From 074ad04477fd43442551d252e5975f01466d6d46 Mon Sep 17 00:00:00 2001 From: yoa1226 Date: Mon, 14 Oct 2024 22:21:45 +0800 Subject: [PATCH] gc-important component 1 --- .../2024-08-05-g1-gc-important-component.md | 358 +++++++++++++++++- assets/gc-important-component/card.png | Bin 0 -> 25104 bytes assets/gc-important-component/gc-alg-tri.png | Bin 0 -> 122359 bytes assets/gc-important-component/heap-divide.png | Bin 0 -> 40627 bytes assets/gc-important-component/region.png | Bin 0 -> 128125 bytes assets/gc-important-component/rset1.png | Bin 0 -> 22530 bytes assets/gc-important-component/rset2.png | Bin 0 -> 23033 bytes assets/gc-important-component/rset3.png | Bin 0 -> 98774 bytes assets/gc-important-component/rset4.png | Bin 0 -> 35646 bytes 9 files changed, 357 insertions(+), 1 deletion(-) create mode 100644 assets/gc-important-component/card.png create mode 100644 assets/gc-important-component/gc-alg-tri.png create mode 100644 assets/gc-important-component/heap-divide.png create mode 100644 assets/gc-important-component/region.png create mode 100644 assets/gc-important-component/rset1.png create mode 100644 assets/gc-important-component/rset2.png create mode 100644 assets/gc-important-component/rset3.png create mode 100644 assets/gc-important-component/rset4.png diff --git a/_posts/2024-08-05-g1-gc-important-component.md b/_posts/2024-08-05-g1-gc-important-component.md index fbdc22c..332a019 100644 --- a/_posts/2024-08-05-g1-gc-important-component.md +++ b/_posts/2024-08-05-g1-gc-important-component.md @@ -3,4 +3,360 @@ layout: post title: "G1 重要概念" date: 2024-08-05 11:00:00 +0200 tags: [GC, G1] ---- \ No newline at end of file +--- + + G1 是垃圾收集器技术发展史上的里程碑式的成果,开创了收集器面向局部收集的设计思路和基于 Region 的内存布局形式。G1 最早是在 2004 年 David Detlefs 等人的论文 Garbage-First Garbage Collection 中提出。自从 在 2009 年 3 月 JDK 6 Update 14 引入 Early Access 版本,15 年来 G1 的性能和功能得到巨大的提升和完善。 + +> Java 历史版本: [Java/Java SE: All Releases, End of Life, Release Date](https://versionlog.com/java/) + + +## G1 发展历史 + +```mermaid + timeline title G1 发展史 + 2004年 : 论文发表 + 2009年 : JDK 6 实验版本 + 2012年 : JDK 7 Oracle 认为能够商用 + 2015年 : JDK 8 提供并发的类卸载支持, Oracle 称之为全功能的垃圾收集器 + 2017年 : JDK 9 成为默认垃圾收集器 +``` + +```mermaid + timeline title G1 优化 + 2018 : JDK 10 Parallel Full GC for G1 + 2019 : JDK 12 Abortable Mixed Collections for G1 + 2019 : JDK 12 Promptly Return Unused Committed Memory from G1 + 2020 : JDK 14 NUMA-Aware Memory Allocation for G1 + 2021 : JDK 11-18 Optimize memory usage for G1 remembered sets + 2024 : JDK 22 Region Pinning for G1 + 2025 : JDK 24 JEP 475: Late Barrier Expansion for G1 +``` + +### 垃圾收集算法衡量指标 + +在 JVM 中负责管理应用堆内存的组件叫做垃圾收集器(garbage collector,简称 GC)。GC 管理着内存的分配和释放,具体来说管理着堆对象的整个生命周期。JVM 垃圾收集器的基础功是: + +1. 根据应用程序的要求尽快地分配内存。 +2. 高效率地检测应用程序已经不需要的内存进行回收。 + +对于优秀的垃圾收集算法有很多要求,有三点是需要重点讨论的,分别是 `throughput`、`latency`、`Memory footprint`。虽然有很多实现方式满足以上要求,但是某一种算法只能在某一个方面达到最优秀。基于此,JDK 提供了多种垃圾回收算法来应对不同的业务场景。 + +1. `Throughput` 表示在单位时间内所在的工作量,更多的工作量意味着更高的 throughput。 +2. `Latency`意味着单个操作所花费的时间,具体来说是垃圾收集期间 stop the world 的时间。 +3. `Memory footprint` 说的是垃圾收集需要的内存,比如与垃圾收集相关的数据结构,统计数据。 + +上述三个指标是相互联系的:更高的 throughput 会导致高 latency ,反之亦然,更低的 latency 会降低 throughput。而更低的 Memory footprint 的算法可能使得其他二者的指标变得更差。 + +理想的垃圾回收算法是更高的 throughput,更低的 lantency, 更低的 footprint。 + + + +### 垃圾收集器 + +针对不同的场景, JDK 21 提供五种不同类型垃圾收集器。 + +| Garbage Collector | Focus Area | Concepts | +| ---------------------------------------- | -------------------------- | ------------------------------------------------------------------------------ | +| Parallel | Throughput | Multithreaded stop-the-world (STW) compaction and generational collection | +| Garbage First (G1) | Balanced performance | Multithreaded STW compaction, concurrent liveness, and generational collection | +| Z Garbage Collector (ZGC) (since JDK 15) | Latency | Everything concurrent to the application | +| Shenandoah (since JDK 12) | Latency | Everything concurrent to the application | +| Serial | Footprint and startup time | Single-threaded STW compaction and generational collection | + +Parallel GC 是 JDK 8 及以前版本的默认垃圾收集器。它聚焦于 throughput 的最大化而稍微降低对 latency 的要求。 + +G1 从 JDK 9 开始成为默认垃圾收集器,它试图平衡 throughput 和 lantency 。 + +ZGC 和 Shenandoah GC 专注于低 lantency。ZGC 在 JDK 11 中引入,JDK 15 中达到生产可用,后续版本中逐渐增强,在 JDK 21 中加入分代收集功能 [ZGC history](https://wiki.openjdk.org/display/zgc)。Shenandoah GC 在 JDK 12 中开始引入,后续被下放到之前版的版本,根据 [Shenandoah history](https://wiki.openjdk.org/display/shenandoah),Shenandoah GC 在 JDK 8 及以后的长期支持版均可用,有望在 JDK 24 引入分代收集功能。 + +Serial GC 专注于 footprint 和 startup time,是单线程版的 Parallel GC。 + +> 在 throughput 优先的情况下,Parallel GC 比 G1 和 ZGC 都要好,见 [How fast is Java 21](https://timefold.ai/blog/java-21-performance)。 + +## G1 重要概念 + +### 堆划分 + +G1 是一个分代、增量收集、并行、大多数时间并发、少量停顿用户线程收集器,它能最大限度的满足用户设置的最大停顿时间。G1 是默认的垃圾收集器,也可以用 `-XX:+UseG1GC` 开启。使用参数 `-XX:MaxGCPauseMillis` 设置最大停顿时间,默认为 200 ms。 + +### Java 堆内存总体结构 + + + +G1 通过参数`-Xmx` 和 `-Xms` 设置最大最小堆内存。 + +G1 是分代收集器,将堆分成年轻代和老年代,年轻代的大小通过`-XX:G1NewSizePercent` 和 `-XX:G1MaxNewSizePercent` 来设置,前者默认值为 5,后者默认值为 60。意味着年轻代大小占总的堆大小为 5% ~ 60%,G1 会根据情况动态调整年轻代大小以满足最大停顿时间。 + +### region + +G1 开创了基于 region 的内存布局,如图所示,G1 将连续的堆内存分成多个大小相等的独立区域(Region),每个 Region 都可以根据需要扮演新生代或者老年代空间。Region 的大小通过 -XX:G1HeapRegionSize 指定,取值范围为 1MB ~ 32 MB,且应为 2 的 N 次幂。 + + + +> 注意:`-XX:NewSize` 和 `-XX:MaxNewSize`同样能设置新生大小,如果只有一个参数被设置值,那么新生代就会被固定为这个值,会影响暂停时间的控制。 + +JDK 18 突破了 region 最大内存 32MB 的限制,最大可以达到 512 M。