CN111930604B - Online transaction performance analysis method and device, electronic equipment and readable storage medium - Google Patents
Online transaction performance analysis method and device, electronic equipment and readable storage medium Download PDFInfo
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Abstract
The present disclosure provides an online transaction performance analysis method, an online transaction performance analysis apparatus, an electronic device, and a computer-readable storage medium, which can be used in the financial field or other fields. Wherein the method comprises the following steps: acquiring transaction information of each transaction in the operation process, wherein the transaction information comprises resource calling information and transaction real-time operation data; and analyzing the online transaction performance according to the resource calling information and the transaction real-time operation data.
Description
Technical Field
The present disclosure relates to the field of online transactions, and in particular, to an online transaction performance analysis method and apparatus, an electronic device, and a readable storage medium.
Background
At present, the method for managing the online transaction performance of the host computer is to utilize a tool to import a performance capacity database after the host computer smf (background service management mechanism) generates relevant information at fixed time, and then make trend judgment through SQL (structured query language) sentences, so as to find out certain transactions with possible processing time efficiency problems in running time. Then for these potentially problematic transactions, comprehensive analysis is performed using online logs, CICS (customer information control System, custom Information Control System, which is the most popular transaction processing System for IBM), DB2 (IBM DB2 is a set of relational database management systems developed by IBM corporation of America), and so forth, to locate efficient online programs, database tables, etc. And finally, carrying out solutions such as related optimization and the like according to the analysis and determination result.
However, there are some drawbacks in the prior art: if the evaluation dimension of the transaction is single at present, the situation of single performance index of the transaction is often checked in a split way, for example, only response time is checked, or only processor consumption is checked, and the like, the whole operation situation of the transaction cannot be controlled from the global angle; the performance data of the transaction are all sourced from the host smf, and the information can be acquired only by printing a report after the fact, so that the problem analysis timeliness can be influenced; the access relationship of the internal resources of the host transaction is unknown, so that sustainable optimization treatment cannot be realized; the KPI trend indexes of transactions are all based on expert rules, and false alarm or missing alarm phenomena often occur.
With larger and faster production scale, the trading rate of the host system in peak period has increased from about 5500 in 12 years to about 16000 at present, and the service volume increases by 1.9 times more throughout the day. The adoption of the current management method is far from the requirement of business development, and a more effective and rapid host transaction performance management and analysis method is urgently needed to replace the traditional operation and maintenance mode, so that the operation safety of a production operation system is ensured.
Disclosure of Invention
In view of this, the present disclosure provides an online transaction performance analysis method and apparatus, an electronic device, and a readable storage medium.
One aspect of the present disclosure provides an online transaction performance analysis method, comprising: acquiring transaction information of each transaction in the operation process, wherein the transaction information comprises resource calling information and transaction real-time operation data; and analyzing the online transaction performance according to the resource calling information and the transaction real-time operation data.
According to an embodiment of the present disclosure, the analyzing the online transaction performance according to the resource calling information includes: generating a resource calling relation according to the resource calling information of each transaction in the running process; determining repeatedly called resource information and processor resource distribution information according to the resource calling relation; and locating the performance fault according to the repeatedly called resource information and the processor resource distribution information.
According to an embodiment of the disclosure, the analyzing the online transaction performance according to the transaction real-time operation data includes: analyzing transaction amount and application success rate data which are uploaded by each channel application according to the transaction real-time operation data; and estimating the transaction rate of each channel transaction of the host according to the transaction amount and the application success rate data which are uploaded by each channel application.
According to an embodiment of the present disclosure, the online transaction performance analysis method further includes:
after the transaction rate of each channel transaction of the host is estimated, determining the increase amplitude of the transaction rate according to the transaction rate estimated value and the history transaction rate of the history synchronization;
outputting a transaction trend abnormity signal under the condition that the transaction rate increase amplitude exceeds a preset threshold value.
According to an embodiment of the present disclosure, the online transaction performance analysis method further includes: each transaction is analyzed from N dimensions to determine a health composite score for each transaction, where N is a positive integer, the N dimensions including at least two of transaction rate, response time, processor consumption, transaction success rate, and transaction complexity.
According to an embodiment of the present disclosure, the online transaction performance analysis method further includes: and adopting an N-dimensional radar chart to manufacture a proprietary label corresponding to each dimension for each transaction.
