as reserved interfaces, and the third data interface and the fourth data interface are set as unreserved interfaces.
Based on this, in response to determining the target data source as an anomalous data source, the determining method further includes the steps of:
s600, disconnecting each unreserved interface of the server from the target data source, and determining the current time as the disconnection time mom 0 。
And S700, each data interface of the server is connected with a standby data source corresponding to the target data source.
S800, in response to reaching the first detection time mom 1 Acquiring a second reliability parameter par corresponding to the target data source 1 。
Wherein par is 1 ＝∑ I＝1 R [s′(I)/v′(I)]R; s' (I) is the second detection time mom 2 And mom (mom) 1 The number of target failure identifications, mom, sent by the target data source and received by the server through the I-th reserved interface 0 ＜mom 2 ＜mom 1 V' (I) is the second detection time mom 2 And mom (mom) 1 The server obtains the quantity of requests for data sent to the target data source through the I-th reserved interface; r is the number of reserved interfaces in all data interfaces, and R < n.
Specifically, the ending time of any one detection sliding time window of the detection sliding time windows is taken as mom 1 。
In a specific embodiment, the ending time of each detection sliding time window in a plurality of preset detection sliding time windows is taken as mom 1 For any mom 1 The determination method of the embodiment of the present invention can be performed.
S900, if par 1 If not less than thr, disconnecting each unreserved interface from the standby data source, and connecting each unreserved interface with the target data source; thr is a preset threshold.
Therefore, in the invention, after the target data source is determined to be the abnormal data source, the server can acquire the data through the standby data source corresponding to the target data source, and the data is acquired in par 1 When thr is reached, it indicates that the target data source basically recovers the normal working state, and at this time, the connection between the server and the standby data source can be disconnected and the connection between the server and the target data source can be recovered, so that the target data source can be switched back from the standby data source in time after the target data source recovers the normal working state.
Alternatively, thr is greater than or equal to 0.8.
Optionally, (mom) 1 -mom 2 )≥(mom 1 -mom 2 )。
Specifically, (mom 1 -mom 2 ) To determine, after the server is connected to the backup data source, whether the server is to resume the duration of the time period for which the connection to the target data source is to be made; (mom) 1 -mom 2 ) It is determined whether the server is the duration of the time period for which the server is anomalous.
It can be seen from this that, compared with (mom 1 -mom 2 )＜(mom 1 -mom 2 ) In the present invention, it is determined whether the server is to resume the connection with the target data source for the duration of the time period (mom 1 -mom 2 ) Not less than the duration of the period of time (mom) for which it is determined whether the server is an abnormal server 1 -mom 2 ) The par caused by too short duration of the time period for determining whether the server is to resume connection with the target data source in the case that the target data source is still an abnormal data source can be reduced 1 The probability that the server is restored to be connected with the target data source is high, so that the probability that the server is normally connected with the target data source under the condition that the target data source is an abnormal data source can be reduced, and the purpose of improving the success rate of acquiring data by the server is achieved.
Optionally, the target data source is further configured to, for each data acquisition request sent by the server, if the data acquisition according to the data acquisition request is successful, return the acquired data corresponding to the data acquisition request to the server through the data interface corresponding to the data acquisition request.
In one specific embodiment:
step S100 includes the steps of:
s101, in response to reaching the first time mom 1 Acquiring a target time mom 0 ＝mom 1 。
S102, will be in mom 2 And mom (mom) 1 Each piece of failure information received by the server serves as target failure information, and the target failure information comprises a target failure identifier and target paraphrasing information corresponding to the target failure identifier.
Based on this, step S205 includes the steps of:
s2051, determining whether par meets par not less than pre1; if yes, the target failure information meeting the key conditions meets the preset abnormal conditions, and the step S300 is carried out; otherwise, if mom 1 ＝mom 0 Step S1200 is entered;
the determination method further comprises the following steps:
s1200, determining whether par is greater than or equal to pre2; if yes, the process proceeds to step S1300.
Wherein, pre2 is a second target threshold, pre2 < pre1.
S1300, in response to reaching the third time mom 3 Mom is to 1 Updated to mom 3 Pre1 is updated to γ×pre1, and the process proceeds to step S102.
