CN110727467A - System and method for realizing server performance optimization processing under big data environment - Google Patents
System and method for realizing server performance optimization processing under big data environment Download PDFInfo
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Abstract
The invention relates to a system for realizing performance optimization processing of a server in a big data environment, which comprises an environment deployment module, a configuration auxiliary product module and a configuration management module, wherein the environment deployment module is used for selecting the configuration auxiliary product meeting the requirements according to a project; the data initialization module is used for setting parameters according to the actual conditions of enterprises; the file and parameter analysis module is used for carrying out resource allocation and parameter adjustment in the running process of the server; the service optimization module is used for properly adjusting the related parameters; and the product starting module is used for checking the running condition of the product after the service is optimized. The invention also relates to a method for realizing the performance optimization processing of the server in the big data environment. By adopting the system and the method for realizing the performance optimization processing of the server in the big data environment, the configuration file parameters needing to be loaded in the starting operation of the optimization server are adjusted, so that the starting efficiency and the operating efficiency of the server are improved compared with the original efficiency, and the system performance, the user experience degree, the efficiency and the data value are improved.
Description
Technical Field
The invention relates to the field of big data, in particular to the field of server performance management, and specifically relates to a system and a method for realizing server performance optimization processing in a big data environment.
Background
Data is a very important resource in the current society, the use of the data reflects the information development level of a region or even a country to a certain extent, and the higher the use efficiency of the data is, the higher the information development level is. To realize efficient use of data, the performance of the server should be adjusted and optimized first, so that the data system can be operated stably and efficiently on the server.
The performance optimization of the server is an important part for application and large data use, is an important link for using data, and directly influences the running state of a data system according to the state of the performance of the server. The performance tuning is an important part of using the server, and the performance of the server has a certain influence on the state and efficiency of a system running on the server, so that the use efficiency of data and the user experience are influenced.
At present, performance optimization of an application server in a big data environment is adjusted progressively according to characteristics and configuration parameters of the server and an actual architecture of a deployment project, and then the server is started and the project is loaded, and the specific implementation steps are as follows:
1. selecting a server type according to the project condition;
2. analyzing the parameter function according to the server characteristics;
3. configuring relevant parameters according to project requirements;
4. initializing an environment, starting a service and loading a project;
5. and checking whether the starting environment operates normally or not, and testing the normal function of the system.
According to the steps, performance optimization of the application server is carried out in a big data environment, in the performance optimization process, relevant parameters are configured according to system requirements, the server and the application can be started normally, the running state of the server and the use of the system can be normal, but in the actual use process, along with iteration of versions, change of data quantity and continuous change of the requirement for system access, the performance of the server can change gradually, so that the performance of the server is not good like user experience when the server is just started to run.
At present, in a big data environment, relevant parameters are configured according to system requirements in the process of optimizing the performance of a server, the server and application can be started normally, and the running state and the system use of the server can be normal. For example, the starting time of the application server is too slow, the time for accessing the background service is obviously prolonged, the response is responded, the time for accessing the database is obviously prolonged, the memory is overflowed, and the like, so that different problems influencing the user experience degree can occur in the using process of the system.
In the prior art, most performance optimization is performed from a virtual machine and then from a hardware device, and basically, the server itself is optimized by adopting a default configuration without changing parameter configuration.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a system and a method for realizing the performance optimization processing of a server under a big data environment, which have the advantages of high efficiency, good user experience and wide application range.
In order to achieve the above object, the system and method for implementing server performance optimization processing in big data environment of the present invention are as follows:
the system for realizing the performance optimization processing of the server under the big data environment is mainly characterized by comprising the following components:
the environment deployment module is used for selecting configuration auxiliary products meeting the requirements according to the project, and increasing and configuring servers and system operation environments;
the data initialization module is connected with the environment deployment module and used for setting parameters according to the actual conditions of enterprises and inputting basic files and initial data;
the file and parameter analysis module is connected with the data initialization module and is used for carrying out resource allocation and parameter adjustment in the running process of the server;
the service optimization module is connected with the file and parameter analysis module and is used for properly adjusting the related parameters according to the actual conditions of the project;
and the product starting module is connected with the service optimization module and used for checking the running state of the product after service optimization.
Preferably, the initial data entered by the data initialization module includes initialized user login name and password, basic directory information, function information and page data.
Preferably, the service optimization module includes a configuration file modification unit, connected to the file and parameter analysis module and the product start module, and configured to perform performance optimization by modifying the configuration file.
