为什么我提高内存时更频繁地获得 GC?

Why do I get GC more often when I raise memory?

我有一个关于 g1gc 的问题。

这些是堆使用图。

上面是-Xms4g -Xmx4g.
最下面是-Xms8g -Xmx8g.

我不知道为什么 8g 选项导致 g1gc 更频繁地发生。其他选项全部默认。

并且服务器规格是 40 个逻辑进程。

ps. What are the proper tuning options?


附加问题

内存分配是否可以更快,因为内存大小越大->区域大小越大?


gc.log

4G gc.log

2019-05-07T21:03:42.093+0900: 10.280: [GC pause (G1 Evacuation Pause) (young), 0.1785373 secs]
   [Parallel Time: 43.4 ms, GC Workers: 28]
      [GC Worker Start (ms): Min: 10280.0, Avg: 10280.1, Max: 10280.6, Diff: 0.6]
      [Ext Root Scanning (ms): Min: 0.0, Avg: 0.4, Max: 0.8, Diff: 0.8, Sum: 12.0]
      [Update RS (ms): Min: 0.8, Avg: 1.1, Max: 1.6, Diff: 0.8, Sum: 31.5]
         [Processed Buffers: Min: 0, Avg: 2.0, Max: 3, Diff: 3, Sum: 56]
      [Scan RS (ms): Min: 0.0, Avg: 0.4, Max: 0.7, Diff: 0.7, Sum: 10.9]
      [Code Root Scanning (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.0]
      [Object Copy (ms): Min: 38.0, Avg: 38.5, Max: 39.9, Diff: 1.9, Sum: 1079.0]
      [Termination (ms): Min: 1.3, Avg: 2.6, Max: 3.2, Diff: 1.9, Sum: 74.1]
         [Termination Attempts: Min: 413, Avg: 769.6, Max: 855, Diff: 442, Sum: 21549]
      [GC Worker Other (ms): Min: 0.0, Avg: 0.1, Max: 0.2, Diff: 0.1, Sum: 2.0]
      [GC Worker Total (ms): Min: 42.7, Avg: 43.2, Max: 43.4, Diff: 0.7, Sum: 1209.5]
      [GC Worker End (ms): Min: 10323.3, Avg: 10323.3, Max: 10323.4, Diff: 0.1]
   [Code Root Fixup: 0.0 ms]
   [Code Root Purge: 0.0 ms]
   [Clear CT: 0.4 ms]
   [Other: 134.7 ms]
      [Choose CSet: 0.0 ms]
      [Ref Proc: 132.4 ms]
      [Ref Enq: 0.9 ms]
      [Redirty Cards: 0.3 ms]
      [Humongous Register: 0.1 ms]
      [Humongous Reclaim: 0.0 ms]
      [Free CSet: 0.7 ms]
   [Eden: 928.0M(928.0M)->0.0B(828.0M) Survivors: 26.0M->120.0M Heap: 1193.0M(4096.0M)->409.0M(4096.0M)]
Heap after GC invocations=8 (full 0):
 garbage-first heap   total 4194304K, used 418816K [0x00000006c0000000, 0x00000006c0204000, 0x00000007c0000000)
  region size 2048K, 60 young (122880K), 60 survivors (122880K)
 Metaspace       used 28525K, capacity 30824K, committed 31104K, reserved 1077248K
  class space    used 3583K, capacity 4166K, committed 4224K, reserved 1048576K
}
 [Times: user=1.21 sys=0.08, real=0.18 secs]
{Heap before GC invocations=8 (full 0):
 garbage-first heap   total 4194304K, used 744448K [0x00000006c0000000, 0x00000006c0204000, 0x00000007c0000000)
  region size 2048K, 219 young (448512K), 60 survivors (122880K)
