deploy: b648b4a

Author: charles-tan

Builtin.html

@@ -237,7 +237,7 @@
 <ul style="display: none">
 <li class="md-nav__item md-version" id="project.version">
 <label class="md-nav__link" for="__version">
-<i class="md-icon" title="Version">label_outline</i> 0.14.16-9-3cf3f89-20250507T143400Z*
+<i class="md-icon" title="Version">label_outline</i> 0.14.17-31-b648b4a-20250714T202047Z*
 </label>
 </li>
 </ul>
@@ -277,9 +277,9 @@ <h1><a href="#built-in-functionality" name="built-in-functionality" class="ancho
 <p>Scio is a thin wrapper on top of Beam offering idiomatic Scala APIs. Check out the <a href="https://beam.apache.org/documentation/programming-guide/">Beam Programming Guide</a> first for a detailed explanation of the Beam programming model and concepts.</p>
 <h2><a href="#basics" name="basics" class="anchor"><span class="anchor-link"></span></a>Basics</h2>
 <ul>
-  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/ScioContext.html" title="com.spotify.scio.ScioContext"><code>ScioContext</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/Pipeline.html" title="org.apache.beam.sdk.Pipeline"><code>Pipeline</code></a></li>
-  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html" title="com.spotify.scio.values.SCollection"><code>SCollection</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/values/PCollection.html" title="org.apache.beam.sdk.values.PCollection"><code>PCollection</code></a></li>
-  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/ScioResult.html" title="com.spotify.scio.ScioResult"><code>ScioResult</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/PipelineResult.html" title="org.apache.beam.sdk.PipelineResult"><code>PipelineResult</code></a></li>
+  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/ScioContext.html" title="com.spotify.scio.ScioContext"><code>ScioContext</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/Pipeline.html" title="org.apache.beam.sdk.Pipeline"><code>Pipeline</code></a></li>
+  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html" title="com.spotify.scio.values.SCollection"><code>SCollection</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/values/PCollection.html" title="org.apache.beam.sdk.values.PCollection"><code>PCollection</code></a></li>
+  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/ScioResult.html" title="com.spotify.scio.ScioResult"><code>ScioResult</code></a> wraps Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/PipelineResult.html" title="org.apache.beam.sdk.PipelineResult"><code>PipelineResult</code></a></li>
 </ul>
 <p>See dedicated sections on:</p>
 <ul>
@@ -338,7 +338,7 @@ <h2><a href="#contextandargs" name="contextandargs" class="anchor"><span class="
 val cmdlineArgs: Array[String] = ???
 val (sc, args) = ContextAndArgs(cmdlineArgs)
 </code></pre>
-<p>If you need custom pipeline options, subclass Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/options/PipelineOptions.html" title="org.apache.beam.sdk.options.PipelineOptions"><code>PipelineOptions</code></a> and use <code>ContextAndArgs.typed</code>:</p>
+<p>If you need custom pipeline options, subclass Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/options/PipelineOptions.html" title="org.apache.beam.sdk.options.PipelineOptions"><code>PipelineOptions</code></a> and use <code>ContextAndArgs.typed</code>:</p>
 <pre class="prettyprint"><code class="language-scala mdoc:compile-only">import com.spotify.scio._
 import org.apache.beam.sdk.options.PipelineOptions
 
