CN101882109B - Software performance analysis system and method based on banking business - Google Patents

Software performance analysis system and method based on banking business Download PDF

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CN101882109B
CN101882109B CN 201010232830 CN201010232830A CN101882109B CN 101882109 B CN101882109 B CN 101882109B CN 201010232830 CN201010232830 CN 201010232830 CN 201010232830 A CN201010232830 A CN 201010232830A CN 101882109 B CN101882109 B CN 101882109B
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information
transaction
database
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CN101882109A (en
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曾美财
吴能斌
刘映镇
周建平
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Industrial and Commercial Bank of China Ltd ICBC
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Industrial and Commercial Bank of China Ltd ICBC
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Abstract

The invention relates to a software performance analysis system and a method based on banking business. The method comprises the following steps that a software performance processing server receives software information which comprises exchange list information, program list information, sheet list information, file list information and operation list information from a software information input device; the software performance processing server receives quantitative performance index information which comprises the quantitative performance index of database operation, the quantitative performance index of middleware operation and performance conversion factors from a database server; the software performance processing server generates performance analysis result information which comprises exchange response time, CPU (Central Processing Unit) resource consumption and storage space demand information according to the software information and the quantitative performance index information; and the software performance processing server outputs the performance analysis result information to an output storage server for storage. The invention can improve the accuracy of relevant performance assess analysis to ensure the safe and stable running of a production system when host software is put into production.

Description

Software performance analysis system and method based on banking business
Technical Field
The invention relates to a software analysis technology, in particular to a software performance analysis system and a software performance analysis method based on banking business.
Background
With the development of banking business, the transaction amount of a production system is larger and larger, and the performance of software transaction directly influences the stable and safe operation of the production system. Therefore, when software design development testing is carried out, the performance of relevant transactions needs to be strictly evaluated and analyzed, and the individual performance of the relevant transactions and the overall performance of software application need to be comprehensively known and mastered.
At present, the industry is relatively dispersed and incomplete in the aspect of evaluation and analysis of the performance and capacity of host software, does not have a related quantitative index system, and does not form a standard evaluation model. For example, some evaluation methods evaluate the CPU condition of future transactions by taking the overall average CPU of the current transactions, taking the average response time of the current transactions as the response time of the future transactions, taking what percentage of the current disk capacity as the disk requirements of future applications, and the like, and the evaluation methods have no quantitative calculation evaluation and are not guaranteed in accuracy.
Disclosure of Invention
The invention provides a software performance analysis system and method based on banking business, which are used for improving the accuracy of related performance evaluation analysis and ensuring the safe and stable operation of a production system when host software is put into production.
In one embodiment, the present invention provides a software performance analysis system based on banking, the system comprising: the system comprises a software information input device, a database server, a software performance processing server and an output storage server; the software information input device, the database server and the output storage server are respectively connected with the software performance processing server through an enterprise local area network; wherein,
the software information input device is used for inputting software information by a user, and comprises: a transaction list input device for inputting transaction list information of the software application; program list input means for inputting program list information of the software application; table list input means for inputting table list information of the software application; the software application management system includes a file list input device for inputting file list information of the software application, and a job list input device for inputting job list information of the software application.
The database server includes: the database quantization performance index storage device is used for storing quantization performance index information of database operation; the middleware quantization performance index storage device is used for storing quantization performance index information of the middleware operation; performance conversion coefficient storage means for storing the performance conversion coefficient; the information preprocessing device is used for preprocessing the quantitative performance index information of the database operation, the quantitative performance index information of the middleware operation and the performance conversion coefficient and generating preprocessing result information;
the software performance processing server comprises: a software information reading device for reading the software information from the software information input device; the information preprocessing device is used for preprocessing the information of the database operation, and preprocessing the information of the database operation; the performance analysis processing device is used for generating analysis processing results comprising transaction response time, CPU resource consumption and storage space requirements according to the software information read by the software information reading device and the database operation quantitative performance index information read by the quantitative performance index reading device and the CPU resource consumption evaluation analysis calculation model, the response time evaluation analysis calculation model and the disk space calculation model; the analysis result output device is used for outputting the analysis processing result;
the output storage server includes: the performance analysis result storage device is used for storing the transaction response time and the CPU resource consumption information; the storage space analysis result storage device is used for storing the storage space requirement;
the CPU resource consumption evaluation analysis calculation model comprises the following steps:
modifying the class software: software overall increase CPU time ═ Σ (transaction individual change CPU time × transaction amount);
newly adding software: the software increases the CPU time ═ sigma (newly increased transaction single CPU time multiplied by transaction amount);
the response time evaluation analysis calculation model is as follows:
modifying the class software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + ∑ (single trade increase response time multiplied by single trade volume))/the current whole trade volume;
newly adding software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + (newly increased monomer trade response time multiplied by single trade volume))/(the current whole trade volume + (single trade volume));
the disk space calculation model is as follows: the software disk space requirement is the database storage requirement + the software file storage requirement + the software data migration file storage requirement.