Preferably, the server is a tomcat server.
The method for realizing the server performance optimization processing in the big data environment by using the system is mainly characterized by comprising the following steps of:
(1) the environment deployment module is used for increasing and configuring a server and a system operation environment;
(2) the data initialization module initializes the database data;
(3) the file and parameter analysis module is used for carrying out resource allocation and parameter adjustment;
(4) the service optimization module optimizes and adjusts parameters;
(5) the product starting module verifies the starting time of the server.
Preferably, the step (5) specifically comprises the following steps:
(5.1) checking the service status of the product;
(5.2) checking the log, judging whether error data are printed, if so, manually modifying or removing, restarting until no error log exists, and checking service starting time and request response time; otherwise, the step is exited.
By adopting the system and the method for realizing the performance optimization processing of the server in the big data environment, the parameters of the configuration files needing to be loaded during the starting and running of the optimized server are adjusted by analyzing the running mechanism, the server directory and the file meanings of the web server and the parameter meanings of the corresponding files, so that the starting and running efficiency of the server is improved compared with the original efficiency, and the system performance, the user experience degree, the efficiency and the data value are improved.
Drawings
Fig. 1 is a block diagram of a system for implementing server performance optimization processing in a big data environment according to the present invention.
Fig. 2 is a flowchart of an embodiment of a method for implementing server performance optimization processing in a big data environment according to the present invention.
Detailed Description
In order to more clearly describe the technical contents of the present invention, the following further description is given in conjunction with specific embodiments.
The system for realizing the performance optimization processing of the server in the big data environment comprises the following steps:
the environment deployment module is used for selecting configuration auxiliary products meeting the requirements according to the project, and increasing and configuring servers and system operation environments;
the data initialization module is connected with the environment deployment module and used for setting parameters according to the actual conditions of enterprises and inputting basic files and initial data;
the file and parameter analysis module is connected with the data initialization module and is used for carrying out resource allocation and parameter adjustment in the running process of the server;
the service optimization module is connected with the file and parameter analysis module and is used for properly adjusting the related parameters according to the actual conditions of the project;
and the product starting module is connected with the service optimization module and used for checking the running state of the product after service optimization.
As a preferred embodiment of the present invention, the initial data entered by the data initialization module includes an initialized user login name and password, basic directory information, function information, and page data.
As a preferred embodiment of the present invention, the service optimization module includes a configuration file modification unit, connected to the file and parameter analysis module and the product start module, for performing performance optimization by modifying the configuration file.
In a preferred embodiment of the present invention, the server is a tomcat server.
The method for realizing the server performance optimization processing in the big data environment by using the system comprises the following steps:
(1) the environment deployment module is used for increasing and configuring a server and a system operation environment;
(2) the data initialization module initializes the database data;
(3) the file and parameter analysis module is used for carrying out resource allocation and parameter adjustment;
(4) the service optimization module optimizes and adjusts parameters;
(5) the product starting module verifies the starting time of the server.
(5.1) checking the service status of the product;
(5.2) checking the log, judging whether error data are printed, if so, manually modifying or removing, restarting until no error log exists, and checking service starting time and request response time; otherwise, the step is exited.
In the specific implementation mode of the invention, the invention relates to a method for optimizing the performance of a server based on a big data environment. At present, in a big data environment, an application server is an indispensable part in project operation, supports a container of an application program, operates on a virtual machine, binds an IP address and monitors a TCP port, manages the life cycle of the application, maps an address requested by a client to a corresponding program, and cooperates with the program to process the request. The running performance of the application server directly affects the performance of system requests and responses running on the server, the performance of the system is reduced due to the reduction of the performance of the application server, and the user experience is low. The invention adjusts and optimizes the configuration file parameters needing to be loaded in the starting and running of the server by analyzing the running mechanism of the web server, the server directory and file meanings and the parameter meanings of the corresponding files, so that the starting and running efficiency of the server is improved compared with the original efficiency, and the system performance and the user experience are improved.
The invention adjusts and optimizes the configuration file parameters needing to be loaded in the starting and running of the server by analyzing the running mechanism of the web server, the server directory and file meanings and the parameter meanings of the corresponding files, so that the starting and running efficiency of the server is improved compared with the original efficiency, and the system performance, the user experience degree, the efficiency and the data value are improved.
The system comprises an environment deployment module, a data initialization module, a server file and parameter analysis module, a service optimization module and a product starting module.
