CN116701152A - Database performance determining method, device, equipment and medium - Google Patents

Database performance determining method, device, equipment and medium Download PDF

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Publication number
CN116701152A
CN116701152A CN202310842401.0A CN202310842401A CN116701152A CN 116701152 A CN116701152 A CN 116701152A CN 202310842401 A CN202310842401 A CN 202310842401A CN 116701152 A CN116701152 A CN 116701152A
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database
test result
test
source database
target database
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张晓娜
暨光耀
傅媛媛
黄琼
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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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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The disclosure provides a database performance determining method, device, equipment and medium, which can be applied to the technical fields of big data and finance. The method comprises the following steps: configuring a source database and a target database with the same data source so that the types of the source database and the target database are different, and the structures of database tables of the source database and the target database are the same; based on a first structured query language running in a source database, carrying out concurrent pressure test on the source database and a target database to obtain a first test result, wherein the first test result is used for representing performance change of the first structured query language after the source database is migrated to the target database; based on the transaction operation, concurrent pressure testing is carried out on the source database and the target database to obtain a second test result, wherein the second test result is used for representing performance change of the transaction operation after the source database is migrated to the target database; and determining the performance of the target database based on the first test result and the second test result.

Description

Database performance determining method, device, equipment and medium
Technical Field
The present disclosure relates to the field of big data and financial technologies, and in particular, to a database performance determining method, apparatus, device, and medium.
Background
For application systems that use databases in large numbers for data storage and processing, the performance status of the databases is critical, and if there is a problem with database performance, the service system cannot operate normally or even is interrupted. The performance of the database is dynamically changed along with the increase of data volume, expansion of service system, and change of equipment, network and other software and hardware environments, so that the performance of the database needs to be continuously monitored, and the database needs to be timely processed once faults occur.
In the process of implementing the present disclosure, it is found that the database in the prior art has a problem of unstable performance before and after migration.
Disclosure of Invention
In view of the foregoing, the present disclosure provides a database performance determination method, apparatus, device, medium, and program product.
According to a first aspect of the present disclosure, there is provided a database performance determining method, including:
configuring a source database and a target database with the same data source so that the types of the source database and the target database are different, and the structures of database tables of the source database and the target database are the same;
based on a first structured query language running in a source database, carrying out concurrent pressure test on the source database and a target database to obtain a first test result, wherein the first test result is used for representing performance change of the first structured query language after the source database is migrated to the target database;
Based on the transaction operation, carrying out concurrent pressure test on the source database and the target database to obtain a second test result, wherein the second test result is used for representing performance change of the transaction operation after the source database is migrated to the target database;
and determining the performance of the target database based on the first test result and the second test result.
According to embodiments of the present disclosure, the transaction operations include a plurality of single business transaction operations and/or a plurality of bulk business transaction operations;
based on transaction operation, concurrent pressure testing is carried out on the source database and the target database to obtain a second test result, wherein the method comprises the following steps:
grouping the single business transaction operations and/or the batch business transaction operations according to the database table accessed by the transaction operations to obtain grouping results;
and carrying out concurrent pressure test on the source database and the target database according to the grouping result to obtain a second test result.
According to an embodiment of the present disclosure, the grouping result includes a first grouping result and a second grouping result;
the method for grouping the single business transaction operation and/or the batch business transaction operation according to the database table accessed by the transaction operation to obtain a grouping result comprises the following steps:
Under the condition that database tables accessed by single business transaction operations and/or batch business transaction operations are the same, dividing the single business transaction operations and/or the batch business transaction operations into a group to obtain a first grouping result;
and under the condition that the database tables accessed by the single business transaction operation and/or the batch business transaction operation are different, dividing the single business transaction operation and/or the batch business transaction operation into a group of preset business and/or preset batch operation, and obtaining a second grouping result.
According to an embodiment of the present disclosure, according to the grouping result, concurrent pressure testing is performed on the source database and the target database to obtain a second test result, including:
according to the first grouping result, concurrent pressure testing is conducted on the source database and the target database, and a first testing duration and a second testing duration are obtained;
determining a first sub-test result based on the first test duration and the second test duration;
according to the second grouping result, concurrent pressure testing is carried out on the source database and the target database, and a third testing duration and a fourth testing duration are obtained;
determining a second sub-test result based on the third test duration and the fourth test duration;
a second test result is determined based on the first sub-test result and the second sub-test result.
