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<section id="smallpond-logical-dataset-parquetdataset">
|
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<h1>smallpond.logical.dataset.ParquetDataSet<a class="headerlink" href="#smallpond-logical-dataset-parquetdataset" title="Permalink to this heading">#</a></h1>
|
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<dl class="py class">
|
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<dt class="sig sig-object py" id="smallpond.logical.dataset.ParquetDataSet">
|
||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">smallpond.logical.dataset.</span></span><span class="sig-name descname"><span class="pre">ParquetDataSet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">root_dir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generated_columns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">union_by_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#smallpond.logical.dataset.ParquetDataSet" title="Permalink to this definition">#</a></dt>
|
||
<dd><p>A set of parquet files.</p>
|
||
<dl class="py method">
|
||
<dt class="sig sig-object py" id="smallpond.logical.dataset.ParquetDataSet.__init__">
|
||
<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">root_dir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">recursive</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">generated_columns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">union_by_name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="headerlink" href="#smallpond.logical.dataset.ParquetDataSet.__init__" title="Permalink to this definition">#</a></dt>
|
||
<dd><p>Construct a dataset from a list of paths.</p>
|
||
<section id="parameters">
|
||
<h2>Parameters<a class="headerlink" href="#parameters" title="Permalink to this heading">#</a></h2>
|
||
<dl class="simple">
|
||
<dt>paths</dt><dd><p>A path or a list of paths or path patterns.
|
||
e.g. <cite>[‘data/100.parquet’, ‘/datasetA/*.parquet’]</cite>.</p>
|
||
</dd>
|
||
<dt>root_dir, optional</dt><dd><p>Relative paths in <cite>paths</cite> would be resolved under <cite>root_dir</cite> if specified.</p>
|
||
</dd>
|
||
<dt>recursive, optional</dt><dd><p>Resolve path patterns recursively if true.</p>
|
||
</dd>
|
||
<dt>columns, optional</dt><dd><p>Only load the specified columns if not None.</p>
|
||
</dd>
|
||
<dt>union_by_name, optional</dt><dd><p>Unify the columns of different files by name (see <a class="reference external" href="https://duckdb.org/docs/data/multiple_files/combining_schemas#union-by-name">https://duckdb.org/docs/data/multiple_files/combining_schemas#union-by-name</a>).</p>
|
||
</dd>
|
||
</dl>
|
||
</section>
|
||
</dd></dl>
|
||
|
||
<p class="rubric">Methods</p>
|
||
<table class="autosummary longtable table autosummary">
|
||
<tbody>
|
||
<tr class="row-odd"><td><p><a class="reference internal" href="#smallpond.logical.dataset.ParquetDataSet.__init__" title="smallpond.logical.dataset.ParquetDataSet.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(paths[, root_dir, recursive, ...])</p></td>
|
||
<td><p>Construct a dataset from a list of paths.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">create_from</span></code>(table, output_dir[, filename])</p></td>
|
||
<td><p></p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">load_partitioned_datasets</span></code>(npartition, ...[, ...])</p></td>
|
||
<td><p>Split the dataset into a list of partitioned datasets.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">log</span></code>([num_rows])</p></td>
|
||
<td><p>Log the dataset to the logger.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">merge</span></code>(datasets)</p></td>
|
||
<td><p>Merge multiple datasets into a single dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">partition_by_files</span></code>(npartition[, random_shuffle])</p></td>
|
||
<td><p>Evenly split into <cite>npartition</cite> datasets by files.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">partition_by_rows</span></code>(npartition[, random_shuffle])</p></td>
|
||
<td><p>Evenly split the dataset into <cite>npartition</cite> partitions by rows.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">partition_by_size</span></code>(max_partition_size)</p></td>
|
||
<td><p>Split the dataset into multiple partitions so that each partition has at most <cite>max_partition_size</cite> bytes.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">remove_empty_files</span></code>()</p></td>
|
||
<td><p>Remove empty parquet files from the dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">reset</span></code>([paths, root_dir, recursive])</p></td>
|
||
<td><p>NOTE: all row ranges will be cleared.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">sql_query_fragment</span></code>([filesystem, conn])</p></td>
|
||
<td><p>Return a sql fragment that represents the dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_arrow_table</span></code>([max_workers, filesystem, conn])</p></td>
|
||
<td><p>Load the dataset to an arrow table.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_batch_reader</span></code>([batch_size, filesystem, conn])</p></td>
|
||
<td><p>Return an arrow record batch reader to read the dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_pandas</span></code>()</p></td>
|
||
<td><p>Convert the dataset to a pandas dataframe.</p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
<p class="rubric">Attributes</p>
|
||
<table class="autosummary longtable table autosummary">
|
||
<tbody>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">generated_columns</span></code></p></td>
|
||
<td><p>Generated columns of DuckDB <cite>read_parquet</cite> function.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">absolute_paths</span></code></p></td>
|
||
<td><p>An ordered list of absolute paths of the given file patterns.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">columns</span></code></p></td>
|
||
<td><p>The columns to load from the dataset files.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty</span></code></p></td>
|
||
<td><p>Whether the dataset is empty.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">estimated_data_size</span></code></p></td>
|
||
<td><p>Return the estimated data size in bytes.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_files</span></code></p></td>
|
||
<td><p>The number of files in the dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_rows</span></code></p></td>
|
||
<td><p>The number of rows in the dataset.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">paths</span></code></p></td>
|
||
<td><p>The paths to the dataset files.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">recursive</span></code></p></td>
|
||
<td><p>Whether to resolve path patterns recursively.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">resolved_paths</span></code></p></td>
|
||
<td><p>An ordered list of absolute paths of files.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">resolved_row_ranges</span></code></p></td>
|
||
<td><p>Return row ranges for each parquet file.</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">root_dir</span></code></p></td>
|
||
<td><p>The root directory of paths.</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">udfs</span></code></p></td>
|
||
<td><p></p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">union_by_name</span></code></p></td>
|
||
<td><p>Whether to unify the columns of different files by name.</p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</dd></dl>
|
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|
||
</section>
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