CN110888712A - Java virtual machine optimization method and system - Google Patents
Java virtual machine optimization method and system Download PDFInfo
- Publication number
- CN110888712A CN110888712A CN201910960132.1A CN201910960132A CN110888712A CN 110888712 A CN110888712 A CN 110888712A CN 201910960132 A CN201910960132 A CN 201910960132A CN 110888712 A CN110888712 A CN 110888712A
- Authority
- CN
- China
- Prior art keywords
- heap memory
- threshold
- jvm
- parameters
- subject
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
- G06F9/5016—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals the resource being the memory
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/45583—Memory management, e.g. access or allocation
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Devices For Executing Special Programs (AREA)
- Debugging And Monitoring (AREA)
Abstract
The application discloses a Java virtual machine optimization method and a system, wherein the method comprises the following steps: acquiring the current configuration of parameters of a Java virtual machine JVM (Java virtual machine), wherein the parameters comprise an initial heap memory, a maximum heap memory, the proportion of a new generation to an old generation, an object GC age threshold and an object direct promotion threshold to the old generation; determining whether the generated stack file of the size is an abnormally generated stack file or a stack file generated before/after FullGC; reconfiguring the initial heap memory, the maximum heap memory and the object GC age threshold in response to the fact that the dump file is the abnormally generated dump file; in response to determining that the dump file is a dump file generated before/after FullGC, the ratio of new to old generations, the subject GC age threshold, and the subject's direct promotion to an old generation threshold are adjusted. The invention can save development time and improve development efficiency.
Description
Technical Field
The application relates to the field of electric digital data processing, in particular to a Java virtual machine optimization method and system.
Background
UNIEAP is a development platform developed by the east Soft group. Memory overflow is a very common phenomenon for developers at first school of UNIEAP. The optimal parameter configuration of the Java Virtual Machine (JVM) varies from device to device.
Currently, for beginners of UNIEAP, the JVM size stacks are different due to different versions of UNIEAP and different parameters of the devices. In the development process, the creating and recycling strategies of objects in the new generation, the old generation and the persistent generation are different, and GC recycling (garbage recycling) is not timely or can not be completely recycled, so that the stack overflow of a memory is easily caused.
There is thus a need for a solution that avoids the UNIEAP beginner spending too much time in JVM parameter configuration.
Disclosure of Invention
In order to overcome the defects in the prior art, the technical problem to be solved by the invention is to provide a Java virtual machine optimization method and system, which can save the time of a developer and improve the development efficiency.
To solve the above technical problem, according to a first aspect of the present invention, there is provided a Java virtual machine optimization method, including:
acquiring the current configuration of parameters of a Java virtual machine JVM (Java virtual machine), wherein the parameters comprise an initial heap memory, a maximum heap memory, the proportion of a new generation to an old generation, an object GC age threshold and an object direct promotion threshold to the old generation;
determining whether the generated stack file of the size is an abnormally generated stack file or a stack file generated before/after FullGC;
reconfiguring the initial heap memory, the maximum heap memory and the object GC age threshold in response to the fact that the dump file is the abnormally generated dump file;
in response to determining that the dump file is a dump file generated before/after FullGC, the ratio of new to old generations, the subject GC age threshold, and the subject's direct promotion to an old generation threshold are adjusted.
As an improvement of the method of the present invention, the adjusting the ratio of the new generation to the old generation, the subject GC age threshold and the subject direct promotion to the old generation threshold in response to determining that the dump file is a dump file generated before and after fulllgc comprises: recording the execution times and execution time of the FullGC; the subject GC age threshold and the subject's direct promotion to the senior threshold are adjusted based on the number of Fullgc executions, with the greater the number of Fullgc executions, the lesser the subject GC age threshold and the subject's direct promotion to the senior threshold.
As another improvement of the method of the present invention, the method further comprises: recording the change of the available space of the initial heap memory and the maximum heap memory before and after the FullGC is executed; in response to the change being less than a predetermined threshold, the initial heap memory and the maximum heap memory are expanded.
As a further improvement of the method of the present invention, the method further comprises: and recording and storing JVM parameters with the times of stack exception less than a first preset time and the times of FullGC less than a second preset time, and taking the JVM parameters as JVM optimization configuration parameters of corresponding equipment.