According to an embodiment of the present disclosure, a concurrent stress test is performed on a source database and a target database based on a first structured query language running in the source database, to obtain a first test result, including:
converting the first structured query language into a second structured query language that matches the target database;
respectively executing a first structured query language in a source database and a second structured query language in a target database to respectively obtain a first execution duration and a second execution duration;
and determining a first test result based on the first execution duration and the second execution duration.
According to an embodiment of the present disclosure, determining a first test result based on a first execution duration and a second execution duration includes:
under the condition that the first execution time length is longer than the second execution time length, determining that the performance of the first test result for the first structured query language is not deteriorated after the first test result is used for representing that the source database is migrated to the target database;
under the condition that the first execution duration is equal to the second execution duration, determining that the performance of the first test result for the first structured query language is unchanged after the first test result is used for representing that the source database is migrated to the target database;
And under the condition that the first execution duration is smaller than the second execution duration, determining that the first test result is used for representing performance degradation of the first structured query language after the source database is migrated to the target database.
According to an embodiment of the present disclosure, the database performance determining method further includes:
generating a first problem list based on the first structured query language under the condition that the performance of the first structured query language is poor after determining that the first test result is used for representing the migration of the source database to the target database;
generating a second problem list based on the single business transaction operation and/or the batch business transaction operation under the condition that the performance of the single business transaction operation and/or the batch business transaction operation is poor after the second test result is used for representing that the source database is migrated to the target database;
and generating a performance report according to the first problem list and the second problem list so as to optimize the performance of the target database.
A second aspect of the present disclosure provides a database performance determining apparatus, comprising:
the configuration module is used for configuring a source database and a target database which have the same data source, wherein the types of the source database and the target database are different, and the structures of database tables of the source database and the target database are the same;
The first test module is used for carrying out concurrent pressure test on the source database and the target database based on a first structured query language running in the source database to obtain a first test result, wherein the first test result is used for representing the performance change of the source database in the first structured query language after the source database is migrated to the target database;
the second test module is used for carrying out concurrent pressure test on the source database and the target database based on preset business and/or preset batch transaction operation to obtain a second test result, wherein the second test result is used for representing the performance change of the source database for the preset business and/or preset batch transaction operation after the source database is migrated to the target database; and
and the determining module is used for determining the performance of the target database based on the first test result and the second test result.
A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the database performance determination method described above.
A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the database performance determination method described above.
A fifth aspect of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the database performance determination method described above.
According to the embodiment of the disclosure, the structural query language performance before and after migration is subjected to comparison test, and the high concurrency pressure test is performed through transaction operation, so that the database performance can be compared in a whole way in the process of migrating from the source database to the target database, problems are found in advance, the problems are solved, the performance stability of the database after migration is ensured, and the problem that the performance is unstable before and after the database migration in the prior art is solved.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be more apparent from the following description of embodiments of the disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an application scenario diagram of a database performance determination method, apparatus, device, medium and program product according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a database performance determination method according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates a flow chart of a method for concurrent stress testing of a source database and a target database based on a transaction operation to obtain a second test result, in accordance with an embodiment of the present disclosure;
FIG. 4 schematically illustrates a method flow diagram for concurrent stress testing of a source database and a target database based on a first structured query language running in the source database, resulting in a first test result, in accordance with an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flowchart of a database performance determination method according to another embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of a database performance determining apparatus according to an embodiment of the present disclosure; and
fig. 7 schematically illustrates a block diagram of an electronic device adapted to implement a database performance determination method according to an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
In the technical scheme of the disclosure, the related data (such as including but not limited to personal information of a user) are collected, stored, used, processed, transmitted, provided, disclosed, applied and the like, all conform to the regulations of related laws and regulations, necessary security measures are adopted, and the public welcome is not violated.
In the technical scheme of the embodiment of the disclosure, the authorization or consent of the user is obtained before the personal information of the user is obtained or acquired.
In the process of implementing the present disclosure, it is found that the database in the prior art has a problem of unstable performance before and after migration. For example, the GaussDB database, due to its own cloud ecosystem, can better adapt to new usage scenarios required by the internet for the database, and migration from the Oracle database to the GaussDB database is more and more, but in the process of migration from the Oracle database to the GaussDB database, the same structured query language SQL may match indexes in the Oracle database due to the fact that the index matching mechanism of the GaussDB database is different from that of the Oracle database, but the problems such as the fact that the GaussDB database cannot match may occur.
