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new 23bf5d9 Publishing website 2020/06/02 00:02:56 at commit 89fc35b
23bf5d9 is described below
commit 23bf5d98b21094c1b3f1432269d0ece83b7f292c
Author: jenkins <[email protected]>
AuthorDate: Tue Jun 2 00:02:56 2020 +0000
Publishing website 2020/06/02 00:02:56 at commit 89fc35b
---
.../documentation/dsls/sql/overview/index.html | 3 +--
website/generated-content/documentation/index.xml | 14 +++++++-------
.../documentation/programming-guide/index.html | 12 ++++++------
website/generated-content/sitemap.xml | 2 +-
4 files changed, 15 insertions(+), 16 deletions(-)
diff --git
a/website/generated-content/documentation/dsls/sql/overview/index.html
b/website/generated-content/documentation/dsls/sql/overview/index.html
index 9ad4338..797a7f1 100644
--- a/website/generated-content/documentation/dsls/sql/overview/index.html
+++ b/website/generated-content/documentation/dsls/sql/overview/index.html
@@ -6,8 +6,7 @@ bounded and unbounded <code>PCollections</code> with SQL
statements. Your SQL qu
is translated to a <code>PTransform</code>, an encapsulated segment of a Beam
pipeline.
You can freely mix SQL <code>PTransforms</code> and other
<code>PTransforms</code> in your pipeline.</p><p>Beam SQL includes the
following dialects:</p><ul><li><a href=https://calcite.apache.org>Beam Calcite
SQL</a></li><li><a href=https://github.com/google/zetasql>Beam
ZetaSQL</a></li></ul><p>Beam Calcite SQL is a variant of Apache Calcite, a
dialect widespread in
big data processing. Beam Calcite SQL is the default Beam SQL dialect. Beam
ZetaSQL is more compatible with BigQuery, so it’s especially useful in
pipelines that <a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.html>write
to or read from BigQuery tables</a>.</p><p>To change dialects, pass <a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/extensions/sql/package-summary.html>the
dialect’s full pac [...]
-the type of elements that Beam SQL operates on. A
<code>PCollection<Row></code> plays the role of a table.
-2.21.0</li></ul><h2 id=walkthrough>Walkthrough</h2><p>The <a
href=/documentation/dsls/sql/walkthrough>SQL pipeline walkthrough</a> works
through how to use Beam SQL with example code.</p><h2 id=shell>Shell</h2><p>The
Beam SQL shell allows you to write pipelines as SQL queries without using the
Java SDK.
+the type of elements that Beam SQL operates on. A
<code>PCollection<Row></code> plays the role of a table.</li></ul><h2
id=walkthrough>Walkthrough</h2><p>The <a
href=/documentation/dsls/sql/walkthrough>SQL pipeline walkthrough</a> works
through how to use Beam SQL with example code.</p><h2 id=shell>Shell</h2><p>The
Beam SQL shell allows you to write pipelines as SQL queries without using the
Java SDK.
The <a href=/documentation/dsls/sql/shell>Shell page</a> describes how to work
with the interactive Beam SQL shell.</p><h2 id=apache-calcite-dialect>Apache
Calcite dialect</h2><p>The <a
href=/documentation/dsls/sql/calcite/overview>Beam Calcite SQL overview</a>
summarizes Apache Calcite operators,
functions, syntax, and data types supported by Beam Calcite SQL.</p><h2
id=zetasql-dialect>ZetaSQL dialect</h2><p>For more information on the ZetaSQL
features in Beam SQL, see the <a
href=/documentation/dsls/sql/zetasql/overview>Beam ZetaSQL dialect
reference</a>.</p><p>To switch to Beam ZetaSQL, configure the <a
href=https://beam.apache.org/releases/javadoc/2.15.0/org/apache/beam/sdk/options/PipelineOptions.html>pipeline
options</a> as follows:</p><pre><code>setPlannerName("org.apa [...]
</code></pre><h2 id=beam-sql-extensions>Beam SQL extensions</h2><p>Beam SQL
has additional extensions leveraging Beam’s unified batch/streaming model and
processing complex data types. You can use these extensions with all Beam SQL
dialects.</p></div></div><footer class=footer><div class=footer__contained><div
class=footer__cols><div class=footer__cols__col><div
class=footer__cols__col__logo><img src=/images/beam_logo_circle.svg
class=footer__logo alt="Beam logo"></div><div class=footer_ [...]
diff --git a/website/generated-content/documentation/index.xml
b/website/generated-content/documentation/index.xml
index 52a2b12..873fd6b 100644
--- a/website/generated-content/documentation/index.xml
+++ b/website/generated-content/documentation/index.xml
@@ -3885,7 +3885,7 @@ one to easily project out only the fields of interest.
The resulting <code>PC
field as a top-level field. Both top-level and nested fields can be selected.