Another aspect of the present disclosure provides an online transaction performance analysis apparatus, comprising:
the first acquisition module is used for acquiring transaction information of each transaction in the operation process, wherein the transaction information comprises resource calling information and transaction real-time operation data; and
the first analysis module is used for analyzing the online transaction performance according to the resource calling information and the transaction real-time operation data.
According to an embodiment of the present disclosure, the first analysis module includes:
the generating unit is used for generating a resource calling relation according to the resource calling information of each transaction in the running process;
the determining unit is used for determining repeatedly called resource information and processor resource distribution information according to the resource calling relation; and
and the positioning unit is used for positioning the performance fault according to the repeatedly called resource information and the processor resource distribution information.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes:
the second analysis module is used for analyzing the transaction amount and the application success rate data which are uploaded by each channel application according to the transaction real-time operation data; and
and the estimating module is used for estimating the transaction rate of each channel transaction of the host according to the transaction amount and the application success rate data which are uploaded by each channel application.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes:
the output module is used for determining the transaction rate increase amplitude according to the transaction rate estimated value and the history transaction rate of the history synchronization after the transaction rate of each channel transaction of the host computer is estimated; outputting a transaction trend abnormity signal under the condition that the transaction rate increase amplitude exceeds a preset threshold value.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes:
and the third analysis module is used for analyzing each transaction from N dimensions to determine the health comprehensive score of each transaction, wherein N is a positive integer, and the N dimensions comprise at least two of transaction rate, response time, processor consumption, service success rate and transaction complexity.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes:
and the manufacturing module is used for manufacturing exclusive labels corresponding to each dimension for each transaction by adopting the N-dimensional radar chart.
Another aspect of the present disclosure provides an electronic device, comprising: one or more processors; a memory for storing one or more instructions; wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to implement the online transaction performance management analysis method described above.
Another aspect of the present disclosure provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to implement the online transaction performance management analysis method described above.
According to the embodiment of the disclosure, the online transaction performance analysis method at least partially solves the technical problems of low accuracy, low performance fault locating speed, poor monitoring timeliness and single evaluation dimension of the transaction in the current transaction index abnormal monitoring, further improves the transaction index abnormal monitoring accuracy, the performance fault locating speed, carries out health evaluation on all the transactions according to the transaction rate, the response time, the processor consumption, the service success rate and the processing complexity in a multi-dimension manner, and removes the overall operation condition of the controlled transaction from the global angle.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof with reference to the accompanying drawings in which:
FIG. 1 schematically illustrates an exemplary system architecture to which an online transaction performance analysis method and apparatus, an electronic device, and a computer-readable storage medium may be applied, according to embodiments of the present disclosure;
FIG. 2 schematically illustrates a flow chart of an online transaction performance analysis method according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates a flow chart for locating a performance fault according to an embodiment of the disclosure;
FIG. 4 schematically illustrates a flow chart of a transaction rate estimation method according to an embodiment of the disclosure;
FIG. 5 schematically illustrates a bubble diagram exhibiting five trade dimensional relationships in accordance with an embodiment of the present disclosure;
FIG. 6 schematically illustrates transaction distributions across dimensions according to an embodiment of the present disclosure;
FIG. 7 schematically illustrates a block diagram of an online transaction performance analysis device according to an embodiment of the disclosure;
FIG. 8 schematically illustrates a block diagram of a computer system suitable for implementing online transaction performance analysis, in accordance with an embodiment of the present disclosure.
Detailed Description
The present invention will be further described in detail below with reference to specific embodiments and with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent.
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a formulation similar to at least one of "A, B or C, etc." is used, in general such a formulation should be interpreted in accordance with the ordinary understanding of one skilled in the art (e.g. "a system with at least one of A, B or C" would include but not be limited to systems with a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
FIG. 1 schematically illustrates an exemplary system architecture 100 in which online transaction performance analysis methods and apparatus, electronic devices, and computer-readable storage media may be applied, according to embodiments of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which embodiments of the present disclosure may be applied to assist those skilled in the art in understanding the technical content of the present disclosure, but does not mean that embodiments of the present disclosure may not be used in other devices, systems, environments, or scenarios.
As shown in fig. 1, a system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and/or wireless communication links, and the like.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages etc., e.g. the terminal devices 101, 102, 103 obtain resource invocation information for each transaction in operation from the server 105 via the network 104. Various communication client applications may be installed on the terminal devices 101, 102, 103, such as shopping class applications, web browser applications, search class applications, transaction class applications, instant messaging tools, mailbox clients and/or social platform software, to name a few.
