CN111506484A - Program performance evaluation method, system and equipment - Google Patents
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Abstract
The embodiment of the invention discloses a program performance evaluation method, a system and equipment, wherein program performance evaluation is carried out from a plurality of different evaluation dimensions through evaluation dimension setting, dimension evaluation is carried out by setting different evaluation indexes aiming at various relational databases under each evaluation dimension, the evaluation indexes comprise main evaluation indexes, the main evaluation indexes generally select key performance indexes which have larger influence on program performance, in addition, the evaluation indexes also comprise revision evaluation indexes, and the fraction revision of single digit is carried out on the basis of the main evaluation index grading, and no matter index evaluation is carried out on the main evaluation indexes, the index evaluation is carried out by utilizing preset index evaluation information to carry out comparison and calculation, so that accurate quantitative program performance evaluation is carried out on various business application programs.
Description
Technical Field
The invention relates to the technical field of program performance testing, in particular to a program performance evaluation method, system and device.
Background
When various business application programs are developed and implemented in various industries at present, the performance quality of the programs often cannot be accurately and quantitatively evaluated.
The performance quality of the program mainly comprises the code structure quality, the code logic quality, the data structure quality and the like of the program. The current situation is: the user can easily confirm whether the function requirements are realized (by the developer) or not, but is difficult to confirm whether the code quality and the structure quality of the background are reasonable or not to realize the functions or not, and whether other influences are caused or not. Therefore, after the program is on line, the risk and economic loss are brought to a user due to poor performance quality.
Disclosure of Invention
The embodiment of the invention aims to provide a program performance evaluation method, a system and equipment, which are used for solving the problem that the performance quality of the program cannot be accurately and quantitatively evaluated in the performance evaluation of the current business application program.
In order to achieve the above object, an embodiment of the present invention provides a program performance evaluation method, where the method includes: setting a plurality of evaluation dimensions and allocating a preset weight ratio to each evaluation dimension; setting at least one evaluation index for each evaluation dimension aiming at various relational databases; selecting at least one evaluation index for each evaluation dimension; acquiring an actual measurement value of each selected evaluation index; evaluating each selected evaluation index according to the actual measurement value and preset index evaluation information, and acquiring a first evaluation result; evaluating each evaluation dimension according to the first evaluation result and acquiring a second evaluation result; and comprehensively evaluating the program performance according to the second evaluation result and obtaining a final evaluation result.
Further, the evaluation index includes: the evaluation system comprises main evaluation indexes, wherein one main evaluation index is selected for each evaluation dimension, and index evaluation information corresponding to the main evaluation indexes comprises: the evaluation method of the main evaluation index comprises the following steps of: presetting a first recommendation threshold and a second recommendation threshold as an 80% recommendation threshold and a first 0-point recommendation threshold which reach 80% of full score respectively; comparing the full score threshold value with the 80% recommended threshold value to obtain a first comparison result; comparing the actual measurement value with the first 0-point recommended threshold value to obtain a second comparison result; and evaluating the main evaluation index by combining the first comparison result and the second comparison result.
Further, the evaluation of the main evaluation index by combining the first comparison result and the second comparison result comprises that when the full score threshold is smaller than the 80% recommendation threshold and the actual measurement value is greater than or equal to the first 0-point recommendation threshold, the evaluation score of the main evaluation index is 0, when the full score threshold is smaller than the 80% recommendation threshold and the actual measurement value is smaller than the first 0-point recommendation threshold, the evaluation score of the main evaluation index is calculated by a first algorithm formula, wherein when the evaluation score of the main evaluation index is × [1- (actual measurement value/first 0-point recommendation threshold) ] × first weight percentage, when the full score threshold is greater than the 80% recommendation threshold and the actual measurement value is smaller than or equal to the first 0-point recommendation threshold, the evaluation score of the main evaluation index is 0, when the full score threshold is greater than the 80% recommendation threshold and the actual measurement value is greater than the first 0-point recommendation threshold, the evaluation score of the main evaluation index is calculated by a second algorithm formula, and when the actual measurement value is greater than the first 0-point recommendation threshold, the evaluation score of the main evaluation index is calculated by a second algorithm formula, namely a first weight percentage recommendation threshold of the full score of the main evaluation index is × - × -100.
Further, the evaluation index further includes: revising evaluation indexes, and selecting all corresponding revising evaluation indexes at a time for each evaluation dimension, wherein the index evaluation information corresponding to the revising evaluation indexes comprises: the second weight proportion, the first recommendation threshold and the second recommendation threshold are set to be negative values, and the method for evaluating the revised evaluation index comprises the following steps: presetting a first recommendation threshold and a second recommendation threshold as a second 0-point recommendation threshold and a negative-point recommendation extreme value respectively; comparing the second 0-point recommendation threshold value with the negative-point recommendation extreme value to obtain a third comparison result; comparing the actual measurement value with the second 0-point recommended threshold value to obtain a fourth comparison result; comparing the actual measurement value with the negative score recommended extreme value to obtain a fifth comparison result; and evaluating the revision evaluation index in combination with the third comparison result, the fourth comparison result and the fifth comparison result.
