CN105590224A - Method for determining failure node in transaction process - Google Patents
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- CN105590224A CN105590224A CN201510396627.8A CN201510396627A CN105590224A CN 105590224 A CN105590224 A CN 105590224A CN 201510396627 A CN201510396627 A CN 201510396627A CN 105590224 A CN105590224 A CN 105590224A
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- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000012544 monitoring process Methods 0.000 claims abstract description 76
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 230000000977 initiatory effect Effects 0.000 claims description 3
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 claims 2
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- 238000007619 statistical method Methods 0.000 abstract description 3
- 238000004458 analytical method Methods 0.000 description 9
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- 238000012216 screening Methods 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
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Abstract
The invention relates to a method for determining a failure node in a transaction process. The method comprises the steps of: acquiring a failure transaction set; determining at least one monitoring dimension based on the transaction process; determining a failure transaction probability corresponding to each monitoring dimension and relevancy between each monitoring dimension and the failure transaction set; and ranking the relevancies corresponding to the monitoring dimensions, and determining the failure node based on the monitoring dimension corresponding to the highest relevancy. The method can ensure the positioning accuracy of the failure node, and does not need to perform statistical analysis on massive data, thereby being higher in efficiency.
Description
Technical Field
The invention relates to the technical field of electronic commerce, in particular to a method for determining a failure node in a transaction process.
Background
With the development and popularization of the electronic commerce technology, the analysis of transaction failure is one of the focuses of attention in the industry, the success rate of electronic transaction can be improved, the transaction safety performance can be improved, the bottleneck of each transaction node can be found, and the stability of the whole transaction system can be optimized.
The existing transaction failure analysis is generally a fault study and judgment method based on success rate and TPS, the transaction failure analysis can only do qualitative study and judgment, and the fault occurring at a certain node in a transaction flow/path can not be accurately positioned. It is often the case that in a failure scenario, multiple nodes will reflect different levels of failure or fluctuation at the same time, and it is difficult to accurately screen and locate the true failed node. In order to obtain the accuracy of locating the failed node, a lot of time is often spent on analyzing and counting huge amount of data.
Disclosure of Invention
The invention aims to provide a method for determining a failure node in a transaction flow, which can accurately and efficiently locate the failure node in the transaction flow.
In order to achieve the above purpose, the invention provides a technical scheme as follows:
a method for determining failure nodes in a transaction flow comprises the following steps: a) acquiring a failure transaction set, wherein the failure transaction set comprises a plurality of failure transaction records; b) determining at least one monitoring dimension based on the transaction flow; c) determining the probability of the failure transaction corresponding to each monitoring dimension and the correlation degree of the failure transaction set; d) and sequencing the relevancy corresponding to each monitoring dimensionality, and determining a failure node based on the monitoring dimensionality corresponding to the highest relevancy.
Preferably, step e) is also included after step d): determining the failure degree and/or failure range of the failed node.
The method for determining the failure node in the transaction flow can accurately and efficiently locate the most possible failure node in the transaction flow. Even under the condition that the number of transaction records corresponding to a certain monitoring dimension is small, the most possible failure node can be accurately positioned. Compared with the method provided in the prior art, the method is simple to implement, and does not need to carry out statistical analysis on massive data under the condition of ensuring the accuracy of the positioning of the failure node, so that the efficiency is higher. The method is suitable for popularization and application in the industry.
Drawings
FIG. 1 illustrates a set of transaction records corresponding to a monitoring dimension with a set of failed transactions.
FIG. 2 illustrates a set of transaction records and a set of failed transactions corresponding to the same monitoring dimension in two different scenarios.
FIG. 3 illustrates a set of transaction records and a set of failed transactions for the same and different monitoring dimensions in three different scenarios.
Fig. 4 shows a flow of a method for determining a failure node in a transaction flow according to a first embodiment of the present invention.
Fig. 5 is a block diagram of a system for determining a failed node in a transaction flow according to a third embodiment of the present invention.
Detailed Description
It should be noted that, the "monitoring dimension" referred to herein is whether a certain determination is met or not, and the transaction records meeting the determination are formed into the transaction records corresponding to the monitoring dimension.