 Metaspace       used 28525K, capacity 30824K, committed 31104K, reserved 1077248K
  class space    used 3583K, capacity 4166K, committed 4224K, reserved 1048576K
2019-05-07T21:03:42.895+0900: 11.082: [GC pause (G1 Evacuation Pause) (young), 0.0505563 secs]
   [Parallel Time: 11.6 ms, GC Workers: 28]
      [GC Worker Start (ms): Min: 11082.3, Avg: 11082.6, Max: 11083.6, Diff: 1.3]
      [Ext Root Scanning (ms): Min: 0.0, Avg: 0.4, Max: 0.8, Diff: 0.8, Sum: 9.9]
      [Update RS (ms): Min: 0.4, Avg: 1.0, Max: 1.5, Diff: 1.1, Sum: 29.4]
         [Processed Buffers: Min: 1, Avg: 1.8, Max: 3, Diff: 2, Sum: 50]
      [Scan RS (ms): Min: 0.8, Avg: 1.2, Max: 1.4, Diff: 0.6, Sum: 32.4]
      [Code Root Scanning (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.0]
      [Object Copy (ms): Min: 8.3, Avg: 8.4, Max: 8.6, Diff: 0.2, Sum: 236.3]
      [Termination (ms): Min: 0.0, Avg: 0.1, Max: 0.1, Diff: 0.1, Sum: 2.8]
         [Termination Attempts: Min: 1, Avg: 42.7, Max: 52, Diff: 51, Sum: 1195]
      [GC Worker Other (ms): Min: 0.0, Avg: 0.1, Max: 0.2, Diff: 0.1, Sum: 2.0]
      [GC Worker Total (ms): Min: 10.2, Avg: 11.2, Max: 11.5, Diff: 1.3, Sum: 312.9]
      [GC Worker End (ms): Min: 11093.7, Avg: 11093.8, Max: 11093.8, Diff: 0.1]
   [Code Root Fixup: 0.0 ms]
   [Code Root Purge: 0.0 ms]
   [Clear CT: 0.3 ms]
   [Other: 38.6 ms]
      [Choose CSet: 0.0 ms]
      [Ref Proc: 37.0 ms]
      [Ref Enq: 0.5 ms]
      [Redirty Cards: 0.3 ms]
      [Humongous Register: 0.1 ms]
      [Humongous Reclaim: 0.0 ms]
      [Free CSet: 0.5 ms]
   [Eden: 318.0M(252.0M)->0.0B(1052.0M) Survivors: 120.0M->48.0M Heap: 727.0M(4096.0M)->397.0M(4096.0M)]
Heap after GC invocations=9 (full 0):
 garbage-first heap   total 4194304K, used 406528K [0x00000006c0000000, 0x00000006c0204000, 0x00000007c0000000)
  region size 2048K, 24 young (49152K), 24 survivors (49152K)
 Metaspace       used 28525K, capacity 30824K, committed 31104K, reserved 1077248K
  class space    used 3583K, capacity 4166K, committed 4224K, reserved 1048576K
}
 [Times: user=0.34 sys=0.02, real=0.05 secs]
{Heap before GC invocations=9 (full 0):
 garbage-first heap   total 4194304K, used 912384K [0x00000006c0000000, 0x00000006c0204000, 0x00000007c0000000)
  region size 2048K, 271 young (555008K), 24 survivors (49152K)
 Metaspace       used 29461K, capacity 31868K, committed 32256K, reserved 1077248K
  class space    used 3681K, capacity 4237K, committed 4352K, reserved 1048576K