The evaluation of the revised evaluation index in combination with the third comparison result, the fourth comparison result and the fifth comparison result comprises that when the second 0-point recommendation threshold is smaller than the negative-point recommendation threshold and the actual measurement value is smaller than or equal to the second 0-point recommendation threshold, the evaluation score of the revised evaluation index is 0, when the second 0-point recommendation threshold is smaller than the negative-point recommendation threshold and the actual measurement value is greater than or equal to the negative-point recommendation threshold, the evaluation score of the revised evaluation index is a full-weighted revision score obtained according to the second weight-point recommendation ratio, when the second 0-point recommendation threshold is smaller than the negative-point recommendation threshold and the actual measurement value is greater than the second 0-point recommendation threshold and smaller than the negative-point recommendation threshold, the evaluation score of the revised evaluation index is calculated according to a third calculation formula, wherein when the evaluation score of the revised evaluation index is greater than the actual recommendation threshold, the second 0-point recommendation threshold)/(the negative-actual measurement value-point recommendation threshold is ×, the evaluation score of the revised evaluation index is greater than the actual recommendation threshold, the second 0-point recommendation threshold is greater than the negative-point recommendation threshold, the evaluation score recommendation threshold is greater than the actual recommendation threshold, the negative-recommendation threshold, the evaluation score recommendation threshold is greater than the negative-recommendation threshold, the actual recommendation threshold, the negative-recommendation threshold is calculated according to a weighted recommendation threshold, the evaluation score recommendation threshold, the actual recommendation evaluation score recommendation threshold is greater than the negative-recommendation threshold, the negative-recommendation threshold is greater than the negative recommendation evaluation score recommendation threshold, the negative recommendation evaluation score recommendation threshold is greater than the negative recommendation threshold, the negative recommendation evaluation score recommendation threshold.
The evaluation dimension comprises execution logic, statement analysis, query performance, transaction waiting and environment configuration, the main evaluation index corresponding to the execution logic comprises login number per second, the revision evaluation index corresponding to the execution logic comprises average required per transaction SQ L, the main evaluation index corresponding to the statement analysis comprises analysis amount per second and program cache hit rate, the revision evaluation index corresponding to the statement analysis comprises re-analysis amount per second and concurrent waiting events, the main evaluation index corresponding to the query performance comprises buffer pool hit rate and page cache time, the revision evaluation index corresponding to the query performance comprises record read and select rate and I/O input/output average waiting time, the main evaluation index corresponding to the transaction waiting comprises lock waiting percentage, the main evaluation index corresponding to the environment configuration comprises configuration type waiting and average non-idle waiting time, and the revision evaluation index corresponding to the environment configuration comprises log cache hit rate and average log write-in time.
In another aspect of the embodiments of the present invention, there is provided a program performance evaluation system, including: the evaluation dimension setting module is used for setting a plurality of evaluation dimensions and distributing a preset weight ratio to each evaluation dimension; the evaluation index setting module is used for setting at least one evaluation index for each evaluation dimension aiming at various relational databases and presetting index evaluation information for each evaluation index; selecting at least one evaluation index for each evaluation dimension; the evaluation index actual measurement module is used for acquiring an actual measurement value of each selected evaluation index; the selected index evaluation module is used for evaluating each selected evaluation index according to the actual measurement value and preset index evaluation information and acquiring a first evaluation result; the dimension evaluation module is used for evaluating each evaluation dimension according to the first evaluation result and acquiring a second evaluation result; and the comprehensive evaluation module is used for comprehensively evaluating the program performance according to the second evaluation result and acquiring a final evaluation result.
Further, the evaluation index includes: the evaluation index setting module selects one main evaluation index for each evaluation dimension at a time, and the index evaluation information corresponding to the main evaluation index comprises: a first weight proportion, a full score threshold, a first recommendation threshold and a second recommendation threshold that are the same as the corresponding evaluation dimension; the evaluation index setting module is further used for presetting a first recommendation threshold and a second recommendation threshold as an 80% recommendation threshold and a first 0-point recommendation threshold which reach 80% of full score respectively; the selected metric evaluation module includes: the main index evaluation unit is used for comparing the full score threshold value with the 80% recommended threshold value to obtain a first comparison result; comparing the actual measurement value with the first 0-point recommended threshold value to obtain a second comparison result; and evaluating the main evaluation index by combining the first comparison result and the second comparison result.
Further, the evaluation index further includes: revising evaluation indexes, wherein the evaluation index setting module selects all corresponding revising evaluation indexes at a time for each evaluation dimension, and the index evaluation information corresponding to the revising evaluation indexes comprises: a second weight fraction set to a negative value, the first recommendation threshold, and the second recommendation threshold; the evaluation index setting module is further used for presetting a first recommendation threshold and a second recommendation threshold as a second 0-point recommendation threshold and a negative-point recommendation extreme value respectively; the selected metric evaluation module further comprises: the revision index evaluation unit is used for comparing the second 0-point recommendation threshold value with the negative-point recommendation extreme value to obtain a third comparison result; comparing the actual measurement value with the second 0-point recommended threshold value to obtain a fourth comparison result; comparing the actual measurement value with the negative score recommended extreme value to obtain a fifth comparison result; and evaluating the revision evaluation index in combination with the third comparison result, the fourth comparison result and the fifth comparison result.
In another aspect of the embodiments of the present invention, there is also provided a computer device, where the computer device includes: one or more processors; a memory for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement the method as described above.