The environment deployment module is a configuration auxiliary product which is selected according to a product developed by a developer or an implemented project and meets the running condition and the requirement of the product, for example, an operating system and the version of the product, the type and the version of a required database, a plurality of plug-ins and versions which are required by the product to run, a virtual machine and the like; the data initialization module is used for setting parameters according to the actual conditions of an enterprise and inputting a basic file and initial data when the product installation system is initialized and the system is used for the first time; the server file and parameter analysis module is the influence generated by resource allocation and parameter adjustment involved in the server operation process; the service optimization module is used for properly adjusting the related parameters according to the actual conditions of the project, so that the performance of the service optimization module is further improved within a certain range; the product starting module is used for checking the running condition of the product after optimization. The present invention is constructed as shown in fig. 1.
The environment deployment module, the data initialization module, the server file and parameter analysis module, the service optimization module, and the product start module will be described in detail below.
SQL grammar involved in the description is operated according to oracle grammar, and codes are operated according to java grammar.
First, environment deployment module
The environment deployment module is a configuration auxiliary product which is selected according to a product developed by a developer or an implemented project and meets the running condition and the requirement of the product, for example, an operating system and a version of the product, a required database type and a version of the database, a plurality of plug-ins and versions which are required by the product to run, a virtual machine and the like.
Second, data initialization module
The data initialization module is an initialization data script in a big data platform, indexes the creation of tables and the insertion of data related to a database, comprises an initialized user login name and password, most basic directory information, function information and page data, is mainly an installation package of the database script and a product, only comprises the simplest table creation and the data addition, and also adds new data in the using process of the system.
The number of tables is large, the tables are mainly added, modified and deleted, and specific scripts for adding data are not described here.
Third, file, parameter analysis module
Here, a tomcat server is used for explanation, and the tomcat server is a free Web application server with open source codes, belongs to a lightweight application server, is generally used in small and medium-sized systems and in situations where there are not many concurrent access users, and is used in developing, debugging and running programs.
Tomcat version: tomcat8.0.11
tomcat product catalog file meaning:
(1) bin: mainly used for storing commands, bat is under windows, sh is under Linux
(2) conf: some profiles primarily for storing tomcat
(3) B, lib: deposit some jar packages that tomcat depends on
(4) logs: deposit log files generated by tomcat at runtime
(5) temp: storing temporary files generated during runtime
(6) webapps: hosting applications
(7) work: storing files compiled at tomcat runtime, e.g. JSP compiled files
Service optimization module
tomcat performance optimization is essentially to return to the nature of the problem, the flow of a client's connection request response, seeing what the process goes through and where it can be optimized. It should be noted that, of course, the CPU, the memory, the hard disk, and the like of the server have a decisive influence on the performance, and the higher the hardware configuration, the better.
The connection request of the client will be handed over to the Connector, and the Connector can be selected, such as Http Connector, AJP Connector;
executor represents a thread pool that can be shared among components;
context represents a web application running in one component;
the source code when the web.xml file is loaded in the Context has a global web.xml file, and processes some filters, global servlets, sessions, and the like, and under the conf directory, the source code and the global web.xml file are merged.
To change the above, and adjust properly, it is obviously not appropriate to modify the tomcat source code, and tomcat provides us with relevant profiles that can be customized to build by itself, such as server.
Xml conf/web xml can be located by the previous analysis, which currently locates two important profiles conf/server
Context represents a web application, is relatively close to us, and considers the appropriate optimization for it
Reduce tags in web.xml/server.xml
mime-mapping removes responsive content
The best thread number formula of the executor attribute is as follows: ((thread latency + thread cpu time)/thread cpu time) × number of cpus
enablelokups set to false
AJP deleted Connector
autoDeploy: during the operation of Tomcat, a thread is required to be taken out for inspection, and the thread must be changed to false under the production environment
reloadable：false
reloadable: if the attribute is set to true, the tomcat server monitors the change of class files under WEB-INF/classes and WEB-INF/lib directories in the running state, and if the class files are monitored to be updated, the server automatically reloads Web application. Setting the reloadable attribute to true during the development phase helps debug servlets and other class files, but this places a heavy load on the server, suggesting that the reloadable is set to false during the launch phase of the Web application.
Product starting module
And the product starting module is optimized according to the fourth module, the service of the product is checked to be normally started after the optimization, the state is available, the log is checked, whether error data is printed or not is manually modified or removed, and the product is restarted until no error log exists, and the service starting time and the time for requesting response are checked.