@@ -357,7 +357,7 @@ <h3><a href="#counting" name="counting" class="anchor"><span class="anchor-link"
 <ul>
   <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#count:com.spotify.scio.values.SCollection[Long]" title="com.spotify.scio.values.SCollection"><code>count</code></a> (or <code>countByKey</code>) counts the number of elements</li>
   <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#countByValue:com.spotify.scio.values.SCollection[(T,Long)]" title="com.spotify.scio.values.SCollection"><code>countByValue</code></a> counts the number of elements for each value in a <code>SCollection[T]</code></li>
-  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#countApproxDistinct(estimator:com.spotify.scio.estimators.ApproxDistinctCounter[T]):com.spotify.scio.values.SCollection[Long]" title="com.spotify.scio.values.SCollection"><code>countApproxDistinct</code></a> (or <code>countApproxDistinctByKey</code>) estimates a distinct count, with Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/transforms/ApproximateUnique.html" title="org.apache.beam.sdk.transforms.ApproximateUnique"><code>ApproximateUnique</code></a> or Scio&rsquo;s HyperLogLog-based <a href="https://spotify.github.io/scio/api/com/spotify/scio/estimators/ApproxDistinctCounter.html" title="com.spotify.scio.estimators.ApproxDistinctCounter"><code>ApproxDistinctCounter</code></a></li>
+  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#countApproxDistinct(estimator:com.spotify.scio.estimators.ApproxDistinctCounter[T]):com.spotify.scio.values.SCollection[Long]" title="com.spotify.scio.values.SCollection"><code>countApproxDistinct</code></a> (or <code>countApproxDistinctByKey</code>) estimates a distinct count, with Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/transforms/ApproximateUnique.html" title="org.apache.beam.sdk.transforms.ApproximateUnique"><code>ApproximateUnique</code></a> or Scio&rsquo;s HyperLogLog-based <a href="https://spotify.github.io/scio/api/com/spotify/scio/estimators/ApproxDistinctCounter.html" title="com.spotify.scio.estimators.ApproxDistinctCounter"><code>ApproxDistinctCounter</code></a></li>
 </ul>
 <pre class="prettyprint"><code class="language-scala mdoc:compile-only">import com.spotify.scio.values.SCollection
 import com.spotify.scio.extra.hll.zetasketch.ZetaSketchHllPlusPlus
@@ -371,7 +371,7 @@ <h3><a href="#statistics" name="statistics" class="anchor"><span class="anchor-l
   <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#max(implicitord:Ordering[T]):com.spotify.scio.values.SCollection[T]" title="com.spotify.scio.values.SCollection"><code>max</code></a> (or <code>maxByKey</code>) finds the maximum element given some <a href="http://www.scala-lang.org/api/2.13.16/scala/math/Ordering.html" title="scala.math.Ordering"><code>Ordering</code></a></li>
   <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#min(implicitord:Ordering[T]):com.spotify.scio.values.SCollection[T]" title="com.spotify.scio.values.SCollection"><code>min</code></a> (or <code>minByKey</code>) finds the minimum element given some <a href="http://www.scala-lang.org/api/2.13.16/scala/math/Ordering.html" title="scala.math.Ordering"><code>Ordering</code></a></li>
   <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#mean(implicitev:Numeric[T]):com.spotify.scio.values.SCollection[Double]" title="com.spotify.scio.values.SCollection"><code>mean</code></a> finds the mean given some <a href="http://www.scala-lang.org/api/2.13.16/scala/math/Numeric.html" title="scala.math.Numeric"><code>Numeric</code></a></li>