As a further improvement of the method of the invention, the method further comprises: in response to the spare heap memory being smaller than a first threshold, increasing the initial heap memory; and decreasing the maximum heap memory in response to the free heap memory being greater than a second threshold.
As another improvement of the method of the present invention, the method further comprises: and in response to determining that the new device and the device corresponding to the JVM optimized configuration parameters are the same or similar devices, taking the JVM optimized configuration parameters as the initial JVM configuration parameters of the new device.
As a further improvement of the method of the present invention, the reconfiguring the initial heap memory, the maximum heap memory, and the object GC age threshold in response to determining that the dump file is an abnormally generated dump file comprises: increasing the initial heap memory and the maximum heap memory; and reducing the subject GC age threshold.
To solve the above technical problem, according to a second aspect of the present invention, there is provided a Java virtual machine optimization system, the system including:
the current configuration acquisition module is used for acquiring the current configuration of parameters of the JVM, wherein the parameters comprise an initial heap memory, a maximum heap memory, the proportion of a new generation to an old generation, an object GC age threshold and an object direct promotion threshold of the old generation;
the file type determining module is used for determining whether the generated stack file with the size is an abnormally generated stack file or a stack file generated before/after FullGC;
the reconfiguration module is used for reconfiguring the initial heap memory, the maximum heap memory and the object GC age threshold in response to the fact that the dump file is the abnormally generated dump file;
an adjusting module, configured to adjust a ratio of the new generation to the old generation, a subject GC age threshold, and a subject direct promotion to the old generation threshold in response to determining that the dump file is a dump file generated before/after fulllgc.
To solve the above technical problem, the tangible computer readable medium of the present invention includes computer program code for executing the Java virtual machine optimization method of the present invention.
To solve the above technical problem, the present invention provides an apparatus, comprising at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least some of the steps of the Java virtual machine optimization method of the present invention.
According to the invention, jvm parameters can be adjusted in real time according to the dump file condition, so that the development process is more convenient, the time is saved, and the development efficiency of especially beginners is improved. In addition, by recording the optimal parameter configuration of different devices, the parameter configuration of new devices can be initialized according to the past device parameters, and the development time is also saved.
Other features and advantages of the present invention will become more apparent from the detailed description of the embodiments of the present invention when taken in conjunction with the accompanying drawings.
Drawings
FIG. 1 is a flow chart of an embodiment of a method according to the present invention.
FIG. 2 is a schematic diagram of an embodiment of a system according to the present invention.
For the sake of clarity, the figures are schematic and simplified drawings, which only show details which are necessary for understanding the invention and other details are omitted.
Detailed Description
Embodiments and examples of the present invention will be described in detail below with reference to the accompanying drawings.
The scope of applicability of the present invention will become apparent from the detailed description given hereinafter. It should be understood, however, that the detailed description and the specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only.
Fig. 1 shows a flowchart of a preferred embodiment of the Java virtual machine optimization method according to the present invention.
In step S102, the current configuration of the parameters of the Java virtual machine JVM is obtained, the JVM parameters include but are not limited to initial heap memory-Xms, maximum heap memory-Xmx, ratio of new generation to old generation-XX: NewRatio, subject GC age threshold-XX: MaxTenuringThreshold and subject escalation directly to the geriatric threshold-XX: PretenureSemizenethreshold.
The JVM specific parameter configuration may be recorded.
When the software runs, the configuration parameters (such as Windows: 32 bits/64 bits, physical memory and CPU information) of the equipment are obtained through scripts (different scripts may be needed by Windows, Mac and Linux, and the scripts can be embedded into the software or manually executed).
The JVM parameters may be initially configured according to configuration parameters of the device or set, in combination with big data, an optimal JVM parameter configuration of the device equivalent to the current device as an initial configuration.
The JVM general parameter configuration is as follows:
large and small heap arrangement
-Xms: and (5) initial heap memory. 1/64, which is the default physical memory, is also the minimum allocated heap memory. When the free heap memory is less than 40%, the maximum limit of-Xms is increased;
-Xmx: and (4) maximum heap memory. The default physical memory 1/4 is reduced to a minimum limit of-Xms when the free heap memory is greater than 70%.
