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+  <article class="page" itemscope itemtype="http://schema.org/CreativeWork";>
+    <meta itemprop="headline" 
content="ServiceComb中的数据最终一致性方案 - part 2">
+    <meta itemprop="description" 
content="ServiceComb中的分布式Saga设计">
+    <meta itemprop="datePublished" content="September 16, 2017">
+    <meta itemprop="dateModified" content="September 16, 2017">
+
+    <div class="page__inner-wrap">
+      
+        
+          <header>
+            <h1 class="page__title" 
itemprop="headline">ServiceComb中的数据最终一致性方案 - part 2
+</h1>
+            
+              <p class="page__meta"><i class="fa fa-clock-o" 
aria-hidden="true"></i> 
+
+
+
+
+  少于 1 分钟 阅读
+
+</p>
+            
+          </header>
+        
+      
+
+      <section class="page__content" itemprop="text">
+        <p>在我的前一篇<a href="/cn/docs/distributed_saga_1/">文章
</a>，我谈到怎么用<a 
href="https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf";>Saga</a>解决行程规划应用的数据一致性问题。
+现在让我们尝试设计实现Saga。</p>
+
+<h2 id="saga-log">Saga Log</h2>
+<p>Saga保证所有的子事务都得以完成或补偿，但Saga系统本身也可能会崩溃。Saga崩溃时可能处于以下å‡
 ä¸ªçŠ¶æ€ï¼š</p>
+<ul>
+  <li>Saga收到事务请求，但尚未开始。因
子事务对应的微服务状态未被Saga修改，我们什么也不需要做。</li>
+  <li>一些子事务已经完成。重启后，Saga必
须接着上次完成的事务恢复。</li>
+  
<li>子事务已开始，但尚未完成。由于远程服务可能已完成事务，也可能事务失败，甚至服务请求è¶
…
时，saga只能重新发起之前未确认完成的子事务。这意味着子事务å¿
…须幂等。</li>
+  <li>子事务失败，其补偿事务尚未开始。Saga必
须在重启后执行对应补偿事务。</li>
+  
<li>补偿事务已开始但尚未完成。解决方案与上一个相同。这意味着补偿事务也å¿
…须是幂等的。</li>
+  <li>所有子事务或补偿事务均已完成，与第一种情
况相同。</li>
+</ul>
+
+<p>为了恢复到上述状态，我们必
须追踪子事务及补偿事务的每一步。我们决定通过事件的方式达到以上要求，并将以下事件保存在名为saga
 log的持久存储中：</p>
+<ul>
+  <li><strong>Saga started event</strong> 保存整个saga请求，其中包
括多个事务/补偿请求</li>
+  <li><strong>Transaction started event</strong> 保存对应事务请求</li>
+  <li><strong>Transaction ended event</strong> 保存对应事务请求及å…
¶å›žå¤</li>
+  <li><strong>Transaction aborted event</strong> 
保存对应事务请求和失败的原因</li>
+  <li><strong>Transaction compensated event</strong> 
保存对应补偿请求及其回复</li>
+  <li><strong>Saga ended event</strong> æ 
‡å¿—着saga事务请求的结束，不需要保存任何内容</li>
+</ul>
+
+<p><img src="/assets/images/saga.events.png" alt="Events" class="align-center" 
/></p>
+
+<p>通过将这些事件持久化在saga 
log中，我们可以将saga恢复到上述任何状态。</p>
+
+<p>由于Saga只需要做事件的持久化，而事件内
容以JSON的形式存储，Saga 
log的实现非常灵活，数据库（SQL或NoSQL），持久
消息队列，甚至普通文件可以用作事件存储，
+当然有些能更快得帮saga恢复状态。</p>
+