Wherein mom 3 ＞mom 0 Gamma is the reduction parameter, gamma= { [ (mom) 0 -mom 2 )/(mom 3 -mom 2 )]*(v 1 /v 2 )*H}^(1/3)。
v 1 For the server at mom 2 And mom (mom) 0 The number of data acquisition requests sent to the target data source, v 1 ＝∑ i＝1 n v(i)；v 2 For the server at mom 2 And mom (mom) 3 The number of data acquisition requests sent to the target data source; h is the influence coefficient, if dur ave ≤dur 0 H= (dur) 0 -dur ave )/dur 0 If dur ave ＞dur 0 H=0; dur (dur) 0 The response time is preset; dur (dur) ave To reference the response duration dur ave ＝∑ L＝1 v(i) dur L ，dur L For the server at mom 2 And mom (mom) 3 The difference between the time of the L-th data acquisition request sent to the target data source and the time of the acquired data or target failure identification corresponding to the data acquisition request received by the server.
Optionally, step S2051 includes the steps of:
s20511, determining whether par is greater than or equal to pre1; if yes, the target failure information meeting the key conditions meets the preset abnormal conditions; otherwise, the process advances to step S20512.
S20512, determining mom 1 Whether or not mom is satisfied 1 ＝mom 0 The method comprises the steps of carrying out a first treatment on the surface of the If yes, go to step S1200; otherwise, the target failure information meeting the key conditions does not meet the preset abnormal conditions, and the target data source is determined to be a normal data source.
Optionally, (mom) 3 -mom 0 )≤(mom 0 -mom 2 )。
It can be seen from this that, compared with (mom 3 -mom 0 )＞(mom 0 -mom 2 ) In the present invention (mom) 3 -mom 0 )≤(mom 0 -mom 2 ) Can reduce the number of the components due to (mom 3 -mom 0 ) The possibility that the target data source is determined to be the abnormal data source after being abnormal due to overlong time can be achieved, and the purpose of improving the timeliness of determining the abnormal data source is achieved.
Alternatively, 3 seconds is less than or equal to dur 0 And the time is less than or equal to 15 seconds.
Optionally, step S1200 includes the steps of:
s1201, determining whether par is greater than or equal to pre2; if yes, go to step S1300; otherwise, the target failure information meeting the key conditions does not meet the preset abnormal conditions, and the target data source is determined to be a normal data source.
Embodiments of the present invention also provide a non-transitory computer readable storage medium that may be disposed in an electronic device to store at least one instruction or at least one program for implementing one of the methods of the method embodiments, the at least one instruction or the at least one program being loaded and executed by the processor to implement the determination method provided by the above embodiments.
Embodiments of the present invention also provide an electronic device comprising a processor and the aforementioned non-transitory computer-readable storage medium.
Embodiments of the present invention also provide a computer program product comprising program code for causing an electronic device to carry out the steps of the method of determining according to the various exemplary embodiments of the invention described in the present specification when the program product is run on the electronic device.
While certain specific embodiments of the invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the invention. Those skilled in the art will also appreciate that many modifications may be made to the embodiments without departing from the scope and spirit of the invention. The scope of the present disclosure is defined by the appended claims.