The embodiment of the invention is used for explaining the implementation example of the invention by a method for optimizing the performance of the server in the property industry.
In a certain production data implementation case, through business investigation, customer data information is identified, as shown in the following table:
| attribute item numbering | Attribute classification | English name | Attribute name | Type of field | Length of field |
| 1001 | Basic Properties | CstGUID | Customer unique identification | varchar2 | 64 |
| 1002 | Basic Properties | CstName | Customer name | varchar2 | 256 |
| 1003 | Basic Properties | CstType | Type of client | varchar2 | 16 |
| 1004 | Basic Properties | CardType | Document type | varchar2 | 16 |
| 1005 | Basic genusProperty of (2) | CardID | Certificate number | varchar2 | 256 |
| 1006 | Basic Properties | MainMobileTel | Main mobile phone number | varchar2 | 32 |
| 1007 | Basic Properties | OfficeTel | Office telephone | varchar2 | 32 |
| 1008 | Basic Properties | HomeTel | Home telephone | varchar2 | 64 |
| 1009 | Basic Properties | Gender | Sex | varchar2 | 16 |
| 1010 | Basic Properties | BirthDate | Birthday | date | |
| 1011 | Basic Properties | NativePlace | Native place | varchar2 | 32 |
| 1012 | Basic Properties | CensusPlace | Household registration area | varchar2 | 32 |
| 1013 | Basic Properties | Address | Address | varchar2 | 256 |
| 1014 | Basic Properties | Nationality | Nationality book | varchar2 | 16 |
| 1015 | Basic Properties | Electronic mail box | varchar2 | 32 | |
| 1016 | Basic Properties | MaritalStatus | Marital status | varchar2 | 16 |
| 1017 | Basic Properties | EduLevel | Degree of education | varchar2 | 16 |
| 1018 | Basic Properties | CstNickName | Nickname | varchar2 | 256 |
| 1019 | Basic Properties | ContactName | Contact name | varchar2 | 256 |
| 1020 | System attributes | CREATEUSER | Creators | varchar2 | 64 |
| 1021 | System attributes | MODIFYUSER | Reviser | varchar2 | 64 |
| 1022 | System attributes | CreateTime | Creation time | timestamp | |
| 1023 | System attributes | ModifyTime | Modifying time | timestamp | |
| 1024 | System attributes | IsUsedCode | Data usage status code | varchar2 | 16 |
After obtaining the customer data table, the method according to the invention is mainly implemented as shown in fig. 2.
First, environment deployment module
The environment deployment module is a configuration auxiliary product which is selected according to a product developed by a developer or an implemented project and meets the running condition and the requirement of the product, for example, an operating system and a version of the product, a required database type and a version of the database, a plurality of plug-ins and versions which are required by the product to run, a virtual machine and the like.
Operating environment hardware information:
data platform version information:
DSP 6.0LA
database information:
oracle Database 11g Enterprise Edition Release 11.2.0.1.0-64bit production jdk information:
Oracle JDK1.8.0_172
second, data initialization module
The data initialization module is an initialization data script in a big data platform, indexes the creation of tables and the insertion of data related to a database, comprises an initialized user login name and password, most basic directory information, function information and page data, is mainly an installation package of the database script and a product, only comprises the simplest table creation and the data addition, and also adds new data in the using process of the system.
Delete possible tables:
DROP TABLE TSC_MONITOR_RES；
creating a new table:
CREATE TABLE TSC_MONITOR_RES(
C_ID VARCHAR2(255BYTE)NOT NULL,
C_IP VARCHAR2(255BYTE)NULL,
C_DATE VARCHAR2(255BYTE)NULL,
C_TOTALMEMORY VARCHAR2(255BYTE)NULL,
C_FREEMEMORY VARCHAR2(255BYTE)NULL,
C_MAXMEMORY VARCHAR2(255BYTE)NULL,
C_OSNAME VARCHAR2(255BYTE)NULL,
C_TOTALMEMORYSIZE VARCHAR2(255BYTE)NULL,
C_FREEMEMORYSIZE VARCHAR2(255BYTE)NULL,
C_USEDMEMORY VARCHAR2(255BYTE)NULL,
C_TOTALTHREAD VARCHAR2(255BYTE)NULL,
C_CPUUSAGE VARCHAR2(255BYTE)NULL,
C_DISKUSAGE VARCHAR2(4000BYTE)NULL,
C_SERVERTYPE VARCHAR2(255BYTE)NULL,
C_SERVERSTATUS VARCHAR2(255BYTE)NULL,
C_DESCRIPTION VARCHAR2(255BYTE)NULL
)
LOGGING
NOCOMPRESS
NOCACHE；
creating a unique index:
CREATE UNIQUE INDEX SYS_C0010056
ON TSC_MONITOR_RES(C_ID ASC)
LOGGING
VISIBLE；
adding value constraint:
ALTER TABLE TSC_MONITOR_RES ADD CHECK(C_ID IS NOT NULL)；
creating a primary key:
ALTER TABLE TSC_MONITOR_RES ADD PRIMARY KEY(C_ID)；
inserting data:
insert into TSC_MONITOR_RES values(‘’,”,…)；
third, file, parameter analysis module
Here, a tomcat server is used for explanation, and the tomcat server is a free Web application server with open source codes, belongs to a lightweight application server, is generally used in small and medium-sized systems and in situations where there are not many concurrent access users, and is used in developing, debugging and running programs.
