CN113326064A - Method for dividing business logic module, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a method for dividing service logic modules, electronic equipment and a storage medium, wherein the method comprises the following steps: calculating a first increment corresponding to a trading forest based on a set modularity function and a first weight corresponding to every two connected nodes in the trading forest corresponding to the first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located; performing community division on the transaction forest based on the determined first increment, and determining at least two service logic modules corresponding to the first type of service based on the divided communities; the set modularity function at least comprises a first subfunction, and the first subfunction represents the negative correlation relationship between a first community currently corresponding to the first node and a second community currently located by the corresponding second node.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method for partitioning a business logic module, an electronic device, and a storage medium.
Background
With the development of computer technology, more and more technologies (e.g., big data, etc.) are applied in the financial field, and the traditional financial industry is gradually shifting to financial technology, however, the financial technology also puts higher demands on the technologies due to the security and real-time requirements of the financial industry. In the field of financial technology, in order to facilitate anomaly detection or data mining, in some application scenarios, service logic corresponding to the same service needs to be divided into at least two service logic modules, where the processing nodes in the same service logic module are in close contact with each other.
In the related art, a community discovery algorithm is adopted to perform community division on a service logic corresponding to a certain service to obtain at least two service logic modules corresponding to the service, but the number of nodes included in the divided service logic modules is very large and is inconsistent with that of the actually-desired service logic module, and an overfitting situation occurs. The community division of the business logic means that a part with close relation and a part with sparse relation are detected from the business logic.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an electronic device, and a storage medium for dividing a service logic module, so as to solve the technical problem in the related art that the number of nodes included in the service logic module divided by using a community discovery algorithm is too large.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the embodiment of the invention provides a method for dividing service logic modules, which comprises the following steps:
calculating a first increment corresponding to a trading forest based on a set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to a first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located;
performing community division on the transaction forest based on the determined first increment, and determining at least two service logic modules corresponding to the first type of service based on the divided communities; wherein the content of the first and second substances,
the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
In the above scheme, the first sub-function is constructed based on the total number of nodes in the first community and the corresponding total number of nodes in the second community.
In the foregoing solution, the determining, based on the divided communities, at least two service logic modules corresponding to the first type of service includes:
determining a label corresponding to each divided community based on the system identifier and the service identifier corresponding to each divided community;
and clustering the divided communities based on the determined labels to obtain at least two service logic modules corresponding to the first type of service.
In the foregoing solution, before calculating a first increment corresponding to each first node in the trading forest based on the set modularity function and the first weight corresponding to each two connected nodes in the trading forest corresponding to the first type of service, the method further includes: the method comprises the following steps:
based on the historical log corresponding to the historical service request of the first type service, constructing a transaction tree corresponding to each historical service request; wherein the transaction tree characterizes processing logic of historical service requests;
and merging the transaction trees corresponding to the historical service requests of the first type of service into a transaction forest based on the nodes commonly included in the constructed transaction trees.
In the above scheme, the method further comprises:
determining the occurrence frequency of each node in the transaction forest based on the serial number and/or the feature code corresponding to the transaction tree;
and determining a first weight corresponding to every two connected nodes in the trading forest based on the occurrence frequency of each node in the trading forest.
In the above scheme, the method further comprises:
determining a system identifier, a service identifier, a scene identifier and a calling relation among systems which are related to the historical service request; the system is used for processing historical service requests;
based on the calling relation among the systems, sequencing the determined system identification, service identification and scene identification to obtain a first character string;
and carrying out Hash operation on the first character string to obtain a feature code corresponding to the transaction tree.
In the above scheme, the method further comprises at least one of:
determining a community with the highest transaction tree similarity corresponding to a first service request from each determined service logic module to obtain a service logic module corresponding to the first service request;
and detecting whether the second service request responds abnormally based on the determined service logic module and a transaction tree corresponding to the second service request.
An embodiment of the present invention further provides an electronic device, including:
the calculation unit is used for calculating a first increment corresponding to the trading forest based on a set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to the first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located;
the determining unit is used for carrying out community division on the transaction forest based on the determined first increment and determining at least two service logic modules corresponding to the first type of service based on the divided communities; wherein the content of the first and second substances,
the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
An embodiment of the present application further provides an electronic device, including: a processor and a memory for storing a computer program capable of running on the processor,
the processor is configured to execute the steps of the method for partitioning the service logic module when running the computer program.
The embodiment of the present application further provides a storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the method for partitioning the service logic module.
