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| <div class="section" id="pyarrow-dataset-dataset"> |
| <h1>pyarrow.dataset.Dataset<a class="headerlink" href="#pyarrow-dataset-dataset" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyarrow.dataset.Dataset"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyarrow.dataset.</code><code class="sig-name descname">Dataset</code><a class="headerlink" href="#pyarrow.dataset.Dataset" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">pyarrow.lib._Weakrefable</span></code></p> |
| <p>Collection of data fragments and potentially child datasets.</p> |
| <p>Arrow Datasets allow you to query against data that has been split across |
| multiple files. This sharding of data may indicate partitioning, which |
| can accelerate queries that only touch some partitions (files).</p> |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.__init__"> |
| <code class="sig-name descname">__init__</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span><span class="n">args</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.__init__" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Initialize self. See help(type(self)) for accurate signature.</p> |
| </dd></dl> |
| |
| <p class="rubric">Methods</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.__init__" title="pyarrow.dataset.Dataset.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(*args, **kwargs)</p></td> |
| <td><p>Initialize self.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.get_fragments" title="pyarrow.dataset.Dataset.get_fragments"><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_fragments</span></code></a></p></td> |
| <td><p>Returns an iterator over the fragments in this dataset.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.replace_schema" title="pyarrow.dataset.Dataset.replace_schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">replace_schema</span></code></a></p></td> |
| <td><p>Return a copy of this Dataset with a different schema.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.scan" title="pyarrow.dataset.Dataset.scan"><code class="xref py py-obj docutils literal notranslate"><span class="pre">scan</span></code></a></p></td> |
| <td><p>Builds a scan operation against the dataset.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.to_batches" title="pyarrow.dataset.Dataset.to_batches"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_batches</span></code></a></p></td> |
| <td><p>Read the dataset as materialized record batches.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.to_table" title="pyarrow.dataset.Dataset.to_table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_table</span></code></a></p></td> |
| <td><p>Read the dataset to an arrow table.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Attributes</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.partition_expression" title="pyarrow.dataset.Dataset.partition_expression"><code class="xref py py-obj docutils literal notranslate"><span class="pre">partition_expression</span></code></a></p></td> |
| <td><p>An Expression which evaluates to true for all data viewed by this Dataset.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.dataset.Dataset.schema" title="pyarrow.dataset.Dataset.schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">schema</span></code></a></p></td> |
| <td><p>The common schema of the full Dataset</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.get_fragments"> |
| <code class="sig-name descname">get_fragments</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.get_fragments" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns an iterator over the fragments in this dataset.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>filter</strong> (<a class="reference internal" href="pyarrow.dataset.Expression.html#pyarrow.dataset.Expression" title="pyarrow.dataset.Expression"><em>Expression</em></a><em>, </em><em>default None</em>) – Return fragments matching the optional filter, either using the |
| partition_expression or internal information like Parquet’s |
| statistics.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>fragments</strong> (<em>iterator of Fragment</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.dataset.Dataset.partition_expression"> |
| <code class="sig-name descname">partition_expression</code><a class="headerlink" href="#pyarrow.dataset.Dataset.partition_expression" title="Permalink to this definition">¶</a></dt> |
| <dd><p>An Expression which evaluates to true for all data viewed by this |
| Dataset.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.replace_schema"> |
| <code class="sig-name descname">replace_schema</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.replace_schema" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return a copy of this Dataset with a different schema.</p> |
| <p>The copy will view the same Fragments. If the new schema is not |
| compatible with the original dataset’s schema then an error will |
| be raised.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.scan"> |
| <code class="sig-name descname">scan</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.scan" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Builds a scan operation against the dataset.</p> |
| <p>It produces a stream of ScanTasks which is meant to be a unit of work |
| to be dispatched. The tasks are not executed automatically, the user is |
| responsible to execute and dispatch the individual tasks, so custom |
| local task scheduling can be implemented.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>columns</strong> (<em>list of str</em><em>, </em><em>default None</em>) – List of columns to project. Order and duplicates will be preserved. |
| The columns will be passed down to Datasets and corresponding data |
| fragments to avoid loading, copying, and deserializing columns |
| that will not be required further down the compute chain. |
| By default all of the available columns are projected. Raises |
| an exception if any of the referenced column names does not exist |
| in the dataset’s Schema.</p></li> |
| <li><p><strong>filter</strong> (<a class="reference internal" href="pyarrow.dataset.Expression.html#pyarrow.dataset.Expression" title="pyarrow.dataset.Expression"><em>Expression</em></a><em>, </em><em>default None</em>) – Scan will return only the rows matching the filter. |
| If possible the predicate will be pushed down to exploit the |
| partition information or internal metadata found in the data |
| source, e.g. Parquet statistics. Otherwise filters the loaded |
| RecordBatches before yielding them.</p></li> |
| <li><p><strong>batch_size</strong> (<em>int</em><em>, </em><em>default 1M</em>) – The maximum row count for scanned record batches. If scanned |
| record batches are overflowing memory then this method can be |
| called to reduce their size.</p></li> |
| <li><p><strong>use_threads</strong> (<em>bool</em><em>, </em><em>default True</em>) – If enabled, then maximum parallelism will be used determined by |
| the number of available CPU cores.</p></li> |
| <li><p><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>default None</em>) – For memory allocations, if required. If not specified, uses the |
| default pool.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>scan_tasks</strong> (<em>iterator of ScanTask</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.dataset.Dataset.schema"> |
| <code class="sig-name descname">schema</code><a class="headerlink" href="#pyarrow.dataset.Dataset.schema" title="Permalink to this definition">¶</a></dt> |
| <dd><p>The common schema of the full Dataset</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.to_batches"> |
| <code class="sig-name descname">to_batches</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.to_batches" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read the dataset as materialized record batches.</p> |
| <p>Builds a scan operation against the dataset and sequentially executes |
| the ScanTasks as the returned generator gets consumed.</p> |
| <p>See scan method parameters documentation.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><strong>record_batches</strong> (<em>iterator of RecordBatch</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.dataset.Dataset.to_table"> |
| <code class="sig-name descname">to_table</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.dataset.Dataset.to_table" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read the dataset to an arrow table.</p> |
| <p>Note that this method reads all the selected data from the dataset |
| into memory.</p> |
| <p>See scan method parameters documentation.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><strong>table</strong> (<em>Table instance</em>)</p> |
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