-  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#quantilesApprox(numQuantiles:Int)(implicitord:Ordering[T]):com.spotify.scio.values.SCollection[Iterable[T]]" title="com.spotify.scio.values.SCollection"><code>quantilesApprox</code></a> (or <code>approxQuantilesByKey</code>) finds the distribution using Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/transforms/ApproximateQuantiles.html" title="org.apache.beam.sdk.transforms.ApproximateQuantiles"><code>ApproximateQuantiles</code></a></li>
+  <li><a href="https://spotify.github.io/scio/api/com/spotify/scio/values/SCollection.html#quantilesApprox(numQuantiles:Int)(implicitord:Ordering[T]):com.spotify.scio.values.SCollection[Iterable[T]]" title="com.spotify.scio.values.SCollection"><code>quantilesApprox</code></a> (or <code>approxQuantilesByKey</code>) finds the distribution using Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/transforms/ApproximateQuantiles.html" title="org.apache.beam.sdk.transforms.ApproximateQuantiles"><code>ApproximateQuantiles</code></a></li>
 </ul>
 <p>For <code>SCollection</code>s containing <code>Double</code>, Scio additionally provides a <a href="https://spotify.github.io/scio/api/com/spotify/scio/values/DoubleSCollectionFunctions.html#stats:com.spotify.scio.values.SCollection[com.spotify.scio.util.StatCounter]" title="com.spotify.scio.values.DoubleSCollectionFunctions"><code>stats</code></a> method that computes the count, mean, min, max, variance, standard deviation, sample variance, and sample standard deviation over the <code>SCollection</code>. Convenience methods are available directly on the <a href="https://spotify.github.io/scio/api/com/spotify/scio/values/DoubleSCollectionFunctions.html" title="com.spotify.scio.values.DoubleSCollectionFunctions"><code>SCollection</code></a> if only a single value is required:</p>
 <pre class="prettyprint"><code class="language-scala mdoc:compile-only">import com.spotify.scio.values.SCollection
@@ -423,7 +423,7 @@ <h3><a href="#sums-combinations" name="sums-combinations" class="anchor"><span c
 </code></pre>
 <p>See also <a href="extras/Algebird.html">Algebird</a></p>
 <h2><a href="#metrics" name="metrics" class="anchor"><span class="anchor-link"></span></a>Metrics</h2>
-<p>Scio supports Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/metrics/Counter.html" title="org.apache.beam.sdk.metrics.Counter"><code>Counter</code></a> <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/metrics/Distribution.html" title="org.apache.beam.sdk.metrics.Distribution"><code>Distribution</code></a> and <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/metrics/Gauge.html" title="org.apache.beam.sdk.metrics.Gauge"><code>Gauge</code></a>.</p>
+<p>Scio supports Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/metrics/Counter.html" title="org.apache.beam.sdk.metrics.Counter"><code>Counter</code></a> <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/metrics/Distribution.html" title="org.apache.beam.sdk.metrics.Distribution"><code>Distribution</code></a> and <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/metrics/Gauge.html" title="org.apache.beam.sdk.metrics.Gauge"><code>Gauge</code></a>.</p>
 <p>See <a href="https://spotify.github.io/scio/examples/MetricsExample.scala.html">MetricsExample</a>.</p>
 <h2><a href="#scioresult" name="scioresult" class="anchor"><span class="anchor-link"></span></a>ScioResult</h2>
 <p><a href="https://spotify.github.io/scio/api/com/spotify/scio/ScioResult.html" title="com.spotify.scio.ScioResult"><code>ScioResult</code></a> can be used to access metric values, individually or as a group:</p>
@@ -596,7 +596,7 @@ <h2><a href="#misc" name="misc" class="anchor"><span class="anchor-link"></span>
 </div>
 <div class="print-only">
 <span class="md-source-file md-version">
-0.14.16-9-3cf3f89-20250507T143400Z*
+0.14.17-31-b648b4a-20250714T202047Z*
 </span>
 </div>
 </article>