8G gc.log

2019-05-05T02:39:16.996+0900: 201016.724: [GC pause (G1 Evacuation Pause) (young), 0.0336675 secs]
   [Parallel Time: 12.9 ms, GC Workers: 28]
      [GC Worker Start (ms): Min: 201016724.7, Avg: 201016724.9, Max: 201016725.0, Diff: 0.2]
      [Ext Root Scanning (ms): Min: 0.8, Avg: 1.2, Max: 5.2, Diff: 4.4, Sum: 32.4]
      [Update RS (ms): Min: 0.0, Avg: 3.1, Max: 3.5, Diff: 3.5, Sum: 87.7]
         [Processed Buffers: Min: 0, Avg: 11.1, Max: 30, Diff: 30, Sum: 310]
      [Scan RS (ms): Min: 0.1, Avg: 0.3, Max: 0.3, Diff: 0.2, Sum: 7.3]
      [Code Root Scanning (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.1]
      [Object Copy (ms): Min: 6.9, Avg: 7.5, Max: 7.7, Diff: 0.8, Sum: 211.2]
      [Termination (ms): Min: 0.2, Avg: 0.3, Max: 0.4, Diff: 0.2, Sum: 9.0]
         [Termination Attempts: Min: 105, Avg: 124.7, Max: 146, Diff: 41, Sum: 3491]
      [GC Worker Other (ms): Min: 0.0, Avg: 0.1, Max: 0.2, Diff: 0.2, Sum: 3.2]
      [GC Worker Total (ms): Min: 12.4, Avg: 12.5, Max: 12.7, Diff: 0.4, Sum: 350.8]
      [GC Worker End (ms): Min: 201016737.3, Avg: 201016737.4, Max: 201016737.5, Diff: 0.2]
   [Code Root Fixup: 0.0 ms]
   [Code Root Purge: 0.0 ms]
   [Clear CT: 0.7 ms]
   [Other: 20.0 ms]
      [Choose CSet: 0.0 ms]
      [Ref Proc: 17.2 ms]
      [Ref Enq: 0.2 ms]
      [Redirty Cards: 0.3 ms]
      [Humongous Register: 0.1 ms]
      [Humongous Reclaim: 0.0 ms]
      [Free CSet: 1.7 ms]
   [Eden: 4864.0M(4864.0M)->0.0B(4868.0M) Survivors: 48.0M->44.0M Heap: 5968.1M(8192.0M)->1091.2M(8192.0M)]
Heap after GC invocations=19405 (full 0):
 garbage-first heap   total 8388608K, used 1117388K [0x00000005c0000000, 0x00000005c0404000, 0x00000007c0000000)
  region size 4096K, 11 young (45056K), 11 survivors (45056K)
 Metaspace       used 187853K, capacity 205120K, committed 210176K, reserved 1232896K
  class space    used 22574K, capacity 25471K, committed 26368K, reserved 1048576K
}
 [Times: user=0.39 sys=0.00, real=0.04 secs]
{Heap before GC invocations=19405 (full 0):
 garbage-first heap   total 8388608K, used 6106497K [0x00000005c0000000, 0x00000005c0404000, 0x00000007c0000000)
  region size 4096K, 1228 young (5029888K), 11 survivors (45056K)
 Metaspace       used 187853K, capacity 205120K, committed 210176K, reserved 1232896K
  class space    used 22574K, capacity 25471K, committed 26368K, reserved 1048576K
2019-05-05T02:39:33.830+0900: 201033.558: [GC pause (G1 Evacuation Pause) (young), 0.0373282 secs]
2019-05-05T02:39:33.830+0900: 201033.558: [GC pause (G1 Evacuation Pause) (young), 0.0373282 secs]
   [Parallel Time: 13.9 ms, GC Workers: 28]
      [GC Worker Start (ms): Min: 201033558.4, Avg: 201033558.5, Max: 201033558.6, Diff: 0.2]
      [Ext Root Scanning (ms): Min: 0.8, Avg: 1.2, Max: 4.5, Diff: 3.7, Sum: 32.5]
      [Update RS (ms): Min: 0.0, Avg: 2.8, Max: 3.1, Diff: 3.1, Sum: 77.4]
         [Processed Buffers: Min: 0, Avg: 10.3, Max: 31, Diff: 31, Sum: 289]
      [Scan RS (ms): Min: 0.1, Avg: 0.3, Max: 0.3, Diff: 0.3, Sum: 7.1]
      [Code Root Scanning (ms): Min: 0.0, Avg: 0.0, Max: 0.0, Diff: 0.0, Sum: 0.1]
      [Object Copy (ms): Min: 8.5, Avg: 8.8, Max: 8.9, Diff: 0.4, Sum: 246.0]
      [Termination (ms): Min: 0.3, Avg: 0.4, Max: 0.5, Diff: 0.2, Sum: 12.0]
         [Termination Attempts: Min: 135, Avg: 156.5, Max: 175, Diff: 40, Sum: 4382]
      [GC Worker Other (ms): Min: 0.0, Avg: 0.1, Max: 0.2, Diff: 0.2, Sum: 3.3]
      [GC Worker Total (ms): Min: 13.3, Avg: 13.5, Max: 13.7, Diff: 0.3, Sum: 378.4]
      [GC Worker End (ms): Min: 201033571.9, Avg: 201033572.0, Max: 201033572.1, Diff: 0.2]
   [Code Root Fixup: 0.0 ms]
   [Code Root Purge: 0.0 ms]
   [Clear CT: 0.8 ms]
   [Other: 22.6 ms]
      [Choose CSet: 0.0 ms]
      [Ref Proc: 18.5 ms]
      [Ref Enq: 0.3 ms]
      [Redirty Cards: 1.0 ms]
      [Humongous Register: 0.1 ms]
      [Humongous Reclaim: 0.0 ms]
      [Free CSet: 2.1 ms]
   [Eden: 4868.0M(4868.0M)->0.0B(4880.0M) Survivors: 44.0M->32.0M Heap: 5963.4M(8192.0M)->1082.0M(8192.0M)]
Heap after GC invocations=19406 (full 0):
 garbage-first heap   total 8388608K, used 1107927K [0x00000005c0000000, 0x00000005c0404000, 0x00000007c0000000)
  region size 4096K, 8 young (32768K), 8 survivors (32768K)
 Metaspace       used 187853K, capacity 205120K, committed 210176K, reserved 1232896K
  class space    used 22574K, capacity 25471K, committed 26368K, reserved 1048576K
}
 [Times: user=0.41 sys=0.00, real=0.04 secs]
{Heap before GC invocations=19406 (full 0):
 garbage-first heap   total 8388608K, used 6122963K [0x00000005c0000000, 0x00000005c0404000, 0x00000007c0000000)
  region size 4096K, 1228 young (5029888K), 8 survivors (32768K)
 Metaspace       used 187853K, capacity 205120K, committed 210176K, reserved 1232896K
  class space    used 22574K, capacity 25471K, committed 26368K, reserved 1048576K