In the embodiment of the invention, a modularity function is improved, and a first sub-function is added in the modularity function and is a punishment item of the modularity; when the node i is tried to be distributed to the community where a certain connected node j is located, the larger the value of the first sub-function is, the smaller the modularity of the transaction forest is, and the smaller the probability of distributing the node i to the community where the node j is located is, so that the condition that the partitioned community is over-fitted can be prevented, and therefore, the finally partitioned community accords with an expected business logic module in the number and size.
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Fig. 1 is a schematic flow chart illustrating an implementation of a method for partitioning service logic modules according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a service logic module according to an embodiment of the present invention;
fig. 3 is a schematic flow chart illustrating an implementation of a method for partitioning service logic modules according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to another embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware component structure of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present invention.
Fig. 1 is a schematic view of an implementation process of a method for partitioning a service logic module according to an embodiment of the present invention, where an execution subject of the process is an electronic device such as a terminal and a server. As shown in fig. 1, the method for dividing the service logic module includes:
step 101: and calculating a first increment corresponding to the trading forest based on the set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to the first type of service.
The first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located; the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
Here, the electronic device regards each node in the trading forest corresponding to the first type of service as an independent community; aiming at a first node in the trading forest, trying to distribute the first node to communities where each second node connected with the first node is located, and calculating a first increment corresponding to the trading forest. Wherein the content of the first and second substances,
and the transaction forest is obtained by combining the transaction trees corresponding to the historical service requests of the first type of service. The first node may be an initial node in a trading forest, or may be a new node compressed by all nodes in the same community after community division, that is, all nodes in the same community are considered as a new node.
The first increment characterizing a difference between the second modularity and the first modularity; the first modularity is the modularity of the trading forest before the first node is allocated to the community where the corresponding second node is located; the second modularity is the modularity of the trading forest after the first node is assigned to the community where the corresponding second node is located.
Modularity (Modularity) is a value Q describing the degree of closeness within a community, the Modularity characterizing the sum of the differences of the weights of the edges inside the community minus the weights of all the edges connected to the nodes of the community.
The modularity is used for measuring community division quality, and the value range of the modularity is larger than or equal to-0.5 and smaller than 1. The larger the Q value is, the better the community division quality is represented; the community division quality is good, the compactness of the nodes inside the representative community is high, and the compactness of the nodes outside the community is low.
The transaction tree represents the processing logic of the historical service request; a historical service request corresponds to a transaction tree; the nodes included in the transaction tree characterize the system that handles the historical service requests. The connection relationship between nodes in the transaction tree characterizes the call relationship between systems.
In order to avoid dividing a large community with a large number of nodes, the number of the divided communities is small, and the community division result is over-fitted, the embodiment of the invention improves the modularity function, wherein the modularity function in the embodiment of the invention comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community currently corresponding to a first node and a second community where a corresponding second node is located; the first sub-function is a punishment item of modularity; the larger the penalty term, the smaller the modularity.
In practical application, the electronic device may use a set first modularity function or a set second modularity function to respectively calculate a first modularity and a second modularity, and then calculate a difference between the second modularity and the first modularity to obtain a first increment corresponding to the trading forest. The electronic device can also calculate a first increment corresponding to the transaction forest by adopting a set third modularity function. Wherein the content of the first and second substances,
the first modularity function set is:
Aija first weight characterizing an edge between node i (first node) and node j (second node),
representing the sum of the weights of all edges connected with the node i;
the sum (also called degree) of the weights characterizing all edges connected to node j; c. CiRepresenting a community corresponding to the node i currently; c. CjRepresenting a community corresponding to the node j currently;
representing the sum of the weights of all edges in the trading forest; sigma (c)i,cj) Characterization ciAnd cjWhether the connection is made or not; when c is going toiAnd cjWhen connected, σ (c)i,cj) 1 is ═ 1; when c is going toiAnd cjWhen not connected, σ (c)i,cj)＝0。
Is a first sub-function, SiRepresenting the setting information of a first community corresponding to the first node at present; sjAnd representing the setting information of the second community corresponding to the second node currently.
Due to the fact that
The probability that node j is connected to any one node is
Degree of node i is kiIn some embodiments, the electronic device simplifies the set first modularity function to obtain a set second modularity function:
the set second modularity function is calculated by taking a community C as a minimum unit, wherein the community C is any community in the trading forest. Σ in represents the sum of the weights of the edges in the community C; Σ tot characterizes the sum of the weights of the edges connected to the nodes within community C.
The third modularity function is set as:
wherein k isi,inThe sum of the weights characterizing the edges connected to node i within community C.