In another embodiment, the present invention provides a software performance analysis method based on banking services, the method including:
the software performance processing server receives software information including transaction list, program list, file list and operation list information from the software information input device; the software performance processing server receives quantitative performance index information comprising a quantitative performance index of database operation, a quantitative performance index of middleware operation and a performance conversion coefficient from the database server; the software performance processing server generates performance analysis result information including transaction response time, CPU resource consumption and storage space demand information according to the software information and the preprocessed quantitative performance index information and a CPU resource consumption evaluation analysis calculation model, a response time evaluation analysis calculation model and a disk space calculation model; the software performance processing server outputs the performance analysis result information to an output storage server for storage;
the CPU resource consumption evaluation analysis calculation model comprises the following steps:
modifying the class software: software overall increase CPU time ═ Σ (transaction individual change CPU time × transaction amount);
newly adding software: the software increases the CPU time ═ sigma (newly increased transaction single CPU time multiplied by transaction amount);
the response time evaluation analysis calculation model is as follows:
modifying the class software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + ∑ (single trade increase response time multiplied by single trade volume))/the current whole trade volume;
newly adding software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + (newly increased monomer trade response time multiplied by single trade volume))/(the current whole trade volume + (single trade volume));
the disk space calculation model is as follows: the software disk space requirement is the database storage requirement + the software file storage requirement + the software data migration file storage requirement.
The invention has the beneficial technical effects that: the system can improve the accuracy of related performance evaluation analysis and ensure the safe and stable operation of the production system when the host software is put into production.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts. In the drawings:
FIG. 1 is a schematic structural diagram of a software performance analysis system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a software information input device 100 according to an embodiment of the present invention;
FIG. 3 is a block diagram of a software performance processing server 200 according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an output storage server 300 according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of signaling interaction among various components in a software performance analysis system according to an embodiment of the present invention;
FIG. 6 is a flowchart of a method for preprocessing database operation quantization performance indicator information according to an embodiment of the present invention;
FIG. 7 is a flowchart illustrating a method for preprocessing the quantified performance indicator information of the middleware operation according to an embodiment of the present invention;
FIG. 8 is a flowchart of a method for pre-processing performance reduction factor information according to an embodiment of the present invention;
FIG. 9 is a flowchart of a method for software performance analysis processing according to an embodiment of the present invention;
FIG. 10 is a flowchart of a method for analyzing software performance according to another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
Example 1
As shown in fig. 1, the present invention provides a software performance analysis system based on banking services, the system includes: a software information input device 100, a software performance processing server 200, an output storage server 300, and a database server 400; the software performance processing server 200, which is a core part of the system of the present invention, is connected to the software information input device 100, the database server 400 and the output storage server 300 through the enterprise lan, respectively.
The software information input device 100 is mainly used for a user to input software information; the software performance processing server 200 can read in software information according to the software information input device 100, read in relevant quantitative performance indexes including information such as database operation quantitative performance indexes, middleware operation quantitative performance indexes and performance conversion coefficients from the database server 400, obtain results such as software application relevant performance conditions and service data storage space requirements after detailed evaluation, calculation and analysis, and output the evaluation, calculation and analysis results to the output storage server 300; the output storage server 300 is used for storing the analysis processing result of the software performance processing server 200, including the software performance condition (including transaction response time and transaction CPU resource consumption), the service data storage space requirement, and the like; the database server 400 is used to store the relevant data that needs to be pre-stored before the analysis of the software performance processing server 200, so as to ensure the accuracy and comprehensiveness of the analysis processing of the software performance processing server 200.
As shown in fig. 2, the software information input device 100 includes: a transaction list input device 101, a program list input device 102, a list input device 103, a file list input device 104 and a job list input device 105.
The transaction list input device 101 is used for inputting transaction list information of a software application, and the transaction list information comprises: transaction name, transaction function description, transaction amount, transaction related SQL variation, transaction calling program condition, and the like.
The program list input device 102 is used for inputting program list information of a software application, and the program list information comprises: program name, program function description, program call amount, program related SQL variation, etc.
The table list input device 103 is used for inputting table list information of the software application, and the table list information comprises: table name, table record length, index design, etc.
The file list input device 104 is used for inputting file list information of the software application, and the file list information comprises: file name, file record length, etc.
The job list input device 105 is used for inputting job list information of a software application, and the job list information comprises: job name, job function description, job related SQL delta, etc.
In fig. 1, the database server 400 includes: database quantization performance index storage 401, middleware quantization performance index storage 402, performance conversion coefficient storage 403, and information preprocessing device 404.