According to embodiments of the present invention, there is an intersection between the set of transaction records corresponding to the monitoring dimension and the failed transaction set, where the intersection is the set of failed transaction records corresponding to the monitoring dimension. The "set of failed transactions" referred to herein is derived from an electronic transaction database, which may represent the collective set of all of the failed transaction records, or may represent the collective set of failed transaction records resulting from a certain type of transaction failure.
For a certain monitoring dimension, the ratio of the number of the corresponding failed transaction records to the number of the failed transaction records in the failed transaction set is defined as the probability of the failed transaction corresponding to the monitoring dimension.
The "area" of a collection as referred to herein refers to the number of transaction records that the collection contains.
As shown in FIG. 1, A represents a set of transaction records corresponding to a certain monitoring dimension, B represents a set of failed transactions, and it can be seen that an intersection AB exists between the two, which is shown by the overlapping part of two circlesAnd AB is the set of the failure transaction records corresponding to the monitoring dimension. The probability of a failed transaction corresponding to the monitoring dimension can be expressed asI.e. it may be calculated as the ratio of the area of the overlapping part AB to the area of the set a.
FIG. 2 illustrates two scenarios, where in the first scenario, A represents a set of transaction records corresponding to a certain monitoring dimension, and B represents a set of failed transactions corresponding to a first type of transaction failure; in a second scenario, a represents a set of transaction records corresponding to the same monitoring dimension, and C represents a failed transaction set corresponding to a second type of transaction fault. It can be seen that even though the probability of a failed transaction for the monitoring dimension is the same in two different scenarios (because of the fact thatThereby to make) But the actual transaction failure is different.
According to the fault studying and judging method based on the success rate provided in the prior art, different actual transaction faults cannot be distinguished, and further failure nodes in a transaction flow cannot be determined.
According to a first embodiment of the present invention, a method for determining a failure node in a transaction flow is provided, which introduces a correlation between monitoring dimensions and failed transaction sets to resolve different actual transaction failures (such as the above-mentioned situation). The relevance of a monitoring dimension to a set of failed transactions can be defined as. A represents a set of transaction records corresponding to a certain monitoring dimension, B represents a failure transaction set, and Area (A | | B) represents the Area of the union of the set A and the set B.
The first embodiment of the present invention will be specifically described with reference to three scenarios shown in fig. 3. In a first scene, A represents a set of transaction records corresponding to a first monitoring dimension, and B represents a failure transaction set corresponding to a first type of transaction fault; in a second scenario, A represents a set of transaction records corresponding to the first monitoring dimension, and C represents a failure transaction set corresponding to the second type of transaction fault; in a third scenario, a' represents a set of transaction records corresponding to the second monitoring dimension, and D represents a set of failed transactions corresponding to a third type of transaction failure.
Wherein,indicating that the number of failed transaction records in the failed transaction set corresponding to the first type of transaction fault is equal to the number of failed transaction records in the failed transaction set corresponding to the second type of transaction fault.It is indicated that the number of transaction records in the transaction record set a corresponding to the first type of monitoring dimension is much larger than the number of transaction records in the transaction record set a' corresponding to the second type of monitoring dimension.
It can be seen that even inIn the case of (2), it is still possible to satisfy the definition of the degree of correlation of the monitoring dimension with the set of failed transactions. This means that even if the number of transaction records corresponding to a certain monitoring dimension is small, it is possible to distinguish transaction faults by the index of correlation.
The method for determining a failure node in a transaction flow according to the first embodiment of the present invention specifically includes the following steps, as shown in fig. 4.
Step S10, a failure transaction set is obtained, wherein the failure transaction set comprises a plurality of failure transaction records.
Specifically, a set of failed transactions may be obtained from the electronic transaction database, which may be a set of failed transaction records as a whole, or a set of failed transaction records caused by a certain type of transaction failure. The acquisition process may be performed using SQL query statements.
Step S11, determining at least one monitoring dimension based on the transaction flow.
It will be appreciated that the transaction flow includes a plurality of transaction nodes, each of which may be disabled, whereby at least one monitoring dimension may be determined based on the transaction flow.
Transaction records corresponding to any monitoring dimension are also derived from the electronic transaction database, and comprise failure transaction records and successful transaction records. The method for determining the failure node in the transaction process mainly analyzes the failure transaction record corresponding to the monitoring dimension.