In some embodiments, the first sub-function is constructed based on a total number of nodes of the first community and a corresponding total number of nodes of the second community.
That is to say that the position of the first electrode,
middle SiRepresenting the total number of nodes of a first community corresponding to the first node currently; sjAnd characterizing the total number of nodes of the second community corresponding to the second node currently. The larger the difference between the total number of nodes in the first community and the total number of nodes in the second community is, the smaller the actual value is because the first sub-function is a negative number, and therefore the lower the modularity Q is, the lower the probability of allocating the first node to the second node is.
In practical application, the expression of the first sub-function is as follows:
wherein n is a positive integer. In practical application, n is a positive integer less than or equal to 5.
Step 102: and performing community division on the transaction forest based on the determined first increment, and determining at least two service logic modules corresponding to the first type of service based on the divided communities.
Here, the electronic device determines the largest first increment from the determined first increments when determining the first increments corresponding to the transaction forests; in the event that the maximum first increment is less than or equal to zero, the first node is not assigned to other communities.
Under the condition that the maximum first increment is larger than zero, the first node is distributed to a community where a second node corresponding to the maximum first increment is located, and all nodes in the community are regarded as a new first node; and executing step 101, and performing community division on the transaction forest based on the determined first increment.
And under the condition that each node in the trading forest is subjected to community division and the modularity of the trading forest is not changed any more, determining at least two service logic modules corresponding to the first type of service based on the finally divided communities. The electronic device may perform clustering processing on the finally divided communities by using the communities as a minimum unit to obtain clustering results, and determine at least two service logic modules corresponding to the first type of service based on the clustering results. One type of community in the clustering result corresponds to a business logic module. In practice, the first type of service may correspond to a virtual product, such as a loan product. The first type of service may correspond to a service corresponding to a certain set function in a virtual product. Such as a query function.
In practical application, the implementation process of determining at least two service logic modules corresponding to the first type of service is as follows:
1. regarding each node in the trading forest as an independent community;
2. aiming at each node i in the trading forest, trying to distribute the node i to a community where each node j connected with the node i is located, and calculating a first increment corresponding to the trading forest; recording the community where the node j corresponding to the maximum first increment is located, and distributing the node i to the recorded community;
3. repeating the step 2 until communities corresponding to all the nodes do not change any more, and performing the step 4;
4. regarding all nodes in the same community as a new node, converting the weight of edges between the nodes in the community into the weight of a ring of the new node, converting the edge weight between the community intervals into the weight of edges between the new nodes, and circularly executing the steps 2 and 4 until the modularity of the transaction forest is not changed any more, and taking the result obtained by carrying out the community division for the last time as the community division result of the transaction forest;
5. and determining at least two service logic modules corresponding to the first type of service based on the divided communities.
Illustratively, the trading forest shown in fig. 2 is divided into 12 communities, and the 12 communities are divided into 8 business logic modules. Wherein different business logic modules are labeled with 1-8 in fig. 2; some of the partitioned communities in fig. 2 include only one node, and some include 3, 4, 5, or 6 nodes.
In the embodiment, the modularity function is improved, and a first sub-function is added in the modularity function, wherein the first sub-function is a punishment item of the modularity; when the node i is tried to be distributed to the community where a certain connected node j is located, the larger the value of the first sub-function is, the smaller the modularity of the transaction forest is, and the smaller the probability of distributing the node i to the community where the node j is located is, so that the condition that the partitioned community is over-fitted can be prevented, and therefore, the finally partitioned community accords with an expected business logic module in the number and size.
In order to determine the service logic modules more accurately, in some embodiments, the determining at least two service logic modules corresponding to the first type of service based on the divided communities includes:
determining a label corresponding to each divided community based on the system identifier and the service identifier corresponding to each divided community;
and clustering the divided communities based on the determined labels to obtain at least two service logic modules corresponding to the first type of service.
The electronic equipment determines a corresponding keyword based on the finally divided system identification and service identification corresponding to each community, and determines the keyword as a label of the corresponding community; based on the determined labels, clustering communities divided in the trading forest so as to classify communities with the same or similar labels into one class; and determining each type of community obtained by clustering as a service logic module corresponding to the first type of service.
The system identification and the service identification corresponding to the community are determined based on the system identification and the service identification corresponding to all the nodes in the community. The electronic device can sort the system identification and the service identification corresponding to the node based on the connection relationship between the nodes in the community, so that the system identification and the service identification corresponding to the community are obtained.