The database quantization performance indicator storage 401 is configured to store quantization performance indicator information of a database operation, where the quantization performance indicator information of the database operation may include: SELECT performance consumption, UPDATE performance consumption, COMMIT performance consumption, etc. The quantitative performance indicators of the relevant database operations are exemplified as follows:
1.SELECT SQL CPU consumption: for example, one SELECT SQL CPU consumes 0.2288 milliseconds for IBM host Z9722 machine DB2V 8;
2. UPDATESQL CPU consumption: for example, one UPDATE SQL CPU consumes 0.26 milliseconds for IBM host Z9722 machine DB2V 8;
3.INSERT SQL CPU consumption: for example, one UPDATE SQL CPU consumes 0.26 milliseconds for IBM host Z9722 machine DB2V 8;
4. one time 2-PHASE COMMIT SQL CPU consumption: for example, one UPDATE SQL CPU consumes 1.114 milliseconds for IBM host Z9722 machine DB2V 8;
5. one LOG WRITE I/O time: for example, one LOG WRITE I/O time is 4.5635 seconds;
6. one UPDATE COMMIT time: for example, the LOG WRITE I/O time is 4.5635 seconds, etc., and the invention is not limited in this regard.
The middleware quantization performance indicator storage 402 is configured to store quantization performance indicator information of the middleware operation, where the quantization performance indicator information of the middleware operation may include: transaction initiation consumption, program call consumption, XML package unpacking consumption, etc.
The related middleware operation quantization performance index is exemplified as follows:
1. local LINK calling program CPU consumption: for example, the CPU calling consumption of a LINK local program of a 4K communication area of an IBM host Z9722 machine is 0.045 millisecond;
2. and (3) LINK calling program CPU consumption of different address spaces of the same system: for example, for IBM host Z9722 machine, the CPU consumption for calling LINK in a 4K communication area and different address space programs of the same system is 0.617 milliseconds;
3. LINK calling program CPU consumption across different address spaces of the system: for example, for IBM host Z9722 machine, the CPU calling consumption for LINK calling of 4K communication zone across different address space programs of the system is 0.679 milliseconds;
4. one TASK initializes CPU consumption: for example, initializing CPU consumption for IBM host Z9722 machine TASK is 0.408 milliseconds;
5.XML 32K unpack CPU consumption: for example, the CPU consumption for unpacking the XML 32K data packet of the IBM host Z9722 machine is 0.087 ms, etc., and the invention is not limited thereto.
The performance conversion factor storage device 403 is used to store performance conversion factors, which may include: the CPU capacity of different machines is converted into performance conversion coefficient, the conversion coefficient from the operation performance consumption of the database to the performance consumption of the middleware, the conversion coefficient from the performance consumption of the middleware to the performance consumption of the system and the like.
The related performance conversion factor index is exemplified as follows:
1. conversion coefficient from database performance index to middleware performance index: for example, the database performance index to middleware performance index conversion factor is 1.72;
2. conversion coefficient from middleware performance index to system overall performance consumption: for example, the conversion coefficient from the middleware performance index to the overall system performance consumption is 1.7;
3. CPU processing capacity conversion coefficients of machines of different models: for example, the IBM host Z9704 to IBM host Z9722 machine CPU processing capacity is 1.36, the IBM host Z9704 to IBM host Z9707 machine CPU processing capacity is 1.04, the IBM host Z9722 to IBM host Z9707 machine CPU processing capacity is 1.26, etc., the invention is not so limited.
The information preprocessing device 404 is configured to preprocess the quantization performance index information of the database operation, the quantization performance index information of the middleware operation, and the performance conversion coefficient and generate preprocessing result information; the information preprocessing device 404 preprocesses the quantization performance index information of the database operation to generate preprocessing result information, which includes: quantitative analysis of the state of a production system, quantitative analysis of related operations of database products, test analysis of quantitative indexes of the database and the like; the information preprocessing device 404 preprocesses the quantization performance indicator information of the middleware operation to generate preprocessing result information, which includes: quantitative analysis of the state of a production system, quantitative analysis of related operations of a middleware product, quantitative index analysis of the middleware and the like; the information preprocessing unit 404 preprocesses the performance conversion coefficient to generate preprocessing result information, which includes: the method comprises the steps of analyzing conversion coefficients from database performance indexes to middleware performance indexes, analyzing conversion coefficients from the middleware performance indexes to the whole system consumption, analyzing conversion coefficients from CPU processing capacities of different types of machines and the like.
As shown in fig. 3, the software performance processing server 200 includes: a software information reading device 201, a quantitative performance index reading device 202, a performance analysis processing device 203 and an analysis result output device 204.
The software information reading device 201 reads the software information from the software information input device, and includes transaction list information related to the software application, program list information related to the software application, table list information related to the software application, file list information related to the software application, job list information related to the software application, and the like.
The quantization performance index reading device 202 is used for reading the quantization performance index information of the database operation preprocessed by the information preprocessing device, the quantization performance index information of the middleware operation and the performance conversion coefficient.
The performance analysis processing device 203 is used for generating analysis processing results including transaction response time, CPU resource consumption and storage space requirements according to the information read by the software information reading device and the quantitative performance index reading device. The analysis result output device 204 is used for outputting the analysis processing result.