For example, in the Purchase schema, one
could select only the userId and streetAddress fields as follows</p>
<div class=language-java>
-<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="n">shippingAddress</span [...]
+<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="s">&#34;shippingAddress [...]
</div>
<p>The resulting <code>PCollection</code> will have the following
schema</p>
<table>
@@ -3909,7 +3909,7 @@ could select only the userId and streetAddress fields as
follows</p>
<br/>
<p>The same is true for wildcard selections. The following</p>
<div class=language-java>
-<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="n">shippingAddress</span [...]
+<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="s">&#34;shippingAddress [...]
</div>
<p>Will result in the following schema</p>
<table>
@@ -3951,7 +3951,7 @@ could select only the userId and streetAddress fields as
follows</p>
top-level field in the resulting row. This means that if multiple fields are
selected from the same nested row, each
selected field will appear as its own array field. For example</p>
<div class=language-java>
-<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span> <span
class="s">&#34;transactions.bank&#34;</span><span
class="o">,</span> <span class="n">transactions [...]
+<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Select</span><span class="o">.</span><span
class="na">fieldNames</span><span class="o">(</span> <span
class="s">&#34;transactions.bank&#34;</span><span
class="o">,</span> <span class="s">&#34;tra [...]
</div>
<p>Will result in the following schema</p>
<table>
@@ -4043,7 +4043,7 @@ has a schema with one field corresponding to each
aggregation performed.</p>
<p>The simplest usage of <code>Group</code> specifies no
aggregations, in which case all inputs matching the provided set of fields
are grouped together into an <code>ITERABLE</code> field. For
example</p>
<div class=language-java>
-<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Group</span><span class="o">.</span><span
class="na">byFieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="n">shippingAddress</spa [...]
+<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Group</span><span class="o">.</span><span
class="na">byFieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="s">&#34;shippingAddres [...]
</div>
<p>The output schema of this is:</p>
<table>
@@ -4069,9 +4069,9 @@ are grouped together into an <code>ITERABLE</code>
field. For example</
<p>The names of the key and values fields in the output schema can be
controlled using this withKeyField and withValueField
builders, as follows:</p>
<div class=language-java>
-<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Group</span><span class="o">.</span><span
class="na">byFieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="n">shippingAddress</spa [...]
-</span><span class="s"> .withKeyField(&#34;</span><span
class="n">userAndStreet</span><span class="s">&#34;)
-</span><span class="s"> .withValueField(&#34;</span><span
class="n">matchingPurchases</span><span
class="err">&#34;</span><span
class="o">));</span></code></pre></div>
+<div class="highlight"><pre class="chroma"><code
class="language-java" data-lang="java"><span
class="n">purchases</span><span class="o">.</span><span
class="na">apply</span><span class="o">(</span><span
class="n">Group</span><span class="o">.</span><span
class="na">byFieldNames</span><span class="o">(</span><span
class="s">&#34;userId&#34;</span><span class="o">,</span>
<span class="s">&#34;shippingAddres [...]
+<span class="o">.</span><span
class="na">withKeyField</span><span class="o">(</span><span
class="s">&#34;userAndStreet&#34;</span><span
class="o">)</span>
+<span class="o">.</span><span
class="na">withValueField</span><span class="o">(</span><span
class="s">&#34;matchingPurchases&#34;</span><span
class="o">));</span></code></pre></div>
</div>
<p>It is quite common to apply one or more aggregations to the grouped
result. Each aggregation can specify one or more fields
to aggregate, an aggregation function, and the name of the resulting field in
the output schema. For example, the
diff --git
a/website/generated-content/documentation/programming-guide/index.html
b/website/generated-content/documentation/programming-guide/index.html
index d2d8cee..39612c3 100644
--- a/website/generated-content/documentation/programming-guide/index.html
+++ b/website/generated-content/documentation/programming-guide/index.html
@@ -1559,19 +1559,19 @@ allowing selections and aggregations in terms of named
schema fields. Following
schema transforms.</p><h5 id=selecting-input><strong>Selecting
input</strong></h5><p>Often a computation is only interested in a subset of the
fields in an input <code>PCollection</code>. The <code>Select</code> transform
allows
one to easily project out only the fields of interest. The resulting
<code>PCollection</code> has a schema containing each selected
field as a top-level field. Both top-level and nested fields can be selected.
For example, in the Purchase schema, one
-could select only the userId and streetAddress fields as follows</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Select</span><span class=o>.</span><span
class=na>fieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=n>shippingAddress</span><span class=o>.</sp [...]
+could select only the userId and streetAddress fields as follows</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Select</span><span class=o>.</span><span
class=na>fieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=s>"shippingAddress.streetAddress"</ [...]
top-level field in the resulting row. This means that if multiple fields are
selected from the same nested row, each
-selected field will appear as its own array field. For example</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Select</span><span class=o>.</span><span
class=na>fieldNames</span><span class=o>(</span> <span
class=s>"transactions.bank"</span><span class=o>,</span> <span
class=n>transactions</span><span class= [...]