In practical application, the electronic equipment determines the label corresponding to each community according to the following method:
the electronic equipment calculates the first occurrence frequency and the first Inverse Document Frequency (IDF) of each system identifier according to the system identifier and the service identifier corresponding to the node included in the finally divided third community; calculating a second occurrence number and a second inverse document frequency of each service identifier; determining a first TF-IDF value corresponding to each system identifier based on the first occurrence frequency corresponding to each system identifier and the corresponding first inverse document frequency; determining a second TF-IDF value corresponding to each service identifier based on the second occurrence frequency corresponding to each service identifier and the corresponding second inverse document frequency; and determining a label corresponding to the third community based on the determined first TF-IDF value and the second TF-IDF value.
The third community is any one of finally obtained communities through division; the first inverse document frequency is determined based on the first total and the second total; the first total number represents the total number of finally divided communities in the transaction forest; the second total characterizes a total of communities that include the corresponding system identification; a second inverse document frequency is determined based on the first total and the third total; the third total characterizes a total number of communities that include the corresponding service identification.
In practical application, the electronic device may combine the first TF-IDF value with the largest occurrence number and the second TF-IDF value with the largest occurrence number to obtain the label corresponding to the third community.
To accurately determine a transaction forest, in some embodiments, prior to step 101, the method further comprises:
based on the historical log corresponding to the historical service request of the first type service, constructing a transaction tree corresponding to each historical service request; wherein the transaction tree characterizes processing logic of historical service requests;
and merging the transaction trees corresponding to the historical service requests of the first type of service into a transaction forest based on the nodes commonly included in the constructed transaction trees.
The electronic equipment determines a historical log corresponding to the historical service request of the first type service from the collected historical logs based on the type identifier; determining a system identifier, a service identifier, an IP address and a calling relation among systems which are related to each historical service request from a historical log corresponding to the historical service request of the first type service; and constructing a transaction tree corresponding to the corresponding historical service request based on the system identification, the service identification, the IP address and the call relation among systems related to each historical service request.
The number of the systems for processing the same historical service request is at least one, and each system corresponds to one historical log, so that one historical service request corresponds to at least one historical log. Each history log comprises a serial number, a system identifier, a service identifier, a scene identifier, an IP address, request initiation time and request end time. The serial number is used for identifying the historical service request, that is, the serial numbers of all the historical logs corresponding to the same historical service request are the same. The IP address refers to an IP address corresponding to the first device which outputs the corresponding history log; the historical log comprises request initiating time and request ending time and is used for determining the calling relationship between systems for processing the corresponding historical service requests. A first device is used to operate at least one system. A system can provide at least one service, and each service corresponds to at least one scene (or business scene); for example, the scenario corresponding to the query service includes querying customer information, querying personal account balance, querying public account balance, and the like.
It should be noted that the system described in the embodiment of the present invention is a sub-service system for processing a service request.
The electronic device can determine a node included in common from all constructed transaction trees under the condition that the transaction tree corresponding to each historical service request corresponding to the first type service is constructed, and aggregate the node in all the transaction trees corresponding to the first type service into one node, so that all the transaction trees corresponding to the first type service are merged into a corresponding transaction forest. In practical application, the same type of service corresponds to only one node which is commonly included in all transaction trees; the electronic device may mark the node as a core node.
In order to save community division time and improve community division efficiency, in some embodiments, under the condition that a transaction tree corresponding to each historical service request corresponding to the first type service is constructed, a transaction tree meeting a set condition can be screened out from the constructed transaction trees; and determining the nodes which are commonly included from the screened transaction trees, and aggregating the nodes in the screened transaction trees into one node, so that the screened transaction trees are combined to obtain a transaction forest corresponding to the first type of service. The set condition can be that the transaction amount is larger than a set threshold value, or the transaction amount is ranked in a set range; the transaction amount is obtained from a history log corresponding to the history service request.
In practical application, the electronic device determines a transaction tree corresponding to the first type of service according to the following method:
when the electronic equipment acquires all historical logs corresponding to one historical service request, constructing a transaction tree corresponding to the corresponding historical service request based on first data in the acquired historical logs; determining second data based on the obtained historical log, and determining a feature code corresponding to the corresponding transaction tree based on the determined second data; determining a transaction tree corresponding to the first type of service based on the feature code corresponding to each transaction tree and the set corresponding relationship between the service type identifier and the set feature code; and combining the transaction trees corresponding to the historical service requests of the first type of service into a transaction forest based on the nodes commonly included in the constructed transaction trees. The first data comprises a serial number, a system identifier, a service identifier, an IP address, request initiating time and request ending time; the second data comprises system identification, service identification, scene identification and call relation among systems related to historical business.
