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Now let's gather the requirements to design +a saga.</p> + +<h2 id="saga-log">Saga Log</h2> +<p>Saga guarantees either all sub-transactions are committed or compensated for, but the saga system itself may crash. There +are a few states that a saga may be in on crash:</p> +<ul> + <li>Saga received a request, but no transaction started yet. States of services involved in sub-transactions are not modified +by saga, nothing has been done.</li> + <li>Some sub-transactions were done. When restarted, saga has to resume from the last completed transaction.</li> + <li>A sub-transaction was started, but not completed yet. Since we are not sure if the remote service completed the transaction, +failed the transaction, or the request to remote service timed out, saga has to redo the sub-transaction on restart. That also +means sub-transactions have to be idempotent.</li> + <li>A sub-transaction failed and its compensating transaction has not started yet. Saga has to resume from the compensating +transaction on restart.</li> + <li>A compensating transaction started but not completed yet. The solution is basically the same as the previous one. That means +compensating transactions have to idempotent too.</li> + <li>All sub-transactions or compensating transactions were done, which is the same as the first case.</li> +</ul> + +<p>In order for saga to recover to the states mentioned above, we have to keep track of each step of sub-transactions and +compensating transactions. We decided to achieve that by saving the following events in a persistent store called saga log:</p> +<ul> + <li><strong>Saga started event</strong> stores the entire saga request, which includes multiple transaction/compensation requests</li> + <li><strong>Transaction started event</strong> stores individual transaction request</li> + <li><strong>Transaction ended event</strong> stores individual transaction request and its response</li> + <li><strong>Transaction aborted event</strong> stores individual transaction request and the cause of failure</li> + <li><strong>Transaction compensated event</strong> stores individual compensation request and its response</li> + <li><strong>Saga ended event</strong> marks the end of a saga request and stores nothing</li> +</ul> + +<p><img src="/assets/images/saga.events.png" alt="Events" class="align-center" /></p> + +<p>By persisting these events in saga log, a crashed saga can be recovered to any states above.</p> + +<p>Since saga only needs persistence of events and the event contents are stored as JSON, the implementation of the saga log +is very flexible. Databases (SQL or NoSQL), durable message queues, or even plain files can be used as event storage, but +some are faster for saga to recover.</p> + +<h2 id="request-data-structure-of-saga">Request Data Structure of Saga</h2> +<p>In our case, flight booking, car rental, and hotel reservation have no dependency among each other at all and they can be +processed in parallel. However, it's more user friendly for our customers to only charge their credit cards once, when all +the bookings are done successfully. That means the transactions of the four services look like the graph below.</p> + +<p><img src="/assets/images/saga.transactions.png" alt="Transactions" class="align-center" /></p> + +<p>It makes sense to implement the data structure of trip planning request as a <a href="https://en.wikipedia.org/wiki/Directed_acyclic_graph";>Directed Acyclic Graph</a>. +The root of the graph is saga start task and the leaf is saga end task.</p> + +<p><img src="/assets/images/saga.graph.png" alt="Request Graph" class="align-center" /></p> + +<h2 id="parallel-saga">Parallel Saga</h2> +<p>As mentioned above, flight booking, car rental, and hotel reservation can be processed in parallel. But doing so creates +another problem: what if flight booking failed while car rental is being processed? We can't keep waiting for the response +from car rental service, because we have no idea how long it will take.</p> + +<p>THe best thing we can do is to send the car rental request again and hope we get a response so that we can continue our +backward recovery. If car rental service never responds, we may have to fallback with manual intervention.</p> + +<p>The delayed booking request may still be received by the remote car rental service. When it does, the service has already +processed the same booking and its cancellation request.</p> + +<p><img src="/assets/images/saga.commutative.png" alt="Network Latency" class="align-center" /></p> + +<p>Therefore, services have to implement transactions and compensations in such a way that transaction request received after +its compensation request takes no effect. Caitie McCaffrey called this <strong>commutative compensating request</strong> in her talk +on <a href="https://www.youtube.com/watch?v=1H6tounpnG8";>Distributed Sagas: A Protocol for Coordinating Microservices</a>.