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new 94343fd85c4 Publishing website 2023/10/20 23:40:20 at commit 879935e
94343fd85c4 is described below
commit 94343fd85c47f83c2c2d07b9328b094867428525
Author: runner <runner@main-runner-7ssrv-fsb8c>
AuthorDate: Fri Oct 20 23:40:20 2023 +0000
Publishing website 2023/10/20 23:40:20 at commit 879935e
---
.../io/built-in/google-bigquery/index.html | 39 +++++++++---------
.../sdks/python-unrecoverable-errors/index.html | 47 +++++++++++-----------
.../get-started/downloads/index.html | 2 +-
website/generated-content/get-started/index.html | 11 +++--
website/generated-content/get-started/index.xml | 2 +-
website/generated-content/sitemap.xml | 2 +-
6 files changed, 55 insertions(+), 48 deletions(-)
diff --git
a/website/generated-content/documentation/io/built-in/google-bigquery/index.html
b/website/generated-content/documentation/io/built-in/google-bigquery/index.html
index 2646340b514..241cdb461cc 100644
---
a/website/generated-content/documentation/io/built-in/google-bigquery/index.html
+++
b/website/generated-content/documentation/io/built-in/google-bigquery/index.html
@@ -192,7 +192,7 @@ transform. <code>ReadFromBigQuery</code> returns a
<code>PCollection</code> of d
where each element in the <code>PCollection</code> represents a single row in
the table.
Integer values in the <code>TableRow</code> objects are encoded as strings to
match
BigQuery’s exported JSON format.</p><p
class=language-py><em><strong>Note:</strong></em> <code>BigQuerySource()</code>
is deprecated as of Beam SDK 2.25.0. Before 2.25.0, to read from
-a BigQuery table using the Beam SDK, you will apply a <code>Read</code>
transform on a <code>BigQuerySource</code>. For example,
+a BigQuery table using the Beam SDK, apply a <code>Read</code> transform on a
<code>BigQuerySource</code>. For example,
<code>beam.io.Read(beam.io.BigQuerySource(table_spec))</code>.</p><h3
id=reading-from-a-table>Reading from a table</h3><p class=language-java>To read
an entire BigQuery table, use the <code>from</code> method with a BigQuery table
name. This example uses <code>readTableRows</code>.</p><p class=language-py>To
read an entire BigQuery table, use the <code>table</code> parameter with the
BigQuery
table name.</p><p>The following code reads an entire table that contains
weather station data and
@@ -407,8 +407,8 @@ to write directly to BigQuery storage. For more
information, see
for the destination table(s):</p><ul><li>The table name.</li><li>The
destination table’s create disposition. The create disposition specifies
whether the destination table must exist or can be created by the write
operation.</li><li>The destination table’s write disposition. The write
disposition specifies
-whether the data you write will replace an existing table, append rows to an
-existing table, or write only to an empty table.</li></ul><p>In addition, if
your write operation creates a new BigQuery table, you must also
+whether the data you write replaces an existing table, appends rows to an
+existing table, or writes only to an empty table.</li></ul><p>In addition, if
your write operation creates a new BigQuery table, you must also
supply a table schema for the destination table.</p><h3
id=create-disposition>Create disposition</h3><p>The create disposition controls
whether or not your BigQuery write operation
should create a table if the destination table does not exist.</p><p
class=language-java>Use <code>.withCreateDisposition</code> to specify the
create disposition. Valid enum
values are:</p><span
class=language-java><ul><li><p><code>Write.CreateDisposition.CREATE_IF_NEEDED</code>:
Specifies that the
@@ -445,10 +445,10 @@ information. The schema contains information about each
field in the table.</p><
use a string that contains a JSON-serialized <code>TableSchema</code>
object.</p><p class=language-py>To create a table schema in Python, you can
either use a <code>TableSchema</code> object,
or use a string that defines a list of fields. Single string based schemas do
not support nested fields, repeated fields, or specifying a BigQuery mode for
-fields (the mode will always be set to <code>NULLABLE</code>).</p><h4
id=using-a-tableschema>Using a TableSchema</h4><p>To create and use a table
schema as a <code>TableSchema</code> object, follow these steps.</p><span
class=language-java><ol><li><p>Create a list of <code>TableFieldSchema</code>
objects. Each <code>TableFieldSchema</code> object
+fields (the mode is always set to <code>NULLABLE</code>).</p><h4
id=using-a-tableschema>Using a TableSchema</h4><p>To create and use a table
