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| |
| <h1>Scio Interpreter for Apache Zeppelin</h1> |
| |
| <div id="toc"></div> |
| |
| <h2>Overview</h2> |
| |
| <p>Scio is a Scala DSL for <a href="https://github.com/GoogleCloudPlatform/DataflowJavaSDK">Google Cloud Dataflow</a> and <a href="http://beam.incubator.apache.org/">Apache Beam</a> inspired by <a href="http://spark.apache.org/">Spark</a> and <a href="https://github.com/twitter/scalding">Scalding</a>. See the current <a href="https://github.com/spotify/scio/wiki">wiki</a> and <a href="http://spotify.github.io/scio/">API documentation</a> for more information.</p> |
| |
| <h2>Configuration</h2> |
| |
| <table class="table-configuration"> |
| <tr> |
| <th>Name</th> |
| <th>Default Value</th> |
| <th>Description</th> |
| </tr> |
| <tr> |
| <td>zeppelin.scio.argz</td> |
| <td>--runner=InProcessPipelineRunner</td> |
| <td>Scio interpreter wide arguments. Documentation: https://github.com/spotify/scio/wiki#options and https://cloud.google.com/dataflow/pipelines/specifying-exec-params</td> |
| </tr> |
| <tr> |
| <td>zeppelin.scio.maxResult</td> |
| <td>1000</td> |
| <td>Max number of SCollection results to display</td> |
| </tr> |
| |
| </table> |
| |
| <h2>Enabling the Scio Interpreter</h2> |
| |
| <p>In a notebook, to enable the <strong>Scio</strong> interpreter, click the <strong>Gear</strong> icon and select <strong>beam</strong> (<strong>beam.scio</strong>).</p> |
| |
| <h2>Using the Scio Interpreter</h2> |
| |
| <p>In a paragraph, use <code>%beam.scio</code> to select the <strong>Scio</strong> interpreter. You can use it much the same way as vanilla Scala REPL and <a href="https://github.com/spotify/scio/wiki/Scio-REPL">Scio REPL</a>. State (like variables, imports, execution etc) is shared among all <em>Scio</em> paragraphs. There is a special variable <strong>argz</strong> which holds arguments from Scio interpreter settings. The easiest way to proceed is to create a Scio context via standard <code>ContextAndArgs</code>.</p> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| </code></pre></div> |
| <p>Use <code>sc</code> context the way you would in a regular pipeline/REPL.</p> |
| |
| <p>Example:</p> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="o">(</span><span class="nc">Seq</span><span class="o">(</span><span class="s">"foo"</span><span class="o">,</span> <span class="s">"foo"</span><span class="o">,</span> <span class="s">"bar"</span><span class="o">)).</span><span class="n">countByValue</span><span class="o">.</span><span class="n">closeAndDisplay</span><span class="o">()</span> |
| </code></pre></div> |
| <p>If you close Scio context, go ahead an create a new one using <code>ContextAndArgs</code>. Please refer to <a href="https://github.com/spotify/scio/wiki">Scio wiki</a> for more complex examples. You can close Scio context much the same way as in Scio REPL, and use Zeppelin display helpers to synchronously close and display results - read more below.</p> |
| |
| <h3>Progress</h3> |
| |
| <p>There can be only one paragraph running at once. There is no notion of overall progress, thus progress bar will show <code>0</code>.</p> |
| |
| <h3>SCollection display helpers</h3> |
| |
| <p>Scio interpreter comes with display helpers to ease working with Zeppelin notebooks. Simply use <code>closeAndDisplay()</code> on <code>SCollection</code> to close context and display the results. The number of results is limited by <code>zeppelin.scio.maxResult</code> (by default 1000).</p> |
| |
| <p>Supported <code>SCollection</code> types:</p> |
| |
| <ul> |
| <li>Scio's typed BigQuery</li> |
| <li>Scala's Products (case classes, tuples)</li> |
| <li>Google BigQuery's TableRow</li> |
| <li>Apache Avro</li> |
| <li>All Scala's <code>AnyVal</code></li> |
| </ul> |
| |
| <h4>Helper methods</h4> |
| |
| <p>There are different helper methods for different objects. You can easily display results from <code>SCollection</code>, <code>Future[Tap]</code> and <code>Tap</code>.</p> |
| |
| <h5><code>SCollection</code> helper</h5> |
| |
| <p><code>SCollection</code> has <code>closeAndDisplay</code> Zeppelin helper method for types listed above. Use it to synchronously close Scio context, and once available pull and display results.</p> |
| |
| <h5><code>Future[Tap]</code> helper</h5> |
| |
| <p><code>Future[Tap]</code> has <code>waitAndDisplay</code> Zeppelin helper method for types listed above. Use it to synchronously wait for results, and once available pull and display results.</p> |
| |
| <h5><code>Tap</code> helper</h5> |
| |
| <p><code>Tap</code> has <code>display</code> Zeppelin helper method for types listed above. Use it to pull and display results.</p> |
| |
| <h3>Examples</h3> |
| |
| <h4>BigQuery example:</h4> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="nd">@BigQueryType</span><span class="o">.</span><span class="n">fromQuery</span><span class="o">(</span><span class="s">"""|SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays</span> |