Tomcat version: tomcat8.0.11
tomcat product catalog file meaning:
(1) bin: mainly used for storing commands, bat is under windows, sh is under Linux
(2) conf: some profiles primarily for storing tomcat
(3) B, lib: storing some jar packages that tomcat depends on, and storing the jar packages needed by the application
(4) logs: deposit log files generated by tomcat at runtime
(5) temp: storing temporary files generated during runtime
(6) webapps: storing the application program, and storing the finished default
(7) work: and storing files compiled in the tomcat runtime, such as files compiled by JSP (Java Server pages) and the like, and some cache files in the system running process.
Fourth, optimization module of server
tomcat performance optimization is essentially to return to the nature of the problem, the flow of a client's connection request response, seeing what the process goes through and where it can be optimized. It should be noted that, of course, the CPU, the memory, the hard disk, and the like of the server have a decisive influence on the performance, and the higher the hardware configuration, the better.
The connection request of the client will be handed over to the Connector, and the Connector can be selected, such as Http Connector, AJP Connector;
executor represents a thread pool that can be shared among components;
context represents a web application running in one component;
the source code when the web.xml file is loaded in the Context has a global web.xml file, and processes some filters, global servlets, sessions, and the like, and under the conf directory, the source code and the global web.xml file are merged.
To change the above, and adjust properly, it is obviously not appropriate to modify the tomcat source code, and tomcat provides us with relevant profiles that can be customized to build by itself, such as server.
From the previous analysis, it is possible to locate two important configuration files conf/server.xml conf/web.xml at present;
context represents a web application, is closer to us, and considers the appropriate optimization;
tag reduction in web.xml/server.xml;
the mime-mapping removes the content of the response;
the best thread number formula of the executor attribute is as follows: ((thread latency + thread cpu time)/thread cpu time) x cpu number;
enablelokups is set to false;
AJP Connector was deleted;
autoDeploy: when Tomcat runs, a thread is required to be taken out for inspection, and the thread is required to be changed into false under the production environment;
reloadable:false；
reloadable: if the attribute is set to true, the tomcat server monitors the change of class files under WEB-INF/classes and WEB-INF/lib directories in the running state, and if the class files are monitored to be updated, the server automatically reloads Web application. Setting the reloadable attribute to true during the development phase helps debug servlets and other class files, but this places a heavy load on the server, suggesting that the reloadable is set to false during the launch phase of the Web application.
The server optimization content mainly comprises the above parameters for optimization.
Product starting module
And the product starting module is optimized according to the fourth module, the service of the product is checked to be normally started after the optimization, the state is available, the log is checked, whether error data is printed or not is manually modified or removed, and the product is restarted until no error log exists, and the service starting time and the time for requesting response are checked.
The time before and after the start is optimized is as follows:
| before/ms optimization | Optimized/ms |
| 57453 | 50287 |
| 56923 | 49504 |
| 58036 | 49839 |
| 55137 | 49625 |
| 57184 | 50028 |
Average time before optimization: 56946.6ms
Average time after optimization: 49856.6ms
(56946.6-49856.6)/49856.6*100％＝14.221％
The calculation result obtained by using the embodiment is improved by 14.221% under the same hardware environment and application condition, so that the starting efficiency and the running efficiency of the server are improved compared with the original efficiency, and the system performance and the user experience are improved.