Considering that in practical application, the number of historical service requests is large, the number of constructed transaction trees is also large, and systems for processing different service requests may be different, so that the number of nodes included in a transaction forest obtained by merging transaction trees is large, and therefore, in order to conveniently and accurately count the number of occurrences of each node in the transaction forest, in some embodiments, before determining that the first type of service corresponds to step 101, the method further includes:
determining the occurrence frequency of each node in the transaction forest based on the serial number and/or the feature code corresponding to the transaction tree;
and determining a first weight corresponding to every two connected nodes in the trading forest based on the occurrence frequency of each node in the trading forest.
The serial number is obtained from a history log corresponding to the historical service request, and one serial number can uniquely identify one historical service request.
The feature code is determined based on data included in all history logs corresponding to the history service request. One feature code characterizes a class of service requests having the same service link. The same service link means that all systems processing the service request are the same, and the calling relationship between the systems is also the same.
When the electronic equipment acquires all historical logs corresponding to one historical service request, constructing a transaction tree corresponding to the corresponding historical service request based on first data in the acquired historical logs; determining a feature code of a corresponding transaction tree based on second data in the acquired history log; and determining the transaction tree corresponding to the first service type based on the feature code of each transaction tree and the set corresponding relationship between the service type identifier and the set feature code. Each service type identifier corresponds to a type of service, and each service type identifier corresponds to at least one set feature code in consideration of that a user can handle the same type of service through different portals (e.g., a web portal and an installed application).
The electronic equipment determines the occurrence frequency of each node in the transaction forest by the following method under the condition of acquiring the serial number corresponding to the transaction tree:
because each historical service request corresponds to a serial number and each historical service request corresponds to a transaction tree, the serial numbers corresponding to all nodes in one transaction tree are the same. The electronic equipment determines the occurrence frequency of each node corresponding to each serial number based on the serial number and the system identification corresponding to each node; and calculating the total occurrence frequency corresponding to each node based on the determined occurrence frequency of each node corresponding to each serial number to obtain the occurrence frequency of each node in the transaction forest.
The electronic equipment determines the occurrence frequency of each node in the transaction forest by the following method under the condition of acquiring the feature code corresponding to the transaction tree:
the electronic equipment determines the occurrence frequency of each node corresponding to each feature code based on the feature code corresponding to each node and the system identification; and calculating the total occurrence frequency corresponding to each node based on the determined occurrence frequency of each node corresponding to each feature code to obtain the occurrence frequency of each node in the transaction forest. Wherein the first type of service corresponds to at least one feature code.
In practical application, under the condition that the serial number and the feature code corresponding to the transaction tree are obtained, the occurrence frequency of each node in the transaction forest is determined in the following mode:
the electronic equipment determines the occurrence frequency of each node corresponding to each serial number based on the serial number and the system identification corresponding to each node; determining the occurrence frequency of each node corresponding to each feature code based on at least one serial number corresponding to each feature code and the occurrence frequency of each node corresponding to each serial number; and calculating the total occurrence frequency corresponding to each node based on the determined occurrence frequency of each node corresponding to each feature code to obtain the occurrence frequency of each node in the transaction forest. Wherein, one feature code can correspond to a plurality of serial numbers.
Under the condition that the occurrence frequency of each node in the trading forest is determined, the electronic equipment divides the occurrence frequency of the downstream node of every two nodes in the trading forest by the occurrence frequency of the upstream node to obtain first weights corresponding to the two corresponding nodes, and therefore the first weights corresponding to every two nodes in the trading forest can be determined.
In some embodiments, the feature code corresponding to the transaction tree is determined by:
determining a system identifier, a service identifier, a scene identifier and a calling relation among systems which are related to the historical service request; the system is used for processing historical service requests;
based on the calling relation among the systems, sequencing the determined system identification, service identification and scene identification to obtain a first character string;
and carrying out Hash operation on the first character string to obtain a feature code corresponding to the transaction tree.
The electronic equipment determines a system identifier, a service identifier, a scene identifier, and the receiving time and the ending time of the request from each historical log corresponding to the historical service request; because one historical service request corresponds to at least one historical log, and one historical log corresponds to one system, the electronic equipment can determine the calling relationship among the systems corresponding to the historical service request based on the system identifier, the request receiving time and the request ending time in each historical service; sequencing the determined system identification, server identification and scene identification based on the determined call relationship among the systems to obtain a first character string; and carrying out Hash operation on the first character string to obtain a feature code corresponding to the transaction tree corresponding to the historical service request.