The embodiment of the invention has the following advantages:
the embodiment of the invention carries out program performance evaluation from a plurality of different evaluation dimensions through evaluation dimension setting, under each evaluation dimension, the dimension evaluation is carried out by setting different evaluation indexes aiming at various relational databases, the evaluation indexes comprise main evaluation indexes, the main evaluation indexes generally select key performance indexes which have larger influence on program performance, in addition, the evaluation indexes also comprise revision evaluation indexes, the fraction revision of single digit is carried out on the basis of the main evaluation index grading, no matter the index evaluation is carried out on the main evaluation indexes, or the index evaluation is carried out on the main evaluation indexes, the comparison and calculation are carried out by utilizing preset index evaluation information, and thus, the accurate quantitative program performance evaluation is carried out on various service application programs.
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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. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
FIG. 1 is a schematic diagram of a logic structure of a program performance evaluation system according to an embodiment of the present invention;
fig. 2 is a flowchart of a program performance evaluation method according to an embodiment of the present invention.
The system comprises a 1-evaluation dimension setting module, a 2-evaluation index setting module, a 3-evaluation index actual measurement module, a 4-selected index evaluation module, a 41-main index evaluation unit, a 42-revised index evaluation unit, a 5-dimension evaluation module and a 6-comprehensive evaluation module.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
The embodiment of the invention aims at business application programs, performs program performance evaluation by setting a series of indexes under different dimensions and aiming at the actual measurement value of each evaluation index, and shows that the current state of the software is excellent when the final evaluation result of the tested software meets the requirement.
Referring to fig. 1, an embodiment of the present invention provides a program performance evaluation system including: the system comprises an evaluation dimension setting module 1, an evaluation index setting module 2, an evaluation index actual measurement module 3, a selected index evaluation module 4, a dimension evaluation module 5 and a comprehensive evaluation module 6.
Specifically, referring to fig. 2, a program performance evaluation method of a program performance evaluation system according to an embodiment of the present invention includes: setting a plurality of evaluation dimensions through an evaluation dimension setting module 1 and distributing a preset weight ratio for each evaluation dimension; setting at least one evaluation index for each evaluation dimension by an evaluation index setting module 2 aiming at various relational databases; selecting at least one evaluation index for each evaluation dimension; the actual measurement value of each selected evaluation index is obtained through an evaluation index actual measurement module 3; evaluating each selected evaluation index through a selected index evaluation module 4 according to the actual measurement value and preset index evaluation information, and acquiring a first evaluation result; evaluating each evaluation dimension according to the first evaluation result through a dimension evaluation module 5 and acquiring a second evaluation result; and comprehensively evaluating the program performance according to the second evaluation result through the comprehensive evaluation module 6 and obtaining a final evaluation result.
The embodiment of the invention carries out program performance evaluation from a plurality of different evaluation dimensions through evaluation dimension setting, carries out dimension evaluation by setting different evaluation indexes aiming at various relational databases under each evaluation dimension, and realizes comparison and calculation of various different indexes by utilizing preset index evaluation information, thereby realizing accurate quantitative program performance evaluation of various business application programs.
In the embodiment of the present invention, the following takes an example that the final evaluation result, i.e., the final composite score full score is 100, and the above program performance evaluation method is specifically described as follows.
Further, the evaluating dimensions specifically include: the method comprises the following steps of executing logic, statement analysis, query performance, transaction waiting and environment configuration, wherein the weight occupation ratio corresponding to each evaluation dimension is shown in the following table 1:
table 1: weight-to-weight assignment list for evaluation dimension
| Assessing dimensionality | The weight is% |
| Execution logic | 15 |
| Statement parsing | 20 |
| Query performance | 20 |
| Transaction wait | 25 |
| Environment configuration | 20 |
。
The comprehensive evaluation module 6 performs comprehensive evaluation on the program performance according to a second evaluation result and obtains a final evaluation result, where the second evaluation result is a weighted score of each evaluation dimension, and the final evaluation result (i.e., a program performance quality comprehensive score) is a sum of the weighted scores of each evaluation dimension, and a specific final evaluation result calculation formula is as follows:
program performance quality composite score- ∑ (execute logic _ weighted score + statement parsing _ weighted score + query performance _ weighted score + transaction wait _ weighted score + environment configuration _ weighted score).
Further, in the embodiment of the present invention, the evaluation index includes: the main evaluation index is a main scoring index of the evaluation dimension where the main evaluation index is located, and is usually a key performance index having a large influence on program performance, where the main evaluation index corresponding to the execution logic includes: the number of logins per second, and the main evaluation indexes corresponding to statement analysis comprise: the main evaluation indexes corresponding to the query performance comprise the per-second analysis amount and the program cache hit rate: the buffer pool hit rate, the page cache time, and the main evaluation index corresponding to the transaction wait include: lock wait percentage; the main evaluation index corresponding to the environment configuration includes: configured wait, average non-idle wait time.
As described above, at least one main evaluation index is set for each evaluation dimension, and for each evaluation dimension, one main evaluation index is selected each time, and there are more than one main evaluation indexes for some evaluation dimensions. For example, when the environment configuration is used as the evaluation dimension, both the configured waiting time and the average non-idle waiting time are the main evaluation indexes, when the environment configuration is evaluated, only one of the configured waiting time and the average non-idle waiting time can be selected as the main evaluation index of the configured waiting time, and the other item does not participate in the evaluation calculation.
The main reason why more than one main evaluation index exists in each evaluation dimension is that the main evaluation indexes depend on the performance view statistics of the relational database, while in different types of real relational database products, the provided main evaluation indexes are different, and some relational database products do not have all the main evaluation indexes indicated above. Therefore, a plurality of main evaluation indexes are prepared to facilitate program performance evaluation of various relational databases.