</p> + +<h2 id="acid-and-saga">ACID and Saga</h2> +<p><a href="https://en.wikipedia.org/wiki/ACID";>ACID</a> is consistency model with the following properties:</p> +<ul> + <li>Atomicity</li> + <li>Consistency</li> + <li>Isolation</li> + <li>Durability</li> +</ul> + +<p>Saga does not provide ACID guarantee, because atomicity and isolation are not satisfied according to the <a href="https://www.cs.cornell.edu/andru/cs711/2002fa/reading/sagas.pdf";>paper</a></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>With durable saga log, saga guarantees consistency and durability.</p> + +<h2 id="saga-architecture">Saga Architecture</h2> +<p>Finally, the architecture of our saga looks like this</p> + +<p><img src="/assets/images/saga.design.png" alt="Saga Architecture" class="align-center" /></p> + +<ul> + <li>Saga execution component parses the request JSON and builds a graph of requests</li> + <li>TaskRunner ensures the execution order of requests with task queue</li> + <li>TaskConsumer processes tasks to write events to saga log and send requests to remote services</li> +</ul> + +<h2 id="summary">Summary</h2> +<p>In this article, we talked about how saga can be implemented with a saga log to persist transaction/compensation events +and request graph. A crashed saga can also be recovered from all the persisted events in saga log on restart. However, +there are a few requirements on design of microservices to ensure saga consistency guarantee:</p> +<ul> + <li>transaction and compensation requests must be idempotent</li> + <li>compensation requests must be 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 & Kenneth Salem</li> +</ol> + + + + </section> + + <footer class="page__meta"> + + + + + + + + + + <p class="page__taxonomy"> + <strong><i class="fa fa-fw fa-tags" aria-hidden="true"></i> Tags: </strong> + <span itemprop="keywords"> + + + + <a href="/tags/#saga" class="page__taxonomy-item" rel="tag">saga</a> + + </span> + </p> + + + + + + + + + <p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Updated:</strong> <time datetime="2017-09-16">September 16, 2017</time></p> + + + + </footer> + + <section class="page__share"> + + <h4 class="page__share-title">Share on</h4> + + + <a href="https://twitter.com/intent/tweet?via=ServiceComb&text=Eventual Data Consistency Solution in ServiceComb - part 2 /docs/distributed_saga_2/" class="btn btn--twitter" title="Share on Twitter"><i class="fa fa-fw fa-twitter" aria-hidden="true"></i><span> Twitter</span></a> + + <a href="https://www.facebook.com/sharer/sharer.php?u=/docs/distributed_saga_2/"; class="btn btn--facebook" title="Share on Facebook"><i class="fa fa-fw fa-facebook" aria-hidden="true"></i><span> Facebook</span></a> + + <a href="https://plus.google.com/share?url=/docs/distributed_saga_2/"; class="btn btn--google-plus" title="Share on Google Plus"><i class="fa fa-fw fa-google-plus" aria-hidden="true"></i><span> Google+</span></a> + + <a href="https://www.linkedin.com/shareArticle?mini=true&url=/docs/distributed_saga_2/"; class="btn btn--linkedin" title="Share on LinkedIn"><i class="fa fa-fw fa-linkedin" aria-hidden="true"></i><span> LinkedIn</span></a> +</section> + + + + <nav class="pagination"> + + <a href="/cn/docs/performance-test-on-seckill-with-jmeter/" class="pagination--pager" title="使ç¨JMeter对ç§æ示ä¾è¿è¡æ§è½æµè¯ +">Previous</a> + + + <a href="/cn/docs/distributed_saga_2/" class="pagination--pager" title="ServiceCombä¸çæ°æ®æç»ä¸è´æ§æ¹æ¡ - part 2 +">Next</a> + + </nav> + + + </div> + + + <div class="page__comments"> + + + <section id="static-comments"> + + <!-- Start static comments --> + <div class="js-comments"> + + </div> + <!-- End static comments --> + + <!-- Start new comment form --> + <h4 class="page__comments-title">Leave a Comment</h4> + <p class="small">Your email address will not be published. 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However, there are quite a few data consistency solutions such as Two-Phase Commit (2PC) +and Try-Confirm/Cancel (TCC). What makes saga special?</p> + +<h2 id="two-phase-commit-2pc">Two-Phase Commit (2PC)</h2> +<blockquote> + <p>Two-phase commit protocol is a distributed algorithm that coordinates all the processes that participate in a distributed +atomic transaction on whether to commit or abort (roll back) the transaction. <a href="https://en.wikipedia.org/wiki/Two-phase_commit_protocol";>1</a></p> +</blockquote> + +<p>It has two phases:</p> +<ul> + <li><strong>voting phase</strong> coordinator sends vote request to all services and services respond with either yes or no. If any service +refuse with no or timeout, coordinator sends abort message in the next phase.</li> +</ul> + +<p><img src="/assets/images/saga.2pc.phase1.png" alt="voting phase" class="align-center" /></p> + +<ul> + <li><strong>decision phase</strong> if all services say yes, coordinator sends commit message to services and services acknowledge either +transaction done or failed. If any service fails to commit, coordinator will initiate additional rounds to abort the transaction.</li> +</ul> + +<p><img src="/assets/images/saga.2pc.phase2.png" alt="decision phase" class="align-center" /></p> + +<p>Between the end of voting phase and the end of decision phase, services are in <strong>uncertain</strong> state, because they are not sure +if the transaction is going to proceed or not. When a service is in uncertain state and loses connection with coordinator, +it may either wait for coordinator's recovery, or consult other services in certain state for coordinator's decision. +In the worst case, n uncertain services broadcasting messages to other n - 1 services will incur <strong>O(n<sup>2</sup>)</strong> messages.</p> + +<p>Another disadvantage of 2PC is that it is a blocking protocol. A service will block and lock resources, while waiting for +decision from coordinator after voting. 2PC does not scale well when the number of services involved in a transaction grows, +because of its blocking mechanism and worst case time complexity.</p> + +<p>More details on implementation of 2PC can be found at <a href="https://cs.nyu.edu/courses/spring03/G22.2631-001/lecture8.pdf";>2</a> and <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 is a compensating transaction pattern for business model that is two-phased.</p> +<ul> + <li><strong>try phase</strong> puts a service in pending state. For example, a try request in our flight booking service will reserve a +seat for the customer and insert a customer reservation record with reserved state into database. If any service fails to +make a reservation or times out, the coordinator will send a cancel request in the next phase.</li> +</ul> + +<p><img src="/assets/images/saga.tcc.try.png" alt="try phase" class="align-center" /></p> + +<ul> + <li><strong>confirm phase</strong> moves the service to confirmed state. A confirm request will confirm that a seat is booked for the +customer and he or she will be billed. The customer reservation record in database will be updated to confirmed state. +If any service fails to confirm or times out, the coordinator will either retry confirmation until success or involve manual +intervention after it retries a certain number of times.</li> +</ul> + +<p><img src="/assets/images/saga.tcc.confirm.png" alt="confirm phase" class="align-center" /></p> + +<p>Comparing with saga, TCC has an advantage in that try phase transitions services into pending state instead of final +state, which makes cancellation trivial to design.</p> + +<p>For example, a try request for an email service may mark an email as ready to send and the email is only sent on confirm +request. Its corresponding cancel request needs only to mark the email as obsolete. However, in case of using saga, a transaction +will send the email and its corresponding compensating transaction may have to send another email to explain the problem.</p> + +<p>The disadvantage of TCC, comparing with saga, is that its two-phased protocol requires services to be designed with additional +pending state and interface to handle try request. And it may take twice the time to complete a TCC request than a saga request, +because TCC communicates with each service twice and the confirm phase can only be started when responses of try request +are received from all services.</p> + +<p>More detailed explanation of TCC can be found at <a href="https://www.infoq.com/presentations/Transactions-HTTP-REST";>Transactions for the REST of Us</a>.</p> + +<h2 id="event-driven-architecture">Event Driven Architecture</h2> +<p>In event driven architecture, just like TCC, an extra pending status is required for each service involved in a long live transaction. +Services receiving transaction request insert a new record into its database with pending status and send a new event to +the next service in the transaction sequence.</p> + +<p>Because it's possible that a service crashes after inserting the record and we are not sure if the new event is sent, +an extra event table is required for each service to keep track of which step the current long live transaction is in.</p> + +<p><img src="/assets/images/saga.event.driven.request.png" alt="event driven architecture - request" class="align-center" /></p> + +<p>Once the last service in the long live transaction completes its job, it notifies the previous service in the transaction. +Services receiving completion event set its record status to done in its database.</p> + +<p><img src="/assets/images/saga.event.driven.response.png" alt="event driven architecture - response" class="align-center" /></p> + +<p>If you look closer, event driven architecture is just like a decentralized implementation of event driven TCC. If we remove +the pending state for each service, this architecture looks like a decentralized and event driven saga. +Being decentralized is good, but it creates much tighter coupling between services. Let's assume a new business requirement adds a new +process D between B and C. With event driven architecture, service B and C have to change their code to accommodate the new +process D.</p> + +<p><img src="/assets/images/saga.event.coupling.png" alt="event driven architecture - coupling" class="align-center" /></p> + +<p>On the contrary, all these coupling is in saga and no change is required for existing services when a new process is added +to the long live transaction.