In this step S11, the number of monitoring dimensions determined can be customized by the user. The user may consider the following factors in determining the monitoring dimension based on the transaction flow: a network node through which transaction data flows; a communication line through which transaction data flows; application software (App) employed by the exchange; a transaction time; a transaction initiation location; and identity information of both parties of the transaction, etc.
And step S12, determining the probability of the failed transaction corresponding to each monitoring dimension and the correlation degree of the failed transaction set.
According to the related definition of the invention, for any monitoring dimension, the corresponding failure transaction probability is defined according to the definitionAnd (6) performing calculation. Wherein, a represents the set of transaction records corresponding to any monitoring dimension, B represents the failed transaction set, Area (AB) represents the area of the intersection AB, and area (a) represents the area of the set a. For any monitoring dimension, the degree of correlation with the failure transaction set is definedAnd (6) performing calculation.
And S13, sequencing the relevancy corresponding to each monitoring dimension, and determining a failure node based on the monitoring dimension corresponding to the highest relevancy.
In this step, the relevance degrees corresponding to the monitoring dimensions are arranged in a descending order, wherein the monitoring dimension corresponding to the highest relevance degree indicates the most likely failed node.
Those skilled in the art will appreciate that 2 or more failed nodes may also be determined from the monitoring dimension corresponding to the top 2 or more relevance ranks. Then further screening is performed according to other criteria.
According to a further improved embodiment of the present invention, after the above step S13, the method further comprises step S14: determining the failure degree and/or failure range of the failed node.
Further, the failure degree is defined as P (AB | A), and the failure range is defined as P (AB | B); wherein, a represents a set of transaction records corresponding to a monitoring dimension corresponding to a failed node, B represents the failed transaction set, P (AB | a) represents a probability of AB occurring under a condition of a occurring, and P (AB | B) represents a probability of AB occurring under a condition of B occurring.
The degree of failure and the extent of failure may be used to further screen the determined 2 or more failed nodes.
Further improved, after the step S13, a step of feeding back the determined failed node to the user may be further included. Alternatively, after determining the failure degree and/or failure range of each failed node according to step S14, feedback is given to the user together.
After the feedback is obtained, the user can perform corresponding processing on each failure node. For example, troubleshooting the most likely failed node. If the user confirms that a certain failed node is an interference item, the following steps can be further carried out: and deleting the transaction record corresponding to the failure node from the failure transaction set.
According to the second embodiment of the present invention, failure transaction scenario analysis and fluctuation transaction scenario analysis can also be performed.
The analysis of the failure transaction scene can be carried out according to the following steps: 1) determining a monitoring view and the overall monitoring range. 2) And calculating the total transaction amount in the monitoring view field, and determining a failure transaction record set B. 3) Determining a required monitoring dimension in a monitoring view, and determining a transaction record set A corresponding to the monitoring dimension and a failure transaction record set AB corresponding to the monitoring dimension. 4) And calculating the correlation corresponding to the monitoring dimension according to the set A, B, AB. 5) And repeating the steps 3) and 4), sorting the relevancy corresponding to all the monitoring dimensions and outputting the sorted relevancy, and determining the failure node by using the monitoring dimension corresponding to the maximum relevancy. 6) And determining the failure degree P (AB | A) and the failure range P (AB | B) of the current failure node.
The analysis of the fluctuating trading scenario is similar to that of the failed trading scenario, but the difference points are as follows:
1) two monitoring intervals need to be specified to carry out fluctuation calculation. 2) And respectively calculating two fluctuation conditions of transaction increase and transaction decrease. 3) Under the condition of not using the intermediate table, the correlation calculation can be carried out on the monitoring dimensionality in one domain to replace the calculation of the universe, an approximate result is obtained, and common misjudgment scenes are eliminated.
After failure transaction scenario analysis and fluctuation transaction scenario analysis are performed, the failure nodes can be divided into nodes causing transaction failure and nodes causing transaction fluctuation. Nodes that cause transaction failures have the highest priority to be screened for processing, while nodes that cause transaction fluctuations have lower processing priorities, which are typically observed or monitored first.
Further, depending on the transaction flow, the determined failed node may be any one or any number of the following: a network node through which transaction data flows; a communication line through which transaction data flows; application software adopted by the exchange; a transaction time; a transaction initiation location; and identity information of both parties of the transaction.