schema as a <code>TableSchema</code> object, follow these steps.</p><span
class=language-java><ol><li><p>Create a list of <code>TableFieldSchema</code>
objects. Each <code>TableFieldSchema</code> object
represents a field in the table.</p></li><li><p>Create a
<code>TableSchema</code> object and use the <code>setFields</code> method to
specify your
list of fields.</p></li><li><p>Use the <code>withSchema</code> method to
provide your table schema when you apply a
-write transform.</p></li></ol></span><span class=language-py><ol><li><p>Create
a <code>TableSchema</code> object.</p></li><li><p>Create and append a
<code>TableFieldSchema</code> object for each field in your
table.</p></li><li><p>Next, use the <code>schema</code> parameter to provide
your table schema when you apply
+write transform.</p></li></ol></span><span class=language-py><ol><li><p>Create
a <code>TableSchema</code> object.</p></li><li><p>Create and append a
<code>TableFieldSchema</code> object for each field in your
table.</p></li><li><p>Use the <code>schema</code> parameter to provide your
table schema when you apply
a write transform. Set the parameter’s value to the <code>TableSchema</code>
object.</p></li></ol></span><p>The following example code shows how to create a
<code>TableSchema</code> for a table with
two fields (source and quote) of type string.</p><div class='language-java
snippet'><div class="notebook-skip code-snippet"><a class=copy type=button
data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=kn>import</span> <span
class=nn>com.google.api.services.bigquery.model.TableFieldSchema</span><spa
[...]
</span></span><span class=line><span class=cl><span class=kn>import</span>
<span class=nn>com.google.api.services.bigquery.model.TableSchema</span><span
class=o>;</span>
@@ -568,8 +568,8 @@ another transform, such as <code>ParDo</code>, to format
your output data into a
collection.</p><p class=language-py>The following examples use this
<code>PCollection</code> that contains quotes.</p><p class=language-java>The
<code>writeTableRows</code> method writes a <code>PCollection</code> of
BigQuery <code>TableRow</code>
objects to a BigQuery table. Each element in the <code>PCollection</code>
represents a
single row in the table. This example uses <code>writeTableRows</code> to
write elements to a
-<code>PCollection<TableRow></code>. The write operation creates a table if
needed; if the
-table already exists, it will be replaced.</p><div class='language-java
snippet'><div class="notebook-skip code-snippet"><a class=copy type=button
data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=kn>import</span> <span
class=nn>com.google.api.services.bigquery.model.TableRow</span><span
class=o>;</span>
+<code>PCollection<TableRow></code>. The write operation creates a table if
needed. If the
+table already exists, it is replaced.</p><div class='language-java
snippet'><div class="notebook-skip code-snippet"><a class=copy type=button
data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=kn>import</span> <span
class=nn>com.google.api.services.bigquery.model.TableRow</span><span
class=o>;</span>
</span></span><span class=line><span class=cl><span class=kn>import</span>
<span class=nn>com.google.api.services.bigquery.model.TableSchema</span><span
class=o>;</span>
</span></span><span class=line><span class=cl><span class=kn>import</span>
<span class=nn>org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO</span><span
class=o>;</span>
</span></span><span class=line><span class=cl><span class=kn>import</span>
<span
class=nn>org.apache.beam.sdk.io.gcp.bigquery.BigQueryIO.Write.CreateDisposition</span><span
class=o>;</span>
@@ -620,7 +620,7 @@ table already exists, it will be replaced.</p><div
class='language-java snippet'
</span></span><span class=line><span class=cl> <span class=p>},</span>
</span></span><span class=line><span class=cl><span
class=p>])</span></span></span></code></pre></div></div></div><p
class=language-py>The following example code shows how to apply a
<code>WriteToBigQuery</code> transform to
write a <code>PCollection</code> of dictionaries to a BigQuery table. The
write operation
-creates a table if needed; if the table already exists, it will be
replaced.</p><div class='language-py snippet'><div class="notebook-skip
code-snippet"><a class=copy type=button data-bs-toggle=tooltip
data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-py data-lang=py><span class=line><span
class=cl><span class=n>quotes</span> <span class=o>|</span> <span
class=n>beam</span><span cla [...]