After determining at least two service logic modules corresponding to the first type of service, in some embodiments, the method further comprises at least one of:
determining a community with the highest transaction tree similarity corresponding to a first service request from each determined service logic module to obtain a service logic module corresponding to the first service request;
and detecting whether the second service request responds abnormally based on the determined service logic module and a transaction tree corresponding to the second service request.
Here, the first service request and the second service request are both service requests of a first type of service. The first service request and the second service request may be the same or different.
After determining at least two service logic modules corresponding to the first type of service, the electronic device constructs a transaction tree corresponding to the first service request based on the log corresponding to the first service request under the condition of acquiring the log corresponding to the first service request; calculating the similarity between the transaction tree corresponding to the first service request and each determined community in each service logic module based on the system identifier and the service identifier included in the transaction tree corresponding to the first service request and the system identifier and the service identifier corresponding to each node in each determined community included in each service logic module; and when the similarity is greater than or equal to a first set threshold, determining a community with the highest similarity of the transaction tree corresponding to the first service request from each determined service logic module, so as to obtain the service logic module corresponding to the first service request. The electronic device may output a service logic module corresponding to the first service request for viewing or analysis by a relevant person.
After determining at least two service logic modules corresponding to the first type of service, the electronic device constructs a transaction tree corresponding to a second service request based on a log corresponding to the second service request under the condition of acquiring the log corresponding to the second service request; and determining whether the second service request responds to abnormity or not based on the transaction tree corresponding to the second service request and each community included in the determined service logic module. Wherein the content of the first and second substances,
under the condition that the similarity between the transaction tree corresponding to the second service request and all communities in the first service logic module is smaller than a second set threshold, representing that part or all of nodes in the communities corresponding to the first service logic module are missing in the transaction tree corresponding to the second service request, and responding to the second service request is abnormal; at this time, the electronic device may output prompt information based on a node in the community included in the first business logic module, so that the relevant person performs exception handling. The first service logic module is any one of the determined service logic modules. The second set threshold is less than or equal to the first set threshold.
And under the condition that the similarity between at least one community and the transaction tree corresponding to the second service request is greater than or equal to a second set threshold value in each determined service logic module, the second service request is represented to respond normally, and no missing node exists in the transaction tree corresponding to the second service request.
In this embodiment, the electronic device may quickly determine, based on the transaction tree corresponding to the new service request, a service logic module corresponding to the new service request from the determined service logic module; and whether the new service request responds abnormally can be quickly determined based on the determined service logic module, and under the condition that the new service request responds abnormally, the reason of the abnormality can be checked by taking the service logic module as a unit so as to improve the efficiency of abnormality processing.
Fig. 3 is a schematic flow chart illustrating an implementation of the method for partitioning service logic modules according to an embodiment of the present invention. As shown in fig. 3, the method for dividing the service logic module includes:
step 301: constructing a transaction tree corresponding to each historical service request based on the historical log corresponding to the historical service request; wherein the transaction tree characterizes processing logic of historical service requests.
Here, each time the electronic device acquires all history logs corresponding to one history service request, a transaction tree corresponding to the history service request is constructed.
Step 302: determining a system identifier, a service identifier, a scene identifier and a calling relation among systems which are related to the historical service request; the system is used for processing historical service requests.
Step 303: and sequencing the determined system identifier, service identifier and scene identifier based on the call relation among the systems to obtain a first character string.
Step 304: and carrying out Hash operation on the first character string to obtain a feature code corresponding to a transaction tree corresponding to the historical service request.
Step 305: and determining all transaction trees corresponding to the first type of service from the constructed transaction trees based on at least one set feature code corresponding to the first type of service.
The first type of service may be a service corresponding to a set function of a virtual product, and in actual application, the first type of service is a query type service of a particulate credit product.
Step 306: and merging the transaction trees corresponding to the first type services with the transaction amount meeting the set conditions into a transaction forest based on the nodes which are commonly included in all the transaction trees corresponding to the first type services.
And acquiring the transaction amount from a history log corresponding to the corresponding history service request. In practical applications, the transaction amount satisfying the setting condition may be the top 20 of the transaction amount ranking.
Step 307: and determining the occurrence frequency of each node in the transaction forest based on the feature codes corresponding to the transaction trees.
The electronic equipment determines the occurrence frequency of each node corresponding to each feature code based on the feature code corresponding to each node and the system identification; and calculating the total occurrence frequency corresponding to each node based on the determined occurrence frequency of each node corresponding to each feature code to obtain the occurrence frequency of each node in the transaction forest.