Further, in the embodiment of the present invention, the evaluation index setting module 2 sets index evaluation information in advance for each main evaluation index, and the index evaluation information corresponding to the main evaluation index includes: the first weight proportion, the full-scale threshold, the first recommendation threshold and the second recommendation threshold which are the same as the corresponding evaluation dimensionality are preset, and the first recommendation threshold and the second recommendation threshold are respectively an 80% recommendation threshold and a first 0-point recommendation threshold which reach 80% of full scale; wherein, the score-full threshold specifically means: when a certain main evaluation index obtains the evaluation satisfaction, the program obtains the value to be reached on the main evaluation index; the 80% recommended threshold specifically refers to: when the evaluation score of a certain main evaluation index reaches 80% of the full score, the program is healthy on the index and does not need to be optimized according to the numerical value required to be reached on the main evaluation index, and the first 0-point recommendation threshold specifically refers to: when the evaluation score of a certain main evaluation index is 0, the program is used for obtaining the value on the main evaluation index. Specific setting information of the main evaluation index is shown in the following table 2:
table 2: setting information list of main evaluation index
In the embodiment of the present invention, the selected index evaluation module 4 includes: a main index evaluation unit 41, and an evaluation method of the main evaluation index includes: a first recommendation threshold and a second recommendation threshold are preset for the main evaluation index through an evaluation index setting module 2 and are respectively an 80% recommendation threshold and a first 0-point recommendation threshold; comparing the score-full threshold value with the 80% recommended threshold value through a main index evaluation unit 41 to obtain a first comparison result; the actual measurement value of each selected main evaluation index is obtained through the evaluation index actual measurement module 3 and is sent to the main index evaluation unit 41, and the actual measurement value is compared with the first 0-point recommendation threshold value of the corresponding main evaluation index through the main index evaluation unit 41 to obtain a second comparison result; and the main index evaluation unit 41 evaluates the selected main evaluation index in combination with the first comparison result and the second comparison result.
The main index evaluation unit 41 evaluates the main evaluation index by combining the first comparison result and the second comparison result, wherein the evaluation score of the selected main evaluation index is 0 when the first comparison result is that the full score threshold is less than 80% of the recommended threshold and the second comparison result is that the actual measurement value is greater than or equal to the first 0-point recommended threshold, the evaluation score of the selected main evaluation index is calculated by a first algorithm formula, wherein the evaluation score of the main evaluation index is 100% × [1- (actual measurement value/first 0-point recommended threshold) ] × first weight occupation ratio, for example, when the actual measurement value of the resolution per second is 10, the evaluation score of the resolution per second is 100% × [1- (10/60) ] 64% ] 16.67, the first comparison result is 80% of the full score threshold)/(first 0-point recommended threshold, and the second comparison result is less than 0% of the actual measurement value, the evaluation score of the selected main evaluation index is equal to 4830% of the recommended threshold, the evaluation score of the selected main evaluation index is equal to 100% of the actual measurement value, the evaluation score is equal to 95% -95%, and the evaluation score of the second evaluation index is equal to 90% of the selected main evaluation index, (e.g., when the actual measurement value is greater than 80% recommended threshold, the evaluation score of the second comparison result is equal to 10%), and the evaluation score of the selected main evaluation index is equal to 5% -95%, and the evaluation index is equal to 5%, and the evaluation score of the selected main evaluation index is equal to 5%, and the evaluation score of the selected main evaluation index is equal to 5%, and the second evaluation index is equal to 95%, and the evaluation threshold.
In the embodiment of the invention, the evaluation indexes further comprise revision evaluation indexes which have definite influence on the program performance, but the influence of the revision evaluation indexes on the program performance is generally weaker than that of the main evaluation index, therefore, when the program performance evaluation calculation is carried out, the influence score of the revision evaluation indexes is smaller, and the score is smaller when the score is revised by a single-digit score on the basis of the program performance evaluation of the main evaluation index, wherein the revision evaluation indexes corresponding to the execution logic comprise SQ L required by each transaction on average, the revision evaluation indexes corresponding to statement analysis comprise analysis amount per second and concurrent waiting events, the evaluation indexes corresponding to the query performance revision comprise log cache hit rate and average log writing time.
As described above, some evaluation dimensions are provided with revised evaluation indexes, and some evaluation dimensions are provided with no revised evaluation indexes, for example, no revised evaluation indexes are provided when a transaction waits; when calculating the evaluation score of the evaluation dimension, all the corresponding revised evaluation indexes are selected for each evaluation dimension at a time. Thus, the evaluation score of each evaluation dimension is the sum of the evaluation score of the selected main evaluation index corresponding to the evaluation dimension and all the revised evaluation indexes corresponding to the evaluation dimension. For example, taking the resolution performance as an example, the main evaluation index corresponding to the resolution performance includes a resolution amount per second and a program cache hit rate, and the revised evaluation index corresponding to the resolution performance includes a re-resolution amount per second and a program cache hit rate, if the evaluation score of the resolution amount per second is 18 minutes, the evaluation score of the program cache hit rate is 18 minutes, the evaluation score of the re-resolution amount per second is-2 minutes, the evaluation score of the concurrent waiting event is-3 minutes, and the resolution amount per second is selected as the main evaluation index, then: the evaluation score of analytical performance was 18+ (-2) + (-3) — 13.