下面是源码中对 region 大小的定义: + +```cpp +//src/hotspot/share/gc/g1/heapRegionBounds.hpp +static const size_t MIN_REGION_SIZE = 1024 * 1024; //1M +static const size_t MAX_ERGONOMICS_SIZE = 32 * 1024 * 1024; // 32M,G1 自动调节的最大值 +static const size_t MAX_REGION_SIZE = 512 * 1024 * 1024; //512 Mb +``` + +>细节请参考: [G1: Refactor remembered sets](https://bugs.openjdk.org/browse/JDK-8017163) 和 [8275056: Virtualize G1CardSet containers over heap region](https://github.com/openjdk/jdk/commit/1830b8da9028af430ee4791f310b5fc9cb1ff37d#diff-05a26063eefdc656c3ec8d13940777799a58f17cfdec601f6143785c3b78a5efR40)。 + +### card + +为了更好的管理内存,Java 将 Region 划分成多个 card,每个 card 是 512(2^9) 字节,G1 很多操作是以 card 为颗粒度管理的。 + + + +> G1 可以通过对象的地址,计算出对象所处的 region 和 card。 + +### 记忆集 + +G1 利用记忆集(Remembered Sets)解决分代收集和部分收集的问题,具体来说用于记录非收集区域指向收集区域的指针集合的抽象数据结构。由于 young GC(回收新生代) 和 mixed GC(回收新生代和部分老年代)都会回收整个新生代,那么记忆集只需要记录两类跨区域指针。 + +1. 老年代到新生代的指针。 +2. 老年代到老年代的指针。 + + + +如图,r1的记忆集记应该是{ (r6,[c12])},r6的记忆集记应该是 {(r7,[c14])}。 + +> 实际记录的是索引,是整数。 + + + +如上图,存在 R1 中 C card 指向 R0 A card,那么在 R0 的记忆集就会记录下类似 {(R1,[C])}。 + +> 实际上是 card C 中的对象指向 card A 中 的对象,但是记忆集记录的是 card。 + +当 R0 被回收时,存活的对象被转移(G1 称为 evacuate)到 R2 ,并且更新对应的记忆集。 + + + +记忆集在 G1 中扮演了非常重要的角色,是实现部分收集的关键技术,深入源码有助于我们深入理解其实现原理。 + +#### JDK 18 之前 + +在 G1 中每个 region 都有一个记忆集(后面简称 rset),每个 rset 根据记录信息的数量和颗粒度分成三个容器。从记录数量的从少到多、信息颗粒度从细到粗、遍历记忆集速度从快到慢分成 `_sparse_table`、`_fine_grain_regions`、`_coarse_map`。如果使用 Java 中数据结构对比理解,那么三个容器分别对应于 ` HashMap>()` 、`new HashMap()`、`BitMap`。 + +```cpp +// HeapRegion -> HeapRegionRemSet* _rem_set -> OtherRegionsTable _other_regions +class OtherRegionsTable VALUE_OBJ_CLASS_SPEC { + BitMap _coarse_map; + PerRegionTable** _fine_grain_regions; + SparsePRT _sparse_table; +} +``` + +其中 `SparsePRT` 的实现导致 region 最大只能为 32 M,`typedef uint16_t card_elem_t` 导致 card 索引最大为 2^16-1,即 region 中包含 card 最大数量 2^16 个,Region 的最大内存为 2^16 * 2^9 = 2^25 = 32MB。(2^9 = 512 byte, 是 card 的大小) + +```cpp +class SparsePRTEntry: public CHeapObj { + typedef uint16_t card_elem_t; + card_elem_t _cards[card_array_alignment]; +} +``` + +rset 添加的逻辑在 [OtherRegionsTable::add_reference](https://github.com/openjdk/jdk/blob/0b8a0e2b58dbdd5c9553e502212d32c033a5efb5/src/hotspot/share/gc/g1/heapRegionRemSet.cpp#L131),下面是伪代码: + +```cpp +var exist = find_in(_coarse_map, region_idx, card_idx); +if(exist) return; + +var exist = find_in(_fine_grain_regions,region_idx, card_idx); +if(exist) return; + +var res = add_card_to(_sparse_table,region_idx, card_idx); +if(res == SparsePRT::added) return ; + +add_card_to_fine_grain_regions_and_transfer(_fine_grain_regions,_sparse_table ,region_idx, card_idx) +``` + +#### JDK 18 + +JDK 18 之前存在,rset 存在很多性能方面的问题,特别是内存占用方面。 +[G1: Refactor remembered sets](https://bugs.openjdk.org/browse/JDK-8017163) 对问题描述的非常清楚,感兴趣可以认真阅读。文中提到优化之后的 rset 内存占用能减少 25%。 + +> The problems are that there is nothing between "no card at all" and "sparse" and in particular the difference between the capability to hold entries of "sparse" and "fine". I.e. memory usage difference when exceeding a "sparse" array (holding 128 entries at 32M regions, taking \~256 bytes) to fine that is able to hold 65k entries using 8kB is significant. + +其中提到缺少很多 “中间” 容器。 + +例如:使用 "sparse" 数组存储 32M 大小 region 的 128 个元素(card 索引)需要 256 字节(128 * 2, card index 使用 `uint16_t` 保存)。 如果有更多的元素进来,要升级成 “fine” 容器,则需要8kb(32M/512byte/8bit/1024),存储空间增加了32倍(8kb/256byte)。 + +```cpp +//G1HeapRegion rem_set -> G1HeapRegionRemSet _card_set +class G1CardSet : public CHeapObj { + G1CardSetHashTable* _table; +} + +class G1CardSetHashTable : public CHeapObj { + CardSetHash _table; + CHTScanTask _table_scanner; +} +using CardSetHash = ConcurrentHashTable; +``` + +reset 整体结构是一个 hashtable,底层使用的是 `ConcurrentHashTable`,为了保证易用性,使用 G1CardSet 对其进行封装。`hashtable` 中 key 存储 region index,value 指向的的是包含 card index 的容器。容器指针的定义是 `void*`。 + +```java +using ContainerPtr = void*; +static const uintptr_t ContainerInlinePtr = 0x0; +static const uintptr_t ContainerArrayOfCards = 0x1; +static const uintptr_t ContainerBitMap = 0x2; +static const uintptr_t ContainerHowl = 0x3 +``` +容器分成四种类型,对应四种标志位,标志位存储在指针中。 + +> 由于地址是按照 N 字节对齐的,标记位的存储并不影响原地址的正确性。Java 的指针压缩也是利用字节对齐实现的。 + + +容器初始化是 `ContainerInlinePtr` : + +```cpp +G1CardSetHashTableValue value(region_idx, G1CardSetInlinePtr()); +``` + +然后依据元素数量升级,注意 `ContainerBitMap` 只有作为嵌套类型在 `ContainerHowl` 才会被使用到。 + +`ContainerInlinePtr -> ContainerArrayOfCards -> ContainerHowl -> Full` + +对于 ContainerBitMap 没有作为直接容器使用,源码注释: + +1. ContainerHowl 能够很好的处理 card 存储,相比 ContainerBitMap 无足轻重。 +2. 在并发情况下,将 ContainerHowl 转换成 ContainerBitMap 非常困难。 + +在源码中可以看到升级流程: + +```cpp +bool G1CardSet::coarsen_container(ContainerPtr volatile* container_addr, ContainerPtr cur_container,uint card_in_region, bool within_howl) { + ContainerPtr new_container = nullptr; + switch (container_type(cur_container)) { + case ContainerArrayOfCards: { + //如果当前容器被 ContainerHowl 包含,则升级成 ContainerBitMap, + //反之则升级成 ContainerHowl + new_container = create_coarsened_array_of_cards(card_in_region, within_howl); + break; + } + case ContainerBitMap: { + new_container = FullCardSet; + break; + } + case ContainerInlinePtr: { + //升级为 ContainerArrayOfCards + uint8_t* data = allocate_mem_object(ContainerArrayOfCards); + break; + } + case ContainerHowl: { + new_container = FullCardSet; // anything will do at this point. + break; + } +// omit + } +``` + +`ContainerHowl` 嵌套容器升级流程代码和上述一样,此时 within_howl 位 true,升级顺序如下: +`Free -> ContainerInlinePtr -> ContainerArrayOfCards -> ContainerBitMap -> Full` + +#### ContainerInlinePtr + +本文着重说一下 ContainerInlinePtr的结构, 其他容器读者可自行查阅源码。 + +ContainerInlinePtr 使用 64 位(64位机器)指针存储,最低两位 bit 为 00 表示容器类型。剩下最低三位表示存储 card 的数量,余下的高位存储 card。ContainerInlinePtr 只能存储 3 至 5 个 card 信息。 + +```cpp// MSB LSB +// +------+ +---------------+--------------+-----+ +// |unused| ... | card_index1 | card_index0 |SSS00| +// +------+ +---------------+--------------+-----+ +``` + +举个例子,对于 8M 大小的 region,card 的编号从 0 到 16383(8\*1024\*1024/512)。14 个bit才能表示 16383 (2^14-1)。最多能存储 4 个(4\*14 + 5 = 61 bit)。 + +#### 添加操作 + +添加操作由函数 `add_reference` 完成,例如函数 `do_oop_work` 会调用它。`add_reference` 实现细节读者可自行查阅。 + +下面函数参数 p 是指向源对象属性的指针,通过这个指针可以获取源对象属性所在的 region、card,同样可以获取目标对象的所在的 region、 card,体现了指针的强大之处。 + +```cpp +inline void G1ConcurrentRefineOopClosure::do_oop_work(T* p) { + T o = RawAccess::oop_load(p); + oop obj = CompressedOops::decode_not_null(o); //目标对象 + //目标对象的记忆集 + G1HeapRegionRemSet* to_rem_set = _g1h->heap_region_containing(obj)->rem_set(); + + if (to_rem_set->is_tracked()) {//将源对象添加到目标对象的记忆集中 + to_rem_set->add_reference(p, _worker_id); + } +} +``` + +用下面的图表示老年代跨 region 引用,p 是指向某个源对象的属性,此属性又指向目标对象。 + + + +#### 遍历操作 + +在垃圾收集阶段需要对记忆集进行遍历。记忆集遍历时需要借助于 `CHTScanTask _table_scanner` ,并且每次遍历之前都需要调用 `reset_table_scanner` 重置。 + +```cpp + // 垃圾收集遍历记忆集传入 at_safepoint 为 true +void G1CardSet::iterate_containers(ContainerPtrClosure* cl, bool at_safepoint) { + //omit + _table->iterate_safepoint(do_value); +} + +template + void iterate_safepoint(SCAN_FUNC& scan_f) { + _table_scanner.do_safepoint_scan(scan_f); + } + +void reset_table_scanner(uint claim_size) { + _table_scanner.set(&_table, claim_size); + } +``` + +#### 记忆集的优化 + +[8336086: G1: Use one G1CardSet instance for all young regions](https://github.com/openjdk/jdk/commit/f536f5ab68235d27e9708674f707bcbff7840730#diff-9de15630db460d66fdee5ec408be02b3275a2fbf32764f9fb2910b0d1bff7e3aR2695) 对 G1 记忆集进行优化,所有年轻代 region 共享一个记忆集,将在 JDK 24 中发布。优化基于两点: + +1. 年轻代之间跨 region 引用并不需要记录。 +2. GC 时会回收所有年轻代 region。 + +在堆中申明全局的 G1CardSet 类型的字段 _young_regions_cardset,并且在在堆初始化的时候创建好,当申请一个新的 region 时,将堆中全局的 _young_regions_cardset 赋值给新的 region。 + + +```cpp +class G1CollectedHeap : public CollectedHeap { + G1CardSet _young_regions_cardset; +} +//堆初始化的时候创建 +_young_regions_cardset(card_set_config(), &_young_regions_cardset_mm) + +//G1CollectedHeap::set_region_short_lived_locked-> G1HeapRegion::install_group_cardset + +void install_group_cardset(G1CardSet* group_cardset) { + _card_set = group_cardset; // 堆中全局的 `G1CardSet` 赋值给新的 region。 +} +``` + +> 针对老年 region rset 的优化正在进行。 + +### 写屏障 + +### 线程缓冲区 + +## G1 收集阶段 + +### GC 日志 + +### Young GC + +### 并发标记 + +### Full GC + + diff --git a/assets/gc-important-component/card.png b/assets/gc-important-component/card.png new file mode 100644 index 0000000000000000000000000000000000000000..739083f3e3aab36a745a794d0cf1d6efc1e90dd4 GIT binary patch literal 25104 zcmeFZ2T+q++ct_7x2UKnY(ZeNMNz5>g4D1$uJ4o+RLkUE;B3luVj#Lo?B29V; 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