+<h2 id="saga请求的数据结构">Saga请求的数据结构</h2>
+<p>在我们的业务场景下，航班预订、租车、和é…
’店预订没有依赖å…
³ç³»ï¼Œå¯ä»¥å¹¶è¡Œå¤„理，但对于我们的客户来说，只在所有预订成功后一次付费更åŠ
 å‹å¥½ã€‚
+那么这四个服务的事务关系可以用下图表示：</p>
+
+<p><img src="/assets/images/saga.transactions.png" alt="Transactions" 
class="align-center" /></p>
+
+<p>将行程规划请求的数据结构实现为<a 
href="https://en.wikipedia.org/wiki/Directed_acyclic_graph";>有向非循环图</a>恰好合适。
+图的根是saga启动任务，叶是saga结束任务。</p>
+
+<p><img src="/assets/images/saga.graph.png" alt="Request Graph" 
class="align-center" /></p>
+
+<h2 id="parallel-saga">Parallel Saga</h2>
+<p>如上所述，航班预订，租车和é…
’店预订可以并行处理。但是这样做会造
成另一个问题：如果航班预订失败，而租车正在处理怎么办？我们不能一直等å¾
…租车服务回应，
+因为不知道需要等多久。</p>
+
+<p>最好的办法是再次发送租车请求，获得回应，以便我们能够继续补偿操作。但如果租车服务永不回应，我们可能需要采取回退措施，比如手动干预。</p>
+
+<p>超
时的预订请求可能最后仍被租车服务收到，这时服务已经处理了相同的预订和取消请求。</p>
+
+<p><img src="/assets/images/saga.commutative.png" alt="Network Latency" 
class="align-center" /></p>
+
+<p>因此，服务的实现必
须保证补偿请求执行以后，再次收到的对应事务请求无效。
+Caitie McCaffrey在她的演讲<a 
href="https://www.youtube.com/watch?v=1H6tounpnG8";>Distributed Sagas: A 
Protocol for Coordinating 
Microservices</a>中把这个称为<strong>可交换的补偿请求 
(commutative compensating request)</strong> 。</p>
+
+<h2 id="acid-and-saga">ACID and Saga</h2>
+<p><a href="https://en.wikipedia.org/wiki/ACID";>ACID</a>是å…
·æœ‰ä»¥ä¸‹å±žæ€§çš„一致性模型:</p>
+<ul>
+  <li>原子性（Atomicity）</li>
+  <li>一致性（Consistency）</li>
+  <li>隔离性（Isolation）</li>
+  <li>持久性（Durability）</li>
+</ul>
+
+<p>Saga不提供ACID保证，因
为原子性和隔离性不能得到满足。原<a 
href="https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf";>论文</a>描述如下：</p>
+<blockquote>
+  <p>full atomicity is not provided. That is, sagas may view the partial 
results of other sagas [<a 
href="https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf";>1</a>]</p>
+</blockquote>
+
+<p>通过saga log，saga可以保证一致性和持久性。</p>
+
+<h2 id="saga-架构">Saga 架构</h2>
+<p>最后，我们的Saga架构如下</p>
+
+<p><img src="/assets/images/saga.design.png" alt="Saga Architecture" 
class="align-center" /></p>
+
+<ul>
+  <li>Saga Execution Component解析请求JSON并构建请求图</li>
+  <li>TaskRunner 用任务队列确保请求的执行顺序</li>
+  <li>TaskConsumer 处理Saga任务，将事件写入saga 
log，并将请求发送到远程服务</li>
+</ul>
+
+<h2 id="总结">总结</h2>
+<p>本文讨论了如何实现saga，通过saga 
log来保存事务和补偿事件。也提到如何从saga log中持久
化的事件恢复崩溃的saga系统。
+为了满足saga的一致性保证，微服务的设计有以下几
个要求：</p>
+<ul>
+  <li>事务和赔偿请求必须幂等</li>
+  <li>补偿请求必须可交换（commutative）</li>
+</ul>
+