Step 308: and determining a first weight corresponding to every two connected nodes in the trading forest based on the occurrence frequency of each node in the trading forest.
Step 309: each node in a trading forest is considered an independent community.
Step 310: aiming at each node i in the trading forest, trying to distribute the node i to a community where each node j connected with the node i is located, and calculating a first increment corresponding to the trading forest; and distributing the node i to the community where the node j corresponding to the maximum first increment is located.
Wherein the first increment represents a modularity increment when the corresponding node i is allocated to a community where the connected node j is located. The set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community currently corresponding to the node i and a second community currently located by the corresponding node j. That is, node i is the first node in the above, and node j is the second node in the above.
In the case that the community corresponding to each node i in the trading forest does not change any more, step 311 is executed. Under the condition that the maximum first increment is 0, representing that communities corresponding to corresponding nodes i in the trading forest change;
in the case that the maximum first increment is less than or equal to 0, the community corresponding to each node i in the characterization trading forest does not change any more.
Step 311: step 310 is performed by considering all nodes in the same community as a new node.
And under the condition that the modularity of the transaction forest is not changed any more, stopping the community division and executing the step 312.
Step 312: and determining at least two service logic modules corresponding to the first type of service based on the divided communities.
In order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides an electronic device, as shown in fig. 4, where the electronic device includes:
the calculating unit 41 is configured to calculate a first increment corresponding to a trading forest based on a set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to the first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located;
a determining unit 42, configured to perform community division on the transaction forest based on the determined first increment, and determine, based on the divided communities, at least two service logic modules corresponding to the first type of service; wherein the content of the first and second substances,
the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
In some embodiments, the first sub-function is constructed based on a total number of nodes of the first community and a corresponding total number of nodes of the second community.
In some embodiments, the determining unit 42 is specifically configured to:
determining a label corresponding to each divided community based on the system identifier and the service identifier corresponding to each divided community;
and clustering the divided communities based on the determined labels to obtain at least two service logic modules corresponding to the first type of service.
In some embodiments, the electronic device further comprises:
the construction unit is used for constructing a transaction tree corresponding to each historical service request based on the historical log corresponding to the historical service request of the first type service; wherein the transaction tree characterizes processing logic of historical service requests;
and the merging unit is used for merging the transaction trees corresponding to the historical service requests of the first type of service into a transaction forest based on the nodes commonly included in the constructed transaction trees.
In some embodiments, the electronic device further comprises a weight determination unit to:
determining the occurrence frequency of each node in the transaction forest based on the serial number and/or the feature code corresponding to the transaction tree;
and determining a first weight corresponding to every two connected nodes in the trading forest based on the occurrence frequency of each node in the trading forest.
In some embodiments, the electronic device further comprises a feature code determination unit configured to:
determining a system identifier, a service identifier, a scene identifier and a calling relation among systems which are related to the historical service request; the system is used for processing historical service requests;
based on the calling relation among the systems, sequencing the determined system identification, service identification and scene identification to obtain a first character string;
and carrying out Hash operation on the first character string to obtain a feature code corresponding to the transaction tree.
In some embodiments, the electronic device further comprises a detection unit for performing at least one of:
determining a community with the highest transaction tree similarity corresponding to a first service request from each determined service logic module to obtain a service logic module corresponding to the first service request;
and detecting whether the second service request responds abnormally based on the determined service logic module and a transaction tree corresponding to the second service request.
In practical applications, the calculating Unit 41, the determining Unit 42, the constructing Unit, the merging Unit, the weight determining Unit and the feature code determining Unit may be implemented by a Processor in an electronic device, such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Micro Control Unit (MCU) or a Programmable Gate Array (FPGA), and the like.
It should be noted that: in the electronic device provided in the foregoing embodiment, when the business logic module is divided, only the division of each program module is taken as an example, and in practical applications, the processing distribution may be completed by different program modules according to needs, that is, the internal structure of the apparatus is divided into different program modules, so as to complete all or part of the processing described above. In addition, the electronic device provided by the above embodiment and the method embodiment for dividing the service logic module belong to the same concept, and specific implementation processes thereof are detailed in the method embodiment and are not described herein again.
Based on the hardware implementation of the program module, in order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides an electronic device. Fig. 5 is a schematic diagram of a hardware component structure of an electronic device according to an embodiment of the present invention, and as shown in fig. 5, the electronic device 5 includes:
a communication interface 51 capable of information interaction with other devices such as network devices and the like;
and the processor 52 is connected with the communication interface 51 to implement information interaction with other devices, and is used for executing the method for dividing the service logic module provided by one or more of the above technical solutions when running the computer program. And the computer program is stored on the memory 53.