The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the online transaction performance analysis method provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the online transaction performance analysis device provided by the embodiments of the present disclosure may be generally disposed in the server 105. The online transaction performance analysis method provided by the embodiments of the present disclosure may also be performed by a server or cluster of servers other than the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the online transaction performance analysis apparatus provided by the embodiments of the present disclosure may also be provided in a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
Alternatively, the online transaction performance analysis method provided by the embodiment of the present disclosure may be performed by the terminal device 101, 102, or 103, or may be performed by another terminal device other than the terminal device 101, 102, or 103. Accordingly, the online transaction performance analysis apparatus provided by the embodiments of the present disclosure may also be provided in the terminal device 101, 102, or 103, or in another terminal device different from the terminal device 101, 102, or 103.
For example, one of the terminal devices 101, 102, or 103 acquires resource call information of each transaction in the course of operation from the server 105. Then, one of the terminal devices 101, 102, or 103 may locally perform the online transaction performance analysis method provided by the embodiments of the present disclosure, or send the resource call information to other terminal devices, servers, or server clusters, and perform the online transaction performance analysis method provided by the embodiments of the present disclosure by the other terminal devices, servers, or server clusters that receive the resource call information.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
It should be noted that the method and apparatus for online transaction performance analysis provided by the present disclosure may be used in the financial field, and may also be used in any field other than the financial field, and the application field of the method and apparatus for online transaction performance analysis provided by the present disclosure is not limited.
FIG. 2 schematically illustrates a flow chart of an online transaction performance analysis method according to an embodiment of the present disclosure.
As shown in fig. 2, the method includes operations S201 to S202.
In operation S201, transaction information of each transaction in the operation process is acquired, wherein the transaction information includes resource call information and transaction real-time operation data.
According to embodiments of the present disclosure, the resource call information may include, for example, programs to be accessed, data request amounts, various transaction branches, judgment logic, and the like; the various transaction branches may include, for example, inter-bank transactions between different banks, transactions between banks and third party payment applications (e.g., weChat payments, payment of bank), and so forth.
According to embodiments of the present disclosure, resource call information may be obtained through an RCAP tool (CICS TRANSACTION RESOURCE CAPTURE TOOL, host online resource collection tool), where RCAP may collect program call and database query request information on-the-fly transactions.
In operation S202, the online transaction performance is analyzed according to the resource call information and the transaction real-time operation data.
According to the embodiment of the disclosure, the online transaction performance analysis method is adopted to at least partially solve the technical problems of low accuracy, low performance fault locating speed, poor monitoring timeliness and single evaluation dimension of the transaction in the current transaction index abnormal monitoring, so that the accuracy of the transaction index abnormal monitoring, the performance fault locating speed and the overall operation condition of the transaction are improved, wherein the health evaluation is carried out on all the transactions according to the transaction rate, the response time, the processor consumption, the service success rate and the processing complexity.
FIG. 3 schematically illustrates a flow chart of FIG. 3 schematically illustrating locating a performance fault according to an embodiment of the present disclosure;
as shown in fig. 3, the method includes operations S301 to S303.
In operation S301, a resource call relationship is generated according to resource call information of each transaction in the running process.
According to the embodiment of the disclosure, the resource calling relationship includes the relationship between each transaction and the program, the data request amount, various transaction branches, judgment logic and the like which need to be accessed by the transaction, for example, one transaction relates to the transaction service between the banking service and the third party payment application, and the relationship between the banking service and the third party payment software service related to the transaction, the respective transaction amounts of the banking service and the third party payment software service, the time distribution occupied by the CPU and the like can be known in the resource calling relationship. The method for analyzing the online transaction performance by the resource calling relation can be applied to various aspects such as online problem analysis, online flow optimization, resource pressure drop, system decoupling, application architecture design, business influence analysis and the like. The processor is, for example, a CPU.
In operation S302, repeatedly called resource information and processor resource distribution information are determined according to the resource call relationship.
In operation S303, a performance fault is located according to the repeatedly called resource information and the processor resource distribution information.
According to the embodiment of the disclosure, repeated calling is prompted to be emphasized when the calling relation of the internal resources of the transaction is displayed, program processing time and processor resource distribution conditions are provided for potential fault occurrence points, so that the fault occurrence positions can be positioned conveniently and rapidly, and the fault positioning efficiency is improved.