Typically, the developer will set the-Xmx and-Xms sizes to be the same at initialization, so that the virtual machine will not automatically increase or decrease memory usage any more, and the virtual machine is relatively stable. If the two parameters are different, the virtual machine will acquire the minimum memory of-Xms, when the memory is not enough, the virtual machine will gradually apply for expanding the memory, the maximum is-Xmx, when the virtual machine unloads a part of programs (namely GC plays a role in retraction), a part of used memory becomes available, and when the spare memory is more than 70%, the virtual machine will automatically optimize, reduce the memory occupation and reduce to-Xms again in order to save the device memory.
-XX: PermSze: the initial value of non-heap memory, 1/64 for default physical memory, is also the minimum non-heap memory;
-XX: MaxPermSize: non-heap memory maximum, 1/4 of default physical memory.
New generation setting
-Xmn: new generation size (default setting: Eden: Survivor ═ 8: 1. once set, typically no longer modified). Typically 1/3 or 1/4 of Xmx. New generation ═ Eden +2 Survivor spaces. The actual available space is ═ Eden +1 Survivor, i.e. 90%.
Old age setting
-XX: new ratio: the ratio of new to old generations, such as-XX: new ratio is 2, the new generation accounts for 1/3 of the whole stack space, and the old generation accounts for 2/3.
GC control settings
-XX: MaxTenuringThreshold: subject GC age threshold;
-XX: pretenerzethreshold: subjects promoted directly to the age threshold (values greater than this would promote directly to the old, avoiding frequent minor GC).
Dump file setup
-XX: + heappdumpnonoutofmemoryrer: the JVM automatically generates a dump file when abnormal;
-XX: + heappdumpbeforefulllgc: dump before Full GC;
-XX: + heappdumfafterfullgc: dump after Full GC;
-XX: HeapdumPath ═ concept/dump/date/: the dump file stores the path.
In step S104, a dump file of the heap is generated. The generation and storage locations of the dump files are controlled by the above parameter configuration, and different dump files are stored in different locations.
In step S106, it is determined whether the generated big-and-small heap dump file is an abnormally generated dump file or a dump file generated before/after FullGC, based on the storage location of the dump file. If it is the abnormally generated dump file, the process proceeds to step S108; otherwise, if it is the dump file generated before/after the FullGC, the process proceeds to step S150.
In step S108, the values of initial heap memory-Xms and maximum heap memory-Xmx are expanded, for example 256 or 512 megabytes at a time, while the subject GC age threshold (generation age) is reduced, for example 2 at a time.
In step S150, the number of times and the execution time of the FullGC execution are recorded.
In step S152, the subject GC age threshold and the subject direct promotion to the old generation threshold are adjusted according to the number of times the fulllgc is performed, and the greater the number of times the fulllgc is performed, the smaller the subject GC age threshold and the subject direct promotion to the old generation threshold. The number of FullGC is usually not more than 2 or 1 times per day, but is not limited thereto, and a smaller number is better according to the size of the project and the equipment configuration. If more memory space is released after fulllgc, indicating more old age subjects, it is appropriate to increase GC age, increase old age memory size (NewRatio), and increase promotion to old age threshold (pretenerzethreshold).
In step S154, the change of the initial heap memory and the maximum heap memory available space before and after the FullGC is executed is recorded. After FullGC, if more memory space is released, two parameters of-Xms and-Xmx are increased, and the GC generation age and the threshold value for directly promoting the GC generation age to the aged generation object are increased; otherwise, the current memory is normal.
In step S156, when it is determined that the change of the available space of the initial heap memory and the maximum heap memory before and after the FullGC is executed is smaller than the predetermined threshold, the initial heap memory and the maximum heap memory are expanded.
In step S160, the JVM parameters with the number of times of occurrence of stack exception being less than the first predetermined number of times and the number of times of occurrence of FullGC being less than the second predetermined number of times are recorded and saved as the JVM optimized configuration parameters of the corresponding device. For example, after a certain configuration, if no exception occurs for at least one week or one month, and the number of FullGC times per day or one week is very small, such as no occurrence or 1 time, the current JVM parameters can be considered as the optimal configuration parameters of the current device.
In other embodiments, the method of the present invention may further include comparing the device parameters of the new device with the device parameters of the recorded device, and finding the JVM optimized configuration parameters of the device with the same or similar device parameters according to the device parameters of the new device and using the JVM optimized configuration parameters as the initial JVM configuration parameters of the new device, so as to save development time.