+creates a table if needed. If the table already exists, it is
replaced.</p><div class='language-py snippet'><div class="notebook-skip
code-snippet"><a class=copy type=button data-bs-toggle=tooltip
data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-py data-lang=py><span class=line><span
class=cl><span class=n>quotes</span> <span class=o>|</span> <span
class=n>beam</span><span class=o> [...]
</span></span><span class=line><span class=cl> <span
class=n>table_spec</span><span class=p>,</span>
</span></span><span class=line><span class=cl> <span
class=n>schema</span><span class=o>=</span><span
class=n>table_schema</span><span class=p>,</span>
</span></span><span class=line><span class=cl> <span
class=n>write_disposition</span><span class=o>=</span><span
class=n>beam</span><span class=o>.</span><span class=n>io</span><span
class=o>.</span><span class=n>BigQueryDisposition</span><span
class=o>.</span><span class=n>WRITE_TRUNCATE</span><span class=p>,</span>
@@ -628,8 +628,8 @@ creates a table if needed; if the table already exists, it
will be replaced.</p>
table. Use <code>.withFormatFunction(SerializableFunction)</code> to provide a
formatting
function that converts each input element in the <code>PCollection</code> into
a
<code>TableRow</code>. This example uses <code>write</code> to write a
<code>PCollection<String></code>. The
-write operation creates a table if needed; if the table already exists, it will
-be replaced.</p><div class='language-java snippet'><div class="notebook-skip
code-snippet"><a class=copy type=button data-bs-toggle=tooltip
data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=n>quotes</span><span class=o>.</span><span
class=na>apply</span><span class=o>(</span>
+write operation creates a table if needed. If the table already exists, it is
+replaced.</p><div class='language-java snippet'><div class="notebook-skip
code-snippet"><a class=copy type=button data-bs-toggle=tooltip
data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=n>quotes</span><span class=o>.</span><span
class=na>apply</span><span class=o>(</span>
</span></span><span class=line><span class=cl> <span
class=n>BigQueryIO</span><span class=o>.<</span><span
class=n>Quote</span><span class=o>></span><span class=n>write</span><span
class=o>()</span>
</span></span><span class=line><span class=cl> <span
class=o>.</span><span class=na>to</span><span class=o>(</span><span
class=n>tableSpec</span><span class=o>)</span>
</span></span><span class=line><span class=cl> <span
class=o>.</span><span class=na>withSchema</span><span class=o>(</span><span
class=n>tableSchema</span><span class=o>)</span>
@@ -641,7 +641,7 @@ be replaced.</p><div class='language-java snippet'><div
class="notebook-skip cod
You can either keep retrying, or return the failed records in a separate
<code>PCollection</code> using the <code>WriteResult.getFailedInserts()</code>
method.</p><h3 id=storage-write-api>Using the Storage Write API</h3><p>Starting
with version 2.36.0 of the Beam SDK for Java, you can use the
<a href=https://cloud.google.com/bigquery/docs/write-api>BigQuery Storage
Write API</a>
-from the BigQueryIO connector.</p><p>Also after version 2.47.0 of Beam SDK for
Python, SDK supports BigQuery Storage Write API.</p><p
class=language-py>BigQuery Storage Write API for Python SDK currently has some
limitations on supported data types. As this method makes use of cross-language
transforms, we are limited to the types supported at the cross-language
boundary. For example, <code>apache_beam.utils.timestamp.Timestamp</code> is
needed to write a <code>TIMESTAMP</code> BigQuery [...]
+from the BigQueryIO connector.</p><p>Also after version 2.47.0 of Beam SDK for
Python, SDK supports BigQuery Storage Write API.</p><p
class=language-py>BigQuery Storage Write API for Python SDK currently has some
limitations on supported data types. As this method makes use of cross-language
transforms, we are limited to the types supported at the cross-language
boundary. For example, <code>apache_beam.utils.timestamp.Timestamp</code> is
needed to write a <code>TIMESTAMP</code> BigQuery [...]
<a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.Method.html#STORAGE_WRITE_API><code>Method.STORAGE_WRITE_API</code></a>.