FAQ.html

@@ -233,7 +233,7 @@
 <ul style="display: none">
 <li class="md-nav__item md-version" id="project.version">
 <label class="md-nav__link" for="__version">
-<i class="md-icon" title="Version">label_outline</i> 0.14.16-9-3cf3f89-20250507T143400Z*
+<i class="md-icon" title="Version">label_outline</i> 0.14.17-31-b648b4a-20250714T202047Z*
 </label>
 </li>
 </ul>
@@ -585,7 +585,7 @@ <h4><a href="#how-do-i-access-various-files-outside-of-a-sciocontext-" name="how
 <ul>
   <li>For Scio version &gt;= <code>0.4.0</code></li>
 </ul>
-<p>Starting from Scio <code>0.4.0</code> you can use Apache Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/io/FileSystems.html" title="org.apache.beam.sdk.io.FileSystems"><code>Filesystems</code></a> abstraction:</p>
+<p>Starting from Scio <code>0.4.0</code> you can use Apache Beam&rsquo;s <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/io/FileSystems.html" title="org.apache.beam.sdk.io.FileSystems"><code>Filesystems</code></a> abstraction:</p>
 <pre class="prettyprint"><code class="language-scala mdoc:reset:silent">import org.apache.beam.sdk.io.FileSystems
 // the path can be any of the supported Filesystems, e.g. local, GCS, HDFS
 def readmeResource = FileSystems.matchNewResource(&quot;gs://&lt;bucket&gt;/README.md&quot;, false)
@@ -595,7 +595,7 @@ <h4><a href="#how-do-i-access-various-files-outside-of-a-sciocontext-" name="how
   <li>For Scio version &lt; <code>0.4.0</code></li>
 </ul><div class="callout note "><div class="callout-title">Note</div>
 <p>This part is GCS specific.</p></div>
-<p>You can get a <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/sdk/extensions/gcp/options/GcsOptions.html#getGcsUtil--" title="org.apache.beam.sdk.extensions.gcp.options.GcsOptions"><code>GcsUtil</code></a> instance from <code>ScioContext</code>, which can be used to open GCS files in read or write mode.</p>
+<p>You can get a <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/sdk/extensions/gcp/options/GcsOptions.html#getGcsUtil--" title="org.apache.beam.sdk.extensions.gcp.options.GcsOptions"><code>GcsUtil</code></a> instance from <code>ScioContext</code>, which can be used to open GCS files in read or write mode.</p>
 <pre class="prettyprint"><code class="language-scala mdoc:reset:silent">import com.spotify.scio.ContextAndArgs
 import org.apache.beam.sdk.extensions.gcp.options.GcsOptions
 
@@ -786,7 +786,7 @@ <h4><a href="#how-to-inspect-the-content-of-an-scollection-" name="how-to-inspec
   <li>In <a href="./Scio-REPL.html">Scio-REPL</a>, use <code>runAndCollect()</code> to execute the pipeline and materialize the contents of an <code>SCollection</code></li>
 </ul>
 <h4><a href="#how-do-i-improve-side-input-performance-" name="how-do-i-improve-side-input-performance-" class="anchor"><span class="anchor-link"></span></a>How do I improve side input performance?</h4>
-<p>By default, Dataflow workers allocate 100MB (see <a href="https://beam.apache.org/releases/javadoc/2.64.0/?org/apache/beam/runners/dataflow/options/DataflowWorkerHarnessOptions.html#getWorkerCacheMb--" title="org.apache.beam.runners.dataflow.options.DataflowWorkerHarnessOptions"><code>DataflowWorkerHarnessOptions#getWorkerCacheMb</code></a>) of memory for caching side inputs, and falls back to disk or network. Therefore jobs with large side inputs may be slow. To override this default, register <code>DataflowWorkerHarnessOptions</code> before parsing command line arguments and then pass <code>--workerCacheMb=N</code> when submitting the job.</p>
+<p>By default, Dataflow workers allocate 100MB (see <a href="https://beam.apache.org/releases/javadoc/2.66.0/?org/apache/beam/runners/dataflow/options/DataflowWorkerHarnessOptions.html#getWorkerCacheMb--" title="org.apache.beam.runners.dataflow.options.DataflowWorkerHarnessOptions"><code>DataflowWorkerHarnessOptions#getWorkerCacheMb</code></a>) of memory for caching side inputs, and falls back to disk or network. Therefore jobs with large side inputs may be slow. To override this default, register <code>DataflowWorkerHarnessOptions</code> before parsing command line arguments and then pass <code>--workerCacheMb=N</code> when submitting the job.</p>
 <pre class="prettyprint"><code class="language-scala mdoc:reset:silent">import com.spotify.scio._
 import org.apache.beam.sdk.options.PipelineOptionsFactory
 import org.apache.beam.runners.dataflow.options.DataflowWorkerHarnessOptions
@@ -830,7 +830,7 @@ <h4><a href="#how-to-manually-investigate-a-cloud-dataflow-worker" name="how-to-
 </div>
 <div class="print-only">
 <span class="md-source-file md-version">
-0.14.16-9-3cf3f89-20250507T143400Z*
+0.14.17-31-b648b4a-20250714T202047Z*
 </span>
 </div>
 </article>