Further, in the embodiment of the present invention, similarly, the evaluation index setting module 2 sets in advance index evaluation information for each revised evaluation index, and the index evaluation information corresponding to the revised evaluation index includes: a second weight fraction set to a negative value, a first recommendation threshold, and a second recommendation threshold. The second weight duty setting to a negative value indicates: the influence on the performance quality of the program is reflected by the revision evaluation index in a point deduction mode, and the better the revision evaluation index is expressed, the less the point deduction is. Presetting a first recommendation threshold and a second recommendation threshold as a second 0-point recommendation threshold and a negative-point recommendation extreme value respectively; wherein, the second 0-point recommendation threshold specifically means: when a certain item of the revised and ordered evaluation index reaches the optimum value, and the evaluation score is 0 min, the program revises the numerical value required to be reached on the evaluation index on the item; the negative score recommended extreme value specifically means: when a certain item of the revised and evaluated indexes are not good in performance and the weight evaluation score is completely deducted, the program revises the numerical value required to be achieved on the evaluation index. The specific setting information of the revision evaluation index is shown in the following table 3:
table 3: revision of setting information list of evaluation index
In the embodiment of the present invention, the selected index evaluation module 4 further includes: the revision indicator evaluation unit 42, the evaluation method of the revision evaluation indicator, includes: the first recommendation threshold and the second recommendation threshold are preset as a second 0-point recommendation threshold and a negative-point recommendation extremum respectively for the revised evaluation index through the evaluation index setting module 2; comparing the second 0-point recommendation threshold value with the negative-point recommendation extreme value through the revision index evaluation unit 42 to obtain a third comparison result; the actual measurement value of each selected revision evaluation index is obtained through the evaluation index actual measurement module 3 and is sent to the revision index evaluation unit 42, and the actual measurement value is compared with the second 0-point recommendation threshold value through the revision index evaluation unit 42 to obtain a fourth comparison result; comparing the actual measurement value with the negatively-divided recommended extreme value to obtain a fifth comparison result; and the revision indicator evaluation unit 42 evaluates the revision indicator in combination with the third comparison result, the fourth comparison result, and the fifth comparison result.
The modification index evaluation unit 42 further evaluates the modification evaluation index according to a third comparison result, a fourth comparison result and a fifth comparison result, wherein the modification evaluation index is divided into 0 when the third comparison result is that the second 0-point recommended threshold is smaller than the negative-point recommended extremum and the fourth comparison result is that the actual measurement value is smaller than or equal to the second 0-point recommended threshold, the modification evaluation index is divided into a modification weighted full score obtained according to the second weight-point recommended threshold when the third comparison result is that the second 0-point recommended threshold is smaller than the negative-point recommended extremum and the fifth comparison result is that the actual measurement value is greater than or equal to the negative-point recommended extremum, the modification evaluation score of the modification evaluation index is divided into a modification weighted full score obtained according to the second weight-point recommended threshold, the third comparison result is that the second 0-point recommended threshold is smaller than the negative-point recommended extremum, and the two-fourth comparison result and the fifth comparison result are that the actual measurement value is greater than the second 0-point recommended extremum and smaller than the negative-point recommended extremum, the modification evaluation score of the modification evaluation index is calculated by a third calculation formula (3688-3695)/(the modification evaluation index) and the modification evaluation index is calculated by a third comparison result when the third comparison result is smaller than the third comparison result is larger than the third comparison result, the third comparison result is larger than the third comparison result is smaller than the negative-36-7-two.
The embodiment of the invention carries out program performance evaluation from a plurality of different evaluation dimensions through evaluation dimension setting, under each evaluation dimension, the dimension evaluation is carried out by setting different evaluation indexes aiming at various relational databases, the evaluation indexes comprise main evaluation indexes, the main evaluation indexes generally select key performance indexes which have larger influence on program performance, in addition, the evaluation indexes also comprise revision evaluation indexes, the fraction revision of single digit is carried out on the basis of the main evaluation index grading, no matter the index evaluation is carried out on the main evaluation indexes, or the index evaluation is carried out on the main evaluation indexes, the comparison and calculation are carried out by utilizing preset index evaluation information, and thus, the accurate quantitative program performance evaluation is carried out on various service application programs.
The main-order evaluation index and the revised evaluation index related to the above are described in detail below.
In most cases, even in a system with very large traffic, the value of the index should not exceed 10, the index is higher than a recommended value, and usually only has a relationship with access logic set by development codes, namely whether the transaction is set to be a short connection mode when the code is written, for example, an access database transaction containing a plurality of sql statements is usually set to be logged into the system when a task starts, and is logged out after the execution is finished, and at this time, the execution of the whole transaction only generates logging behavior of the database once.
The average per-transaction required SQ L is that for a business system, the quantity of SQ L contained in each transaction should not be too much, the excessive SQ L means that the execution time of the transaction is longer, various resources (such as row lock, table lock, bolt and other database resources) are occupied and the locking time is correspondingly longer, and other transactions needing to use the resources are forced to wait, so that the quantity of SQ L contained in the transaction must be reasonably considered, the recommended value is that the quantity of SQ L contained in each transaction preferably does not exceed 10, and the excessive quantity of transactions containing SQ L should be considered for splitting.
For example, for transfer business of banks, all transfer operations are different in variables such as account number, time, amount and the like, and transaction logics of the transfer operations are the same, but the conditions are not the same, a reasonable code writing mode is that the conditions are written into the conditions of the code in a variable mode, so that the operations of the same thing logic only need to be resolved once, and if the code writing mode is improper, for example, the operations of the same thing logic can be fixedly written into a constant value by using a variable, how many times the operations of the same thing logic result in resolution, the resolving operation consumes a large amount of CPU and memory resources of the database, the influence on the performance of the whole system is influenced by a large number of variables, and if the writing mode is changed frequently, the number of the operations of the same thing logic is determined by using a variable binding mode which is not more than the usual, and the SQ L code is not changed into a specific execution plan which can be executed by using the database (L).
