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   <div class="section" id="module-apache_beam.io.gcp.bigtableio">
 <span id="apache-beam-io-gcp-bigtableio-module"></span><h1>apache_beam.io.gcp.bigtableio module<a class="headerlink" href="#module-apache_beam.io.gcp.bigtableio" title="Permalink to this headline">¶</a></h1>
 <p>BigTable connector</p>
 <p>This module implements writing to BigTable tables.
 The default mode is to set row data to write to BigTable tables.
 The syntax supported is described here:
 <a class="reference external" href="https://cloud.google.com/bigtable/docs/quickstart-cbt">https://cloud.google.com/bigtable/docs/quickstart-cbt</a></p>
 <p>BigTable connector can be used as main outputs. A main output
 (common case) is expected to be massive and will be split into
 manageable chunks and processed in parallel. In the example below
 we created a list of rows then passed to the GeneratedDirectRows
 DoFn to set the Cells and then we call the BigTableWriteFn to insert
 those generated rows in the table.</p>
 <blockquote>
 <div><dl class="docutils">
 <dt>main_table = (p</dt>
 <dd><div class="first last line-block">
 <div class="line">beam.Create(self._generate())</div>
 <div class="line">WriteToBigTable(project_id,
 instance_id,
 table_id))</div>
 </div>
 </dd>
 </dl>
 </div></blockquote>
 <dl class="class">
 <dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable">
 <em class="property">class </em><code class="descclassname">apache_beam.io.gcp.bigtableio.</code><code class="descname">WriteToBigTable</code><span class="sig-paren">(</span><em>project_id</em>, <em>instance_id</em>, <em>table_id</em>, <em>use_cross_language=False</em>, <em>expansion_service=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#WriteToBigTable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
 <p>A transform that writes rows to a Bigtable table.</p>
 <p>Takes an input PCollection of <cite>DirectRow</cite> objects containing un-committed
 mutations. For more information about this row object, visit
 <a class="reference external" href="https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowdirectrowrowkey-tablenone">https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowdirectrowrowkey-tablenone</a></p>
 <p>If flag <cite>use_cross_language</cite> is set to true, this transform will use the
 multi-language transforms framework to inject the Java native write transform
 into the pipeline.</p>
 <p>Initialize an WriteToBigTable transform.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
 <col class="field-body" />
 <tbody valign="top">
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>table_id</strong> – The ID of the table to write to.</li>
 <li><strong>instance_id</strong> – The ID of the instance where the table resides.</li>
 <li><strong>project_id</strong> – The GCP project ID.</li>
 <li><strong>use_cross_language</strong> – If set to True, will use the Java native transform via cross-language.</li>
 <li><strong>expansion_service</strong> – The address of the expansion service in the case of using cross-language.
 If no expansion service is provided, will attempt to run the default GCP
 expansion service.</li>
 </ul>
 </td>
 </tr>
 </tbody>
 </table>
 <dl class="attribute">
 <dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable.URN">
 <code class="descname">URN</code><em class="property"> = 'beam:schematransform:org.apache.beam:bigtable_write:v1'</em><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable.URN" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 <dl class="method">
 <dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable.expand">
 <code class="descname">expand</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#WriteToBigTable.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable.expand" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 </dd></dl>

 <dl class="class">
 <dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable">
 <em class="property">class </em><code class="descclassname">apache_beam.io.gcp.bigtableio.</code><code class="descname">ReadFromBigtable</code><span class="sig-paren">(</span><em>project_id</em>, <em>instance_id</em>, <em>table_id</em>, <em>expansion_service=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#ReadFromBigtable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
 <p>Reads rows from Bigtable.</p>
 <p>Returns a PCollection of PartialRowData objects, each representing a
 Bigtable row. For more information about this row object, visit
 <a class="reference external" href="https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowpartialrowdatarowkey">https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowpartialrowdatarowkey</a></p>
 <p>Initialize a ReadFromBigtable transform.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
 <col class="field-body" />
 <tbody valign="top">
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>table_id</strong> – The ID of the table to read from.</li>
 <li><strong>instance_id</strong> – The ID of the instance where the table resides.</li>
 <li><strong>project_id</strong> – The GCP project ID.</li>
 <li><strong>expansion_service</strong> – The address of the expansion service. If no expansion service is
 provided, will attempt to run the default GCP expansion service.</li>
 </ul>
 </td>
 </tr>
 </tbody>
 </table>
 <dl class="attribute">
 <dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable.URN">
 <code class="descname">URN</code><em class="property"> = 'beam:schematransform:org.apache.beam:bigtable_read:v1'</em><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable.URN" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 <dl class="method">
 <dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable.expand">
 <code class="descname">expand</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#ReadFromBigtable.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable.expand" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 </dd></dl>