The embodiment of the disclosure provides a database performance determining method, which comprises the following steps: configuring a source database and a target database with the same data source so that the types of the source database and the target database are different, and the structures of database tables of the source database and the target database are the same; based on a first structured query language running in a source database, carrying out concurrent pressure test on the source database and a target database to obtain a first test result, wherein the first test result is used for representing performance change of the first structured query language after the source database is migrated to the target database; based on the transaction operation, carrying out concurrent pressure test on the source database and the target database to obtain a second test result, wherein the second test result is used for representing performance change of the transaction operation after the source database is migrated to the target database; and determining the performance of the target database based on the first test result and the second test result.
Fig. 1 schematically illustrates an application scenario diagram of a database performance determination method, apparatus, device, medium and program product according to an embodiment of the present disclosure.
As shown in fig. 1, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is a medium used to provide a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 through the network 104 using at least one of the first terminal device 101, the second terminal device 102, the third terminal device 103, to receive or send messages, etc. Various communication client applications, such as a shopping class application, a web browser application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc. (by way of example only) may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103.
The first terminal device 101, the second terminal device 102, the third terminal device 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by the user using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the database performance determining method provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the database performance determining apparatus provided by the embodiments of the present disclosure may be generally provided in the server 105. The database performance determination method provided by the embodiments of the present disclosure may also be performed by a server or a server cluster that is different from the server 105 and is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and/or the server 105. Accordingly, the database performance determining apparatus provided by the embodiments of the present disclosure may also be provided in a server or a server cluster that is different from the server 105 and is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and/or the server 105.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The database performance determining method of the disclosed embodiment will be described in detail below with reference to fig. 2 to 5 based on the scenario described in fig. 1.
Fig. 2 schematically illustrates a flowchart of a database performance determination method according to an embodiment of the present disclosure.
As shown in fig. 2, the database performance determining method 200 of this embodiment includes operations S210 to S240.
In operation S210, the source database and the target database, which are the same in data source, are configured such that the types of the source database and the target database are different, and the structures of database tables of the source database and the target database are the same.
According to an embodiment of the present disclosure, the source database may be an Oracle database. The target database may be a GaussDB database.
For example, the data sources imported into the Oracle database and the GaussDB database are kept consistent, and data can be exported from the production environment in the development stage and subjected to certain desensitization processing. And then importing the data subjected to desensitization processing into an Oracle database of a test environment in a development stage, and migrating the data to a GaussDB database through a Dynamic Resource Scheduling (DRS) tool carried by the GaussDB database, wherein the consistency of the data can be ensured through DRS migration, so that the method is relatively simple and quick.
According to embodiments of the present disclosure, the configurations of the source database and the target database are identical in order to verify different support capabilities between the two databases in the same configuration environment in order to evaluate how many target databases are needed to replace the source database.
In operation S220, concurrent stress testing is performed on the source database and the target database based on the first structured query language running in the source database, to obtain a first test result, where the first test result is used to characterize a performance change of the source database with respect to the first structured query language after migrating to the target database.
According to the embodiment of the disclosure, a first structured query language can be run in a source database, and a structured query language matched with the first structured query language is run in a target database, so that a running result is obtained. And determining a first test result according to the operation result.
In operation S230, based on the transaction operation, concurrent pressure testing is performed on the source database and the target database, so as to obtain a second test result, where the second test result is used to characterize performance change of the source database for the transaction operation after migrating to the target database.
According to embodiments of the present disclosure, the transaction operations may include a plurality of single business transaction operations and/or a plurality of bulk business transaction operations. The pressure test can be performed on the source database and the target database based on a plurality of single business transaction operations and/or a plurality of batch business transaction operations, respectively, so as to obtain a second test result.
In operation S240, the performance of the target database is determined based on the first test result and the second test result.
According to the embodiment of the disclosure, the performance stability of the target database can be determined under the condition that the performance of the first structured query language is unchanged after the first test result is used for representing the migration of the source database to the target database and the performance of the second test result is unchanged after the migration of the source database to the target database for transaction operation.
According to the embodiment of the disclosure, the performance of the target database with respect to the first structured query language can be determined to be unstable when the first test result is used for representing the performance of the source database with respect to the transaction operation after being migrated to the target database and the performance of the target database with respect to the first structured query language is determined to be stable when the second test result is used for representing the performance of the source database with respect to the transaction operation after being migrated to the target database.