According to the embodiment of the disclosure, for example, when 100 transactions are called for online performance fault location analysis, each transaction in the 100 transactions has N programs to be accessed and different data request amounts Q, for example, a first transaction needs to access a first program, a second program, a third program and a fourth program, the data request amount requested to be obtained when accessing the first program is Q1, the data request amount requested to be obtained when accessing the second program is Q2, the data request amount requested to be obtained when accessing the third program is Q3, and the data request amount requested to be obtained when accessing the fourth program is Q4; the second transaction needs to access the second program, the third program, the fourth program and the fifth program, the request quantity Q5 is requested to be obtained when the second program data is accessed, the request quantity Q6 is requested to be obtained when the third program is accessed, the request quantity Q7 is requested to be obtained when the fourth program is accessed, the request quantity Q8 is requested to be obtained when the fifth program is accessed, and the like, so that the program and the data request quantity which need to be accessed for each transaction can be obtained, then the total consumed program processing time of 100 transactions respectively accessing each program in the transaction process is counted, and then the processor resource distribution is formed according to the total consumed program processing time of each program. The program with more consumed program processing time is determined, for example, a third program and a fourth program, which are the programs with more repeated calling times and more occupied processor resources, and the third program and the fourth program are considered to be location points with higher potential failure occurrence rate, and the locations where the third program and the fourth program are located are preferentially checked when the failure is found.
According to embodiments of the present disclosure, program processing time and processor resource distribution may be presented using graphs, such as tables or pie charts.
FIG. 4 schematically illustrates a flow chart of transaction rate estimation for host channel transactions according to an embodiment of the present disclosure.
As shown in fig. 4, the method includes operations S301 to S302.
In operation S301, transaction amount and application success rate data uploaded by each channel application are analyzed according to the transaction real-time operation data.
In operation S302, the transaction rate of each channel transaction of the host is estimated according to the transaction amount and the application success rate data uploaded by each channel application.
According to an embodiment of the present disclosure, a method for estimating transaction rate for each channel transaction of a host includes estimating transaction rate for each channel transaction of a host using a differential integrated moving average autoregressive model (ARIMA).
According to the embodiment of the disclosure, the transaction abnormality reminding is performed by combining the expert rules with the machine learning algorithm, the transaction abnormality is calculated by the learning algorithm, the transaction abnormality trend is predicted in advance by predicting the transaction rate, the transaction abnormality reminding is performed by combining the expert rules with the machine learning algorithm, the accuracy of monitoring the transaction index abnormality is improved, and meanwhile the monitoring timeliness is improved.
According to the embodiment of the disclosure, expert rules are that historical daily transaction traffic is compared with average synchronous traffic on the previous day or the last week, and abnormal transaction trend is reported when the limit ratio exceeds a first preset value or the increment exceeds a second preset value; the first preset value and the second preset value may be set according to practical situations, for example, the first preset value is 1.5, and the second preset value is 40 ten thousand.
According to the embodiment of the disclosure, after the transaction rate estimation is carried out on the transactions of each channel of the host, the increase amplitude of the transaction rate is determined according to the transaction rate estimated value and the historical transaction rate of the historical synchronization; outputting a transaction trend abnormity signal under the condition that the transaction rate increase amplitude exceeds a preset threshold value.
According to an embodiment of the present disclosure, a transaction trend anomaly signal is output if the transaction rate estimate exceeds a historical contemporaneous increase in magnitude by more than a preset proportion for a future period of time. The future period of time can be set according to actual needs, for example, five minutes, ten minutes, twenty minutes and the like; the more historical synchronization can be set according to actual needs, such as yesterday; the preset ratio may be set according to actual needs, for example, 40%, 50%, 60%, etc.
According to an embodiment of the disclosure, the method for predicting the transaction rate may further report a transaction trend anomaly signal when the actual value of the predicted transaction index deviates from the preset ratio of the predicted value. The preset proportion is set according to practical needs, for example, 30%.
According to embodiments of the present disclosure, a method of predicting a transaction index may employ big data analysis techniques, using linear regression algorithm prediction. Other methods may be used to predict the transaction index, so long as the technical effects of the present disclosure can be achieved.