Here’s an example transform that writes to BigQuery using the Storage Write
API and exactly-once semantics:</p><p><div class='language-java snippet'><div
class="notebook-skip code-snippet"><a class=copy type=button
data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img
src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0
class=chroma><code class=language-java data-lang=java><span class=line><span
class=cl><span class=n>WriteResult</span> <span class= [...]
</span></span><span class=line><span class=cl><span
class=n>BigQueryIO</span><span class=o>.</span><span
class=na>writeTableRows</span><span class=o>()</span>
@@ -700,19 +700,20 @@ the BigQuery service, so you should use only as many
streams as needed for your
use case. Triggering frequency in single-digit seconds is a good choice for
most
pipelines.</p><span class=language-java><p>Similar to streaming inserts,
<code>STORAGE_WRITE_API</code> supports dynamically determining
the number of parallel streams to write to BigQuery (starting 2.42.0). You can
-explicitly enable this using <a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.html#withAutoSharding--><code>withAutoSharding</code></a>.</p><p><em><strong>Note:</strong></em>
<code>STORAGE_WRITE_API</code> will default to dynamic sharding when
-<code>numStorageWriteApiStreams</code> is set to 0 or is
unspecified.</p><p><em><strong>Note:</strong></em> Auto sharding with
<code>STORAGE_WRITE_API</code> is supported on Dataflow’s legacy runner,
but <strong>not</strong> on Runner V2</p></span><p>When using
<code>STORAGE_WRITE_API</code>, the <code>PCollection</code> returned by
+explicitly enable this using <a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.html#withAutoSharding--><code>withAutoSharding</code></a>.</p><p><code>STORAGE_WRITE_API</code>
defaults to dynamic sharding when
+<code>numStorageWriteApiStreams</code> is set to 0 or is
unspecified.</p><p><em><strong>Note:</strong></em> Auto sharding with
<code>STORAGE_WRITE_API</code> is supported by Dataflow, but
<strong>not</strong> on Runner v2.</p></span><p>When using
<code>STORAGE_WRITE_API</code>, the <code>PCollection</code> returned by
<a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/WriteResult.html#getFailedStorageApiInserts--><code>WriteResult.getFailedStorageApiInserts</code></a>
-will contain the rows that failed to be written to the Storage Write API
sink.</p><h4 id=at-least-once-semantics>At-least-once semantics</h4><p>If your
use case allows for potential duplicate records in the target table, you
+contains the rows that failed to be written to the Storage Write API
sink.</p><h4 id=at-least-once-semantics>At-least-once semantics</h4><p>If your
use case allows for potential duplicate records in the target table, you
can use the
<a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.Method.html#STORAGE_API_AT_LEAST_ONCE><code>STORAGE_API_AT_LEAST_ONCE</code></a>
-method. Because this method doesn’t persist the records to be written to
-BigQuery into its shuffle storage (needed to provide the exactly-once semantics
-of the <code>STORAGE_WRITE_API</code> method), it is cheaper and results in
lower latency
-for most pipelines. If you use <code>STORAGE_API_AT_LEAST_ONCE</code>, you
don’t need to
+method. This method doesn’t persist the records to be written to
+BigQuery into its shuffle storage, which is needed to provide the exactly-once
semantics
+of the <code>STORAGE_WRITE_API</code> method. Therefore, for most pipelines,
using this method is often
+less expensive and results in lower latency.
+If you use <code>STORAGE_API_AT_LEAST_ONCE</code>, you don’t need to
specify the number of streams, and you can’t specify the triggering
frequency.</p><p>Auto sharding is not applicable for
<code>STORAGE_API_AT_LEAST_ONCE</code>.</p><p>When using
<code>STORAGE_API_AT_LEAST_ONCE</code>, the <code>PCollection</code> returned by
<a
href=https://beam.apache.org/releases/javadoc/current/org/apache/beam/sdk/io/gcp/bigquery/WriteResult.html#getFailedStorageApiInserts--><code>WriteResult.getFailedStorageApiInserts</code></a>
-will contain the rows that failed to be written to the Storage Write API
sink.</p><h4 id=quotas>Quotas</h4><p>Before using the Storage Write API, be
aware of the
+contains the rows that failed to be written to the Storage Write API
sink.</p><h4 id=quotas>Quotas</h4><p>Before using the Storage Write API, be
aware of the
<a href=https://cloud.google.com/bigquery/quotas#write-api-limits>BigQuery
Storage Write API quotas</a>.</p><h3 id=using-dynamic-destinations>Using
dynamic destinations</h3><p>You can use the dynamic destinations feature to
write elements in a
<code>PCollection</code> to different BigQuery tables, possibly with different
schemas.</p><p>The dynamic destinations feature groups your user type by a
user-defined
destination key, uses the key to compute a destination table and/or schema, and
diff --git
a/website/generated-content/documentation/sdks/python-unrecoverable-errors/index.html
b/website/generated-content/documentation/sdks/python-unrecoverable-errors/index.html
index cd6b3ff79f8..17759619149 100644
---
a/website/generated-content/documentation/sdks/python-unrecoverable-errors/index.html
+++
b/website/generated-content/documentation/sdks/python-unrecoverable-errors/index.html
@@ -36,29 +36,30 @@
<img class=banner-img-mobile
src=/images/banners/tour-of-beam/tour-of-beam-mobile.png alt="Start Tour of
Beam"></a></div><div class=swiper-slide><a
href=https://beam.apache.org/documentation/ml/overview/><img
class=banner-img-desktop
src=/images/banners/machine-learning/machine-learning-desktop.jpg alt="Machine
Learning">
<img class=banner-img-mobile
src=/images/banners/machine-learning/machine-learning-mobile.jpg alt="Machine
Learning"></a></div></div><div class=swiper-pagination></div></div><script
src=/js/swiper-bundle.min.min.e0e8f81b0b15728d35ff73c07f42ddbb17a108d6f23df4953cb3e60df7ade675.js></script>
<script
src=/js/sliders/top-banners.min.91104c476b3d8123ebee5ed9a8168556ec546abb698549551b38a0cee187ee1c.js></script>
-<script>function showSearch(){addPlaceholder();var
e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function
addPlaceholder(){$("input:text").attr("placeholder","What are you looking
for?")}function endSearch(){var
e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
blockScroll(){$("body").toggleClass(" [...]
-prevent a job from ever running successfully, usually due to some kind
-of misconfiguration. Solving these issues when they occur is key to
-successfully running a Beam Python pipeline.</p><h2
id=common-unrecoverable-errors>Common Unrecoverable Errors</h2><h3
id=job-submissionruntime-python-version-mismatch>Job Submission/Runtime Python
Version Mismatch</h3><p>If the Python version used for job submission does not
match the
-Python version used to build the worker container, the job will not
-execute. Ensure that the Python version being used for job submission
-and the container Python version match.</p><h3
id=pip-dependency-resolution-failures>PIP Dependency Resolution
Failures</h3><p>During worker start-up, dependencies are checked and installed
in
-the worker container before accepting work. If a pipeline requires
-additional dependencies not already present in the runtime environment,
-they are installed here. If there’s an issue during this process
-(e.g. a dependency version cannot be found, or a worker cannot
-connect to PyPI) the worker will fail and may try to restart
-depending on the runner. Ensure that dependency versions provided in
-your requirements.txt file exist and can be installed locally before
-submitting jobs.</p><h3 id=dependency-version-mismatches>Dependency Version
Mismatches</h3><p>When additional dependencies like <code>torch</code>,
<code>transformers</code>, etc. are not
-specified via a requirements_file or preinstalled in a custom container
-then the worker might fail to deserialize (unpickle) the user code.
-This can result in <code>ModuleNotFound</code> errors. If dependencies are
installed
-but their versions don’t match the versions in submission environment,
-pipeline might have <code>AttributeError</code> messages.</p><p>Ensure that
the required dependencies at runtime and in the submission
-environment are the same along with their versions. For better visibility,
-debug logs are added specifying the dependencies at both stages starting in
-Beam 2.52.0. For more information, see: <a
href=https://beam.apache.org/documentation/sdks/python-pipeline-dependencies/#control-dependencies>https://beam.apache.org/documentation/sdks/python-pipeline-dependencies/#control-dependencies</a></p></div></div><footer
class=footer><div class=footer__contained><div class=footer__cols><div
class="footer__cols__col footer__cols__col__logos"><div
class=footer__cols__col__logo><img src=/images/beam_logo_circle.svg
class=footer__logo alt="Beam logo" [...]