FIG. 2 shows a block diagram of an embodiment of a Java virtual machine optimization system according to the present invention, comprising: a current configuration obtaining module 202, configured to obtain a current configuration of parameters of the Java virtual machine JVM, where the parameters include an initial heap memory, a maximum heap memory, a ratio of a new generation to an old generation, an age threshold of an object GC, and an age threshold of an object promoted directly to the old generation; a file type determining module 204, configured to determine whether the generated stack file of the size is an abnormally generated stack file or a stack file generated before/after the FullGC; a reconfiguration module 206, configured to reconfigure the initial heap memory, the maximum heap memory, and the object GC age threshold in response to determining that the dump file is an abnormally generated dump file; an adjustment module 208 for adjusting a ratio of new generation to old generation, a subject GC age threshold, and a subject direct promotion to an old generation threshold in response to determining that the dump file is a dump file generated before/after fulllgc.
In other embodiments, the inventive system may further comprise: the recording module is used for recording and storing the JVM parameters of which the times of occurrence of stack exception are less than a first preset time and the times of FullGC are less than a second preset time, and the JVM parameters are used as JVM optimization configuration parameters of corresponding equipment; and/or an initialization module, configured to, in response to determining that the new device and the device corresponding to the JVM optimal configuration parameter are the same or similar devices, take the JVM optimal configuration parameter as an initial JVM configuration parameter of the new device.
The particular features, structures, or characteristics of the various embodiments described herein may be combined as suitable in one or more embodiments of the invention. Additionally, in some cases, the order of steps depicted in the flowcharts and/or in the pipelined process may be modified, as appropriate, and need not be performed exactly in the order depicted. In addition, various aspects of the invention may be implemented using software, hardware, firmware, or a combination thereof, and/or other computer implemented modules or devices that perform the described functions. Software implementations of the present invention may include executable code stored in a computer readable medium and executed by one or more processors. The computer readable medium may include a computer hard drive, ROM, RAM, flash memory, portable computer storage media such as CD-ROM, DVD-ROM, flash drives, and/or other devices, for example, having a Universal Serial Bus (USB) interface, and/or any other suitable tangible or non-transitory computer readable medium or computer memory on which executable code may be stored and executed by a processor. The present invention may be used in conjunction with any suitable operating system.
As used herein, the singular forms "a", "an" and "the" include plural references (i.e., have the meaning "at least one"), unless the context clearly dictates otherwise. It will be further understood that the terms "has," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The foregoing describes some preferred embodiments of the present invention, but it should be emphasized that the invention is not limited to these embodiments, but can be implemented in other ways within the scope of the inventive subject matter. Various modifications and alterations of this invention will become apparent to those skilled in the art without departing from the spirit and scope of this invention.
Claims (10)
1. A Java virtual machine optimization method, the method comprising:
acquiring the current configuration of parameters of a Java virtual machine JVM (Java virtual machine), wherein the parameters comprise an initial heap memory, a maximum heap memory, the proportion of a new generation to an old generation, an object GC age threshold and an object direct promotion threshold to the old generation;
determining whether the generated stack file of the size is an abnormally generated stack file or a stack file generated before/after FullGC;
reconfiguring the initial heap memory, the maximum heap memory and the object GC age threshold in response to the fact that the dump file is the abnormally generated dump file;
in response to determining that the dump file is a dump file generated before/after FullGC, the ratio of new to old generations, the subject GC age threshold, and the subject's direct promotion to an old generation threshold are adjusted.
2. The method of claim 1, wherein adjusting the ratio of new to old generations, the subject GC age threshold, and the subject's direct promotion to old generation threshold in response to determining that the dump file is a dump file generated before and after fulllgc comprises:
recording the execution times and execution time of the FullGC;
the subject GC age threshold and the subject's direct promotion to the senior threshold are adjusted based on the number of Fullgc executions, with the greater the number of Fullgc executions, the lesser the subject GC age threshold and the subject's direct promotion to the senior threshold.
3. The method of claim 2, further comprising:
recording the change of the available space of the initial heap memory and the maximum heap memory before and after the FullGC is executed;
in response to the change being less than a predetermined threshold, the initial heap memory and the maximum heap memory are expanded.
4. The method of claim 1, further comprising:
and recording and storing JVM parameters with the times of stack exception less than a first preset time and the times of FullGC less than a second preset time, and taking the JVM parameters as JVM optimization configuration parameters of corresponding equipment.