Of course, in practice, the various components in the electronic device 5 are coupled together by a bus system 54. It will be appreciated that the bus system 54 is used to enable communications among the components. The bus system 54 includes a power bus, a control bus, and a status signal bus in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 54 in fig. 5.
The memory 53 in embodiments of the present invention is used to store various types of data to support the operation of the electronic device 5. Examples of such data include: any computer program for operating on the electronic device 5.
It will be appreciated that the memory 53 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 53 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The method disclosed in the above embodiments of the present invention may be applied to the processor 52, or implemented by the processor 52. Processor 52 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 52. The processor 52 described above may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 52 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 53, and the processor 52 reads the program in the memory 53 and performs the steps of the aforementioned method in conjunction with its hardware.
Optionally, when the processor 52 executes the program, the corresponding process implemented by the terminal in each method according to the embodiment of the present invention is implemented, and for brevity, no further description is given here.
In an exemplary embodiment, the present invention further provides a storage medium, i.e. a computer storage medium, in particular a computer readable storage medium, for example comprising a first memory 53 storing a computer program, which is executable by a processor 52 of a terminal to perform the steps of the aforementioned method. The computer readable storage medium may be Memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The technical means described in the embodiments of the present invention may be arbitrarily combined without conflict.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for partitioning business logic modules, comprising:
calculating a first increment corresponding to a trading forest based on a set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to a first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located;
performing community division on the transaction forest based on the determined first increment, and determining at least two service logic modules corresponding to the first type of service based on the divided communities; wherein the content of the first and second substances,
the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
2. The method of claim 1, wherein the first sub-function is constructed based on a total number of nodes of the first community and a corresponding total number of nodes of the second community.
3. The method of claim 1, wherein the determining at least two service logic modules corresponding to the first type of service based on the divided communities comprises:
determining a label corresponding to each divided community based on the system identifier and the service identifier corresponding to each divided community;
and clustering the divided communities based on the determined labels to obtain at least two service logic modules corresponding to the first type of service.
4. The method of claim 1, wherein prior to calculating the first increment for each first node in the trading forest based on the set modularity function and the first weights for each two connected nodes in the trading forest corresponding to the first type of traffic, the method further comprises: the method comprises the following steps:
based on the historical log corresponding to the historical service request of the first type service, constructing a transaction tree corresponding to each historical service request; wherein the transaction tree characterizes processing logic of historical service requests;
and merging the transaction trees corresponding to the historical service requests of the first type of service into a transaction forest based on the nodes commonly included in the constructed transaction trees.
5. The method of claim 4, further comprising:
determining the occurrence frequency of each node in the transaction forest based on the serial number and/or the feature code corresponding to the transaction tree;
and determining a first weight corresponding to every two connected nodes in the trading forest based on the occurrence frequency of each node in the trading forest.
6. The method of claim 5, further comprising:
determining a system identifier, a service identifier, a scene identifier and a calling relation among systems which are related to the historical service request; the system is used for processing historical service requests;
based on the calling relation among the systems, sequencing the determined system identification, service identification and scene identification to obtain a first character string;
and carrying out Hash operation on the first character string to obtain a feature code corresponding to the transaction tree.
7. The method according to any one of claims 1 to 6, further comprising at least one of:
determining a community with the highest transaction tree similarity corresponding to a first service request from each determined service logic module to obtain a service logic module corresponding to the first service request;
and detecting whether the second service request responds abnormally based on the determined service logic module and a transaction tree corresponding to the second service request.
8. An electronic device, comprising:
the calculation unit is used for calculating a first increment corresponding to the trading forest based on a set modularity function and first weights corresponding to every two connected nodes in the trading forest corresponding to the first type of service; the first increment represents the modularity increment when the corresponding first node is distributed to the community where each connected second node is located;
the determining unit is used for carrying out community division on the transaction forest based on the determined first increment and determining at least two service logic modules corresponding to the first type of service based on the divided communities; wherein the content of the first and second substances,
the set modularity function at least comprises a first sub-function, and the first sub-function represents the negative correlation relationship between a first community corresponding to the first node and a second community corresponding to the second node.
9. An electronic device, comprising: a processor and a memory for storing a computer program capable of running on the processor,
wherein the processor is adapted to perform the steps of the method of any one of claims 1 to 7 when running the computer program.
10. A storage medium having a computer program stored thereon, the computer program, when being executed by a processor, realizing the steps of the method of any one of claims 1 to 7.
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