+<script>function showSearch(){addPlaceholder();var
e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function
addPlaceholder(){$("input:text").attr("placeholder","What are you looking
for?")}function endSearch(){var
e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
blockScroll(){$("body").toggleClass(" [...]
+prevent jobs from ever running successfully. The problem usually stems
+from a misconfiguration. This page provides context about
+common errors and troubleshooting information.</p><h2
id=python-version-mismatch>Job submission or Python runtime version
mismatch</h2><p>If the Python version that you use to submit your job
doesn’t match the
+Python version used to build the worker container, the job doesn’t run.
+The job fails immediately after job submission.</p><p>To resolve this issue,
ensure that the Python version used to submit the job
+matches the Python container version.</p><h2
id=dependency-resolution-failures>Dependency resolution failures with
pip</h2><p>During worker start-up, the worker might fail and, depending on the
+runner, try to restart.</p><p>Before workers accept work, dependencies are
checked and installed in
+the worker container. If a pipeline requires
+dependencies not already present in the runtime environment,
+they are installed at this time.
+When a problem occurs during this process, you might encounter
+dependency resolution failures.</p><p>Examples of problems include the
following:</p><ul><li>A dependency version can’t be found.</li><li>A
worker can’t connect to PyPI.</li></ul><p>To resolve this issue, before
submitting your job, ensure that the
+dependency versions provided in your <code>requirements.txt</code> file exist
+and that you can install them locally.</p><h2 id=dependency-version>Dependency
version mismatches</h2><p>When your pipeline has dependency version mismatches,
you might
+see <code>ModuleNotFound</code> errors or <code>AttributeError</code>
messages.</p><ul><li><p>The <code>ModuleNotFound</code> errors occur when
additional dependencies,
+such as <code>torch</code> and <code>transformers</code>, are neither
specified in a
+<code>requirements_file</code> nor preinstalled in a custom container.
+In this case, the worker might fail to deserialize (unpickle) the user
code.</p></li><li><p>Your pipeline might have <code>AttributeError</code>
messages when dependencies
+are installed but their versions don’t match the versions in submission
environment.</p></li></ul><p>To resolve these problems, ensure that the
required dependencies and their versions are the same
+at runtime and in the submission environment. To help you identify these
issues,
+in Apache Beam 2.52.0 and later versions, debug logs specify the dependencies
at both stages.
+For more information, see
+<a
href=https://beam.apache.org/documentation/sdks/python-pipeline-dependencies/#control-dependencies>Control
the dependencies the pipeline uses</a>.</p></div></div><footer
class=footer><div class=footer__contained><div class=footer__cols><div
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index 184d2fdb93f..73c1e26b7a2 100644
--- a/website/generated-content/get-started/downloads/index.html
+++ b/website/generated-content/get-started/downloads/index.html
@@ -36,7 +36,7 @@
<img class=banner-img-mobile
src=/images/banners/tour-of-beam/tour-of-beam-mobile.png alt="Start Tour of
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addPlaceholder(){$("input:text").attr("placeholder","What are you looking
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e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
blockScroll(){$("body").toggleClass(" [...]
+<script>function showSearch(){addPlaceholder();var
e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function
addPlaceholder(){$("input:text").attr("placeholder","What are you looking
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e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
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central repository. The Java SDK is available on <a
href=https://search.maven.org/#search%7Cga%7C1%7Cg%3A%22org.apache.beam%22>Maven
Central Repository</a>,
and the Python SDK is available on <a
href=https://pypi.python.org/pypi/apache-beam>PyPI</a>.</p><p>For example, if
you are developing using Maven and want to use the SDK for Java
with the <code>DirectRunner</code>, add the following dependencies to your
<code>pom.xml</code> file:</p><pre><code><dependency>
diff --git a/website/generated-content/get-started/index.html
b/website/generated-content/get-started/index.html
index c9e6dce8669..53ec766bc3c 100644
--- a/website/generated-content/get-started/index.html
+++ b/website/generated-content/get-started/index.html
@@ -36,9 +36,14 @@
<img class=banner-img-mobile
src=/images/banners/tour-of-beam/tour-of-beam-mobile.png alt="Start Tour of
Beam"></a></div><div class=swiper-slide><a
href=https://beam.apache.org/documentation/ml/overview/><img
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<script
src=/js/sliders/top-banners.min.91104c476b3d8123ebee5ed9a8168556ec546abb698549551b38a0cee187ee1c.js></script>
-<script>function showSearch(){addPlaceholder();var
e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function
addPlaceholder(){$("input:text").attr("placeholder","What are you looking
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e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
blockScroll(){$("body").toggleClass(" [...]