5. The method of claim 1, further comprising:
in response to the spare heap memory being smaller than a first threshold, increasing the initial heap memory; and
in response to the free heap memory being greater than a second threshold, the maximum heap memory is decreased.
6. The method of claim 4, further comprising:
and in response to determining that the new device and the device corresponding to the JVM optimized configuration parameters are the same or similar devices, taking the JVM optimized configuration parameters as the initial JVM configuration parameters of the new device.
7. The method of claim 1, wherein the reconfiguring the initial heap memory, the maximum heap memory, and the object GC age thresholds in response to determining that the dump file is an abnormally generated dump file comprises:
increasing the initial heap memory and the maximum heap memory; and
the subject GC age threshold is decreased.
8. A Java virtual machine optimization system, the system comprising:
the current configuration acquisition module is used for acquiring the current configuration of parameters of the JVM, wherein the parameters comprise an initial heap memory, a maximum heap memory, the proportion of a new generation to an old generation, an object GC age threshold and an object direct promotion threshold of the old generation;
the file type determining module is used for determining whether the generated stack file with the size is an abnormally generated stack file or a stack file generated before/after FullGC;
the reconfiguration module is used for reconfiguring the initial heap memory, the maximum heap memory and the object GC age threshold in response to the fact that the dump file is the abnormally generated dump file;
an adjusting module, configured to adjust a ratio of the new generation to the old generation, a subject GC age threshold, and a subject direct promotion to the old generation threshold in response to determining that the dump file is a dump file generated before/after fulllgc.
9. The system of claim 8, further comprising:
and the recording module is used for recording and storing the JVM parameters of which the times of stack exception occurrence are less than the first preset times and the times of FullGC occurrence are less than the second preset times, and taking the JVM parameters as the JVM optimization configuration parameters of corresponding equipment.
10. The system of claim 9, further comprising:
and the initialization module is used for responding to the fact that the new equipment and the equipment corresponding to the JVM optimized configuration parameters are the same or similar equipment, and taking the JVM optimized configuration parameters as the initial JVM configuration parameters of the new equipment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910960132.1A CN110888712B (en) | 2019-10-10 | 2019-10-10 | Java virtual machine optimization method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910960132.1A CN110888712B (en) | 2019-10-10 | 2019-10-10 | Java virtual machine optimization method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110888712A true CN110888712A (en) | 2020-03-17 |
| CN110888712B CN110888712B (en) | 2022-10-11 |
Family
ID=69746034
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910960132.1A Active CN110888712B (en) | 2019-10-10 | 2019-10-10 | Java virtual machine optimization method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110888712B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111427667A (en) * | 2020-04-03 | 2020-07-17 | 帆软软件有限公司 | JVM load quantification and optimization method |
| CN111949377A (en) * | 2020-08-25 | 2020-11-17 | 深圳市广通软件有限公司 | JVM parameter optimization method, device, server and storage medium for WEB middleware |
| CN112579259A (en) * | 2020-12-14 | 2021-03-30 | 中国科学院软件研究所 | GC self-adaptive adjusting method and device for big data processing framework |
| CN113778740A (en) * | 2021-11-10 | 2021-12-10 | 中航金网(北京)电子商务有限公司 | Exception handling method and device based on garbage collection log |
| US11972242B2 (en) | 2022-07-26 | 2024-04-30 | Red Hat, Inc. | Runtime environment optimizer for JVM-style languages |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080046673A1 (en) * | 2006-08-16 | 2008-02-21 | International Business Machines Corporation | Method and system to optimize java virtual machine performance |
| CN103186412A (en) * | 2011-12-31 | 2013-07-03 | 北京新媒传信科技有限公司 | Performance optimization method based on JVM (java virtual machine) server |
| CN103714004A (en) * | 2014-01-02 | 2014-04-09 | 金蝶软件（中国）有限公司 | JVM online memory leak analysis method and system |
