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<!DOCTYPE html>
<html lang="en" prefix="og: http://ogp.me/ns# fb: https://www.facebook.com/2008/fbml">
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<article>
<h2><a href="http://www.lyh.me/scio-a-scala-api-for-google-cloud-dataflow.html">Scio, a Scala <span class="caps">API</span> for Google Cloud Dataflow</a></h2>
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<span class="label label-default">Date</span>
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<i class="fa fa-calendar"></i><time datetime="2016-04-21T12:47:00-04:00"> Thu 21 April 2016</time>
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<div class="summary"><p>We recently open sourced <a href="https://github.com/spotify/scio">Scio</a>, a Scala <span class="caps">API</span> for <a href="https://github.com/GoogleCloudPlatform/DataflowJavaSDK">Google Cloud Dataflow</a>. Here are the slides of our talk at <a href="https://cloudplatformonline.com/NEXT2016.html"><span class="caps">GCPNEXT16</span></a> a few weeks ago.</p>
<iframe src="//www.slideshare.net/slideshow/embed_code/key/rRPUB4cSAvgF8M" width="800" height="490" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe>
<p><div style="margin-bottom:5px"> <strong> <a href="//www.slideshare.net/sinisalyh/from-stream-to-recommendation-using-apache-beam-with-cloud-pubsub-and-cloud-dataflow" title="From stream to recommendation using apache beam with cloud pubsub and cloud dataflow" target="_blank">From stream to recommendation using apache beam with cloud pubsub and cloud dataflow</a> </strong> from <strong><a href="//www.slideshare.net/sinisalyh" target="_blank">Neville Li</a></strong> </div></p>
<p>The first half of the talk covers our experiments with Dataflow and Pub/Sub for streaming application while the second half covers Scio and BigQuery for batch analysis and machine learning.</p>
<a class="btn btn-default btn-xs" href="http://www.lyh.me/scio-a-scala-api-for-google-cloud-dataflow.html">more ...</a>
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<article>
<h2><a href="http://www.lyh.me/scala-data-pipelines-spotify.html">Scala Data Pipelines @ Spotify</a></h2>
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<footer class="post-info">
<span class="label label-default">Date</span>
<span class="published">
<i class="fa fa-calendar"></i><time datetime="2015-11-10T11:26:00-05:00"> Tue 10 November 2015</time>
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<div class="summary"><p>It’s been a while since I last updated this blog. I did a talk at <a href="http://bigdatascala.bythebay.io/">Big Data Scala</a> this summer and here are the <a href="http://www.slideshare.net/sinisalyh/scala-data-pipelines-spotify">slides</a></p>
<iframe src="//www.slideshare.net/slideshow/embed_code/key/10GyruQgE9UUpv" width="800" height="490" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe>
<p><div style="margin-bottom:5px"> <strong> <a href="//www.slideshare.net/sinisalyh/scala-data-pipelines-spotify" title="Scala Data Pipelines @ Spotify" target="_blank">Scala Data Pipelines @ Spotify</a> </strong> from <strong><a href="//www.slideshare.net/sinisalyh" target="_blank">Neville Li</a></strong> </div></p>
<a class="btn btn-default btn-xs" href="http://www.lyh.me/scala-data-pipelines-spotify.html">more ...</a>
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<h2><a href="http://www.lyh.me/primitives.html">Primitives</a></h2>
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<i class="fa fa-calendar"></i><time datetime="2015-05-14T08:50:00-04:00"> Thu 14 May 2015</time>
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<div class="summary"><p>Another day, another talk. This one is on primitives and here are the <a href="/slides/primitives.html">slides</a></p>
<iframe src="/slides/primitives.html" width="800" height="450"></iframe>
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<h2><a href="http://www.lyh.me/type-classes.html">Type Classes</a></h2>
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<i class="fa fa-calendar"></i><time datetime="2015-04-20T15:39:00-04:00"> Mon 20 April 2015</time>