As shown in fig. 4, the output storage server 300 includes: performance analysis result storage means 301 and storage space analysis result storage means 302.
The performance analysis result storage device 301 is used for storing the transaction response time and the CPU resource consumption information; the storage space analysis result storage device 302 is used for storing the business data storage space requirement. The transaction response time, CPU resource consumption information, and business data storage space requirements are mainly output results of the analysis result output device 204 in the software performance processing server 200.
Example 2
The software performance analysis method based on banking will be described with reference to the system in embodiment 1, which is implemented by using a software performance analysis system including at least a software information input device 100, a software performance processing server 200, an output storage server 300, and a database server 400.
The method comprises the following steps:
first, the performance index information is quantized by the database operation, the middleware operation quantization performance index, and the performance conversion coefficient information stored in the database server 400 are preprocessed. Next, the software performance processing server 200 reads relevant information from the database quantitative performance index storage device 401, the middleware quantitative performance index storage device 402, and the performance conversion coefficient storage device 403 of the database server 400 according to the user software information read by the software information input device 100, obtains response time of the software related to the transaction, CPU resource consumption, application data storage space requirement, and the like after detailed analysis and calculation, and outputs and stores the calculation and analysis result through the output storage server 300.
As is apparent from the above description, the analysis method is specifically divided into the following three steps.
A pretreatment step: the database server 400 preprocesses relevant information such as database operation quantization performance index information, middleware operation quantization performance index, performance conversion coefficient information, and the like in the server.
An information reading step: the performance analysis processing means 203 in the software performance processing server 200 calls the software information reading means 201 to read user software information from the software information input means 100, and calls the quantized performance index reading means 202 to operate information such as quantized performance index information, middleware operation quantized performance index, and performance conversion coefficient information from the database in the database server 400.
And (3) analyzing and processing steps: the performance analysis processing device 203 evaluates and calculates the response time of the software related to the transaction, the CPU resource consumption, the application data storage space requirement, and the like according to the read software information, the database operation quantitative performance index information, the middleware operation quantitative performance index and the performance conversion coefficient information and the related calculation model, and outputs the evaluation calculation result to the output storage server 300.
The CPU resource consumption evaluation analysis calculation model specifically comprises the following steps:
modifying the class software: the software increases the total CPU time ═ Σ (transaction-by-transaction change CPU time × transaction amount).
Newly adding software: the software increases the CPU time ═ Σ (new transaction individual CPU time × transaction amount).
The response time evaluation analysis calculation model specifically includes:
modifying the class software: the software trade mean response time ═ current trade mean response time × current overall trading volume + ∑ (individual trade increase response time × individual trading volume))/current overall trading volume.
Newly adding software: the software trade mean response time ═ current trade mean response time × current overall trading volume +/(new individual trading response time × individual trading volume)).
The disk space calculation model specifically includes: the software disk space requirement is the database storage requirement + the software file storage requirement + the software data migration file storage requirement.
Fig. 5 is a schematic diagram of signaling interaction among the components in the software performance analysis system of the present invention, including:
s1, the output storage server 300 preprocesses the information such as the database operation quantization performance index information, the middleware operation quantization performance index information, and the performance conversion coefficient.
S2, a software information reading request is transmitted to the software information input device 100.
S3, the user software information input device 100 inputs software information, which includes information such as transaction list, program list, table list, file list and job list.
S4, software performance processing server 200 sends a request for reading the quantized performance index information of the database operation to database server 400.
And S5, the database server 400 returns the database operation quantization performance index information.
S6, software performance processing server 200 sends a request for reading the middleware operation quantization performance index information to database server 400.
And S7, the database server 400 returns the middleware operation quantitative performance index information.
S8, software performance processing server 200 sends a request for reading the related performance reduction coefficient information to database server 400.
And S9, the database server 400 returns the related performance conversion coefficient information.
S10, software performance processing server 200 calculates software related performance consumption including transaction corresponding time, CPU resource consumption, hard disk storage space requirement, etc.
S11, the software performance processing server 200 sends information including transaction corresponding time, CPU resource consumption, hard disk storage space requirement, etc. to the output storage server 300.
In fig. 5, step S1 is the preprocessing step, steps S2 to S9 are the information reading steps, and steps S10 and S11 are the analysis processing steps.
As shown in fig. 6, in the preprocessing step, the database server 400 preprocesses the database operation quantized performance index information in the database quantized performance index storage 401 by:
step S601: and quantitatively analyzing the state of the production system.
Step S602: and quantitatively analyzing related operations of the database product.
Step S603: and testing and analyzing the database quantitative indexes.
Step S604: the relevant database operation quantitative performance index result information is stored in the database quantitative performance index storage device 401.