By adopting the system and the method for realizing the performance optimization processing of the server in the big data environment, the parameters of the configuration files needing to be loaded during the starting and running of the optimized server are adjusted by analyzing the running mechanism, the server directory and the file meanings of the web server and the parameter meanings of the corresponding files, so that the starting and running efficiency of the server is improved compared with the original efficiency, and the system performance, the user experience degree, the efficiency and the data value are improved.
In this specification, the invention has been described with reference to specific embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Claims (6)
1. A system for implementing server performance optimization processing in big data environment is characterized in that the system comprises:
the environment deployment module is used for selecting configuration auxiliary products meeting the requirements according to the project, and increasing and configuring servers and system operation environments;
the data initialization module is connected with the environment deployment module and used for setting parameters according to the actual conditions of enterprises and inputting basic files and initial data;
the file and parameter analysis module is connected with the data initialization module and is used for carrying out resource allocation and parameter adjustment in the running process of the server;
the service optimization module is connected with the file and parameter analysis module and is used for properly adjusting the related parameters according to the actual conditions of the project;
and the product starting module is connected with the service optimization module and used for checking the running state of the product after service optimization.
2. The system for realizing server performance optimization processing under the big data environment according to claim 1, wherein the initial data entered by the data initialization module comprises initialized user login name and password, basic directory information, function information and page data.
3. The system according to claim 1, wherein the service optimization module includes a configuration file modification unit, connected to the file and parameter analysis module and the product start module, for performing performance optimization by modifying the configuration file.
4. The system for implementing server performance optimization processing in big data environment according to claim 1, wherein the server is a tomcat server.
5. A method for implementing server performance optimization processing in big data environment based on the system of claim 1, the method comprising the following steps:
(1) the environment deployment module is used for increasing and configuring a server and a system operation environment;
(2) the data initialization module initializes the database data;
(3) the file and parameter analysis module is used for carrying out resource allocation and parameter adjustment;
(4) the service optimization module optimizes and adjusts parameters;
(5) the product starting module verifies the starting time of the server.
6. The method for implementing server performance optimization processing in a big data environment according to claim 5, wherein the step (5) specifically includes the following steps:
(5.1) checking the service status of the product;
(5.2) checking the log, judging whether error data are printed, if so, manually modifying or removing, restarting until no error log exists, and checking service starting time and request response time; otherwise, the step is exited.
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Cited By (2)
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| CN113064879A (en) * | 2021-03-12 | 2021-07-02 | 腾讯科技（深圳）有限公司 | Database parameter adjusting method and device and computer readable storage medium |
| CN117421186A (en) * | 2023-12-18 | 2024-01-19 | 苏州元脑智能科技有限公司 | Method, device, system and storage medium for adjusting server operation parameters |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751642A (en) * | 2008-12-03 | 2010-06-23 | 清华大学 | Electronic commerce market product/service information management and monitoring platform |
| US20170115977A1 (en) * | 2015-10-27 | 2017-04-27 | Samsung Sds Co., Ltd. | Apparatus and method for automating the installation and configuration of infrastructure |
| CN107357736A (en) * | 2017-07-28 | 2017-11-17 | 郑州云海信息技术有限公司 | A kind of automated detection method for Tomcat security configurations |
-
2019
- 2019-10-22 CN CN201911006347.6A patent/CN110727467A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751642A (en) * | 2008-12-03 | 2010-06-23 | 清华大学 | Electronic commerce market product/service information management and monitoring platform |
| US20170115977A1 (en) * | 2015-10-27 | 2017-04-27 | Samsung Sds Co., Ltd. | Apparatus and method for automating the installation and configuration of infrastructure |
| CN107357736A (en) * | 2017-07-28 | 2017-11-17 | 郑州云海信息技术有限公司 | A kind of automated detection method for Tomcat security configurations |
Non-Patent Citations (2)
| Title |
|---|
| 李萍;: "浅谈TOMCAT之性能优化" * |
| 王国强: "JSP 引 擎的性能优化研究" * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113064879A (en) * | 2021-03-12 | 2021-07-02 | 腾讯科技（深圳）有限公司 | Database parameter adjusting method and device and computer readable storage medium |
| CN117421186A (en) * | 2023-12-18 | 2024-01-19 | 苏州元脑智能科技有限公司 | Method, device, system and storage medium for adjusting server operation parameters |
| CN117421186B (en) * | 2023-12-18 | 2024-03-15 | 苏州元脑智能科技有限公司 | Method, device, system and storage medium for adjusting server operation parameters |
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