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<div class="summary"><p>I started giving more Scala talks internally at <a href="http://www.spotify.com/">Spotify</a>. The first one is on type classes and here are the <a href="/slides/type-classes.html">slides</a></p>
<iframe src="/slides/type-classes.html" width="800" height="450"></iframe>
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<h2><a href="http://www.lyh.me/nescala-2015-talk.html">NEScala 2015 talk</a></h2>
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<i class="fa fa-calendar"></i><time datetime="2015-02-04T11:02:00-05:00"> Wed 04 February 2015</time>
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<div class="summary"><p>I gave a lightning talk at <a href="http://www.nescala.org/">Northeast Scala Symposium</a> last week on Macros in Datapipelines and here are the <a href="/slides/macros.html">slides</a>.</p>
<iframe src="/slides/macros.html" width="800" height="450"></iframe>
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<h2><a href="http://www.lyh.me/fun-with-macros-and-parquet-avro.html">Fun with macros and parquet-avro</a></h2>
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<i class="fa fa-calendar"></i><time datetime="2015-01-08T14:01:00-05:00"> Thu 08 January 2015</time>
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<a href="http://www.lyh.me/tag/scala.html">scala</a>
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<div class="summary"><p>I recently had some fun building <a href="https://github.com/nevillelyh/parquet-avro-extra">parquet-avro-extra</a>, an add-on module for <a href="https://github.com/Parquet/parquet-mr/tree/master/parquet-avro">parquet-avro</a> using <a href="http://scalamacros.org/">Scala macros</a>. I did it mainly to learn Scala macros but also to make it easier to use <a href="http://parquet.incubator.apache.org/">Parquet</a> with <a href="http://avro.apache.org/">Avro</a> in a data pipeline.</p>
<h2>Parquet and Avro</h2>
<p>Parquet is a columnar storage system designed for <span class="caps">HDFS</span>. It offers some nice improvements over row-major systems including better compression and less I/O with column projection and predicate pushdown. Avro is a data serialization system that enables type-safe access to structured data with complex schema. The <code>parquet-avro</code> module makes it possible to store data in Parquet format on disk and process them as Avro objects inside a <span class="caps">JVM</span> data pipeline like <a href="https://github.com/twitter/scalding">Scalding</a> or <a href="http://spark.apache.org/">Spark</a>.</p>
<h2>Projection</h2>
<p>Parquet allows reading only a subset of columns via projection. Here’s an Scalding <a href="https://github.com/epishkin/scalding/tree/parquet_avro/scalding-parquet">example</a> from <a href="http://www.tapad.com/">Tapad</a>.</p>
<div class="highlight"><pre><span></span><span class="nc">Projection</span><span class="o">[</span><span class="kt">Signal</span><span class="o">](</span><span class="s">"field1"</span><span class="o">,</span> <span class="s">"field2.field2a"</span><span class="o">)</span>
</pre></div>
<p>Note that fields specifications are strings even though the <span class="caps">API</span> has access to Avro type <code>Signal</code> which has strongly typed getter methods.</p>
<p>This is slightly counter-intuitive since most Scala developers are used to transformations like <code>pipe.map(_.getField)</code>. It’s however can be easily solved with macro since the syntax tree of is accessible. A modified version has signature of …</p>
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<h2><a href="http://www.lyh.me/three-reasons-a-data-engineer-should-learn-scala.html">Three Reasons a Data Engineer Should Learn Scala</a></h2>
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<span class="published">
<i class="fa fa-calendar"></i><time datetime="2014-11-17T23:15:00-05:00"> Mon 17 November 2014</time>
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<div class="summary"><p><em>This article was written in collaboration with <a href="https://www.hakkalabs.co">Hakka Labs</a> (<a href="https://www.hakkalabs.co/articles/three-reasons-data-eng-learn-scala">original link</a>)</em></p>
