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But a global setup is required for +providing global replicated logs for distributed key/value store to achieve strong consistency +across multiple datacenters. <cite>Global</cite> here means across datacenters, which is different from +<cite>Local</cite> meaning within a datacenter.</p> +<p>A global setup of DistributedLog is organized as a set of <cite>regions</cite>, where each region is the +rough analog of a local setup. Regions are the unit of administrative deployment. The set of +regions is also the set of locations across which data can be replicated. Regions can be added +to or removed from a running system as new datacenters are brought into service and old ones +are turned off, respectively. Regions are also the unit of physical isolation: there may be one +or more regions in a datacenter if they have isolated power or network supplies.</p> +<div class="figure align-center"> +<img alt="../../images/globalreplicatedlog.png" src="../../images/globalreplicatedlog.png" style="width: 600px;" /> +<p class="caption">Figure 1. Global Replicated Log</p> +</div> +<p>Figure 1 illustrates the servers in a <cite>Global Replicated Log</cite> setup. There is no inter datacenter +communication between write proxies or log segment storage nodes. The only component that does +inter datacenters communications within its hosts is the 'Global' metadata store, which is a global +setup of ZooKeeper. Write clients will talk to the write proxies in its local region to bootstrap +the ownership cache and redirect to correct write proxies in other regions through direct TCP +connections. While readers will identify the regions of the log segment storage nodes according to +the <cite>region aware</cite> placement policy, and try reading from local region at most of the time and +speculatively try on remote regions.</p> +<div class="section" id="region-aware-data-placement-policy"> +<h3><a class="toc-backref" href="#id3">Region Aware Data Placement Policy</a></h3> +<p>Region aware placement policy uses hierarchical allocation where-in nodes are allocated so that data +is spread uniformly across the available regions and within each region it uses the <cite>rack-aware</cite> +placement policy to spread the data uniformly across the available racks.</p> +<p>Region aware placement policy is governed by a parameter ensures that the ack quorum covers at least +<em>minRegionsForDurability</em> distinct regions. This ensures that the system can survive the failure of +<cite>(totalRegions - minRegionsForDurability)</cite> regions without loss of availability. For example if we +have bookie nodes in <em>5</em> regions and if the <em>minRegionsForDurability</em> is <em>3</em> then we can survive the +failure of <cite>(5 - 3) = 2</cite> regions.</p> +<p>The placement algorithm follows the following simple invariant:</p> +<pre class="literal-block"> +There is no combination of nodes that would satisfy the ack quorum with +less than "minRegionsForDurability" responses. +</pre> +<p>This invariant ensures that enforcing ack quorum is sufficient to enforce that the entry has been made durable +in <em>minRegionsForDurability</em> regions.</p> +<p>The <em>minRegionsForDurability</em> requirement enforces constraints on the minimum ack quorum as we want to ensure +that when we run in degraded mode - <em>i.e. when only a subset of the regions are available</em> - we would still not +be able to allocate nodes in such a way that the ack quorum would be satisfied by fewer than <em>minRegionsForDurability</em> +regions.</p> +<p>For instance consider the following scenario with three regions each containing 20 bookie nodes:</p> +<pre class="literal-block"> +minRegionsForDurability = 2 +ensemble size = write quorum = 15 +ack quorum = 8 +</pre> +<p>Let's say that one of the regions is currently unavailable and we want to still ensure that writes can continue. +The ensemble placement may then have to choose bookies from the two available regions. Given that <em>15</em> bookies have +to be allocated, we will have to allocate at least <em>8</em> bookies from one of the remaining regions - but with ack quorum +of <em>8</em> we run the risk of satisfying ack quorum with bookies from a single region. Therefore we must require that +the ack quorum is greater than <em>8</em>.</p> +</div> +<div class="section" id="cross-region-speculative-reads"> +<h3><a class="toc-backref" href="#id4">Cross Region Speculative Reads</a></h3> +<p>As discussed before, read requests can be satisfied by any replica of the data, however for high availability +speculative requests are sent to multiple copies to ensure that at least one of the requests returns within +the time specified by the <em>SLA</em>. The reader consults the data placement policy to get the list of replicas that +can satisfy the request in the order of preference. This order is decided as follows:</p> +<ul class="simple"> +<li>The first node in the list is always the bookie node that is closest to the client - if more than one such nodes exist, one is chosen at random.</li> +<li>The second node is usually the closest node in a different failure domain. In the case of a two level hierarchy that would be a node in a different rack.</li> +<li>The third node is chosen from a different region</li> +</ul> +<p>The delay between successive speculative read requests ensures that the probability of sending the <em>nth</em> +speculative read request decays exponentially with <em>n</em>. This ensures that the number of requests that go to +farther nodes is still kept at a minimum. However by making sure that we cross failure domains in the first +few speculative requests improves fault-tolerance of the reader. Transient node failures are transparently +handled by the reader by this simple and generalizable speculative read policy. This can be thought of as +the most granular form of failover where each request essentially fails-over to an alternate node if the +primary node it attempted to access is unavailable. In practice we have found this to also better handle +network congestion where routes between specific pairs of nodes may become unavailable without necessarily +making the nodes completely inaccessible.</p> +<p>In addition to static decisions based on the location of the bookie nodes, we can also make dynamic decisions +based on observed latency or failure rates from specific bookies. These statistics are tracked by the bookie +client and are used to influence the order in which speculative read requests are scheduled. This again is +able to capture partial network outages that affect specific routes within the network.</p> +</div> +</div> + + + </div> + </div> +</div> + + + + </div> + + + <hr> + <div class="row"> + <div class="col-xs-12"> + <footer> + <p class="text-center">© Copyright 2016 + <a href="http://www.apache.org";>The Apache Software Foundation.</a> All Rights Reserved. + </p> + <p class="text-center"> + <a href="http://distributedlog.incubator.apache.org/docs/latest/feed.xml";>RSS Feed</a> + </p> + </footer> + </div> + </div> + <!-- container div end --> +</div> + + + <script> + (function () { + 'use strict'; + anchors.options.placement = 'right'; + anchors.add(); + })(); +</script> + + </body> + +</html>
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records to multiple streams (load balancer) + </a> + </li> + + <li> + <a href="http://distributedlog.incubator.apache.org/docs/latest/tutorials/messaging-3.html";> + At-least-once Processing + </a> + </li> + + <li> + <a href="http://distributedlog.incubator.apache.org/docs/latest/tutorials/messaging-4.html";> + Exact-Once Processing + </a> + </li> + + <li> + <a href="http://distributedlog.incubator.apache.org/docs/latest/tutorials/messaging-5.html";> + Implement a kafka-like pub/sub system + </a> + </li> + + <li role="separator" class="divider"></li> + <li class="dropdown-header"><strong>Replicated State Machines</strong></li> + + + <li> + <a href="http://distributedlog.incubator.apache.org/docs/latest/tutorials/replicatedstatemachines.html";> + Build replicated state machines + </a> + </li> + + <li role="separator" class="divider"></li> + <li class="dropdown-header"><strong>Analytics</strong></li> + <li><a 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