Kar*_*ell 10 java garbage-collection
我不是Java newby,但我只知道垃圾收集.现在我想通过一些实践经验来改变它.我的目标是延迟不到0.3秒,或者在极端情况下0.5也可以.
我有一个-Xmx50gb(-Xms50gb)的应用程序,并设置其他GC选项:
-XX:+UseG1GC -Xloggc:somewhere.gc.log -XX:+PrintGCDateStamps
Run Code Online (Sandbox Code Playgroud)
但是现在我偶尔因为垃圾收集而长时间暂停超过5秒,尽管似乎有足够的可用内存.我找到的一个原因:
[GC pause (G1 Evacuation Pause) (young) 42G->40G(48G), 5.9409662 secs]
Run Code Online (Sandbox Code Playgroud)
为什么GCG1仍然为此做"停止世界"?(或者至少我看到它正好在这个时候停止我的应用程序)为什么它会做这样的负面清理,如果它不是真的有必要,因为有超过12%的可用RAM空闲.另外我认为默认值-XX:MaxGCPauseMillis
是200毫秒,为什么这个值被违反29或甚至50(见下文)?
延迟的另一个原因是:
[GC pause (Metadata GC Threshold) (young) (initial-mark) 40G->39G(48G), 10.4667233 secs]
Run Code Online (Sandbox Code Playgroud)
这可能通过这个答案解决,例如只增加元数据空间-XX:MetaspaceSize=100M
顺便说一句:使用JSE 1.8.0_91-b14
更新:此类事件的详细GC日志
2016-08-12T09:20:31.589+0200: 1178.312: [GC pause (G1 Evacuation Pause) (young) 1178.312: [G1Ergonomics (CSet Construction) start choosing CSet, _pending_cards: 3159, predicted base time: 1.52 ms, remaining time: 198.48 ms, target pause time: 200.00 ms]
1178.312: [G1Ergonomics (CSet Construction) add young regions to CSet, eden: 136 regions, survivors: 20 regions, predicted young region time: 1924.75 ms]
1178.312: [G1Ergonomics (CSet Construction) finish choosing CSet, eden: 136 regions, survivors: 20 regions, old: 0 regions, predicted pause time: 1926.27 ms, target pause time: 200.00 ms]
1185.330: [G1Ergonomics (Heap Sizing) attempt heap expansion, reason: recent GC overhead higher than threshold after GC, recent GC overhead: 21.83 %, threshold: 10.00 %, uncommitted: 0 bytes, calculated expansion amount: 0 bytes (20.00 %)]
1185.330: [G1Ergonomics (Concurrent Cycles) do not request concurrent cycle initiation, reason: still doing mixed collections, occupancy: 42580574208 bytes, allocation request: 0 bytes, threshold: 23592960000 bytes (45.00 %), source: end of GC]
1185.330: [G1Ergonomics (Mixed GCs) do not start mixed GCs, reason: reclaimable percentage not over threshold, candidate old regions: 1 regions, reclaimable: 3381416 bytes (0.01 %), threshold: 5.00 %]
, 7.0181903 secs]
[Parallel Time: 6991.8 ms, GC Workers: 10]
[GC Worker Start (ms): Min: 1178312.6, Avg: 1178312.8, Max: 1178312.9, Diff: 0.2]
[Ext Root Scanning (ms): Min: 1.1, Avg: 1.5, Max: 2.3, Diff: 1.2, Sum: 15.0]
[Update RS (ms): Min: 0.0, Avg: 0.3, Max: 1.3, Diff: 1.3, Sum: 3.4]
[Processed Buffers: Min: 0, Avg: 2.1, Max: 5, Diff: 5, Sum: 21]
[Scan RS (ms): Min: 0.0, Avg: 0.0, Max: 0.1, Diff: 0.1, Sum: 0.4]
[Code Root Scanning (ms): Min: 0.0, Avg: 0.2, Max: 0.4, Diff: 0.4, Sum: 1.7]
[Object Copy (ms): Min: 6964.1, Avg: 6973.0, Max: 6989.5, Diff: 25.3, Sum: 69730.4]
[Termination (ms): Min: 0.0, Avg: 16.4, Max: 25.3, Diff: 25.3, Sum: 164.4]
[Termination Attempts: Min: 1, Avg: 3.2, Max: 13, Diff: 12, Sum: 32]
[GC Worker Other (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.2]
[GC Worker Total (ms): Min: 6991.5, Avg: 6991.6, Max: 6991.7, Diff: 0.2, Sum: 69915.5]
[GC Worker End (ms): Min: 1185304.3, Avg: 1185304.3, Max: 1185304.3, Diff: 0.0]
[Code Root Fixup: 0.1 ms]
[Code Root Purge: 0.0 ms]
[Clear CT: 0.3 ms]
[Other: 26.0 ms]
[Choose CSet: 0.0 ms]
[Ref Proc: 25.3 ms]
[Ref Enq: 0.1 ms]
[Redirty Cards: 0.1 ms]
[Humongous Register: 0.2 ms]
[Humongous Reclaim: 0.0 ms]
[Free CSet: 0.2 ms]
[Eden: 2176.0M(2176.0M)->0.0B(2176.0M) Survivors: 320.0M->320.0M Heap: 40.6G(48.8G)->40.0G(48.8G)]
[Times: user=0.55 sys=46.58, real=7.02 secs]
Run Code Online (Sandbox Code Playgroud)
请阅读此处:复制(停止世界事件) - 这些是世界暂停将实时对象撤离或复制到新的未使用区域的停止.这可以通过记录为[GC暂停(年轻)]的年轻代区域来完成.或者记录为[GC暂停(混合)]的年轻和老一代区域.
为什么GCG1仍为此做一个“停止世界”?
因为G1并不是一个无休止的收集器,所以它只是一个低暂停时间的收集器。
我还认为-XX:MaxGCPauseMillis的默认值为200毫秒,为什么这个值违反29甚至50的倍数(请参见下文)?
是的,但这只是一个目标,而不是保证。许多事情可能导致它无法实现该目标。您有相当大的堆,这使事情变得更加困难,即失败更容易引起。
无论如何,GC调整过程始于通过以下方式启用详细的GC日志记录:
-Xloggc:<path to gc log file>
-XX:+PrintAdaptiveSizePolicy
-XX:+PrintGCDateStamps
-XX:+PrintGCTimeStamps
-XX:+PrintGCDetails
Run Code Online (Sandbox Code Playgroud)
然后通过GCViewer运行生成的日志以获取一般概述,然后返回阅读单个日志条目(有关此主题的答案/博客文章很多),以找出可能导致最坏行为的原因。根据原因,可以尝试各种补救措施。
对于跟踪垃圾收集器的总体工作方式和G1,必须有一些一般性的了解,以避免进行货物耕种。
我的应用程序有许多分配,可以很容易地称为“巨大分配”。
如果这确实是原因,那么当前的VM具有一些实验性选项可以更快地回收它们。
Run Code Online (Sandbox Code Playgroud)[Object Copy (ms): Min: 6964.1, Avg: 6973.0, Max: 6989.5, Diff: 25.3, Sum: 69730.4] [Times: user=0.55 sys=46.58, real=7.02 secs]
这意味着在做大部分应该由内存访问而不是系统调用组成的事情时,它花费了大部分时间在内核中。因此,交换活动或透明的大页面很可能是可疑的。
归档时间: |
|
查看次数: |
3723 次 |
最近记录: |