According to the embodiment of the disclosure, the structural query language performance before and after migration is subjected to comparison test, and the high concurrency pressure test is performed through transaction operation, so that the database performance can be compared in a full aspect in the process of migrating from the source database to the target database, problems are found in advance, the problems are solved, the performance stability of the database after migration is ensured, and the problem of unstable performance before and after the database migration in the prior art is solved.
FIG. 3 schematically illustrates a flow chart of a method for concurrent stress testing of a source database and a target database based on a transaction operation to obtain a second test result, in accordance with an embodiment of the present disclosure.
As shown in fig. 3, the method 330 of performing concurrent pressure testing on the source database and the target database based on the transaction operation to obtain the second test result in this embodiment includes operations S331 to S332.
It should be noted that the transaction operations may include a plurality of single business transaction operations and/or a plurality of bulk business transaction operations. The single-service transaction operation may refer to a transaction operation with a larger call volume in a production environment, for example, transactions with transaction call volumes ranked at top 20, 50 and the like may be selected for high concurrency pressure test according to application characteristics. The batch business transaction operation can refer to batch business transaction operation with more database processing times, for example, batch press measurement can be initiated by selecting batch business transaction operation with the database processing times of 20, 50 and the like according to application characteristics.
In operation S331, the single business transaction operations and/or the batch business transaction operations are grouped according to the database table accessed by the transaction operations, and a grouping result is obtained.
According to the embodiment of the disclosure, single-service transaction operations and/or batch-service transaction operations with the same database table accessed by the transaction operations can be grouped, and different single-service transaction operations and/or batch-service transaction operations with different database tables accessed by the transaction operations can be grouped.
In operation S332, a concurrent pressure test is performed on the source database and the target database according to the grouping result, so as to obtain a second test result.
According to the embodiment of the disclosure, the pressure test can be initiated simultaneously on a plurality of single business transaction operations and/or a plurality of batch business transaction operations which are the same in the accessed database table by the source database and the target database, and the pressure test can be initiated on a plurality of single business transaction operations and/or a plurality of batch business transaction operations which are different in the accessed database table, so that the second test result is obtained.
For example, a pressure test may be initiated on the transaction operation by using a pressure-generating tool such as LoadRunner or Jmeter, and the second test result is automatically collected and stored in a test result database table trans_perf, where the database table fields may be:
unique index |Oracle database IP|GaussDB database IP|contrast status (0-un-contrast ) |packet results|transaction 1|transaction 2| … … |batch transaction 1|batch transaction 2| … … |batch transaction 2| … … |batch transaction 1 using Oracle database|batch transaction 2| … … |batch transaction 1 using Oracle database|batch transaction 2| … … |batch transaction 1 using GaussDB database|batch transaction 2| … … |batch transaction 1|batch transaction 2| … … |GaussDB poor batch transaction name and GaussDB poor batch transaction performance.
After the pressure test is executed, the collected transaction time consumption of executing the transaction in the Oracle database and the batch transaction time consumption can be registered into fields such as the transaction time consumption, the batch time consumption and the like of using the Oracle database; registering the collected transaction time consumption of the batch transaction executed in the GaussDB database into fields of transaction time consumption, batch time consumption and the like using the GaussDB database. The contrast status may be set from 0-un-contrast to 1-compared.
The time consumption of the transaction or batch transaction of initiating the pressure test on the Oracle and GaussDB simultaneously can be compared in pairs, and if the time consumption of the same transaction or batch transaction on the Oracle database is smaller than the time consumption on the GaussDB database, the transaction name or batch transaction name is registered into a field of 'the transaction name with poor GaussDB performance and the batch transaction list with poor GaussDB performance'.
According to the embodiment of the disclosure, the high concurrency pressure test is performed through the combination strategy of a plurality of single business transaction operations and/or a plurality of batch business transaction operations, so that the database performance can be compared in a full aspect in the process of migrating from the source database to the target database, and the problem can be found in advance, so that the problem can be solved, and the performance stability of the database for the business transaction operations after migrating is ensured.
According to an embodiment of the present disclosure, the grouping result may include a first grouping result and a second grouping result.
The grouping of the single business transaction operations and/or the batch business transaction operations according to the database table accessed by the transaction operations to obtain grouping results may include: under the condition that database tables accessed by single business transaction operations and/or batch business transaction operations are the same, dividing the single business transaction operations and/or the batch business transaction operations into a group to obtain a first grouping result; and under the condition that the database tables accessed by the single business transaction operation and/or the batch business transaction operation are different, dividing the single business transaction operation and/or the batch business transaction operation into a group of preset business and/or preset batch operation, and obtaining a second grouping result.
According to the embodiment of the disclosure, the single business transaction operation and/or the batch business transaction operation are grouped according to the database table accessed by the transaction operation, so that the combination strategy is determined, the database performance can be compared in a full-scale manner, the problem can be found in advance, and the problem can be solved.
According to an embodiment of the present disclosure, performing concurrent pressure testing on a source database and a target database according to a grouping result to obtain a second test result may include:
According to the first grouping result, concurrent pressure testing is conducted on the source database and the target database, and a first testing duration and a second testing duration are obtained; determining a first sub-test result based on the first test duration and the second test duration; according to the second grouping result, concurrent pressure testing is carried out on the source database and the target database, and a third testing duration and a fourth testing duration are obtained; determining a second sub-test result based on the third test duration and the fourth test duration; a second test result is determined based on the first sub-test result and the second sub-test result.
According to an embodiment of the disclosure, in the case that the first test time length is determined to be longer than the second test time length, the first sub-test result is determined to be used for representing that performance of the source database for the first grouping result is not degraded after the source database is migrated to the target database. And under the condition that the first test duration is equal to the second test duration, determining that the first sub-test result is used for representing that the performance of the source database for the first grouping result is unchanged after the source database is migrated to the target database. And under the condition that the first test duration is smaller than the second test duration, determining that the first sub-test result is used for representing performance degradation of the first grouping result after the source database is migrated to the target database.
According to an embodiment of the disclosure, in the case that the third test time length is determined to be longer than the fourth test time length, the second sub-test result is determined to be used for representing that performance of the source database for the second packet result is not degraded after the migration to the target database. And under the condition that the third test duration is equal to the fourth test duration, determining that the second sub-test result is used for representing that the performance of the second grouping result is unchanged after the source database is migrated to the target database. And under the condition that the third test duration is smaller than the fourth test duration, determining that the second sub-test result is used for representing performance degradation of the second grouping result after the source database is migrated to the target database.
According to an embodiment of the disclosure, in a case where the first sub-test result is determined to be used to characterize the source database for migration to the target database and the performance for the first sub-test result is determined to be unchanged after the source database is migrated to the target database, and in a case where the second sub-test result is determined to be used to characterize the source database for migration to the target database and the performance for the second sub-test result is determined to be unchanged after the source database is migrated to the target database.
According to the embodiment of the disclosure, the test time length is used for determining the test result, so that the problem can be found in advance, the problem can be solved, and the performance stability of the database for transaction operation after migration can be ensured.
FIG. 4 schematically illustrates a flow chart of a method of concurrent stress testing a source database and a target database based on a first structured query language running in the source database, resulting in a first test result, according to an embodiment of the disclosure.
As shown in fig. 4, the method 420 of performing concurrent stress test on the source database and the target database based on the first structured query language running in the source database to obtain the first test result in this embodiment includes operations S421 to S423.
In operation S421, the first structured query language is converted into a second structured query language that matches the target database.
According to embodiments of the present disclosure, a first structured query language may be converted into a second structured query language that matches a target database according to structured query language statement grammar rules of the source database and the target database.
For example, the SQL statement of Oracle may be converted into a GaussDB database SQL statement based on the difference in syntax rules of the Oracle database and the GaussDB database SQL statement.
The SQL statement of Oracle and the SQL statement of the transformed GaussDB database may be saved to the database SQL_OR_GS table, which may be represented as:
unique index |Oracle database IP|Oracle SQL statement|GaussDB database IP|GaussDB SQL statement|contrast status (0-un-contrast ) |Oracle database SQL time consuming|GaussDB SQL time consuming|performance is degraded (0-NO, 1-yes, 2-same)
The converted SQL can be stored in an SQL_OR_GS table, and the comparison state is set to be 0-un-compared, and three fields, such as the SQL time consumption of the Oracle database, the SQL time consumption of the GaussDB database, whether the performance is poor OR not, are all empty.
In operation S422, a first structured query language is executed in the source database and a second structured query language is executed in the target database, respectively, to obtain a first execution duration and a second execution duration, respectively.
According to embodiments of the present disclosure, for example, one record in the SQL_OR_GS table may be read, and pressure tests of the same number of concurrent users may be simultaneously initiated by a Jmeter tool, executing Oracle SQL statements in an Oracle database, and GaussDB SQL statements in a GaussDB database, respectively. After the high concurrency pressure test of SQL is finished, the time consumption of the SQL of the Oracle database is automatically collected, the time consumption of the SQL of the GaussDB database is automatically collected, and the content of each field in the table is automatically updated. The collected Oracle database SQL time consuming is updated to the corresponding Oracle database SQL time consuming in the table, and the GaussDB database SQL statement time consuming is updated to the corresponding GaussDB database SQL statement time consuming field in the table. The contrast status may be set from 0-un-contrast to 1-compared.
In operation S423, a first test result is determined based on the first execution duration and the second execution duration.
According to the embodiment of the disclosure, the first test result can be obtained by calculating based on the first execution duration and the second execution duration.
For example, if Oracle database SQL takes more time than GaussDB database SQL, then update the performance degradation field state to: 0-no; if the Oracle database SQL time is less than the GaussDB database SQL time, updating the performance degradation field state to: 1-yes; if the Oracle database SQL time consuming is equal to the GaussDB database SQL time consuming, updating the performance degradation field state to: 2-the same.
The comparison state field value in the SQL_OR_GS table can be judged to be 0-number of data pieces which are not compared, and if the number of the data pieces which are not compared is 0, the comparison is completed; if the number of data bars which are not compared and are 0 is greater than 0, the comparison is continued.
According to the embodiment of the disclosure, by comparing SQL performances of the structured query language, comparison pressure measurement is respectively carried out on the source database and the target database, and performance performances of the same SQL in different types of databases are verified, so that problems can be found in advance, and the problems can be solved.
According to an embodiment of the present disclosure, determining a first test result based on a first execution duration and a second execution duration may include:
under the condition that the first execution time length is longer than the second execution time length, determining that the performance of the first test result for the first structured query language is not deteriorated after the first test result is used for representing that the source database is migrated to the target database; under the condition that the first execution duration is equal to the second execution duration, determining that the performance of the first test result for the first structured query language is unchanged after the first test result is used for representing that the source database is migrated to the target database; and under the condition that the first execution duration is smaller than the second execution duration, determining that the first test result is used for representing performance degradation of the first structured query language after the source database is migrated to the target database.
According to the embodiment of the disclosure, the test result is determined by the execution time of the structured query language, so that the problem can be found in advance, the problem can be solved, and the performance stability of the database for the structured query language after migration can be ensured.
Fig. 5 schematically illustrates a flowchart of a database performance determination method according to another embodiment of the present disclosure.
As shown in fig. 5, the database performance determining method 500 of this embodiment includes operations S510 to S530.
In operation S510, in a case where it is determined that the performance of the first structured query language is degraded after the first test result is used to characterize the migration of the source database to the target database, a first problem manifest is generated based on the first structured query language.
According to an embodiment of the present disclosure, the first question list may be a question structured query language list. For example, a SQL list with a field value of 1-YES can be derived from the SQL_OR_GS table to form a problem SQL list.
In operation S520, in a case where it is determined that the second test result is used to characterize performance degradation of the source database with respect to the single-service transaction operation and/or the bulk-service transaction operation after the migration to the target database, a second problem manifest is generated based on the single-service transaction operation and/or the bulk-service transaction operation.
According to an embodiment of the present disclosure, the second issue list may be an issue single business transaction operation and/or an issue bulk business transaction operation. For example, transaction names with degraded GaussDB database performance and batch transaction lists with degraded GaussDB database performance may be derived from the trans_perf table to form a problem single service transaction operation and/or a problem batch service transaction operation.
In operation S530, a performance report is generated based on the first problem list and the second problem list to optimize performance of the target database.
According to the embodiment of the disclosure, the performance report can be sent to the project group in the development stage through mail, so that the project group can be convenient to optimize the performance of the target database.
According to the embodiment of the disclosure, the performance report is generated through the generated first problem list and the generated second problem list, so that the performance of the target database is convenient for related personnel to optimize.
Based on the database performance determining method, the disclosure also provides a database performance determining device. The device will be described in detail below in connection with fig. 6.
Fig. 6 schematically shows a block diagram of a database performance determining apparatus according to an embodiment of the present disclosure.
As shown in fig. 6, the database performance determining apparatus 600 of this embodiment includes a configuration module 610, a first test module 620, a second test module 630, and a determining module 640.