For some considerations, developers may specify certain statements written in the code that must be forced to parse each time they execute, however, such writing is disadvantageous to business systems, and if the forced parsed statements are frequently used on a daily basis, the performance impact on the system cannot be ignored.
The program cache hit rate refers to the hit rate of the SQ L execution plan found in the cache, and the general recommended value is greater than 98%, this index is often closely related to the per-second resolution, and similarly, if the frequently used statements do not use binding variables, the program cache hit rate is also too low except for the too high per-second resolution.
A concurrent wait event refers to a wait that a transaction generates in concurrent execution. Developers often consider that the concurrent execution mode is used for accelerating the operation of the transactions, but the logics of many transactions have precedence, and if the concurrent sub-processing of one transaction must wait for the result of another sub-processing to be executed, a concurrent waiting event is generated at this time. If a transaction generates a large amount of concurrent waiting, the transaction is usually not suitable for executing concurrently, and the execution of concurrent execution may reduce the efficiency of the execution of the transaction. Finding these specific transactions that generate concurrent waits in large quantities, the logic of these transactions indicates that they are not suitable for executing with high concurrency, and the optimized solution is to reduce or cancel the concurrent execution of these transactions.
The buffer pool hit rate refers to the rate at which data blocks to be accessed by a program are hit in memory. The typical recommended value is greater than 98%, and the buffer pool hit rate is too low, which means that the system needs to access the hard disk frequently, thereby generating a large amount of Io overhead and reducing the response time of the whole system. This value is too low, the most likely causes being two: firstly, the storage structure of the service data has no proper index, so that the data blocks to be accessed by the program are excessive, and the hit rate of a buffer pool is low; another reason is related to hardware resources, that is, the memory of the database server system itself is too small, which naturally causes the hit rate during buffering to be too low. Optimization scheme for reason one: optimizing the storage structure of data and setting a proper index; optimization scheme for reason two: and the memory resource of the system is increased.
Recording the read-select ratio, i.e. the ratio of the number of scanned lines to the number of selected lines, usually we want to be as close to 1 as possible, i.e. only the selected lines are scanned, but this is not possible in real data access, and the general recommended value is the ratio of the number of selected lines to the number of scanned lines if it can be kept at 1: above 10, the recording/reading ratio can be considered to be more optimal, otherwise, the data structure should be considered to be optimized to improve the recording/reading ratio. Generally, establishing a suitable index or using a partition table or the like is a common means for increasing the ratio of reading and selecting records.
Page buffer time, which refers to the time value at which a data page/block is buffered in memory. If the cache time is high, the memory does not need to be frequently cleared, that is, the cache hit rate is high, so that actually, the value is the same as the problem reflected by the cache pool hit rate, that is, when the value is lower than the recommended value, or the data storage structure lacks a proper index, at this time, the storage structure of the data needs to be optimized, and a proper index is set; or the memory of the system itself is too small compared to the business program, and at this time, the memory resource of the system needs to be increased.
The average I/O input/output waiting time, which is the index reflecting the deployment quality of the service program, is not more than 10 +/-5 ms, and the value exceeds the recommended value, which generally means that the program is deployed on the storage device with the read-write speed which is not enough to meet the service requirement, namely the read-write speed of the storage device does not meet the service requirement. The storage device with faster read-write speed should be replaced to meet the business needs.
Lock wait percentage, the wait event that one transaction runs (occupying some resources) causing another transaction to be forced to wait for the release of resources before executing, is called the lock wait event, and the duration of this type of event divided by the total execution time of the database is called the lock wait percentage. The recommended value lock wait percentage should be less than 10% ± 5%, and lock wait events are the most common non-idle wait events in the operation of business systems, and are not expected, and too high a lock wait event is a main experience for front-end users that business response time is long and operation is slow. Examples are: in a charging system, the first transaction is to update (update) the amount of money in a certain row of charging records, and the database processes the operation steps of: firstly, a row lock is added to a row related to change in the charging record table, and you can ensure that no other things can perform any other change operation on the row in the transaction process, thereby ensuring the consistency of data. Other transactions are not affected if they do not involve the row record, but if there are other transactions that also attempt to change the row record, they must wait until the first event ends before they can be executed, the total time to wait, i.e., the lock latency. The lock waiting time is too long or the lock waiting percentage is too high, which means that the program execution is not smooth, and the slow and congestion situations often occur, and the solution is generally divided into three solutions: firstly, finding source statements which often cause lock waiting and combining with business logic to see the statements for optimization; secondly, most lock waiting events can be relieved by increasing system resources (CPU and internal memory); thirdly, the mode that the lock waiting event caused by a specific operation at a specific time can be considered to change the execution time point of the lock waiting event can be avoided.
The configuration type waiting event is a non-idle waiting event of various business systems caused by improper setting of some configuration or parameters of a database or a deployment environment, and is collectively called as the configuration type waiting event. Such waiting events can typically be addressed and avoided by modifying the relevant configuration parameters.
And the log cache hit rate refers to the online log cache hit rate of the database. If the value is less than 99%, there is generally a performance impact on the alteration operation of the business process. The optimization scheme is to reasonably increase the log buffer.