| <span class="s"> |FROM [bigquery-samples:airline_ontime_data.flights]</span> |
| <span class="s"> |group by departure_airport</span> |
| <span class="s"> |order by 2 desc</span> |
| <span class="s"> |limit 10"""</span><span class="o">.</span><span class="n">stripMargin</span><span class="o">)</span> <span class="k">class</span> <span class="nc">Flights</span> |
| |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">bigQuerySelect</span><span class="o">(</span><span class="nc">Flights</span><span class="o">.</span><span class="n">query</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">(</span><span class="nc">Flights</span><span class="o">.</span><span class="n">schema</span><span class="o">)</span> |
| </code></pre></div> |
| <h4>BigQuery typed example:</h4> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="nd">@BigQueryType</span><span class="o">.</span><span class="n">fromQuery</span><span class="o">(</span><span class="s">"""|SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays</span> |
| <span class="s"> |FROM [bigquery-samples:airline_ontime_data.flights]</span> |
| <span class="s"> |group by departure_airport</span> |
| <span class="s"> |order by 2 desc</span> |
| <span class="s"> |limit 10"""</span><span class="o">.</span><span class="n">stripMargin</span><span class="o">)</span> <span class="k">class</span> <span class="nc">Flights</span> |
| |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">typedBigQuery</span><span class="o">[</span><span class="kt">Flights</span><span class="o">]().</span><span class="n">flatMap</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">no_of_delays</span><span class="o">).</span><span class="n">mean</span><span class="o">.</span><span class="n">closeAndDisplay</span><span class="o">()</span> |
| </code></pre></div> |
| <h4>Avro example:</h4> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="k">import</span> <span class="nn">com.spotify.data.ExampleAvro</span> |
| |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| <span class="n">sc</span><span class="o">.</span><span class="n">avroFile</span><span class="o">[</span><span class="kt">ExampleAvro</span><span class="o">](</span><span class="s">"gs://<bucket>/tmp/my.avro"</span><span class="o">).</span><span class="n">take</span><span class="o">(</span><span class="mi">10</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">()</span> |
| </code></pre></div> |
| <h4>Avro example with a view schema:</h4> |
| <div class="highlight"><pre><code class="scala language-scala" data-lang="scala"><span class="o">%</span><span class="n">beam</span><span class="o">.</span><span class="n">scio</span> |
| <span class="k">import</span> <span class="nn">com.spotify.data.ExampleAvro</span> |
| <span class="k">import</span> <span class="nn">org.apache.avro.Schema</span> |
| |
| <span class="k">val</span> <span class="o">(</span><span class="n">sc</span><span class="o">,</span> <span class="n">args</span><span class="o">)</span> <span class="k">=</span> <span class="nc">ContextAndArgs</span><span class="o">(</span><span class="n">argz</span><span class="o">)</span> |
| <span class="k">val</span> <span class="n">view</span> <span class="k">=</span> <span class="nc">Schema</span><span class="o">.</span><span class="n">parse</span><span class="o">(</span><span class="s">"""{"type":"record","name":"ExampleAvro","namespace":"com.spotify.data","fields":[{"name":"track","type":"string"}, {"name":"artist", "type":"string"}]}"""</span><span class="o">)</span> |
| |
| <span class="n">sc</span><span class="o">.</span><span class="n">avroFile</span><span class="o">[</span><span class="kt">EndSongCleaned</span><span class="o">](</span><span class="s">"gs://<bucket>/tmp/my.avro"</span><span class="o">).</span><span class="n">take</span><span class="o">(</span><span class="mi">10</span><span class="o">).</span><span class="n">closeAndDisplay</span><span class="o">(</span><span class="n">view</span><span class="o">)</span> |
| </code></pre></div> |
| <h3>Google credentials</h3> |
| |
| <p>Scio Interpreter will try to infer your Google Cloud credentials from its environment, it will take into the account:</p> |
| |
| <ul> |
| <li><code>argz</code> interpreter settings (<a href="https://github.com/spotify/scio/wiki#options">doc</a>)</li> |
| <li>environment variable (<code>GOOGLE_APPLICATION_CREDENTIALS</code>)</li> |
| <li>gcloud configuration</li> |
| </ul> |
| |
| <h4>BigQuery macro credentials</h4> |
| |
| <p>Currently BigQuery project for macro expansion is inferred using Google Dataflow's <a href="https://github.com/GoogleCloudPlatform/DataflowJavaSDK/blob/master/sdk/src/main/java/com/google/cloud/dataflow/sdk/options/GcpOptions.java#L187">DefaultProjectFactory().create()</a></p> |
| |
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| </div> |
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