Understanding CMS GC Logs

本文详细解析了使用-XX:+PrintGCDetails和-XX:+PrintGCTimeStamps选项时产生的CMS垃圾回收日志。通过具体示例介绍了年轻代、老年代垃圾回收过程,包括初始标记、并发标记等阶段,并探讨了增量CMS模式及全垃圾回收触发的原因。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

 

http://blogs.sun.com/poonam/entry/understanding_cms_gc_logs

 

Understanding CMS GC Logs

 

CMS GC with -XX:+PrintGCDetails and -XX:+PrintGCTimeStamps prints a lot of information. Understanding this information can help in fine tuning various parameters of the application and CMS to achieve best performance.

Let's have a look at some of the CMS logs generated with 1.4.2_10:

39.910: [GC 39.910: [ParNew: 261760K->0K(261952K), 0.2314667 secs] 262017K->26386K(1048384K), 0.2318679 secs]

Young generation (ParNew) collection. Young generation capacity is 261952K and after the collection its occupancy drops down from 261760K to 0. This collection took 0.2318679 secs.

40.146: [GC [1 CMS-initial-mark: 26386K(786432K)] 26404K(1048384K), 0.0074495 secs]

Beginning of tenured generation collection with CMS collector. This is initial Marking phase of CMS where all the objects directly reachable from roots are marked and this is done with all the mutator threads stopped.

Capacity of tenured generation space is 786432K and CMS was triggered at the occupancy of 26386K.

40.154: [CMS-concurrent-mark-start]

Start of concurrent marking phase.
In Concurrent Marking phase, threads stopped in the first phase are started again and all the objects transitively reachable from the objects marked in first phase are marked here.

40.683: [CMS-concurrent-mark: 0.521/0.529 secs]

Concurrent marking took total 0.521 seconds cpu time and 0.529 seconds wall time that includes the yield to other threads also.

40.683: [CMS-concurrent-preclean-start]

Start of precleaning.
Precleaning is also a concurrent phase. Here in this phase we look at the objects in CMS heap which got updated by promotions from young generation or new allocations or got updated by mutators while we were doing the concurrent marking in the previous concurrent marking phase. By rescanning those objects concurrently, the precleaning phase helps reduce the work in the next stop-the-world “remark” phase.

40.701: [CMS-concurrent-preclean: 0.017/0.018 secs]

Concurrent precleaning took 0.017 secs total cpu time and 0.018 wall time.

40.704: [GC40.704: [Rescan (parallel) , 0.1790103 secs]40.883: [weak refs processing, 0.0100966 secs] [1 CMS-remark: 26386K(786432K)] 52644K(1048384K), 0.1897792 secs]

Stop-the-world phase. This phase rescans any residual updated objects in CMS heap, retraces from the roots and also processes Reference objects. Here the rescanning work took 0.1790103 secs and weak reference objects processing took 0.0100966 secs. This phase took total 0.1897792 secs to complete.

40.894: [CMS-concurrent-sweep-start]

Start of sweeping of dead/non-marked objects. Sweeping is concurrent phase performed with all other threads running.

41.020: [CMS-concurrent-sweep: 0.126/0.126 secs]

Sweeping took 0.126 secs.

41.020: [CMS-concurrent-reset-start]

Start of reset.

41.147: [CMS-concurrent-reset: 0.127/0.127 secs]

In this phase, the CMS data structures are reinitialized so that a new cycle may begin at a later time. In this case, it took 0.127 secs.

This was how a normal CMS cycle runs. Now let us look at some other CMS log entries:

197.976: [GC 197.976: [ParNew: 260872K->260872K(261952K), 0.0000688 secs]197.976: [CMS197.981: [CMS-concurrent-sweep: 0.516/0.531 secs]
(concurrent mode failure): 402978K->248977K(786432K), 2.3728734 secs] 663850K->248977K(1048384K), 2.3733725 secs]

This shows that a ParNew collection was requested, but it was not attempted because it was estimated that there was not enough space in the CMS generation to promote the worst case surviving young generation objects. We name this failure as “full promotion guarantee failure”.

Due to this, Concurrent Mode of CMS is interrupted and a Full GC is invoked at 197.981. This mark-sweep-compact stop-the-world Full GC took 2.3733725 secs and the CMS generation space occupancy dropped from 402978K to 248977K.

The concurrent mode failure can either be avoided by increasing the tenured generation size or initiating the CMS collection at a lesser heap occupancy by setting CMSInitiatingOccupancyFraction to a lower value and setting UseCMSInitiatingOccupancyOnly to true. The value for CMSInitiatingOccupancyFraction should be chosen appropriately because setting it to a very low value will result in too frequent CMS collections.

Sometimes we see these promotion failures even when the logs show that there is enough free space in tenured generation. The reason is 'fragmentation' - the free space available in tenured generation is not contiguous, and promotions from young generation require a contiguous free block to be available in tenured generation. CMS collector is a non-compacting collector, so can cause fragmentation of space for some type of applications. In his blog, Jon talks in detail on how to deal with this fragmentation problem:
http://blogs.sun.com/roller/page/jonthecollector?entry=when_the_sum_of_the

Starting with 1.5, for the CMS collector, the promotion guarantee check is done differently. Instead of assuming that the promotions would be worst case i.e. all of the surviving young generation objects would get promoted into old gen, the expected promotion is estimated based on recent history of promotions. This estimation is usually much smaller than the worst case promotion and hence requires less free space to be available in old generation. And if the promotion in a scavenge attempt fails, then the young generation is left in a consistent state and a stop-the-world mark-compact collection is invoked. To get the same functionality with UseSerialGC you need to explicitly specify the switch -XX:+HandlePromotionFailure.