The method for determining the failure node in the transaction flow provided by the first and second embodiments is simple to implement, and compared with the method provided by the prior art, the method can ensure the accuracy of the positioning of the failure node and does not need to perform statistical analysis on a large amount of data, so that the efficiency is higher.
As shown in fig. 5, a system for determining a failure node in a transaction flow according to a third embodiment of the present invention includes a (monitoring) dimension determining module, a transaction record obtaining module, a relevancy calculating module, and a result outputting module.
Wherein the (monitoring) dimension determination module is configured to determine at least one monitoring dimension based on the transaction flow. The transaction record acquisition module acquires a full set or a subset of transaction records from the electronic transaction database, and further determines a transaction record set and a failure transaction set corresponding to the monitoring dimension. And the correlation calculation module is used for calculating the correlation corresponding to each monitoring dimension. And the result output module is used for sequencing the relevancy and outputting the monitoring dimension corresponding to the highest relevancy, and the most possible failure node can be determined from the monitoring dimension.
In the third embodiment, the correlation calculation module performs calculation according to the correlation calculation formula provided in the first embodiment.
In a further refinement, the system may further comprise a feedback module (not shown) which provides feedback results to the (monitoring) dimension determination module with the output of the result output module as input, in order to exclude the influence of invalid nodes which may be interfering terms on the final result.
The system of the third embodiment has a simple structure and is convenient to popularize and apply in the industry.
The above description is only for the preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Various modifications may be made by those skilled in the art without departing from the spirit of the invention and the appended claims.
Claims (8)
1. A method for determining failure nodes in a transaction flow comprises the following steps:
a) acquiring a failure transaction set, wherein the failure transaction set comprises a plurality of failure transaction records;
b) determining at least one monitoring dimension based on the transaction flow;
c) determining the probability of failure transaction corresponding to each monitoring dimension and the correlation degree of the failure transaction set;
d) and sequencing the relevancy corresponding to each monitoring dimension, and determining the failure node based on the monitoring dimension corresponding to the highest relevancy.
2. The method according to claim 1, further comprising step e) after said step d):
determining the failure degree and/or failure range of the failed node.
3. The method of claim 2, wherein the failure degree is defined as P (AB | a), the failure range is defined as P (AB | B);
wherein A represents a set of transaction records corresponding to the monitoring dimension corresponding to the failed node, B represents the failed transaction set, P (AB | A) represents the probability of AB occurring under the condition of A occurring, and P (AB | B) represents the probability of AB occurring under the condition of B occurring.
4. The method of claim 1, wherein the set of failed transactions is from an electronic transaction database.
5. The method of claim 1, further comprising, after step d), step f):
and feeding back the determined failure node to a user.
6. The method according to claim 5, further comprising step g) after said step f):
and after the failure node is confirmed to be an interference item, deleting the transaction record corresponding to the failure node from the failure transaction set.
7. The method according to any one of claims 1 to 6, wherein the failed nodes are divided into nodes causing transaction failure and nodes causing transaction fluctuation.
8. The method according to any one of claims 1 to 6, wherein the failed node comprises any one or more of:
a network node through which transaction data flows;
a communication line through which transaction data flows;
application software adopted by the exchange;
a transaction time;
a transaction initiation location; and
identity information of both parties of the transaction.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510396627.8A CN105590224A (en) | 2015-07-08 | 2015-07-08 | Method for determining failure node in transaction process |
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| CN201510396627.8A CN105590224A (en) | 2015-07-08 | 2015-07-08 | Method for determining failure node in transaction process |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109345249A (en) * | 2018-08-02 | 2019-02-15 | 阿里巴巴集团控股有限公司 | A kind of payment fail processing method and device |
| CN111526063A (en) * | 2020-03-04 | 2020-08-11 | 平安科技（深圳）有限公司 | Link breakpoint monitoring method, device, terminal and storage medium based on whole service |
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2015
- 2015-07-08 CN CN201510396627.8A patent/CN105590224A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109345249A (en) * | 2018-08-02 | 2019-02-15 | 阿里巴巴集团控股有限公司 | A kind of payment fail processing method and device |
| CN109345249B (en) * | 2018-08-02 | 2021-07-20 | 创新先进技术有限公司 | Payment failure processing method and device |
| CN111526063A (en) * | 2020-03-04 | 2020-08-11 | 平安科技（深圳）有限公司 | Link breakpoint monitoring method, device, terminal and storage medium based on whole service |
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