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Guide<span class="caret"></span></a> + <ul class="dropdown-menu"> + + + <li> + <a href="/docs/0.4.0-incubating/basics/introduction.html"> + Introduction + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/considerations/main.html"> + Considerations + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/architecture/main.html"> + Architecture + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/api/main.html"> + API + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/configuration/main.html"> + Configuration + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/design/main.html"> + Detail Design + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/globalreplicatedlog/main.html"> + Global Replicated Log + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/user_guide/implementation/main.html"> + Implementation + </a> + </li> + + <li> + <a 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href="/docs/0.4.0-incubating/admin_guide/zookeeper.html"> + ZooKeeper + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/admin_guide/bookkeeper.html"> + BookKeeper + </a> + </li> + + </ul> + </li> + <!-- Tutorials --> + <li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false">Tutorials<span class="caret"></span></a> + <ul class="dropdown-menu"> + <li class="dropdown-header"><strong>Basic</strong></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-1">Write Records (via Core Library)</a></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-2">Write Records (via Write Proxy)</a></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-3">Write Records to multiple streams</a></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-4">Atomic Write Records</a></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-5">Tailing Read Records</a></li> + <li><a href="/docs/0.4.0-incubating/tutorials/basic-6">Rewind Read Records</a></li> + <li role="separator" class="divider"></li> + <li class="dropdown-header"><strong>Messaging</strong></li> + + + <li> + <a href="/docs/0.4.0-incubating/tutorials/messaging-1.html"> + Write records to partitioned streams + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/tutorials/messaging-2.html"> + Write records to multiple streams (load balancer) + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/tutorials/messaging-3.html"> + At-least-once Processing + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/tutorials/messaging-4.html"> + Exact-Once Processing + </a> + </li> + + <li> + <a href="/docs/0.4.0-incubating/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 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Write traffic comes to <cite>Write Proxy</cite> +and the data is replicated in <cite>RF</cite> (replication factor) ways to <cite>BookKeeper</cite>. BookKeeper +stores the replicated data and keeps the data for a given retention period. The data is +read by <cite>Read Proxy</cite> and fanout to readers.</p> +<p>In such layered architecture, each layer has its own responsibilities and different resource +requirements. It makes the capacity and cost model much clear and users could scale +different layers independently.</p> +<div class="figure align-center"> +<img alt="../images/costmodel.png" src="../images/costmodel.png" /> +<p class="caption">Figure 1. DistributedLog Cost Model</p> +</div> +<div class="section" id="metrics"> +<h3><a class="toc-backref" href="#id3">Metrics</a></h3> +<p>There are different metrics measuring the capability of a service instance in each layer +(e.g a <cite>write proxy</cite> node, a <cite>bookie</cite> storage node, a <cite>read proxy</cite> node and such). These metrics +can be <cite>rps</cite> (requests per second), <cite>bps</cite> (bits per second), <cite>number of streams</cite> that a instance +can support, and latency requirements. <cite>bps</cite> is the best and simple factor on measuring the +capability of current distributedlog architecture.</p> +</div> +<div class="section" id="write-proxy"> +<h3><a class="toc-backref" href="#id4">Write Proxy</a></h3> +<p>Write Proxy (WP) is a stateless serving service that writes and replicates fan-in traffic into BookKeeper. +The capability of a write proxy instance is purely dominated by the <em>OUTBOUND</em> network bandwidth, +which is reflected as incoming <cite>Write Throughput</cite> and <cite>Replication Factor</cite>.