<p>There has been a lot of debate over Scala lately, including criticisms like <a href="http://java.dzone.com/articles/i-dont-scala">this</a>, <a href="http://overwatering.org/blog/2013/12/scala-1-star-would-not-program-again/">this</a>, <a href="http://www.infoq.com/news/2011/11/yammer-scala">this</a>, and defenses like <a href="http://blog.gridgainsystems.com/in-defense-of-scala-response-to-i-dont-like-scala/">this</a> and <a href="http://blog.gridgainsystems.com/in-defense-of-scala-part-2/">this</a>. Most of the criticisms seem to focus on the language’s complexity, performance, and integration with existing tools and libraries, while some praise its elegant syntax, powerful type system, and good fit for domain-specific languages.</p>
<p>However most of the discussions seem based on experiences building production backend or web systems where there are a lot of other options already. There are mature, battle tested options like Java, Erlang or even <span class="caps">PHP</span>, and there are Go, node.js, or Python for those who are more adventurous or prefer agility over performance.</p>
<p>Here I want to argue that there’s a best tool for every job, and Scala shines for data processing and machine learning, for the following reasons:</p>
<ul>
<li>good balance between productivity and performance</li>
<li>integration with big data ecosystem</li>
<li>functional paradigm</li>
</ul>
<h2>Productivity without sacrificing performance</h2>
<p>In the big data <span class="amp">&</span> machine learning world where most developers are from Python/R/Matlab background, Scala’s syntax, or the subset needed for the domain, is a lot less intimidating than that …</p>
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<h2><a href="http://www.lyh.me/scala-workshop.html">Scala Workshop</a></h2>
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<i class="fa fa-calendar"></i><time datetime="2014-10-04T21:52:00-04:00"> Sat 04 October 2014</time>
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<div class="summary"><p>While there are many Scala tutorials and books available, very few of them focus on big data. I did a couple of workshops at Spotify focusing on these areas and here are the <a href="/slides/workshop.html">slides</a>.</p>
<iframe src="/slides/workshop.html" width="800" height="450"></iframe>
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<article>
<h2><a href="http://www.lyh.me/using-cql-with-legacy-column-families.html">Using <span class="caps">CQL</span> with legacy column families</a></h2>
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<span class="published">
<i class="fa fa-calendar"></i><time datetime="2014-09-13T20:47:00-04:00"> Sat 13 September 2014</time>
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<a href="http://www.lyh.me/tag/cassandra.html">cassandra</a>
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<div class="summary"><p>We use <a href="http://cassandra.apache.org/">Cassandra</a> extensively <a href="http://www.slideshare.net/JimmyMrdell/playlists-at-spotify-cassandra-summit-london-2013?related=1">at work</a>, and up till recently we’ve been using mostly Cassandra 1.2 with <a href="https://github.com/Netflix/astyanax">Astyanax</a> and <a href="https://thrift.apache.org/">Thrift</a> protocol in Java applications. Very recently we started adopting Cassandra 2.0 with <span class="caps">CQL</span>, <a href="https://github.com/datastax/java-driver">DataStax Java Driver</a> and binary protocol.</p>
<p>While one should move to <span class="caps">CQL</span> schema to take full advantage of the new protocol and storage engine, it’s still possible to use <span class="caps">CQL</span> and the new driver on existing clusters. Say we have a legacy column family with <code>UTF8Type</code> for row/column keys and <code>BytesType</code> for values, it would look like this in <code>cassandra-cli</code>:</p>
<div class="highlight"><pre><span></span><span class="k">create</span> <span class="k">column</span> <span class="n">family</span> <span class="k">data</span>
<span class="k">with</span> <span class="n">column_type</span> <span class="o">=</span> <span class="s1">'Standard'</span>
<span class="k">and</span> <span class="n">comparator</span> <span class="o">=</span> <span class="s1">'UTF8Type'</span>
<span class="k">and</span> <span class="n">default_validation_class</span> <span class="o">=</span> <span class="s1">'BytesType'</span>