The online transaction performance analysis method of the present disclosure further includes analyzing each transaction from N dimensions to determine a health composite score for each transaction, where N is a positive integer, the N dimensions including at least two of transaction rate, response time, processor consumption, transaction success rate, and transaction complexity. The method adopts a plurality of dimensions to comprehensively score the transaction, solves the problems that in the prior art, the evaluation dimension of the transaction is single, and single performance indexes of the transaction are often checked in a splitting way, for example, only response time or only processor consumption are checked, and the like, and has no way to control the overall operation condition of the transaction from the global angle.
According to the embodiment of the disclosure, the method of analyzing each transaction from N dimensions may adopt a big data analysis method, for example, analysis of variance, regression analysis, correlation analysis, factor analysis, time series analysis, structural equation model, and the like, and different analysis methods may be selected according to specific situations, specific needs, and the like in the actual analysis process, so that the technical effects of the disclosure may be achieved.
Fig. 5 schematically illustrates a bubble diagram exhibiting five trade dimensional relationships according to an embodiment of the present disclosure.
Five dimensions of transaction rate, response time, processor consumption, business success rate, and transaction complexity are used in figure 5 to comprehensively score transactions. According to the embodiment of the disclosure, the distribution condition of the top N transactions (namely the top N transactions with the worst performance) of the current production rank and the performance of the top N transactions in each dimension can be known from the five-dimensional global portrait graph through the size, the color and the like of bubbles. N is set according to practical circumstances, for example, 100. According to embodiments of the present disclosure, different colors may be used to represent different transaction scores during actual production, and the transaction scores may be set according to actual needs, for example, classified into (0, 5), (5,5.5), (5.5,6), (6, 7), (7, … …), the higher the score is closer to the center of the bubble map in fig. 5, and the higher the score is in proportion to the transaction score in fig. 5, the worse the transaction performance is.
The top N transactions with high interest and transaction types may also be listed graphically according to embodiments of the present disclosure. Wherein N is set according to practical situation, for example, 10. The transaction type is at least one of fat/thin transaction, long/short transaction, transaction frequency, transaction complexity, and transaction success rate, for example. Wherein, the fat transaction takes the CPU consumption average value of all online transactions of the host as a boundary, and the online transactions higher than the average value are called fat transactions; thin transactions correspond to fat transactions, and online transactions that are lower than average are referred to as thin transactions.
Fig. 6 schematically illustrates transaction distributions across dimensions according to an embodiment of the present disclosure.
As shown in fig. 6, the trade rate distribution includes a low frequency trade, an intermediate frequency trade, a high frequency trade, and an ultra high frequency trade; the transaction distribution situation in each dimension may be a form, a pie chart, or the like selected according to the actual situation, and is not limited to the way of fig. 6. According to the embodiments of the present disclosure, the transaction frequency may be divided according to actual situations, in which the low frequency transaction refers to a transaction less than 1tps, the medium frequency transaction refers to a transaction of 1-3.8tps, and the high frequency transaction refers to a transaction greater than 8.2 tps. The success rate distribution comprises low success rate, lower success rate, medium success rate, higher success rate and high success rate. The success rate may be divided according to practical situations, in this embodiment, a low success rate means that the success rate is less than 24%, a low success rate means that the success rate is 24-56%, a medium success rate means that the success rate is [ 57-78% > (where "[" means including 57, ")" means excluding 78), a high success rate means that the success rate is [ 78-93% >, and a high success rate means that the success rate is greater than 93%. The complexity distribution comprises low complexity, medium complexity, high complexity and high complexity, and the complexity level can be divided according to actual conditions. Processor consumption includes thin transactions, lean transactions, fat transactions, and super fat transactions; the trade fat-lean level can be divided according to actual situations, in this embodiment, the lean trade refers to the trade which consumes less than 6MIPS (Million Instructions Per Second) of machine voice instructions per second, the lean trade refers to the trade which consumes [6-9 ] MIPS of CPU, the fat trade refers to the trade which consumes [9-23 ] MIPS of CPU, the fat trade refers to the trade which consumes [23-90 ] MIPS of CPU, and the super fat trade refers to the trade which consumes more than 90MIPS of CPU. The response time includes short transaction, long transaction and ultra-long transaction, and the transaction length grade can be classified according to actual conditions, in this embodiment, the short transaction refers to the transaction less than 0.04 seconds, the short transaction refers to the transaction of [0.04-0.06 ], the long transaction refers to the transaction of [0.06-0.18 ], the long transaction refers to the transaction of [ 0.18-1.3), and the ultra-long transaction refers to the transaction greater than 1.3 seconds.