</p> +<p>Calculating the capacity of Write Proxy (number of instances of write proxies) is pretty straightforward. +The formula is listed as below.</p> +<pre class="literal-block"> +Number of Write Proxies = (Write Throughput) * (Replication Factor) / (Write Proxy Outbound Bandwidth) +</pre> +<p>As it is bandwidth bound, we'd recommend using machines that have high network bandwith (e.g 10Gb NIC).</p> +<p>The cost estimation is also straightforward.</p> +<pre class="literal-block"> +Bandwidth TCO ($/day/MB) = (Write Proxy TCO) / (Write Proxy Outbound Bandwidth) +Cost of write proxies = (Write Throughput) * (Replication Factor) / (Bandwidth TCO) +</pre> +<div class="section" id="cpus"> +<h4><a class="toc-backref" href="#id5">CPUs</a></h4> +<p>DistributedLog is not CPU bound. You can run an instance with 8 or 12 cores just fine.</p> +</div> +<div class="section" id="memories"> +<h4><a class="toc-backref" href="#id6">Memories</a></h4> +<p>There's a fair bit of caching. Consider running with at least 8GB of memory.</p> +</div> +<div class="section" id="disks"> +<h4><a class="toc-backref" href="#id7">Disks</a></h4> +<p>This is a stateless process, disk performances are not relevant.</p> +</div> +<div class="section" id="network"> +<h4><a class="toc-backref" href="#id8">Network</a></h4> +<p>Depending on your throughput, you might be better off running this with 10Gb NIC. In this scenario, you can easily achieves 350MBps of writes.</p> +</div> +</div> +<div class="section" id="bookkeeper"> +<h3><a class="toc-backref" href="#id9">BookKeeper</a></h3> +<p>BookKeeper is the log segment store, which is a stateful service. There are two factors to measure the +capability of a Bookie instance: <cite>bandwidth</cite> and <cite>storage</cite>. The bandwidth is majorly dominated by the +outbound traffic from write proxy, which is <cite>(Write Throughput) * (Replication Factor)</cite>. The storage is +majorly dominated by the traffic and also <cite>Retention Period</cite>.</p> +<p>Calculating the capacity of BookKeeper (number of instances of bookies) is a bit more complicated than Write +Proxy. The total number of instances is the maximum number of the instances of bookies calculated using +<cite>bandwidth</cite> and <cite>storage</cite>.</p> +<pre class="literal-block"> +Number of bookies based on bandwidth = (Write Throughput) * (Replication Factor) / (Bookie Inbound Bandwidth) +Number of bookies based on storage = (Write Throughput) * (Replication Factor) * (Replication Factor) / (Bookie disk space) +Number of bookies = maximum((number of bookies based on bandwidth), (number of bookies based on storage)) +</pre> +<p>We should consider both bandwidth and storage when choosing the hardware for bookies. There are several rules to follow: +- A bookie should have multiple disks. +- The number of disks used as journal disks should have similar I/O bandwidth as its <em>INBOUND</em> network bandwidth. For example, if you plan to use a disk for journal which I/O bandwidth is around 100MBps, a 1Gb NIC is a better choice than 10Gb NIC. +- The number of disks used as ledger disks should be large enough to hold data if retention period is typical long.</p> +<p>The cost estimation is straightforward based on the number of bookies estimated above.</p> +<pre class="literal-block"> +Cost of bookies = (Number of bookies) * (Bookie TCO) +</pre> +</div> +<div class="section" id="read-proxy"> +<h3><a class="toc-backref" href="#id10">Read Proxy</a></h3> +<p>Similar as Write Proxy, Read Proxy is also dominated by <em>OUTBOUND</em> bandwidth, which is reflected as incoming <cite>Write Throughput</cite> and <cite>Fanout Factor</cite>.</p> +<p>Calculating the capacity of Read Proxy (number of instances of read proxies) is also pretty straightforward. +The formula is listed as below.</p> +<pre class="literal-block"> +Number of Read Proxies = (Write Throughput) * (Fanout Factor) / (Read Proxy Outbound Bandwidth) +</pre> +<p>As it is bandwidth bound, we'd recommend using machines that have high network bandwith (e.g 10Gb NIC).</p> +<p>The cost estimation is also straightforward.