-from simple ones to more advanced ones.
-You can try examples, do exercises, and solve challenges along the learning
journey.</p><h2 id=beam-overviewget-startedbeam-overview><a
href=/get-started/beam-overview>Beam Overview</a></h2><p>Learn about the Beam
model, the currently available Beam SDKs and Runners, and Beam’s native
I/O connectors.</p><h2
id=quickstarts-for-java-python-go-and-typescript>Quickstarts for Java, Python,
Go, and TypeScript</h2><p>Learn how to set up a Beam project and run a simple
example Beam pipelin [...]
+<script>function showSearch(){addPlaceholder();var
e,t=document.querySelector(".searchBar");t.classList.remove("disappear"),e=document.querySelector("#iconsBar"),e.classList.add("disappear")}function
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e,t=document.querySelector(".searchBar");t.classList.add("disappear"),e=document.querySelector("#iconsBar"),e.classList.remove("disappear")}function
blockScroll(){$("body").toggleClass(" [...]
+Topics include core Beam concepts, from simple to advanced.
+You can try examples, do exercises, and solve challenges along the learning
journey.</p><h2 id=beam-overview>Beam Overview</h2><p>Read the <a
href=/get-started/beam-overview>Apache Beam Overview</a> to learn about the
Beam model,
+the currently available Beam SDKs and runners, and Beam’s native I/O
connectors.</p><h2 id=quickstarts-for-java-python-go-and-typescript>Quickstarts
for Java, Python, Go, and TypeScript</h2><p>Learn how to set up a Beam project
and run a simple example Beam pipeline on your local machine.</p><ul><li><a
href=/get-started/quickstart-java>Java quickstart</a></li><li><a
href=/get-started/quickstart-py>Python quickstart</a></li><li><a
href=/get-started/quickstart-go>Go quickstart</a></l [...]
+on the <a href=/get-started/downloads>Apache Beam Downloads</a> page.</p><h2
id=support>Support</h2><ul><li>Find resources to help you use Beam, such as
mailing lists and issue tracking,
+on the <a href=/get-started/support>Support</a> page.</li><li>Ask questions
and discuss topics on
+<a href=https://stackoverflow.com/questions/tagged/apache-beam>Stack
Overflow</a>
+or in the Beam <a href=https://apachebeam.slack.com>Slack
Channel</a>.</li></ul><div class=feedback><p class=update>Last updated on
2023/10/20</p><h3>Have you found everything you were looking for?</h3><p
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diff --git a/website/generated-content/get-started/index.xml
b/website/generated-content/get-started/index.xml
index 60b2520098b..8d4c26c4701 100644
--- a/website/generated-content/get-started/index.xml
+++ b/website/generated-content/get-started/index.xml
@@ -2015,7 +2015,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
express or implied.
See the License for the specific language governing permissions and
limitations under the License.
-->
-<h1 id="apache-beam8482-downloads">Apache Beam™ Downloads</h1>
+<h1 id="apache-beamsupsup-downloads">Apache Beam<sup>®</sup>
Downloads</h1>
<blockquote>
<p>Beam SDK 2.51.0 is the latest released version.</p>
</blockquote>
diff --git a/website/generated-content/sitemap.xml
b/website/generated-content/sitemap.xml
index 31632ec6869..4dcabaaf142 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";
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[...]
\ 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>/blog/beam-2.51.0/</loc><lastmod>2023-10-20T16:27:36-07:00</lastmod></url><url><loc>/categories/blog/</loc><lastmod>2023-10-20T16:27:36-07:00</lastmod></url><url><loc>/blog/</loc><lastmod>2023-10-20T16:27:36-07:00</lastmod></url><url><loc>/categories/</loc><lastmod>2023-10-20T16:27:36-07:00</lastmod></url><url><loc>/catego
[...]
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