+<h2 id="references">References</h2>
+<ol>
+  <li><a 
href="https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf";>Original 
Paper on Sagas</a> by By Hector Garcia-Molina &amp; Kenneth Salem</li>
+</ol>
+
+
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+    <meta itemprop="headline" 
content="ServiceComb中的数据最终一致性方案 - part 3">
+    <meta itemprop="description" content="Saga和å…
¶ä»–数据一致性解决方案相比有什么不同之处？">
+    <meta itemprop="datePublished" content="September 18, 2017">
+    <meta itemprop="dateModified" content="September 18, 2017">
+
+    <div class="page__inner-wrap">
+      
+        
+          <header>
+            <h1 class="page__title" 
itemprop="headline">ServiceComb中的数据最终一致性方案 - part 3
+</h1>
+            
+              <p class="page__meta"><i class="fa fa-clock-o" 
aria-hidden="true"></i> 
+
+
+
+
+  少于 1 分钟 阅读
+
+</p>
+            
+          </header>
+        
+      
+
+      <section class="page__content" itemprop="text">
+        <p>在我的前一篇<a href="/cn/docs/distributed_saga_2/">文章
</a>，我谈到了ServiceComb下的<a 
href="https://en.wikipedia.org/wiki/Two-phase_commit_protocol";>Saga</a>是怎么设计的。
+然而，业界还有å…
¶ä»–数据一致性解决方案，如两阶段提交（2PC）和Try-Confirm / 
Cancel（TCC）。那saga相比之下有什么特别？</p>
+
+<h2 id="两阶段提交-two-phase-commit-2pc">两阶段提交 Two-Phase Commit 
(2PC)</h2>
+<blockquote>
+  
<p>两阶段提交协议是一种分布式算法，用于协调参与分布式原子事务的所有进程，以保证他们均完成提交或中止（回滚）事务。<a
 href="https://en.wikipedia.org/wiki/Two-phase_commit_protocol";>1</a></p>
+</blockquote>
+
+<p>2PC包含两个阶段：</p>
+<ul>
+  <li><strong>投票阶段</strong> 
协调器向所有服务发起投票请求，服务回答yes或no。如果有任何服务回复no以拒绝或è¶
…时，协调器则在下一阶段发送中止消息。</li>
+</ul>
+
+<p><img src="/assets/images/saga.2pc.phase1.png" alt="voting phase" 
class="align-center" /></p>
+
+<ul>
+  <li><strong>决定阶段</strong> 
如果所有服务都回复yes，协调器则向服务发送commit消息，接着服务告知事务完成或失败。如果任何服务提交失败，
+协调器将启动额外的步骤以中止该事务。</li>
+</ul>
+
+<p><img src="/assets/images/saga.2pc.phase2.png" alt="decision phase" 
class="align-center" /></p>
+
+<p>在投票阶段结束之后与决策阶段结束之前，服务处于<strong>不确定</strong>状态，å›
 
为他们不确定交易是否继续进行。当服务处于不确定状态并与协调器失去连接时，
+它只能选择等待协调器的恢复，或者咨询å…
¶ä»–在确定状态下的服务来得知协调器的决定。在最坏的情
况下，
+n个处于不确定状态的服务向å…
¶ä»–n-1个服务咨询将产生<strong>O(n<sup>2</sup>)</strong>个消息。</p>
+
+<p>另外，2PC是一个阻塞协议。服务在投票后需要等待
协调器的决定，此时服务会阻塞并锁定资源。由于å…
¶é˜»å¡žæœºåˆ¶å’Œæœ€å·®æ—¶é—´å¤æ‚度高，
+2PC不能适应随着事务涉及的服务数量增加而扩展的需要。</p>
+
+<p>有关2PC实现的更多细节可参考<a 