+selected field will appear as its own array field. For example</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Select</span><span class=o>.</span><span
class=na>fieldNames</span><span class=o>(</span> <span
class=s>"transactions.bank"</span><span class=o>,</span> <span
class=s>"transactions.purchaseAmoun [...]
, then each selected field will be expanded to its own map at the top level.
This means that the set of map keys will
be copied, once for each selected field.</p><p>Sometimes different nested rows
will have fields with the same name. Selecting multiple of these fields would
result in
a name conflict, as all selected fields are put in the same row schema. When
this situation arises, the
<code>Select.withFieldNameAs</code> builder method can be used to provide an
alternate name for the selected field.</p><p>Another use of the Select
transform is to flatten a nested schema into a single flat schema. For
example</p><div class=language-java><div class=highlight><pre
class=chroma><code class=language-java data-lang=java><span
class=n>purchases</span><span class=o>.</span><span class=na>apply</span><span
class=o>(</span><span class=n>Select</span><span class=o>.</span><span c [...]
those groupings, and storing the result of those aggregations in a new schema
field. The output of the <code>Group</code> transform
has a schema with one field corresponding to each aggregation
performed.</p><p>The simplest usage of <code>Group</code> specifies no
aggregations, in which case all inputs matching the provided set of fields
-are grouped together into an <code>ITERABLE</code> field. For example</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Group</span><span class=o>.</span><span
class=na>byFieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=n>shippingAddress</span><span class=o [...]
-builders, as follows:</p><div class=language-java><div class=highlight><pre
class=chroma><code class=language-java data-lang=java><span
class=n>purchases</span><span class=o>.</span><span class=na>apply</span><span
class=o>(</span><span class=n>Group</span><span class=o>.</span><span
class=na>byFieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=n>shippingAddress</span><span class=o>.</span><span
class=na>streetAddress</span><spa [...]
-</span><span class=s> .withKeyField("</span><span
class=n>userAndStreet</span><span class=s>")
-</span><span class=s> .withValueField("</span><span
class=n>matchingPurchases</span><span class=err>"</span><span
class=o>));</span></code></pre></div></div><p>It is quite common to apply one
or more aggregations to the grouped result. Each aggregation can specify one or
more fields
+are grouped together into an <code>ITERABLE</code> field. For example</p><div
class=language-java><div class=highlight><pre class=chroma><code
class=language-java data-lang=java><span class=n>purchases</span><span
class=o>.</span><span class=na>apply</span><span class=o>(</span><span
class=n>Group</span><span class=o>.</span><span
class=na>byFieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=s>"shippingAddress.streetAddress& [...]
+builders, as follows:</p><div class=language-java><div class=highlight><pre
class=chroma><code class=language-java data-lang=java><span
class=n>purchases</span><span class=o>.</span><span class=na>apply</span><span
class=o>(</span><span class=n>Group</span><span class=o>.</span><span
class=na>byFieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>,</span> <span
class=s>"shippingAddress.streetAddress"</span><span class=o>)</span>
+ <span class=o>.</span><span class=na>withKeyField</span><span
class=o>(</span><span class=s>"userAndStreet"</span><span
class=o>)</span>
+ <span class=o>.</span><span class=na>withValueField</span><span
class=o>(</span><span class=s>"matchingPurchases"</span><span
class=o>));</span></code></pre></div></div><p>It is quite common to apply one
or more aggregations to the grouped result. Each aggregation can specify one or
more fields
to aggregate, an aggregation function, and the name of the resulting field in
the output schema. For example, the
following application computes three aggregations grouped by userId, with all
aggregations represented in a single
output schema:</p><div class=language-java><div class=highlight><pre
class=chroma><code class=language-java data-lang=java><span
class=n>purchases</span><span class=o>.</span><span class=na>apply</span><span
class=o>(</span><span class=n>Group</span><span class=o>.</span><span
class=na>byFieldNames</span><span class=o>(</span><span
class=s>"userId"</span><span class=o>)</span>
diff --git a/website/generated-content/sitemap.xml
b/website/generated-content/sitemap.xml
index b10c142..d544949 100644
--- a/website/generated-content/sitemap.xml
+++ b/website/generated-content/sitemap.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset
xmlns="http://www.sitemaps.org/schemas/sitemap/0.9";
xmlns:xhtml="http://www.w3.org/1999/xhtml";><url><loc>/categories/blog/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/blog/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/categories/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/categories/python/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/blog/
[...]
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset
xmlns="http://www.sitemaps.org/schemas/sitemap/0.9";
xmlns:xhtml="http://www.w3.org/1999/xhtml";><url><loc>/categories/blog/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/blog/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/categories/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/categories/python/</loc><lastmod>2020-05-28T15:14:36-07:00</lastmod></url><url><loc>/blog/
[...]
\ No newline at end of file