The configuration module 610 is configured to configure a source database and a target database that have the same data source, where the source database and the target database have the same structure, so that the source database and the target database have different types. In an embodiment, the configuration module 610 may be configured to perform the operation S210 described above, which is not described herein.
The first test module 620 is configured to perform concurrent stress testing on the source database and the target database based on a first structured query language running in the source database, to obtain a first test result, where the first test result is used to characterize a performance change of the source database with respect to the first structured query language after migrating to the target database. In an embodiment, the first test module 620 may be used to perform the operation S220 described above, which is not described herein.
The second test module 630 is configured to perform concurrent pressure test on the source database and the target database based on a preset service and/or a preset batch transaction operation, so as to obtain a second test result, where the second test result is used to characterize a performance change of the source database with respect to the preset service and/or the preset batch transaction operation after the source database is migrated to the target database. In an embodiment, the second test module 630 may be used to perform the operation S230 described above, which is not described herein.
The determining module 640 is configured to determine performance of the target database based on the first test result and the second test result. In an embodiment, the determining module 640 may be configured to perform the operation S240 described above, which is not described herein.
According to an embodiment of the present disclosure, the database performance determining apparatus 600 includes a first generation module, a second generation module, and a third generation module.
The first generation module is used for generating a first problem list based on the first structured query language under the condition that the performance of the first structured query language is poor after the first test result is used for representing that the source database is migrated to the target database. In an embodiment, the first generating module may be configured to perform the operation S510 described above, which is not described herein.
The second generating module is used for generating a second problem list based on the single business transaction operation and/or the batch business transaction operation under the condition that the performance of the single business transaction operation and/or the batch business transaction operation is poor after the second test result is used for representing that the source database is migrated to the target database. In an embodiment, the second generating module may be configured to perform the operation S520 described above, which is not described herein.
The third generation module is used for generating a performance report according to the first problem list and the second problem list so as to optimize the performance of the target database. In an embodiment, the third generating module may be configured to perform the operation S530 described above, which is not described herein.
Any of the configuration module 610, the first test module 620, the second test module 630, and the determination module 640 may be combined in one module to be implemented, or any of the modules may be split into a plurality of modules, according to embodiments of the present disclosure. Alternatively, at least some of the functionality of one or more of the modules may be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the configuration module 610, the first test module 620, the second test module 630, and the determination module 640 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging the circuitry, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, at least one of the configuration module 610, the first test module 620, the second test module 630, and the determination module 640 may be at least partially implemented as a computer program module, which when executed, may perform the corresponding functions.
Fig. 7 schematically illustrates a block diagram of an electronic device adapted to implement a database performance determination method according to an embodiment of the disclosure.
As shown in fig. 7, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. The processor 701 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 701 may also include on-board memory for caching purposes. The processor 701 may comprise a single processing unit or a plurality of processing units for performing different actions of the method flows according to embodiments of the disclosure.
In the RAM 703, various programs and data necessary for the operation of the electronic apparatus 700 are stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. The processor 701 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 702 and/or the RAM 703. Note that the program may be stored in one or more memories other than the ROM 702 and the RAM 703. The processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.
According to an embodiment of the present disclosure, the electronic device 700 may further include an input/output (I/O) interface 705, the input/output (I/O) interface 705 also being connected to the bus 704. The electronic device 700 may also include one or more of the following components connected to the I/O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output portion 707 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 708 including a hard disk or the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. The drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read therefrom is mounted into the storage section 708 as necessary.
The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 702 and/or RAM 703 and/or one or more memories other than ROM 702 and RAM 703 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowcharts. The program code, when executed in a computer system, causes the computer system to perform the methods provided by embodiments of the present disclosure.
The above-described functions defined in the system/apparatus of the embodiments of the present disclosure are performed when the computer program is executed by the processor 701. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed over a network medium in the form of signals, downloaded and installed via the communication section 709, and/or installed from the removable medium 711. The computer program may include program code that may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 709, and/or installed from the removable medium 711. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 701. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be provided in a variety of combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.

Claims (11)

1. A database performance determination method, comprising:
configuring a source database and a target database with the same data source so that the types of the source database and the target database are different, wherein the structures of database tables of the source database and the target database are the same;
Based on a first structured query language running in the source database, carrying out concurrent pressure test on the source database and the target database to obtain a first test result, wherein the first test result is used for representing performance change of the source database to the target database for the first structured query language after the source database is migrated to the target database;
based on transaction operation, carrying out concurrent pressure test on the source database and the target database to obtain a second test result, wherein the second test result is used for representing performance change of the transaction operation after the source database is migrated to the target database;
and determining the performance of the target database based on the first test result and the second test result.