href="https://cs.nyu.edu/courses/spring03/G22.2631-001/lecture8.pdf";>2</a>和<a 
href="http://courses.cs.vt.edu/~cs5204/fall00/distributedDBMS/duckett/tpcp.html";>3</a>。</p>
+
+<h2 id="try-confirmcancel-tcc">Try-Confirm/Cancel (TCC)</h2>
+<p>TCC也是补偿型事务模式，支持两阶段的商业模型。</p>
+<ul>
+  <li><strong>尝试阶段</strong> 将服务置于待
处理状态。例如，收到尝试请求时，航班预订服务将为客户预留一个座位，并在数据库插å
…¥å®¢æˆ·é¢„订记录，将记录设为预留状态。
+如果任何服务失败或超
时，协调器将在下一阶段发送取消请求。</li>
+</ul>
+
+<p><img src="/assets/images/saga.tcc.try.png" alt="try phase" 
class="align-center" /></p>
+
+<ul>
+  <li><strong>确认阶段</strong> 
将服务设为确认状态。确认请求将确认客户预订的座位，这时服务已可向客户收取机票费用。数据库中的客户预订记录也会被更新为确认状态。
+如果任何服务无法确认或超
时，协调器将重试确认请求直到成功，或在重试了一定次数后采取回退措施，比如人工干预。</li>
+</ul>
+
+<p><img src="/assets/images/saga.tcc.confirm.png" alt="confirm phase" 
class="align-center" /></p>
+
+<p>与saga相比，TCC的优势在于，尝试阶段将服务转为待
处理状态而不是最终状态，这使得设计相应的取消操作轻而易举。</p>
+
+<p>例如，电邮服务的尝试请求可将邮件æ 
‡è®°ä¸ºå‡†å¤‡å‘送，并且仅在确认后发送邮件，å…
¶ç›¸åº”的取消请求只需将邮件标记为已废弃。但如果使用saga，
+事务将发送电子邮件，及å…
¶ç›¸åº”的补偿事务可能需要发送另一封电子邮件作出解释。</p>
+
+<p>TCC的缺点是其两阶段协议需要设计额外的服务待
处理状态，以及额外的接口来处理尝试请求。另外，TCC处理事务请求所花费的时间可能是saga的两倍，
+因为TCC需要与每个服务进行两次通信，并且å…
¶ç¡®è®¤é˜¶æ®µåªèƒ½åœ¨æ”¶åˆ°æ‰€æœ‰æœåŠ¡å¯¹å°è¯•è¯·æ±‚的响应后开始。</p>
+
+<p>有关TCC的更多细节可参考<a 
href="https://www.infoq.com/presentations/Transactions-HTTP-REST";>Transactions 
for the REST of Us</a>.</p>
+
+<h2 id="事件驱动的架构">事件驱动的架构</h2>
+<p>和TCC一æ 
·ï¼Œåœ¨äº‹ä»¶é©±åŠ¨çš„架构中，长活事务涉及的每个服务都需要支持额外的å¾
…处理状态。接收到事务请求的服务会在其数据库中插å…
¥ä¸€æ¡æ–°çš„记录，
+将该记录状态设为待
处理并发送一个新的事件给事务序列中的下一个服务。</p>
+
+<p>因为在插入记录后服务可能崩溃，我们无
法确定是否新事件已发送，所以每个服务还需要额外的事件表来跟踪当前长活事务处于哪一步。</p>
+
+<p><img src="/assets/images/saga.event.driven.request.png" alt="event driven 
architecture - request" class="align-center" /></p>
+
+<p>一旦长活事务中的最后一个服务完成å…
¶å­äº‹åŠ¡ï¼Œå®ƒå°†é€šçŸ¥å®ƒåœ¨äº‹åŠ¡ä¸­çš„前一个服务。接收到完成事件的服务将å
…¶åœ¨æ•°æ®åº“中的记录状态设为完成。</p>
+
+<p><img src="/assets/images/saga.event.driven.response.png" alt="event driven 
architecture - response" class="align-center" /></p>
+
+<p>如果仔细比较，事件驱动的架构就像非集中式的基于事件的TCC实现。如果去掉å¾
…
处理状态而直接把服务记录设为最终状态，这个架构就像非集中式的基于事件的saga实现。
+去中心化能达到服务自治，但也造
成了服务之间更紧密的的耦合。假设新的业务需求在服务B和C之间的增åŠ
 äº†æ–°çš„流程D。在事件驱动架构下，服务B和C必须改动代ç 
ä»¥é€‚应新的流程D。</p>
+
+<p><img src="/assets/images/saga.event.coupling.png" alt="event driven 
architecture - coupling" class="align-center" /></p>
+
+<p>Saga则正好相反，所有这些耦合都在saga系统中，当在长活事务中添åŠ