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	<div class="section" id="module-apache_beam.io.gcp.bigtableio">
	<span id="apache-beam-io-gcp-bigtableio-module"></span><h1>apache_beam.io.gcp.bigtableio module<a class="headerlink" href="#module-apache_beam.io.gcp.bigtableio" title="Permalink to this headline">¶</a></h1>
	<p>BigTable connector</p>
	<p>This module implements writing to BigTable tables.
	The default mode is to set row data to write to BigTable tables.
	The syntax supported is described here:
	<a class="reference external" href="https://cloud.google.com/bigtable/docs/quickstart-cbt">https://cloud.google.com/bigtable/docs/quickstart-cbt</a></p>
	<p>BigTable connector can be used as main outputs. A main output
	(common case) is expected to be massive and will be split into
	manageable chunks and processed in parallel. In the example below
	we created a list of rows then passed to the GeneratedDirectRows
	DoFn to set the Cells and then we call the BigTableWriteFn to insert
	those generated rows in the table.</p>
	<blockquote>
	<div><dl class="docutils">
	<dt>main_table = (p</dt>
	<dd><div class="first last line-block">
	<div class="line">beam.Create(self._generate())</div>
	<div class="line">WriteToBigTable(project_id,
	instance_id,
	table_id))</div>
	</div>
	</dd>
	</dl>
	</div></blockquote>
	<dl class="class">
	<dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable">
	<em class="property">class </em><code class="descclassname">apache_beam.io.gcp.bigtableio.</code><code class="descname">WriteToBigTable</code><span class="sig-paren">(</span><em>project_id</em>, <em>instance_id</em>, <em>table_id</em>, <em>use_cross_language=False</em>, <em>expansion_service=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#WriteToBigTable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable" title="Permalink to this definition">¶</a></dt>
	<dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
	<p>A transform that writes rows to a Bigtable table.</p>
	<p>Takes an input PCollection of <cite>DirectRow</cite> objects containing un-committed
	mutations. For more information about this row object, visit
	<a class="reference external" href="https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowdirectrowrowkey-tablenone">https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowdirectrowrowkey-tablenone</a></p>
	<p>If flag <cite>use_cross_language</cite> is set to true, this transform will use the
	multi-language transforms framework to inject the Java native write transform
	into the pipeline.</p>
	<p>Initialize an WriteToBigTable transform.</p>
	<table class="docutils field-list" frame="void" rules="none">
	<col class="field-name" />
	<col class="field-body" />
	<tbody valign="top">
	<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
	<li><strong>table_id</strong> – The ID of the table to write to.</li>
	<li><strong>instance_id</strong> – The ID of the instance where the table resides.</li>
	<li><strong>project_id</strong> – The GCP project ID.</li>
	<li><strong>use_cross_language</strong> – If set to True, will use the Java native transform via cross-language.</li>
	<li><strong>expansion_service</strong> – The address of the expansion service in the case of using cross-language.
	If no expansion service is provided, will attempt to run the default GCP
	expansion service.</li>
	</ul>
	</td>
	</tr>
	</tbody>
	</table>
	<dl class="attribute">
	<dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable.URN">
	<code class="descname">URN</code><em class="property"> = 'beam:schematransform:org.apache.beam:bigtable_write:v1'</em><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable.URN" title="Permalink to this definition">¶</a></dt>
	<dd></dd></dl>

	<dl class="method">
	<dt id="apache_beam.io.gcp.bigtableio.WriteToBigTable.expand">
	<code class="descname">expand</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#WriteToBigTable.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.WriteToBigTable.expand" title="Permalink to this definition">¶</a></dt>
	<dd></dd></dl>

	</dd></dl>

	<dl class="class">
	<dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable">
	<em class="property">class </em><code class="descclassname">apache_beam.io.gcp.bigtableio.</code><code class="descname">ReadFromBigtable</code><span class="sig-paren">(</span><em>project_id</em>, <em>instance_id</em>, <em>table_id</em>, <em>expansion_service=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#ReadFromBigtable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable" title="Permalink to this definition">¶</a></dt>
	<dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
	<p>Reads rows from Bigtable.</p>
	<p>Returns a PCollection of PartialRowData objects, each representing a
	Bigtable row. For more information about this row object, visit
	<a class="reference external" href="https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowpartialrowdatarowkey">https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowpartialrowdatarowkey</a></p>
	<p>Initialize a ReadFromBigtable transform.</p>
	<table class="docutils field-list" frame="void" rules="none">
	<col class="field-name" />
	<col class="field-body" />
	<tbody valign="top">
	<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
	<li><strong>table_id</strong> – The ID of the table to read from.</li>
	<li><strong>instance_id</strong> – The ID of the instance where the table resides.</li>
	<li><strong>project_id</strong> – The GCP project ID.</li>
	<li><strong>expansion_service</strong> – The address of the expansion service. If no expansion service is
	provided, will attempt to run the default GCP expansion service.</li>
	</ul>
	</td>
	</tr>
	</tbody>
	</table>
	<dl class="attribute">
	<dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable.URN">
	<code class="descname">URN</code><em class="property"> = 'beam:schematransform:org.apache.beam:bigtable_read:v1'</em><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable.URN" title="Permalink to this definition">¶</a></dt>
	<dd></dd></dl>

	<dl class="method">
	<dt id="apache_beam.io.gcp.bigtableio.ReadFromBigtable.expand">
	<code class="descname">expand</code><span class="sig-paren">(</span><em>input</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/gcp/bigtableio.html#ReadFromBigtable.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.gcp.bigtableio.ReadFromBigtable.expand" title="Permalink to this definition">¶</a></dt>
	<dd></dd></dl>

	</dd></dl>

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