2. The method of claim 1, wherein the transaction operations comprise a plurality of single business transaction operations and/or a plurality of bulk business transaction operations;
the concurrent pressure test is performed on the source database and the target database based on the transaction operation, so as to obtain a second test result, which comprises the following steps:
grouping the single business transaction operations and/or the batch business transaction operations according to the database table accessed by the transaction operations to obtain grouping results;
And carrying out concurrent pressure test on the source database and the target database according to the grouping result to obtain a second test result.
3. The method of claim 2, wherein the grouping result comprises a first grouping result and a second grouping result;
wherein the grouping the single business transaction operations and/or the batch business transaction operations according to the database table accessed by the transaction operations to obtain a grouping result includes:
dividing the single business transaction operation and/or the batch business transaction operation into a group under the condition that the database tables accessed by the single business transaction operation and/or the batch business transaction operation are the same, and obtaining the first grouping result;
and under the condition that the database tables accessed by the single business transaction operation and/or the batch business transaction operation are different, dividing the preset business and/or the preset batch operation of the single business transaction operation and/or the batch business transaction operation into a group to obtain the second grouping result.
4. A method according to claim 3, wherein said performing concurrent pressure testing on said source database and said target database according to said grouping result, to obtain a second test result, comprises:
Carrying out concurrent pressure test on the source database and the target database according to the first grouping result to obtain a first test duration and a second test duration;
determining a first sub-test result based on the first test duration and the second test duration;
carrying out concurrent pressure test on the source database and the target database according to the second grouping result to obtain a third test duration and a fourth test duration;
determining a second sub-test result based on the third test duration and the fourth test duration;
and determining the second test result based on the first sub-test result and the second sub-test result.
5. The method of claim 1, wherein the concurrent stress testing of the source database and the target database based on a first structured query language running in the source database results in a first test result, comprising:
converting the first structured query language into a second structured query language that matches the target database;
executing the first structured query language in the source database and the second structured query language in the target database respectively to obtain a first execution duration and a second execution duration;
And determining the first test result based on the first execution duration and the second execution duration.
6. The method of claim 5, wherein the determining the first test result based on the first execution duration and the second execution duration comprises:
under the condition that the first execution time length is longer than the second execution time length, determining that the first test result is used for representing that the performance of the source database for the first structured query language is not deteriorated after the source database is migrated to the target database;
determining that the first test result is used for representing that the performance of the source database for the first structured query language is unchanged after the source database is migrated to the target database under the condition that the first execution duration is equal to the second execution duration;
and under the condition that the first execution duration is smaller than the second execution duration, determining that the first test result is used for representing performance degradation of the source database for the first structured query language after the source database is migrated to the target database.
7. The method of any one of claims 1-6, further comprising:
generating a first problem list based on the first structured query language under the condition that the performance of the first structured query language is poor after the first test result is used for representing that the source database is migrated to the target database;
Generating a second problem list based on the single business transaction operation and/or the batch business transaction operation under the condition that the performance of the single business transaction operation and/or the batch business transaction operation is poor after the second test result is used for representing that the source database is migrated to the target database;
generating a performance report according to the first problem list and the second problem list so as to optimize the performance of the target database.
8. A database performance determining apparatus comprising:
the configuration module is used for configuring a source database and a target database which are the same in data source, wherein the source database and the target database are different in type, and the structures of database tables of the source database and the target database are the same;
the first test module is used for carrying out concurrent pressure test on the source database and the target database based on a first structured query language running in the source database to obtain a first test result, wherein the first test result is used for representing the performance change of the source database in the first structured query language after the source database is migrated to the target database;
The second test module is used for carrying out concurrent pressure test on the source database and the target database based on preset business and/or preset batch transaction operation to obtain a second test result, wherein the second test result is used for representing the performance change of the source database for the preset business and/or preset batch transaction operation after the source database is migrated to the target database; and
and the determining module is used for determining the performance of the target database based on the first test result and the second test result.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any of claims 1-7.
11. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.
CN202310842401.0A 2023-07-10 2023-07-10 Database performance determining method, device, equipment and medium Pending CN116701152A (en)

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