The online transaction performance management analysis method of the present disclosure further includes: and adopting an N-dimensional radar chart to manufacture a proprietary label corresponding to each dimension for each transaction.
According to the embodiment of the disclosure, a five-dimensional radar chart is adopted to manufacture a proprietary label for each transaction, wherein the proprietary label comprises at least one of fat/thin transaction, long/short transaction, transaction frequency, transaction complexity and service success rate of the transaction. Wherein, the fat transaction takes the CPU consumption average value of all online transactions of the host as a boundary, and the online transactions higher than the average value are called fat transactions; thin transactions correspond to fat transactions, and online transactions that are lower than average are referred to as thin transactions. Or may be set according to the actual situation.
Fig. 7 schematically illustrates a block diagram of an online transaction performance analysis device according to an embodiment of the disclosure.
As shown in fig. 7, the online transaction performance analysis device includes: a first acquisition module 701 and a first analysis module 702.
The first obtaining module 701 is configured to obtain transaction information of each transaction in the operation process, where the transaction information includes resource calling information and transaction real-time operation data.
The first analysis module 702 is configured to analyze the online transaction performance according to the resource calling information and the transaction real-time operation data.
According to the embodiment of the disclosure, the online transaction performance analysis device at least partially solves the technical problems of low accuracy, low performance fault locating speed, poor monitoring timeliness and single evaluation dimension of the transaction in the current transaction index abnormal monitoring, further improves the transaction index abnormal monitoring accuracy, the performance fault locating speed, and carries out health evaluation on all the transactions according to five dimensions of transaction rate, response time, processor consumption, service success rate and processing complexity, and the overall operation condition of the transaction is controlled from a global angle.
According to an embodiment of the present disclosure, the first analysis module includes: the device comprises a generating unit, a determining unit and a positioning unit.
The generating unit is used for generating a resource calling relation according to the resource calling information of each transaction in the running process;
the determining unit is used for determining repeatedly called resource information and processor resource distribution information according to the resource calling relation; and
and the positioning unit is used for positioning the performance fault according to the repeatedly called resource information and the processor resource distribution information.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes: the system comprises a second analysis module and a prediction module.
The second analysis module is used for analyzing the transaction amount and the application success rate data which are uploaded by each channel application according to the transaction real-time operation data; and
and the estimating module is used for estimating the transaction rate of each channel transaction of the host according to the transaction amount and the application success rate data which are uploaded by each channel application.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes: the output module is used for outputting a transaction trend abnormity signal under the condition that the transaction rate increasing amplitude exceeds a preset threshold according to the transaction rate pre-estimation value and the history transaction rate of the history synchronization after the transaction rate pre-estimation is carried out on the transactions of each channel of the host.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes: and the third analysis module is used for analyzing each transaction from N dimensions to determine the health comprehensive score of each transaction, wherein N is a positive integer, and the N dimensions comprise at least two of transaction rate, response time, processor consumption, service success rate and transaction complexity.
According to an embodiment of the present disclosure, the online transaction performance analysis apparatus further includes: and the manufacturing module is used for manufacturing exclusive labels corresponding to each dimension for each transaction by adopting the N-dimensional radar chart.
Any number of modules, sub-modules, units, sub-units, or at least some of the functionality of any number of the sub-units according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented as split into multiple modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in any other reasonable manner of hardware or firmware that integrates or encapsulates the circuit, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be at least partially implemented as computer program modules, which when executed, may perform the corresponding functions.
For example, any of the first acquisition module 701 and the first analysis module 702 may be combined in one module/unit/sub-unit, or any of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least some of the functionality of one or more of these modules/units/sub-units may be combined with at least some of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to embodiments of the present disclosure, at least one of the first acquisition module 701 and the first analysis module 702 may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in hardware or firmware, such as any other reasonable way of integrating or packaging the circuits, or in any one of or a suitable combination of any of the three. Alternatively, at least one of the first acquisition module 701 and the first analysis module 702 may be at least partially implemented as a computer program module, which when executed may perform the respective functions.
It should be noted that, in the embodiment of the present disclosure, the online transaction performance analysis device portion corresponds to the online transaction performance analysis method portion in the embodiment of the present disclosure, and the description of the online transaction performance analysis device portion specifically refers to the online transaction performance analysis method portion and is not described herein again. There is also provided, in accordance with an embodiment of the present disclosure, an electronic device including: one or more processors; and a memory for storing one or more instructions that, when executed by the one or more processors, cause the one or more processors to implement the online transaction performance management analysis method described above.