Claims (10)
1. The abnormal data source determining method based on data updating is characterized in that the determining method is applied to a server, and the server is connected with a target data source; the target data source is configured to return corresponding failure information to the server when data acquisition according to a received data acquisition request sent by the server fails; the server stores a first preset failure information list A 1 ＝(a 1 1 ,a 2 1 ,...,a k 1 ,...,a z 1 )，a k 1 ＝(a k1 1 ,a k2 1 ,...,a kx 1 ,...,a ky(k) 1 )，a kx 1 ＝(bs kx 1 ,ms kx 1 ) K=1, 2,..z, x=1, 2,., y (k); wherein a is k 1 For the kth second preset failure flag c k The corresponding first preset failure information group, z is the number of the second preset failure identifiers, the second preset failure identifiers are generated by the server, and each second preset failure identifier belongs to a key category or a non-key category; a, a kx 1 C is k Corresponding x-th first preset failure information, y (k) is c k The number of corresponding first preset failure information; bs kx 1 Is a as kx 1 Corresponding first preset failure identification, ms kx 1 For bs kx 1 Corresponding preset paraphrasing information; the first preset failure informationGenerated by the target data source; a is that 1 Any two first preset failure identifications in the test result are different; the determination method comprises the following steps:
s100, in response to reaching the first time mom 1 Will be in mom 2 And mom (mom) 1 Each piece of failure information received by the server is used as target failure information, and the target failure information comprises a target failure identifier and target paraphrasing information corresponding to the target failure identifier; mom (mom) 2 For the second time mom 2 ＜mom 1 ；
S200, if the target failure information meeting the key conditions in the target failure information meets the preset abnormal conditions, entering step S300; the key condition is that the target failure identifier in the current target failure information is the same as any first preset failure identifier corresponding to the key category;
s300, determining A 1 Whether first preset failure information with the same target failure information exists or not; if yes, determining the target data source as an abnormal data source; otherwise, performing data updating processing on each target failure identifier, and entering step S200 after performing data updating processing on each target failure identifier;
the data update process includes the steps of:
s310, taking a target failure identifier which is currently subjected to data updating processing as a current failure identifier;
s320, determining A 1 Whether a first preset failure identifier which is the same as the current failure identifier exists or not; if not, go to step S330;
s330, a first preset failure information a is to be added 00 1 Added to A 1 Middle and pri max Corresponding to the first preset failure information group; a, a 00 1 ＝(bs 00 1 ,ms 00 1 )，bs 00 1 Ms for the current failure identification 00 1 Target paraphrasing information corresponding to the current failure identification; maximum priority pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Max () is a preset maximum value determination function, a k 1 Corresponding priority pri k ＝(∑ x＝1 y(k) d kx )/y(k)，d kx Target paraphrasing information corresponding to the current failure identification and ms kx 1 Degree of matching between the two.
2. The method according to claim 1, wherein the step S320 includes the steps of:
s321, determining A 1 Whether a first preset failure identifier which is the same as the current failure identifier exists or not; if yes, go to step S340; otherwise, go to step S330;
the data update process further includes the steps of:
s340, determining whether preset paraphrasing information of a first preset failure identifier which is the same as the current failure identifier is the same as target paraphrasing information corresponding to the current failure identifier; if not, go to step S350;
s350, determining A 1 Whether the preset paraphrasing information which is the same as the target paraphrasing information corresponding to the current failure identification exists or not; if yes, go to step S360;
s360, from A 1 Deleting first preset failure information of a first preset failure identifier identical to the current failure identifier;
s370, will A 1 And replacing the first preset failure identifier corresponding to the preset paraphrasing information which is the same as the target paraphrasing information corresponding to the current failure identifier with the current failure identifier.
3. The method according to claim 2, wherein the step S350 includes the steps of:
s351, determining A 1 Whether the preset paraphrasing information which is the same as the target paraphrasing information corresponding to the current failure identification exists or not; if yes, go to step S360; otherwise, go to step S380;
the data update process further includes the steps of:
s380, adding the first preset failure information a 00 1 Added to A 1 Middle and pri max Corresponding to the first preset failure information group; a, a 00 1 ＝(bs 00 1 ,ms 00 1 )，bs 00 1 Ms for the current failure identification 00 1 Target paraphrasing information corresponding to the current failure identification; maximum priority pri max ＝max(pri 1 ,pri 2 ,...,pri k ,...,pri z ) Max () is a preset maximum value determination function, a k 1 Corresponding priority pri k ＝(∑ x＝1 y(k) d kx )/y(k)，d kx Target paraphrasing information corresponding to the current failure identification and ms kx 1 Matching degree between the two;
s390, mix A 1 In a 00 1 Each piece of first preset failure information is taken as candidate preset failure information, and is shown in A 1 And deleting candidate preset failure information of the first preset failure identifier identical to the current failure identifier.