The average log write-in time, similar to the log cache hit rate, reflects the write-in performance of the log, and whether the performance of the change operation of the service program is affected. Two optimization schemes are provided, one is to increase a log buffer area; another is to place online log stores on storage devices that have faster read and write performance.
The average non-idle waiting time is shorter, the response time of the service system is better, and the natural performance is better, so any non-idle waiting time generated by the service system at a database end is not expected, the non-idle waiting events generated by other reasons are uniformly expressed in the parameter except for lock, configuration concurrency and log type waiting events, and the recommended value is that if the average non-idle waiting time of the system exceeds 10%, the system still has performance problems on one aspect, and has an optimized space. And finding out specific events generating non-idle waiting time, and determining a specific optimization scheme according to the cause of the events.
In addition, an embodiment of the present invention provides a computer device, where the computer device includes: one or more processors; a memory for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement the method as described above.
In embodiments of the invention, the respective module or system may be a processor formed by computer program instructions, which may be an integrated circuit chip having signal processing capabilities. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component.
The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The processor reads the information in the storage medium and completes the steps of the method in combination with the hardware.
The storage medium may be a memory, for example, which may be volatile memory or nonvolatile memory, or which may include both volatile and nonvolatile memory.
The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory.
By way of example, but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous link DRAM (Synchlink DRAM, S L DRAM), and direct Memory bus RAM (DRTrampbus RAM).
The storage media described in connection with the embodiments of the invention are intended to comprise, without being limited to, these and any other suitable types of memory.
Those skilled in the art will appreciate that the functionality described in the present invention may be implemented in a combination of hardware and software in one or more of the examples described above. When software is applied, the corresponding functionality may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
Although the invention has been described in detail above with reference to a general description and specific examples, it will be apparent to one skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (10)
1. A program performance evaluation method, the method comprising:
setting a plurality of evaluation dimensions and allocating a preset weight ratio to each evaluation dimension;
setting at least one evaluation index for each evaluation dimension aiming at various relational databases;
selecting at least one evaluation index for each evaluation dimension;
acquiring an actual measurement value of each selected evaluation index;
evaluating each selected evaluation index according to the actual measurement value and preset index evaluation information, and acquiring a first evaluation result;
evaluating each evaluation dimension according to the first evaluation result and acquiring a second evaluation result; and
and comprehensively evaluating the program performance according to the second evaluation result and obtaining a final evaluation result.
2. The program performance evaluation method of claim 1, wherein the evaluation index comprises: the evaluation system comprises main evaluation indexes, wherein one main evaluation index is selected for each evaluation dimension, and index evaluation information corresponding to the main evaluation indexes comprises: the evaluation method of the main evaluation index comprises the following steps of:
presetting a first recommendation threshold and a second recommendation threshold as an 80% recommendation threshold and a first 0-point recommendation threshold which reach 80% of full score respectively;
comparing the full score threshold value with the 80% recommended threshold value to obtain a first comparison result;
comparing the actual measurement value with the first 0-point recommended threshold value to obtain a second comparison result; and
and evaluating the main evaluation index by combining the first comparison result and the second comparison result.
3. The program performance evaluation method of claim 2, wherein said evaluating the primary evaluation index in combination with the first comparison result and the second comparison result comprises:
when the full score threshold is smaller than the 80% recommended threshold and the actual measurement value is greater than or equal to the first 0-score recommended threshold, the evaluation score of the main evaluation index is 0;
when the full score threshold is smaller than the 80% recommendation threshold and the actual measurement value is smaller than the first 0-score recommendation threshold, the evaluation score of the main evaluation index is calculated and obtained through the following first algorithm formula:
the evaluation score of the main evaluation index is 100 × [1- (actual measurement value/first 0-point recommended threshold) ] × first weight proportion;
when the full score threshold is greater than the 80% recommended threshold and the actual measurement value is less than or equal to the first 0-score recommended threshold, the evaluation score of the main evaluation index is 0;
when the full score threshold is greater than the 80% recommendation threshold and the actual measurement value is greater than the first 0-score recommendation threshold, the evaluation score of the main evaluation index is calculated by the following second algorithm formula:
the evaluation score of the main evaluation index is 100 × [ (actual measurement value-first 0-point recommended threshold)/(full-point threshold-first 0-point recommended threshold) ] × first weight ratio.
4. The program performance evaluation method of claim 3, wherein evaluating the indicator further comprises: revising evaluation indexes, and selecting all corresponding revising evaluation indexes at a time for each evaluation dimension, wherein the index evaluation information corresponding to the revising evaluation indexes comprises: the second weight proportion, the first recommendation threshold and the second recommendation threshold are set to be negative values, and the method for evaluating the revised evaluation index comprises the following steps:
presetting a first recommendation threshold and a second recommendation threshold as a second 0-point recommendation threshold and a negative-point recommendation extreme value respectively;
comparing the second 0-point recommendation threshold value with the negative-point recommendation extreme value to obtain a third comparison result;
comparing the actual measurement value with the second 0-point recommended threshold value to obtain a fourth comparison result;
comparing the actual measurement value with the negative score recommended extreme value to obtain a fifth comparison result; and
evaluating the revised evaluation index in combination with the third comparison result, the fourth comparison result, and the fifth comparison result.