<span class="k">and</span> <span class="n">key_validation_class</span> <span class="o">=</span> <span class="s1">'UTF8Type'</span><span class="p">;</span>
</pre></div>
<p>And this in <code>cqlsh</code> after setting <code>start_native_transport: true</code> in <code>cassandra.yaml</code>:</p>
<div class="highlight"><pre><span></span><span class="k">CREATE</span> <span class="k">TABLE</span> <span class="k">data</span> <span class="p">(</span>
<span class="k">key</span> <span class="nb">text</span><span class="p">,</span>
<span class="n">column1</span> <span class="nb">text</span><span class="p">,</span>
<span class="n">value</span> <span class="nb">blob</span><span class="p">,</span>
<span class="k">PRIMARY</span> <span class="k">KEY</span> <span class="p">(</span><span class="k">key</span><span class="p">,</span> <span class="n">column1</span><span class="p">)</span>
<span class="p">)</span> <span class="k">WITH</span> <span class="n">COMPACT</span> <span class="k">STORAGE</span><span class="p">;</span>
</pre></div>
<p>In this table, <code>key</code> and <code>column1</code> corresponds to row and column keys in the legacy column family and <code>value</code> corresponds to column value.</p>
<p>Queries to look up a column value, an entire row, and selected columns in a row would look like this:</p>
<div class="highlight"><pre><span></span><span class="k">SELECT</span> <span class="n">value</span> <span class="k">FROM</span> <span class="n">mykeyspace</span><span class="p">.</span><span class="k">data</span> <span class="k">WHERE</span> <span class="k">key</span> <span class="o">=</span> <span class="s1">'rowkey'</span> <span class="k">AND</span> <span class="n">column1</span> <span class="o">=</span> <span class="s1">'colkey'</span><span class="p">;</span>
<span class="k">SELECT</span> <span class="n">column1</span><span class="p">,</span> <span class="n">value</span> <span class="k">FROM</span> <span class="n">mykeyspace …</span></pre></div>
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<h2><a href="http://www.lyh.me/dotfiles-update.html">dotfiles update</a></h2>
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<div class="summary"><p>I’ve been using my current <a href="http://www.lyh.me/dotfiles.html">dotfiles</a> setup for a while and felt it’s time to freshen up. I focused on updating the look and feel of Vim and tmux this round.</p>
<p>First I switched to <a href="https://github.com/tomasr/molokai">molokai</a> color theme for Vim, <a href="http://macromates.com/">TextMate</a> (monokai) and <a href="http://www.jetbrains.com/idea/">IntelliJ <span class="caps">IDEA</span></a> (using <a href="https://github.com/y3sh/Intellij-Colors-Sublime-Monokai">this</a>). I guess I grew tired of the old trusted <a href="http://ethanschoonover.com/solarized">solarized</a>, plus with my new MacBook Pro 13” at highest resolution, it just doesn’t feel sharp enough.</p>
<p>The <a href="https://github.com/Lokaltog/vim-powerline">vim-powerline</a> plugin I was using is being deprecated and replaced by <a href="https://github.com/Lokaltog/powerline">powerline</a>, which supports vim, tmux, zsh, and many others. However it requires Python and I had trouble using it with some really old Vim versions at work. So instead I switched to a pure VimL plugin, <a href="https://github.com/bling/vim-airline">vim-airline</a>. Not surprisingly there’s a companion plugin, <a href="https://github.com/edkolev/tmuxline.vim">tmuxline</a> for tmux as well. Both have no extra dependencies which is a big plus for me since I use the same dotfiles on Mac, my Ubuntu Trusty destop at work, and many Debian Squeeze servers.</p>
<p>I also updated a couple of other Vim plugins along the process, replacing <a href="https://github.com/garbas/vim-snipmate">vim-snipmate</a> with <a href="https://github.com/SirVer/ultisnips">ultisnips</a>, <a href="https://github.com/bitc/vim-bad-whitespace">vim-bad-whitespace</a> with <a href="https://github.com/ntpeters/vim-better-whitespace">vim-better-whitespace</a> (no pun intended), and adding <a href="https://github.com/airblade/vim-gitgutter">vim-gutter</a>. The biggest discovery is <a href="https://github.com/Lokaltog/vim-easymotion">vim-easymotion</a> though, perfect …</p>
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