The related database operation quantization performance index information comprises:
select SQL CPU consumption: for example, one SELECT SQL CPU consumes 0.2288 milliseconds for IBM host Z9722 machine DB2V 8;
update SQL CPU consumption: for example, one UPDATE SQL CPU consumes 0.26 milliseconds for IBM host Z9722 machine DB2V 8;
INSERT SQL CPU consumption: for example, one UPDATE SQL CPU consumes 0.26 milliseconds for IBM host Z9722 machine DB2V 8;
a4. one time 2-PHASE COMMIT CPU consumption: for example, one UPDATE SQL CPU consumes 1.114 milliseconds for IBM host Z9722 machine DB2V 8;
a5. one LOG WRITE I/O time: for example, one LOG WRITE I/O time is 4.5635 seconds;
a6. one UPDATE COMMIT time: for example, the LOG WRITE I/O time is 4.5635 seconds at one time. The quantitative performance index of the relevant database operation is continuously updated and perfected through preprocessing operation.
As shown in fig. 7, in the preprocessing step, the method for preprocessing the middleware operation quantization performance indicator information in the middleware quantization performance indicator storage device 402 by the database server 400 specifically includes:
step S701: and quantitatively analyzing the state of the production system.
Step S702: and quantitatively analyzing related operations of the middleware product.
Step S703: and (5) analyzing the quantitative indexes of the middleware.
Step S704: the relevant middleware operation quantized performance indicator result information is stored in the middleware quantized performance indicator storage 402.
The related middleware operation quantization performance index comprises the following steps:
a1. local LINK calling program CPU consumption: for example, the CPU calling consumption of a LINK local program of a 4K communication area of an IBM host Z9722 machine is 0.045 millisecond;
a2. and (3) LINK calling program CPU consumption of different address spaces of the same system: for example, for IBM host Z9722 machine, the CPU consumption for calling LINK in a 4K communication area and different address space programs of the same system is 0.617 milliseconds;
a3. LINK calling program CPU consumption across different address spaces of the system: for example, for IBM host Z9722 machine, the CPU calling consumption for LINK calling of 4K communication zone across different address space programs of the system is 0.679 milliseconds;
a4. one TASK initializes CPU consumption: for example, initializing CPU consumption for IBM host Z9722 machine TASK is 0.408 milliseconds;
XML 32K unpacking CPU consumption: for example, unpacking the CPU for IBM host Z9722 machine XML 32K packets consumes 0.087 milliseconds, etc. The quantitative performance index of the related middleware operation is continuously updated and perfected through preprocessing operation.
As shown in fig. 8, in the preprocessing step, the method for preprocessing the performance conversion factor information in the performance conversion factor storage device 403 by the database server 400 specifically includes:
step S801: and analyzing the conversion coefficient from the database performance index to the middleware performance index.
Step S802: and analyzing the conversion coefficient from the performance index of the middleware to the overall consumption of the system.
Step S803: and (4) CPU processing capacity conversion coefficient analysis of different types of machines.
Step S804: the performance conversion coefficient analysis result is stored in the performance conversion coefficient storage means 403.
The related performance conversion coefficient index comprises:
a1. conversion coefficient from database performance index to middleware performance index: for example, the database performance index to middleware performance index conversion factor is 1.72;
a2. conversion coefficient from middleware performance index to system overall performance consumption: for example, the conversion coefficient from the middleware performance index to the overall system performance consumption is 1.7;
a3. CPU processing capacity conversion coefficients of machines of different models: for example, IBM host Z9704 to IBM host Z9722 machine CPU processing capacity is 1.36, IBM host Z9704 to IBM host Z9707 machine CPU processing capacity is 1.04, IBM host Z9722 to IBM host Z9707 machine CPU processing capacity is 1.26, etc. The related performance conversion coefficient is continuously updated and refined through preprocessing operation.
The specific method of the information reading step comprises the following steps:
b 1: the performance analysis processing means 203 in the software performance processing server 200 calls the software information reading means 201 to read the relevant software information including the transaction list, the program list, the job list, the table list, the file list, and the like from the software information input means 100.
b 2: the performance analysis processing means 203 in the software performance processing server 200 calls the quantized performance index reading means 202 to read the quantized performance index information of the relevant database operation from the database quantized performance index storage means 401.
b 3: the performance analysis processing means 203 in the software performance processing server 200 calls the quantized performance indicators reading means 202 to read the quantized performance indicators information of the relevant middleware operations from the middleware quantized performance indicators storage means 402.
b 4: the performance analysis processing means 203 in the software performance processing server 200 calls the quantized performance index reading means 202 to read the relevant performance conversion factor information from the performance conversion factor storage means 403.
In the analysis processing step, as shown in fig. 9, the software performance analysis processing step specifically includes:
step S901: and reading in user software information.
Step S902: and reading in quantization performance indexes, wherein the quantization performance indexes comprise quantization performance indexes of database operation, quantization performance indexes of middleware operation and performance conversion coefficients.
Step S903: judging whether the application is a new application according to the application mark in the read-in user software information, if so, performing step 904, otherwise, jumping to step 908;
step S904: testing and calculating the single transaction/operation performance: and for the overall scheme stage, calculating the single transaction/operation performance condition by using the related quantitative performance indexes, and for the ending pressure test stage, obtaining the related single transaction/operation performance condition by performing pressure test on the transaction/operation, wherein the single performance condition comprises single transaction/operation response time, CPU time and the like.