| US20140324924A1 (en) * | 2013-04-26 | 2014-10-30 | Oracle International Corporation | System and method for two-tier adaptive heap management in a virtual machine environment |
-
2019
- 2019-10-10 CN CN201910960132.1A patent/CN110888712B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080046673A1 (en) * | 2006-08-16 | 2008-02-21 | International Business Machines Corporation | Method and system to optimize java virtual machine performance |
| CN103186412A (en) * | 2011-12-31 | 2013-07-03 | 北京新媒传信科技有限公司 | Performance optimization method based on JVM (java virtual machine) server |
| US20140324924A1 (en) * | 2013-04-26 | 2014-10-30 | Oracle International Corporation | System and method for two-tier adaptive heap management in a virtual machine environment |
| CN103714004A (en) * | 2014-01-02 | 2014-04-09 | 金蝶软件（中国）有限公司 | JVM online memory leak analysis method and system |
Non-Patent Citations (3)
| Title |
|---|
| MIKECHEN互联网架构: "直通BAT必考题系列：JVM性能调优的6大步骤，及关键调优参数详解", 《HTTPS://BAIJIAHAO.BAIDU.COM/S?ID=1617167971312758600》 * |
| 周志明: "《深入理解Java虚拟机：JVM高级特性与最佳实践（第2版）》", 30 June 2013 * |
| 阿飞的博客: "OMG！又一个频繁FullGC的案例", 《HTTPS://MP.WEIXIN.QQ.COM/S/X-OOLXOMJOYBE_8E4BWQLQ》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111427667A (en) * | 2020-04-03 | 2020-07-17 | 帆软软件有限公司 | JVM load quantification and optimization method |
| CN111949377A (en) * | 2020-08-25 | 2020-11-17 | 深圳市广通软件有限公司 | JVM parameter optimization method, device, server and storage medium for WEB middleware |
| CN111949377B (en) * | 2020-08-25 | 2021-08-31 | 深圳市广通软件有限公司 | JVM parameter optimization method, device, server and storage medium for WEB middleware |
| CN112579259A (en) * | 2020-12-14 | 2021-03-30 | 中国科学院软件研究所 | GC self-adaptive adjusting method and device for big data processing framework |
| CN112579259B (en) * | 2020-12-14 | 2022-07-15 | 中国科学院软件研究所 | GC self-adaptive adjustment method and device for big data processing framework |
| CN113778740A (en) * | 2021-11-10 | 2021-12-10 | 中航金网(北京)电子商务有限公司 | Exception handling method and device based on garbage collection log |
| US11972242B2 (en) | 2022-07-26 | 2024-04-30 | Red Hat, Inc. | Runtime environment optimizer for JVM-style languages |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110888712B (en) | 2022-10-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110888712B (en) | Java virtual machine optimization method and system | |
| US9529609B2 (en) | Tracking guest memory characteristics for memory scheduling | |
| US9405563B2 (en) | Resource management method and apparatus for virtual machine system, and virtual machine system | |
| US9384007B2 (en) | Memory virtualization-based snapshot boot apparatus and method | |
| US9639423B2 (en) | Method and apparatus for recovering metadata lost during an unexpected power down event | |
| US9547510B2 (en) | Tracking guest memory characteristics for memory scheduling | |
| US9229820B2 (en) | Information processing device with memory dump function, memory dump method, and recording medium | |
| JP2013520744A (en) | Method and apparatus for generating minimum boot image | |
| US8589647B2 (en) | Apparatus and method for synchronizing a snapshot image | |
| CN109086222B (en) | Data recovery method of solid state disk and solid state disk | |
| CN102207881A (en) | Quick operation system start-up method based on Android | |
| US7437524B2 (en) | Method and apparatus for dumping memory | |
| JP2014178913A (en) | Electronic apparatus, method of creating snapshot image, and program | |
| CN107463332B (en) | File segmentation method and device | |
| CN102902606B (en) | A kind of data back up method and device | |
| WO2024109076A1 (en) | Memory management method, computer device and storage medium | |
| KR100994723B1 (en) | selective suspend resume method of reducing initial driving time in system, and computer readable medium thereof | |
| CN103123603B (en) | The method of debug system and the operation of execution debug system | |
| US20140372806A1 (en) | Virtual machine system and information storing processing method | |
| CN110908606B (en) | Data reconstruction method of distributed file system | |
| CN115657952A (en) | Method, device and medium for adjusting data reconstruction speed according to slow request | |
| CN112988207A (en) | BIOS updating method, device, equipment and readable storage medium based on Setup interface | |
| US20160266960A1 (en) | Information processing apparatus and kernel dump method | |
| US20230393942A1 (en) | Apparatus and method for adaptive checkpoint in intermittent computing | |
| CN111752851B (en) | Memory recycling method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |