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| <h1>Considerations<a class="headerlink" href="#considerations" title="Permalink to this headline">¶</a></h1> |
| <p>As different applications have different requirements, we’ve carefully considered the capabilities |
| that should be included in DistributedLog leaving the rest up to the applications. These considerations are:</p> |
| <div class="section" id="consistency-durability-and-ordering"> |
| <h2>Consistency, Durability and Ordering<a class="headerlink" href="#consistency-durability-and-ordering" title="Permalink to this headline">¶</a></h2> |
| <p>The distributed systems literature commonly refers to two broad paradigms to use a log |
| for building reliable replicated systems (Figure 1). The <cite>Pub-Sub</cite> paradigm usually |
| refers to an active-active model where we keep a log of the incoming requests and each |
| replica(reader) processes each request. While the <cite>Master-Slave</cite> paradigm elects one |
| replica as the master to process requests as they arrive and log changes to its state. |
| The other replicas referred to as slaves apply the state changes in the same order as |
| the master, thereby being in sync and ready to take over the mastership if the current |
| master fails. If the current master loses connectivity to the slaves due to a network |
| partition, the slaves may elect a new master to continue forward progress. A fencing |
| mechanism is necessary for the old master to discover that it has lost ownership and |
| prevent it from modifying state after network connectivity is restored.</p> |
| <div class="figure align-center"> |
| <img alt="../_images/pubsub.png" src="../_images/pubsub.png" /> |
| <p class="caption">Figure 1. The uses of a log in distributed systems</p> |
| </div> |
| <p>These two different approaches indicate two different types of ordering requirements - |
| <cite>Write Ordering</cite> and <cite>Read Ordering</cite>. <cite>Write ordering</cite> requires that all writes issued |
| by the log writer be written in a strict order to the log, while <cite>read ordering</cite> only |
| requires that any reader that reads the log stream should see the same record at any |
| given position, the log records however may not appear in the same order that the writer |
| wrote them. The replicated log service should be able to support both use cases.</p> |
| </div> |
| <div class="section" id="partitioning"> |
| <h2>Partitioning<a class="headerlink" href="#partitioning" title="Permalink to this headline">¶</a></h2> |
| <p><cite>Partitioning</cite> (also known as sharding or bucketing) facilitates horizontal scale. The |
| partitioning scheme depends on the characteristics of the application and is closely |
| related to the ordering guarantees that the application requires. For example, distributed |
| key/value store that uses DistributedLog as its transaction log, distributes the data into |
| partitions each of which is a unit of consistency. Modifications within each partition are |
| required to be strictly ordered. On the other hand, real-time analytics workloads don’t |
| require strict order, can use <em>round-robin</em> partitioning to evenly distribute the reads and |
| writes across all partitions. It is therefore prudent to provide applications the flexibility |
| to choose a suitable partitioning scheme.</p> |
| </div> |
| <div class="section" id="processing-semantics"> |
| <h2>Processing Semantics<a class="headerlink" href="#processing-semantics" title="Permalink to this headline">¶</a></h2> |
| <p>Applications typically choose between <cite>at-least-once</cite> and <cite>exactly-once</cite> processing semantics. |
| <cite>At-least-once</cite> processing guarantees that the application will process all the log records, |
| however when the application resumes after failure, previously processed records may be |
| re-processed if they have not been acknowledged. <cite>Exactly once</cite> processing is a stricter |
| guarantee where applications must see the effect of processing each record exactly once. |
| <cite>Exactly once</cite> semantics can be achieved by maintaining reader positions together with the |
| application state and atomically updating both the reader position and the effects of the |
| corresponding log records. For instance, for strongly consistent updates in a distributed |
| key/value store the reader position must be persisted atomically with the changes applied |
| from the corresponding log records. Upon restart from a failure, the reader resumes from the |
| last persisted position thereby guaranteeing that each change is applied only once. With at |
| least once processing guarantees the application can store reader positions in an external |
| store and update it periodically. Upon restart the application will reprocess messages since |
| the last updated reader position.</p> |
| </div> |
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| TimeMe.setCurrentPageName("my-home-page"); |
| TimeMe.initialize(); |
| |
| // record page visit event when user leaves the page |
| window.onbeforeunload = function (event) { |
| xmlhttp=new XMLHttpRequest(); |
| xmlhttp.withCredentials = true; |
| xmlhttp.open("POST", "/event/distributedlog:distributedlog/visit", false); |
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| background-color: #fff; |
| border: 1px solid #ccc; |
| position: fixed; |
| bottom: 3px; |
| right: -280px; |
| z-index: 1; |
| } |
| #slidebox .close{ |
| margin-top: -5px; |
| opacity: 0.5; |
| } |
| #slidebox .close:hover{ |
| opacity: 0.7; |
| } |
| </style> --> |
| <script type="text/javascript"> |
| $(function() { |
| // $(window).scroll(function(){ |
| // var distanceTop = $('#last').offset().top - $(window).height(); |
| |
| // if ($(window).scrollTop() > distanceTop) |
| // $('#slidebox').animate({'right':'3px'},300); |
| // else |
| // $('#slidebox').stop(true).animate({'right':'-280px'},100); |
| // }); |
| |
| // $('#slidebox .close').bind('click',function(){ |
| // $(this).parent().remove(); |
| // }); |
| |
| $("#rateYo").rateYo({ |
| normalFill: "#A0A0A0", |
| halfStar: true, |
| rating: (Cookies.get('docbird.rating.distributedlog.distributedlog') || 0.0) |
| }).on("rateyo.set", function (e, data) { |
| var event_data = { |
| comment: '', // see todo note below |
| rating: data.rating, |
| page: window.location.href |
| }; |
| Cookies.get('docbird.rating.distributedlog.distributedlog', data.rating) |
| $.post('/event/distributedlog:distributedlog/rating', event_data) |
| // xmlhttp=new XMLHttpRequest(); |
| // xmlhttp.withCredentials = true; |
| // var event_data = { |
| // comment: '', // see todo note below |
| // rating: data.rating, |
| // page: window.location.href |
| // }; |
| // xmlhttp.open("GET", "/event/distributedlog/rating?" + $.param(event_data), false); |
| // xmlhttp.setRequestHeader("Content-type", "application/x-www-form-urlencoded"); |
| // // todo: implement comment form in rating slide out, |
| // // and instead of hooking this event, include a submit button, |
| // // and read the rating with rating() method |
| |
| // // alert("send: " + $.param(event_data)); |
| // xmlhttp.send(); |
| |
| }); |
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| $('.db-content-body').selectionSharer(); |
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