Step S905: evaluation calculation transaction/job related totals: including transaction call counts (peak and full, etc.), job run counts, table listings, and so forth.
Step S906: evaluating and calculating the overall performance of the new application: and according to the single transaction/job performance condition calculated by testing, and according to the evaluated total transaction/job amount, multiplying the single performance by the total amount to obtain the total performance condition and the like, wherein the total performance condition comprises the total response time of software, CPU time and the like.
Step S907: evaluating and calculating the storage space requirement of the new application corresponding to the service data: based on the evaluated transaction/job total, the transaction/job relates to the table list, the file list, the evaluation and calculation of the business data storage space corresponding to the new application, and so on, then it jumps to step S912.
Step S908: testing and calculating the change of the single modification transaction/operation performance: and for the overall scheme stage, calculating the single transaction/operation performance change condition by using the related quantitative performance indexes, and for the ending pressure test stage, obtaining the related single transaction/operation performance change condition by performing pressure test on the transaction/operation, wherein the single performance condition comprises single transaction/operation response time, CPU time and the like.
Step S909: evaluation calculation modified transaction/job related totals: including transaction call counts (peak and full, etc.), job run counts, table listings, and so forth.
Step S910: evaluating the computing to modify the application overall performance variation: and obtaining the overall performance change situation and the like by multiplying the single transaction/job performance by the total amount according to the single transaction/job performance change situation calculated by the test and the estimated transaction/job total amount, wherein the overall performance situation comprises the overall software response time, the CPU time and the like.
Step S911: evaluating the storage space requirement of the business data corresponding to the calculation and modification application: based on the evaluated transaction/job total, the transaction/job relates to the table list, the file list, the evaluation and calculation of the business data storage space corresponding to the new application, and so on, then it jumps to step S912.
Step S912: and outputting the relevant evaluation calculation result information, and storing the evaluation calculation result information in the output storage server 300.
Example 3
As shown in fig. 10, the present invention provides a software performance analysis method based on banking services, wherein the method includes:
step S101: the software performance processing server receives software information including transaction list, program list, file list and operation list information from the software information input device; the transaction list information includes: transaction name, transaction function description, transaction amount, SQL variation related to transaction and transaction calling program condition; the program list information includes: program name, program function description, program calling amount and program related SQL variation; the table listing information includes: table name, table record length and index design; the file list information comprises: file name, file record length; the job list information includes: job name, job function description, job related SQL delta.
Step S102: the software performance processing server receives quantitative performance index information comprising a quantitative performance index of database operation, a quantitative performance index of middleware operation and a performance conversion coefficient from the database server; the quantitative performance index information of the database operation comprises: SELECT performance consumption, UPDATE performance consumption, COMMIT performance consumption; the quantified performance index information of the middleware operation comprises: transaction initialization consumption, program calling consumption and XML package unpacking consumption; the performance conversion coefficient comprises: the CPU capacity processing performance conversion coefficient of different types of machines, the conversion coefficient from the database operation performance consumption to the middleware performance consumption, and the conversion coefficient from the middleware performance consumption to the method performance consumption.
Step S103: the software performance processing server generates performance analysis result information including transaction response time, CPU resource consumption and storage space demand information according to the software information and the quantitative performance index information;
step S104: the software performance processing server outputs the performance analysis result information to an output storage server for storage.
Before receiving quantization performance index information including a quantization performance index of a database operation, a quantization performance index of a middleware operation and a performance conversion coefficient from a database server, the database server preprocesses the quantization performance index information of the database operation, the quantization performance index information of the middleware operation and the performance conversion coefficient to generate preprocessing result information, wherein the quantization performance index information is preprocessing result information.
The preprocessing result information generated by preprocessing the quantitative performance index information of the database operation by the database server comprises: quantitative analysis of the state of the production method, quantitative analysis of related operations of database products, and test analysis of database quantitative indexes.
The preprocessing result information generated by preprocessing the quantitative performance index information of the middleware operation by the database server comprises: quantitative analysis of the state of the production system, quantitative analysis of related operations of the middleware product and quantitative index analysis of the middleware.
The preprocessing result information generated by preprocessing the performance conversion coefficient by the database server comprises: and analyzing the conversion coefficient from the database performance index to the middleware performance index, analyzing the conversion coefficient from the middleware performance index to the overall consumption of the method, and analyzing the conversion coefficient from the CPU processing capacity of different types of machines.
The embodiment of the invention has the following beneficial technical effects:
firstly, the accuracy of evaluation and analysis of the performance of the host software is improved:
according to the software performance evaluation method, relevant quantitative performance indexes including index information such as database operation quantitative performance indexes, middleware operation quantitative performance indexes and performance conversion coefficients can be read from the database server according to software information read by the software information input device, and after detailed calculation and analysis, software performance relevant conditions and conditions such as service data storage space requirements corresponding to software application are evaluated and determined, so that evaluation and analysis of software performance are realized, and accuracy of evaluation and analysis of host software performance is improved.