根据你的两个图表,你的服务器似乎在更短的时间内分配了更多的内存。正如您在自己的图片上看到的那样,第一种情况是当内存使用量达到 3G 时执行混合集合,第二种情况假设为 5G。但这取决于您的应用程序的内存分配模式。 G1 gc 尝试在不牺牲吞吐量的情况下满足 gc max pause(由 XX:MaxGCPauseMillis= 设置,默认为 500ms)。

设置了G1GC的JVM会通过构造一个名为region的内存块来启动,不区分New/Survivor/Old物理内存。逻辑上有New/Survivor/Old,但物理上没有地址分隔。

对象在任意region创建,对象的referrer信息存储在Remember set中(使用整个Heap的5% level)。 记忆集是一种数据结构,可以很容易地知道哪个区域被分配了一个带有引用的对象。 (跟踪该地区的参考资料)

如果要创建一个大于region大小的object,会在多个region上创建一个Object,这组region称为Humongous。此信息也存储在记忆集中。

区域大小可以从 1 MB 到 32 MB 不等,具体取决于堆大小。下面的 table 显示了如果区域大小未明确设置,将根据最小堆大小选择的区域大小。

|---------------------|------------------|
|    Min Heap Size    |   Region Size    |
|---------------------|------------------|
|     heap < 4GB      |       1MB        |
|---------------------|------------------|
|  4GB <= heap < 8GB  |       2MB        |
|---------------------|------------------|
|  8GB <= heap < 16GB |       4MB        |
|---------------------|------------------|
| 16GB <= heap < 32GB |       8MB        |
|---------------------|------------------|
| 32GB <= heap < 64GB |      16MB        |
|---------------------|------------------|
|     64GB < heap     |      32MB        |
|---------------------|------------------|

因此,在您的情况下,区域大小的计算方式会有所不同。 此外,内存分配模式可能因您的应用程序而异。 为了找到更准确的原因,我们需要垃圾收集日志。

您可以设置InitiatingheapOccupancyPercent让后台线程启动时间。堆使用量与总堆大小的比率。减小该值可以让您快速启动后台线程。默认值为 45。但是,如果该值太小,垃圾回收将 运行 过于频繁。它需要 CPU 个周期,并且可能会影响应用程序本身的性能。

如您所知,链锯图是健康的应用程序。 因此,即使不做额外设置也没有太大问题。


额外:可以帮助您解决问题的错误报告

Bug-8151176中的描述指的是为了实际计算IHOP

而计算old gen occupancy/total heap size

这意味着年轻一代的职业完全被忽略了。即如果年轻代的fraction大于IHOP,则并发循环无法启动。

The reason is that static IHOP starts if old gen occupancy exceeds a fixed percentage of the current heap capacity. If either the user or ergonomics decide that the old gen cannot be larger than that fraction of the heap capacity that triggers concurrent mark, marking will never start.

我想知道更频繁的垃圾回收是否真的发生了,因为你可以更快地分配内存。

如果您查看图表及其比例,第一个显示应用程序能够在大约 12 秒内分配大约 2GB,而 GC 未 运行ning。相比之下,第二张图在大约 6 秒内显示大约 2.5GB,而 GC 未 运行ning。

如果应用程序能够以两倍以上的速率进行分配,则意味着产生了两倍以上的垃圾量。

接下来比较一下两个锯齿图的up-slopes和down-slopes。在第一个中,up-slopes 不均匀且比 down-slopes 更浅。在第二个中,斜坡更平滑,up-slopes 比 down-slopes.

更陡

所以这是一个理论...

在第一种情况下(较小的堆),当收集器空闲时,某些东西正在减慢分配速率......或标记。

在第二种情况下(更大的堆),分配速度更快,这让 GC 要做更多的工作。更多的工作意味着它需要更频繁地 运行。如果我们假设这种更快的分配率也对应于更多 CPU 应用程序线程的利用率,并且在 GC 删除对象时保持更快的分配率 + 应用程序线程 activity,那么这可能是从 GC 线程窃取周期,导致回收率变慢(c.f。down-slopes)。


另一个理论(没有任何证据支持!)是您的应用程序正在大量使用软引用/弱引用来实现缓存。更多的内存可能意味着更大的缓存,这可能会以 "interesting" 方式改变应用程序的行为。例如,它可以导致更快的请求处理和(因此)更快 turn-over 与请求关联的 short-lived 个对象。


这些理论都很站不住脚。我们确实需要有关您的应用程序的更多信息和更多指标。