 æ–°æµç¨‹æ—¶ï¼ŒçŽ°æœ‰æœåŠ¡ä¸éœ€è¦ä»»ä½•æ”¹åŠ¨ã€‚</p>
+
+<p>更多细节可参考<a 
href="https://www.nginx.com/blog/event-driven-data-management-microservices/";>Event-Driven
 Data Management for Microservices</a>.</p>
+
+<h2 id="集中式与非集中式实现">集中式与非集中式实现</h2>
+<p>这个Saga系列的文章
讨论的都是集中式的saga设计。但saga也可用非集中式的方案来实现。那么非集中式的版本有什么不同？</p>
+
+<p>非集中式saga没有专职的协调器。启动下一个服务调用的服务就是当前的协调器。例如，</p>
+<ul>
+  
<li>服务A收到要求服务A，B和C之间的数据一致性的事务请求。</li>
+  <li>A完成其子事务，并将请求传
递给事务中的下一个服务，服务B.</li>
+  <li>B完成其子事务，并将请求传递给C，依此类推。</li>
+  
<li>如果C处理请求失败，B有责任启动补偿事务，并要求A回滚。</li>
+</ul>
+
+<p><img src="/assets/images/saga.decentralized.png" alt="decentralized saga" 
class="align-center" /></p>
+
+<p>与集中式相比，非集中式的实现å…
·æœ‰æœåŠ¡è‡ªæ²»çš„优势。但每个服务都需要包
含数据一致性协议，并提供其所需的额外持久化设施。</p>
+
+<p>我们更倾向于自治的业务服务，但服务还å…
³è”很多应用的复杂性，如数据一致性，服务监控和消息传
递，
+将这些棘手问题集中处理，能将业务服务从应用的复杂性中释放，专注于处理复杂的业务，å›
 æ­¤æˆ‘们采用了集中式的saga设计。</p>
+
+<p>另外，随着长活事务中涉及的服务数量增长，服务之间的å
…³ç³»å˜å¾—越来越难理解，很快便会呈现下图的死星形状。</p>
+
+<p class="figure-caption"><img src="/assets/images/saga.death.star.png" 
alt="death star architecture" class="align-center" />
+图片来源: http://www.slideshare.net/BruceWong3/the-case-for-chaos (s12)</p>
+
+<p>同时，在长活事务中定位问题也变得更加复杂，因
为服务日志遍布群集节点。</p>
+
+<h2 id="summary">Summary</h2>
+<p>本文将saga与å…
¶ä»–数据一致性解决方案进行了比较。Saga比两阶段提交更易扩展。在事务可补偿的æƒ
…况下，
+相比TCC，saga对业务逻辑几
乎没有改动的需要，而且性能更高。集中式的saga设计解耦了服务与数据一致性逻辑及å
…¶æŒä¹…化设施，
+并使排查事务中的问题更容易。</p>
+
+<h2 id="references">References</h2>
+<ol>
+  <li><a 
href="https://en.wikipedia.org/wiki/Two-phase_commit_protocol";>https://en.wikipedia.org/wiki/Two-phase_commit_protocol</a></li>
+  <li><a 
href="https://cs.nyu.edu/courses/spring03/G22.2631-001/lecture8.pdf";>https://cs.nyu.edu/courses/spring03/G22.2631-001/lecture8.pdf</a></li>
+  <li><a 
href="http://courses.cs.vt.edu/~cs5204/fall00/distributedDBMS/duckett/tpcp.html";>http://courses.cs.vt.edu/~cs5204/fall00/distributedDBMS/duckett/tpcp.html</a></li>
+  <li><a 
href="https://www.infoq.com/presentations/Transactions-HTTP-REST";>https://www.infoq.com/presentations/Transactions-HTTP-REST</a></li>
+  <li><a 
href="https://www.nginx.com/blog/event-driven-data-management-microservices/";>https://www.nginx.com/blog/event-driven-data-management-microservices/</a></li>
+</ol>
+
+
+        
+      </section>
+
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