II, providing decision support of a scheme at the stage of the overall scheme:
the software performance evaluation method can realize the evaluation of the project software performance in the project overall scheme stage, comprehensively master the relevant conditions of each scheme in the aspect of performance, is favorable for decision selection of schemes with good performance, and ensures the smooth progress of projects.
And thirdly, the software performance is comprehensively controlled, and the safe operation of production is guaranteed:
the software performance evaluation system can comprehensively evaluate and analyze the related performance condition of the software, and conveniently and comprehensively master and control the performance of the software, thereby facilitating the performance optimization of the software with poor performance, ensuring the good performance of software application and ensuring the safe operation of a production system when the software is put into production.
Fourthly, unification of the software performance analysis method is realized:
at present, software performance evaluation analysis methods are imperfect and non-uniform, and because different analyst levels and understanding of software performance evaluation analysis are different, the difference of software performance analysis results is large, which is very unfavorable for ensuring good performance of software. The software performance evaluation system and the method thereof unify the software performance evaluation analysis method, ensure the accuracy of software performance evaluation analysis, are beneficial to the software performance evaluation analysis management and can find software performance problems in time.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (26)

1. A system for analyzing performance of software based on banking, the system comprising: the system comprises a software information input device, a database server, a software performance processing server and an output storage server;
the software information input device, the database server and the output storage server are respectively connected with the software performance processing server through an enterprise local area network; wherein,
the software information input device is used for inputting software information by a user, and comprises:
a transaction list input device for inputting transaction list information of the software application,
program listing input means for inputting program listing information for the software application,
a table list input means for inputting table list information of the software application,
file list input means for inputting file list information of a software application, and
a job list input means for inputting job list information of the software application;
the database server includes:
database quantization performance index storage means for storing quantization performance index information of database operations,
a middleware quantization performance index storage device for storing quantization performance index information of the middleware operation,
performance conversion coefficient storage means for storing performance conversion coefficients, and
the information preprocessing device is used for preprocessing the quantitative performance index information of the database operation, the quantitative performance index information of the middleware operation and the performance conversion coefficient and generating preprocessing result information;
the software performance processing server comprises:
a software information reading device for reading the software information from the software information input device,
a quantization performance index reading device for reading in the quantization performance index information of the database operation preprocessed by the information preprocessing device, the quantization performance index information of the middleware operation and the performance conversion coefficient,
a performance analysis processing device for generating analysis processing results including transaction response time, CPU resource consumption and storage space requirement according to the software information read in by the software information reading device and the database operation quantitative performance index information read in by the quantitative performance index reading device and the CPU resource consumption evaluation analysis calculation model, the response time evaluation analysis calculation model and the disk space calculation model,
the analysis result output device is used for outputting the analysis processing result;
the output storage server includes:
performance analysis result storage means for storing the transaction response time and CPU resource consumption information, an
The storage space analysis result storage device is used for storing the storage space requirement;
the CPU resource consumption evaluation analysis calculation model comprises the following steps:
modifying the class software: software overall increase CPU time ═ Σ (transaction individual change CPU time × transaction amount);
newly adding software: the software increases the CPU time ═ sigma (newly increased transaction single CPU time multiplied by transaction amount);
the response time evaluation analysis calculation model is as follows:
modifying the class software: the software transaction average response time is (the current transaction average response time is multiplied by the current overall transaction amount + sigma (the single transaction increase response time is multiplied by the single transaction amount))/the current overall transaction amount;
newly adding software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + sigma (the newly added single trade response time is multiplied by the single trade volume))/(the current whole trade volume + sigma (the single trade volume));
the disk space calculation model is as follows: the software disk space requirement = database storage requirement + software file storage requirement + software data migration file storage requirement.
2. The system of claim 1, wherein said transaction list information comprises: transaction name, transaction function description, transaction amount, transaction related SQL variation and transaction calling program condition.
3. The system of claim 1, wherein the program inventory information comprises: program name, program function description, program call amount, program related SQL variation.
4. The system of claim 1, wherein said table inventory information comprises: table name, table record length, index design.
5. The system of claim 1, wherein said file manifest information comprises: file name, file record length.
6. The system of claim 1, wherein said job list information comprises: job name, job function description, job related SQL delta.
7. The system of claim 1, wherein the quantitative performance indicator information of the database operation comprises: SELECT performance consumption, UPDATE performance consumption, COMMIT performance consumption.
8. The system of claim 1, wherein the quantitative performance indicator information of the middleware operation comprises: transaction initialization consumption, program call consumption, XML package unpacking consumption.
9. The system of claim 1, wherein the performance conversion factor comprises: the CPU capacity of different machines is converted into performance conversion coefficient, the operation performance of the database is converted into the middleware performance consumption conversion coefficient, and the middleware performance is converted into the system performance consumption conversion coefficient.