</p> + +<p>More details can be found at <a href="https://www.nginx.com/blog/event-driven-data-management-microservices/";>Event-Driven Data Management for Microservices</a>.</p> + +<h2 id="centralized-vs-decentralized">Centralized vs Decentralized</h2> +<p>This blog series have been talked about centralized saga. But saga can be implemented as decentralized solution too. +How does the decentralized version look like?</p> + +<p>The decentralized version of saga does not have a dedicated coordinator. Whoever calling the next service +in the transaction becomes the current coordinator instead. For example,</p> +<ul> + <li>service A receives a request requiring data consistency across service A, B, and C.</li> + <li>A does its job and passes the request to the next service in the request, service B.</li> + <li>B completes its part and passes the request to C, and so on.</li> + <li>If C fails to process the request, it is B's responsibility to initiate its compensating transaction and asks A to rollback.</li> +</ul> + +<p><img src="/assets/images/saga.decentralized.png" alt="decentralized saga" class="align-center" /></p> + +<p>Comparing with centralized one, the decentralized version has the advantage of service autonomy. But each service is +coupled with data consistency protocol, which may require additional persistence infrastructure.</p> + +<p>We love services implementing business rules to be autonomous, but there are many application related complexity such as +data consistency, service monitoring, and message passing, that are better to be centralized, so that business services +are able to focus on dealing with business complexity instead of application complexity. That's why we designed centralized saga.</p> + +<p>In addition, the relationship among services in a long live transaction becomes harder and harder to understand, as the +number of services grows. It may quickly grow into a death star like the image below.</p> + +<p class="figure-caption"><img src="/assets/images/saga.death.star.png" alt="death star architecture" class="align-center" /> +Image source: http://www.slideshare.net/BruceWong3/the-case-for-chaos (s12)</p> + +<p>Meanwhile, locating the root cause of a problem in a long live transaction also becomes more troublesome, since the +service logs are spread all over cluster nodes.</p> + +<h2 id="summary">Summary</h2> +<p>In this article, we compared saga with other data consistency solutions. Saga is more scalable than two-phase commit and +is preferable to TCC in scenarios where compensating transactions are feasible and minimal changes to business logic is +required. Centralized saga decouples services from data consistency logic and its persistence infrastructure +and allows easier troubleshooting of any problem occurred in transactions.</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> + + <footer class="page__meta"> + + + + + + + + + + <p class="page__taxonomy"> + <strong><i class="fa fa-fw fa-tags" aria-hidden="true"></i> Tags: </strong> + <span itemprop="keywords"> + + + + <a href="/tags/#saga" class="page__taxonomy-item" rel="tag">saga</a> + + </span> + </p> + + + + + + + + + <p class="page__date"><strong><i class="fa fa-fw fa-calendar" aria-hidden="true"></i> Updated:</strong> <time datetime="2017-09-18">September 18, 2017</time></p> + + + + </footer> + + <section class="page__share"> + + <h4 class="page__share-title">Share on</h4> + + + <a href="https://twitter.com/intent/tweet?via=ServiceComb&text=Eventual Data Consistency Solution in ServiceComb - part 3 /docs/distributed_saga_3/" class="btn btn--twitter" title="Share on Twitter"><i class="fa fa-fw fa-twitter" aria-hidden="true"></i><span> Twitter</span></a> + + <a href="https://www.facebook.com/sharer/sharer.php?u=/docs/distributed_saga_3/"; class="btn btn--facebook" title="Share on Facebook"><i class="fa fa-fw fa-facebook" aria-hidden="true"></i><span> Facebook</span></a> + + <a href="https://plus.google.com/share?url=/docs/distributed_saga_3/"; class="btn btn--google-plus" title="Share on Google Plus"><i class="fa fa-fw fa-google-plus" aria-hidden="true"></i><span> Google+</span></a> + + <a href="https://www.linkedin.com/shareArticle?mini=true&url=/docs/distributed_saga_3/"; class="btn btn--linkedin" title="Share on LinkedIn"><i class="fa fa-fw fa-linkedin" aria-hidden="true"></i><span> LinkedIn</span></a> +</section> + + + + <nav class="pagination"> + + <a href="/cn/docs/distributed_saga_2/" class="pagination--pager" title="ServiceCombä¸çæ°æ®æç»ä¸è´æ§æ¹æ¡ - part 2 +">Previous</a> + + + <a href="/cn/docs/distributed_saga_3/" class="pagination--pager" title="ServiceCombä¸çæ°æ®æç»ä¸è´æ§æ¹æ¡ - part 3 +">Next</a> + + </nav> + + + </div> + + + <div class="page__comments"> + + + <section id="static-comments"> + + <!-- Start static comments --> + <div class="js-comments"> + + </div> + <!-- End static comments --> + + <!-- Start new comment form --> + <h4 class="page__comments-title">Leave a Comment</h4> + <p class="small">Your email address will not be published. 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