</p> +<pre class="literal-block"> +Bandwidth TCO ($/day/MB) = (Read Proxy TCO) / (Read Proxy Outbound Bandwidth) +Cost of read proxies = (Write Throughput) * (Fanout Factor) / (Bandwidth TCO) +</pre> +</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="/docs/0.4.0-incubating/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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These applications are suitable for load testing, performance testing, benchmarking, or even simply smoke testing a distributedlog cluster.</p> +<p>The dbench script can run in several modes:</p> +<ol class="arabic simple"> +<li>bkwrite - Benchmark the distributedlog write path using the core library</li> +<li>write - Benchmark the distributedlog write path, via write proxy, using the thin client</li> +<li>read - Benchmark the distributedlog read path using the core library</li> +</ol> +</div> +<div class="section" id="running-dbench"> +<h3><a class="toc-backref" href="#id4">Running Dbench</a></h3> +<p>The distributedlog-benchmark binary dbench is intended to be run simultaneously from many machines with identical settings. Together, all instances of dbench comprise a benchmark job. How you launch a benchmark job will depend on your operating environment. We recommend using a cluster scheduler like aurora or kubernetes to simplify the process, but tools like capistrano can also simplify this process greatly.</p> +<p>The benchmark script can be found at</p> +<pre class="literal-block"> +distributedlog-benchmark/bin/dbench +</pre> +<p>Arguments may be passed to this script via environment variables. The available arguments depend on the execution mode. For an up to date list, check the script itself.</p> +</div> +<div class="section" id="write-to-proxy-with-thin-client"> +<h3><a class="toc-backref" href="#id5">Write to Proxy with Thin Client</a></h3> +<p>The proxy write test (mode = <cite>write</cite>) can be used to send writes to a proxy cluster to be written to a set of streams.</p> +<p>For example to use the proxy write test to generate 10000 requests per second across 10 streams using 50 machines, run the following command on each machine.</p> +<pre class="literal-block"> +STREAM_NAME_PREFIX=loadtest_ +BENCHMARK_DURATION=60 # minutes +DL_NAMESPACE=<dl namespace> +NUM_STREAMS=10 +INITIAL_RATE=200 +distributedlog-benchmark/bin/dbench write +</pre> +</div> +<div class="section" id="write-to-bookkeeper-with-core-library"> +<h3><a class="toc-backref" href="#id6">Write to BookKeeper with Core Library</a></h3> +<p>The core library write test (mode = <cite>bkwrite</cite>) can be used to send writes to directly to bookkeeper using the core library.</p> +<p>For example to use the core library write test to generate 100MBps across 10 streams using 100 machines, run the following command on each machine.</p> +<pre class="literal-block"> +STREAM_NAME_PREFIX=loadtest_ +BENCHMARK_DURATION=60 # minutes +DL_NAMESPACE=<dl namespace> +NUM_STREAMS=10 +INITIAL_RATE=1024 +MSG_SIZE=1024 +distributedlog-benchmark/bin/dbench bkwrite +</pre> +</div> +<div class="section" id="read-from-bookkeeper-with-core-library"> +<h3><a class="toc-backref" href="#id7">Read from BookKeeper with Core Library</a></h3> +<p>The core library read test (mode = <cite>read</cite>) can be used to read directly from bookkeeper using the core library.</p> +<p>For example to use the core library read test to read from 10 streams on 100 instances, run the following command on each machine.</p> +<pre class="literal-block"> +STREAM_NAME_PREFIX=loadtest_ +BENCHMARK_DURATION=60 # minutes +DL_NAMESPACE=<dl namespace> +MAX_STREAM_ID=9 +NUM_READERS_PER_STREAM=5 +TRUNCATION_INTERVAL=60 # seconds +distributedlog-benchmark/bin/dbench read +</pre> +</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="/docs/0.4.0-incubating/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> http://git-wip-us.apache.org/repos/asf/incubator-distributedlog/blob/49afadb4/docs/0.4.0-incubating/admin_guide/main.html ---------------------------------------------------------------------- diff --git a/docs/0.4.0-incubating/admin_guide/main.html b/docs/0.4.0-incubating/admin_guide/main.html new file mode 100644 index 0000000..db6c3d3 --- 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