Fig. 8 schematically illustrates a block diagram of a computer system suitable for implementing the above-described methods, according to an embodiment of the present disclosure. The computer system illustrated in fig. 8 is merely an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 8, a computer system 800 according to an embodiment of the present disclosure includes a processor 801 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. The processor 801 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 801 may also include on-board memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the disclosure.
In the RAM 803, various programs and data required for the operation of the system 800 are stored. The processor 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. The processor 801 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or the RAM 803. Note that the program may be stored in one or more memories other than the ROM 802 and the RAM 803. The processor 801 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in one or more memories.
According to an embodiment of the present disclosure, the system 800 may further include an input/output (I/O) interface 805, the input/output (I/O) interface 805 also being connected to the bus 804. The system 800 may also include one or more of the following components connected to the I/O interface 805: an input portion 806 including a keyboard, mouse, etc.; an output portion 807 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 808 including a hard disk or the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. The drive 810 is also connected to the I/O interface 805 as needed. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as needed so that a computer program read out therefrom is mounted into the storage section 808 as needed.
According to embodiments of the present disclosure, the method flow according to embodiments of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 809, and/or installed from the removable media 811. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 801. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples may include, but are not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 802 and/or RAM 803 and/or one or more memories other than ROM 802 and RAM 803 described above.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (9)
1. An online transaction performance analysis method, comprising:
acquiring transaction information of each transaction in the operation process, wherein the transaction information comprises resource calling information and transaction real-time operation data; and
analyzing the online transaction performance according to the resource calling information and the transaction real-time operation data;
wherein, analyzing the online transaction performance according to the transaction real-time operation data comprises the following steps:
analyzing transaction amount and application success rate data which are uploaded by each channel application according to the transaction real-time operation data; and
and estimating the transaction rate of each channel transaction of the host according to the transaction amount and the application success rate data which are uploaded by each channel application.
2. The method of claim 1, wherein analyzing the online transaction performance based on the resource invocation information comprises:
generating a resource calling relation according to the resource calling information of each transaction in the running process;
determining repeatedly called resource information and processor resource distribution information according to the resource calling relation; and
and positioning the performance fault according to the repeatedly called resource information and the processor resource distribution information.
3. The method of claim 1, further comprising:
after the transaction rate of each channel transaction of the host is estimated, determining the increase amplitude of the transaction rate according to the transaction rate estimated value and the history transaction rate of the history synchronization;
outputting a transaction trend abnormity signal under the condition that the transaction rate increase amplitude exceeds a preset threshold value.
4. The method of claim 1, further comprising:
each of the transactions is analyzed from N dimensions to determine a health composite score for each transaction, where N is a positive integer, the N dimensions including at least two of transaction rate, response time, processor consumption, business success rate, and transaction complexity.
5. The method of claim 4, further comprising:
and adopting an N-dimensional radar chart to manufacture a proprietary label corresponding to each dimension for each transaction.
6. An online transaction performance analysis device, comprising:
the first acquisition module is used for acquiring transaction information of each transaction in the operation process, wherein the transaction information comprises resource calling information and transaction real-time operation data; and
the first analysis module is used for analyzing the online transaction performance according to the resource calling information and the transaction real-time operation data;
wherein, analyzing the online transaction performance according to the transaction real-time operation data comprises the following steps:
analyzing transaction amount and application success rate data which are uploaded by each channel application according to the transaction real-time operation data; and
and estimating the transaction rate of each channel transaction of the host according to the transaction amount and the application success rate data which are uploaded by each channel application.
7. The apparatus of claim 6, wherein the first analysis module comprises:
the generating unit is used for generating a resource calling relation according to the resource calling information of each transaction in the running process;
the determining unit is used for determining repeatedly called resource information and processor resource distribution information according to the resource calling relation; and
and the positioning unit is used for positioning the performance fault according to the repeatedly called resource information and the processor resource distribution information.
8. An electronic device, comprising:
one or more processors;
a memory for storing one or more instructions;
wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to implement the online transaction performance analysis method of any of claims 1 to 5.
9. A computer readable storage medium having stored thereon executable instructions which when executed by a processor cause the processor to implement the online transaction performance analysis method of any one of claims 1 to 5.
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