4. The method of determining according to claim 1, wherein the server is connected to the target data source through a number of data interfaces of the server; the server is used for sending a corresponding data acquisition request to the target data source through each data interface; the target data source is configured to, for each data acquisition request sent by the server, if data acquisition according to the data acquisition request fails, return failure information corresponding to the data acquisition request to the server through a data interface corresponding to the data acquisition request;
the step S200 includes the steps of:
s201, A is as follows 1 Each first preset failure identifier corresponding to the key category is used as a target preset failure identifier;
s202, obtaining a time list TIME＝(time 1 ,time 2 ,...,time i ,...,time n )，time i ＝(time i1 ,time i2 ,...,time iu ,...,time iv(i) ) U=1, 2,. -%, v (i); wherein, time is i For the time group corresponding to the ith data interface, n is the number of the data interfaces, and time iu In mom for the server 2 And mom (mom) 1 Time between sending a ith data acquisition request to the target data source through an ith data interface i1 ≤time i2 ≤...≤time iu ≤...≤time iv(i) ，mom 2 ＜time iu ＜mom 1 The method comprises the steps of carrying out a first treatment on the surface of the v (i) is the server at mom 2 And mom (mom) 1 The number of data acquisition requests sent to the target data source through the ith data interface;
s203, according to TIME, obtaining a TIME difference list DeltaT= (Deltat) 1 ,Δt 2 ,...,Δt Q ,...,Δt n )，Δt i ＝(Δt i1 ,Δt i2 ,...,Δt iu ,...,Δt iv(i) ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein Δt is i For time of i Corresponding time difference group, Δt iu For time of iu A corresponding time difference; Δt (delta t) iu The following conditions are satisfied:
if u=1, Δt i1 ＝[(time i1 -mom 2 )+(time i2 -time i1 )]/2；
If u=q, Δt iq ＝[(time iq -time i(q-1) )+(time i(q+1) -time iq )]/2,q＝2,3,...,v(i)-1；
If u=v (i), Δt iv(i) ＝[(time iv(i) -time i(v(i)-1) )+(mom 1 -time iv(i) )]/2；
S204, according to the delta T, acquiring a first reliability parameter par= Σof the target data source i＝1 n [w i *s(i)/v(i)]The method comprises the steps of carrying out a first treatment on the surface of the S (i) is the number of target failure identifiers which are the same as any target preset failure identifier in all target failure identifiers corresponding to the ith data interface; w (w) i Weight corresponding to the ith data interface, w i ＝α*v(i)+β/F i Alpha is a first preset coefficient, beta is a second preset coefficient, F i For the time difference fluctuation parameter corresponding to the ith data interface, F i ＝[∑ u＝1 v(i) (Δt iu -Δt ave i ) 2 ]/v(i)，Δt ave i For the reference time difference corresponding to the ith data interface, deltat ave i ＝(∑ u＝1 v(i) Δt iu )/v(i)；
S205, determining whether par meets par not less than pre1; if yes, the target failure information meeting the key conditions meets the preset abnormal conditions, and the step S300 is carried out; otherwise, the target failure information meeting the key conditions does not meet the preset abnormal conditions, and the target data source is determined to be a normal data source; pre1 is a preset first target threshold.
5. The method of determining according to claim 4, wherein 1.ltoreq.α.ltoreq.5, and 100.ltoreq.β.ltoreq.10000.
6. The method according to claim 4 or 5, characterized in that pre 1= (Σ) i＝1 n w i ) Coe, coe are preset target coefficients, 0.5 < coe is less than or equal to 0.9.
7. The method according to claim 1, wherein the step S300 includes the steps of:
s301, determining A 1 Whether first preset failure information with the same target failure information exists or not; if yes, determining the target data source as an abnormal data source, and proceeding to step S400; otherwise, performing data updating processing on each target failure identifier, and entering step S300 after performing data updating processing on each target failure identifier;
the determination method further comprises the following steps:
s400, disconnecting the connection between the server and the target data source;
s500, connecting the server with a standby data source corresponding to the target data source.
8. The determination method according to claim 2, wherein the step S340 includes the steps of:
s341, determining whether preset paraphrasing information of a first preset failure identifier which is the same as the current failure identifier is the same as target paraphrasing information corresponding to the current failure identifier; if yes, finishing the data updating processing of the current failure identifier; otherwise, step S350 is entered.
9. A determination method according to any one of claims 1 to 3, wherein the degree of matching is a degree of matching between a characteristic value of the corresponding target paraphrasing information and a characteristic value of the corresponding preset paraphrasing information, or the degree of matching is a degree of semantic matching between the corresponding target paraphrasing information and the corresponding preset paraphrasing information.
10. The method of determining according to claim 9, wherein the characteristic value is a hash value.
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