5. The program performance evaluation method of claim 4, wherein said evaluating the revised evaluation index in combination with the third comparison result, the fourth comparison result, and the fifth comparison result comprises:
when the second 0-point recommendation threshold is smaller than the negative-point recommendation extreme value and the actual measurement value is smaller than or equal to the second 0-point recommendation threshold, the evaluation score of the revised evaluation index is 0;
when the second 0-point recommendation threshold is smaller than the negative-point recommendation extremum and the actual measurement value is greater than or equal to the negative-point recommendation extremum, the evaluation score of the revision evaluation index is a revision weighting full score obtained according to the second weight ratio;
when the second 0-point recommendation threshold is smaller than the negative-point recommendation extremum, and the actual measurement value is greater than the second 0-point recommendation threshold and smaller than the negative-point recommendation extremum, the evaluation score of the revised evaluation index is calculated by a third algorithm formula as follows:
the evaluation score of the revised evaluation index is [ (actual measurement value-second 0-point recommended threshold)/(negative-point recommended extremum-actual measurement value) ] × second weight proportion;
when the second 0-point recommendation threshold is greater than the negative-point recommendation extreme value and the actual measurement value is greater than or equal to the second 0-point recommendation threshold, the evaluation score of the revised evaluation index is 0;
when the second 0-point recommendation threshold is greater than the negative-point recommendation extremum and the actual measurement value is less than or equal to the negative-point recommendation extremum, the evaluation score of the revision evaluation index is a revision weighting full score obtained according to the second weight ratio;
when the second 0-point recommendation threshold is greater than the negative-point recommendation extremum and the actual measurement value is greater than the negative-point recommendation extremum and less than the second 0-point recommendation threshold, the evaluation score of the revised evaluation index is calculated by the following fourth algorithm formula:
the evaluation score of the revised evaluation index is [ (second 0-point recommendation threshold-actual measurement)/(second 0-point recommendation threshold-negative-point recommendation extremum) ] × in the second weight proportion.
6. The program performance evaluation method according to claim 5, wherein the evaluation dimension comprises execution logic, statement resolution, query performance, transaction waiting and environment configuration, the main evaluation index corresponding to the execution logic comprises a login number per second, the revision evaluation index corresponding to the execution logic comprises average required per-transaction SQ L, the main evaluation index corresponding to the statement resolution comprises a resolution amount per second and a program cache hit rate, the revision evaluation index corresponding to the statement resolution comprises a re-resolution amount per second and a concurrent waiting event, the main evaluation index corresponding to the query performance comprises a buffer pool hit rate and a page cache time, the revision evaluation index corresponding to the query performance comprises a record read-select ratio and an I/O input/output average waiting time, the main evaluation index corresponding to the transaction waiting comprises a lock waiting percentage, and the main evaluation index corresponding to the environment configuration comprises a configuration type and an average non-idle waiting time, and the revision evaluation index corresponding to the environment configuration comprises a cache hit rate and an average log write-in time.
7. A program performance evaluation system, the system comprising:
the evaluation dimension setting module is used for setting a plurality of evaluation dimensions and distributing a preset weight ratio to each evaluation dimension;
the evaluation index setting module is used for setting at least one evaluation index for each evaluation dimension aiming at various relational databases and presetting index evaluation information for each evaluation index; selecting at least one evaluation index for each evaluation dimension;
the evaluation index actual measurement module is used for acquiring an actual measurement value of each selected evaluation index;
the selected index evaluation module is used for evaluating each selected evaluation index according to the actual measurement value and preset index evaluation information and acquiring a first evaluation result;
the dimension evaluation module is used for evaluating each evaluation dimension according to the first evaluation result and acquiring a second evaluation result; and
and the comprehensive evaluation module is used for comprehensively evaluating the program performance according to the second evaluation result and acquiring a final evaluation result.
8. The program performance evaluation system of claim 7, wherein the evaluation index comprises: the evaluation index setting module selects one main evaluation index for each evaluation dimension at a time, and the index evaluation information corresponding to the main evaluation index comprises: a first weight proportion, a full score threshold, a first recommendation threshold and a second recommendation threshold that are the same as the corresponding evaluation dimension; the evaluation index setting module is further used for presetting a first recommendation threshold and a second recommendation threshold as an 80% recommendation threshold and a first 0-point recommendation threshold which reach 80% of full score respectively; the selected metric evaluation module includes: the main index evaluation unit is used for comparing the full score threshold value with the 80% recommended threshold value to obtain a first comparison result; comparing the actual measurement value with the first 0-point recommended threshold value to obtain a second comparison result; and evaluating the main evaluation index by combining the first comparison result and the second comparison result.
9. The program performance evaluation system of claim 8, wherein evaluating the metrics further comprises: revising evaluation indexes, wherein the evaluation index setting module selects all corresponding revising evaluation indexes at a time for each evaluation dimension, and the index evaluation information corresponding to the revising evaluation indexes comprises: a second weight fraction set to a negative value, the first recommendation threshold, and the second recommendation threshold; the evaluation index setting module is further used for presetting a first recommendation threshold and a second recommendation threshold as a second 0-point recommendation threshold and a negative-point recommendation extreme value respectively; the selected metric evaluation module further comprises: the revision index evaluation unit is used for comparing the second 0-point recommendation threshold value with the negative-point recommendation extreme value to obtain a third comparison result; comparing the actual measurement value with the second 0-point recommended threshold value to obtain a fourth comparison result; comparing the actual measurement value with the negative score recommended extreme value to obtain a fifth comparison result; and evaluating the revision evaluation index in combination with the third comparison result, the fourth comparison result and the fifth comparison result.
10. A computer device, the device comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
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