283.736: [Full GC 283.736: [ParNew: 261599K->261599K(261952K), 0.0000615 secs] 826554K->826554K(1048384K), 0.0003259 secs]
GC locker: Trying a full collection because scavenge failed
283.736: [Full GC 283.736: [ParNew: 261599K->261599K(261952K), 0.0000288 secs]

Stop-the-world GC happening when a JNI Critical section is released. Here again the young generation collection failed due to “full promotion guarantee failure” and then the Full GC is being invoked.

CMS can also be run in incremental mode (i-cms), enabled with -XX:+CMSIncrementalMode. In this mode, CMS collector does not hold the processor for the entire long concurrent phases but periodically stops them and yields the processor back to other threads in application. It divides the work to be done in concurrent phases in small chunks(called duty cycle) and schedules them between minor collections. This is very useful for applications that need low pause times and are run on machines with small number of processors.

Some logs showing the incremental CMS.

2803.125: [GC 2803.125: [ParNew: 408832K->0K(409216K), 0.5371950 secs] 611130K->206985K(1048192K) icms_dc=4 , 0.5373720 secs]
2824.209: [GC 2824.209: [ParNew: 408832K->0K(409216K), 0.6755540 secs] 615806K->211897K(1048192K) icms_dc=4 , 0.6757740 secs]

Here, the scavenges took respectively 537 ms and 675 ms. In between these two scavenges, iCMS ran for a brief period as indicated by the icms_dc value, which indicates a duty-cycle. In this case the duty cycle was 4%. A simple calculation shows that the iCMS incremental step lasted for 4/100 * (2824.209 - 2803.125 - 0.537) = 821 ms, i.e. 4% of the time between the two scavenges.

Starting with 1.5, CMS has one more phase – concurrent abortable preclean. Abortable preclean is run between a 'concurrent preclean' and 'remark' until we have the desired occupancy in eden. This phase is added to help schedule the 'remark' phase so as to avoid back-to-back pauses for a scavenge closely followed by a CMS remark pause. In order to maximally separate a scavenge from a CMS remark pause, we attempt to schedule the CMS remark pause roughly mid-way between scavenges.

There is a second reason why we do this. Immediately following a scavenge there are likely a large number of grey objects that need rescanning. The abortable preclean phase tries to deal with such newly grey objects thus reducing a subsequent CMS remark pause.

The scheduling of 'remark' phase can be controlled by two jvm options CMSScheduleRemarkEdenSizeThreshold and CMSScheduleRemarkEdenPenetration. The defaults for these are 2m and 50% respectively. The first parameter determines the Eden size below which no attempt is made to schedule the CMS remark pause because the pay off is expected to be minuscule. The second parameter indicates the Eden occupancy at which a CMS remark is attempted.

After 'concurrent preclean' if the Eden occupancy is above CMSScheduleRemarkEdenSizeThreshold, we start 'concurrent abortable preclean' and continue precleanig until we have CMSScheduleRemarkEdenPenetration percentage occupancy in eden, otherwise we schedule 'remark' phase immediately.

7688.150: [CMS-concurrent-preclean-start]
7688.186: [CMS-concurrent-preclean: 0.034/0.035 secs]
7688.186: [CMS-concurrent-abortable-preclean-start]
7688.465: [GC 7688.465: [ParNew: 1040940K->1464K(1044544K), 0.0165840 secs] 1343593K->304365K(2093120K), 0.0167509 secs]
7690.093: [CMS-concurrent-abortable-preclean: 1.012/1.907 secs]
7690.095: [GC[YG occupancy: 522484 K (1044544 K)]7690.095: [Rescan (parallel) , 0.3665541 secs]7690.462: [weak refs processing, 0.0003850 secs] [1 CMS-remark: 302901K(1048576K)] 825385K(2093120K), 0.3670690 secs]

In the above log, after a preclean, 'abortable preclean' starts. After the young generation collection, the young gen occupancy drops down from 1040940K to 1464K. When young gen occupancy reaches 522484K which is 50% of the total capacity, precleaning is aborted and 'remark' phase is started.

Note that in 1.5, young generation occupancy also gets printed in the final remark phase.

For more detailed information and tips on GC tuning, please refer to the following documents:
http://java.sun.com/docs/hotspot/gc5.0/gc_tuning_5.html
http://java.sun.com/docs/hotspot/gc1.4.2/

内容概要:本书《Deep Reinforcement Learning with Guaranteed Performance》探讨了基于李雅普诺夫方法的深度强化学习及其在非线性系统最优控制中的应用。书中提出了一种近似最优自适应控制方法,结合泰勒展开、神经网络、估计器设计及滑模控制思想,解决了不同场景下的跟踪控制问题。该方法不仅保证了性能指标的渐近收敛,还确保了跟踪误差的渐近收敛至零。此外,书中还涉及了执行器饱和、冗余解析等问题,并提出了新的冗余解析方法,验证了所提方法的有效性和优越性。 适合人群:研究生及以上学历的研究人员,特别是从事自适应/最优控制、机器人学和动态神经网络领域的学术界和工业界研究人员。 使用场景及目标:①研究非线性系统的最优控制问题,特别是在存在输入约束和系统动力学的情况下;②解决带有参数不确定性的线性和非线性系统的跟踪控制问题;③探索基于李雅普诺夫方法的深度强化学习在非线性系统控制中的应用;④设计和验证针对冗余机械臂的新型冗余解析方法。 其他说明:本书分为七章,每章内容相对独立,便于读者理解。书中不仅提供了理论分析,还通过实际应用(如欠驱动船舶、冗余机械臂)验证了所提方法的有效性。此外,作者鼓励读者通过仿真和实验进一步验证书中提出的理论和技术。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值