10. The system of claim 1, wherein the preprocessing means for preprocessing the quantitative performance indicator information of the database operation to generate the preprocessing result information comprises: the method comprises the steps of quantitative analysis of the state of a production system, quantitative analysis of related operations of database products and test analysis of database quantitative indexes.
11. The system of claim 1, wherein the preprocessing result information generated by the information preprocessing apparatus preprocessing the quantization performance indicator information of the middleware operation comprises: quantitative analysis of the state of the production system, quantitative analysis of related operations of the middleware product and quantitative index analysis of the middleware.
12. The system of claim 1, wherein the information preprocessing unit generates the preprocessing result information by preprocessing the performance reduction coefficient, and comprises: and analyzing the conversion coefficient from the database performance index to the middleware performance index, analyzing the conversion coefficient from the middleware performance index to the whole system consumption, and analyzing the conversion coefficient from the CPU processing capacity of different types of machines.
13. A software performance analysis method based on banking business is characterized by comprising the following steps:
the software performance processing server receives software information including transaction list information, program list information, table list information, file list information and operation list information from the software information input device;
the software performance processing server receives quantitative performance index information comprising a quantitative performance index of database operation, a quantitative performance index of middleware operation and a performance conversion coefficient from the database server;
the software performance processing server generates performance analysis result information including transaction response time, CPU resource consumption and storage space demand information according to the software information and the quantitative performance index information and a CPU resource consumption evaluation analysis calculation model, a response time evaluation analysis calculation model and a disk space calculation model;
the software performance processing server outputs the performance analysis result information to an output storage server for storage;
the CPU resource consumption evaluation analysis calculation model comprises the following steps:
modifying the class software: software overall increase CPU time ═ Σ (transaction individual change CPU time × transaction amount);
newly adding software: the software increases the CPU time ═ sigma (newly increased transaction single CPU time multiplied by transaction amount);
the response time evaluation analysis calculation model is as follows:
modifying the class software: the software transaction average response time is (the current transaction average response time is multiplied by the current overall transaction amount + sigma (the single transaction increase response time is multiplied by the single transaction amount))/the current overall transaction amount;
newly adding software: the software trade average response time is (the current trade average response time is multiplied by the current whole trade volume + sigma (the newly added single trade response time is multiplied by the single trade volume))/(the current whole trade volume + sigma (the single trade volume));
the disk space calculation model is as follows: the software disk space requirement = database storage requirement + software file storage requirement + software data migration file storage requirement.
14. The method of claim 13, wherein the database server preprocesses the quantized performance indicator information of the database operation, the quantized performance indicator information of the middleware operation, and the performance reduction coefficient to generate preprocessed result information before the software performance processing server receives the quantized performance indicator information including the quantized performance indicator of the database operation, the quantized performance indicator of the middleware operation, and the performance reduction coefficient from the database server.
15. The method of claim 13, wherein the quantization performance indicator information is pre-processing result information.
16. The method of claim 13, wherein said transaction list information comprises: transaction name, transaction function description, transaction amount, transaction related SQL variation and transaction calling program condition.
17. The method of claim 13, wherein the program inventory information comprises: program name, program function description, program call amount, program related SQL variation.
18. The method of claim 13, wherein said table inventory information comprises: table name, table record length, index design.
19. The method of claim 13, wherein the file manifest information comprises: file name, file record length.
20. The method of claim 13, wherein said job list information comprises: job name, job function description, job related SQL delta.
21. The method of claim 13, wherein the quantitative performance indicator information of the database operation comprises: SELECT performance consumption, UPDATE performance consumption, COMMIT performance consumption.
22. The method of claim 13, wherein the quantitative performance indicator information of the middleware operation comprises: transaction initialization consumption, program call consumption, XML package unpacking consumption.
23. The method of claim 13, wherein the performance reduction factor comprises: the CPU capacity processing performance conversion coefficient of different types of machines, the conversion coefficient from the database operation performance consumption to the middleware performance consumption, and the conversion coefficient from the middleware performance consumption to the method performance consumption.
24. The method of claim 14, wherein preprocessing the quantized performance indicator information of the database operation by the database server to generate the preprocessing result information comprises: quantitative analysis of the state of the production method, quantitative analysis of related operations of database products, and test analysis of database quantitative indexes.
25. The method of claim 14, wherein preprocessing result information generated by database server preprocessing the quantitative performance indicator information of the middleware operation comprises: quantitative analysis of the state of the production system, quantitative analysis of related operations of the middleware product and quantitative index analysis of the middleware.
26. The method of claim 14, wherein preprocessing result information generated by preprocessing the performance conversion coefficients by a database server comprises: and analyzing the conversion coefficient from the database performance index to the middleware performance index, analyzing the conversion coefficient from the middleware performance index to the overall consumption of the method, and analyzing the conversion coefficient from the CPU processing capacity of different types of machines.
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