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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.ExtensionScalar.html">pyarrow.ExtensionScalar</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.Tensor.html">pyarrow.Tensor</a></li> |
| </ul> |
| </li> |
| <li class="toctree-l2 has-children"><a class="reference internal" href="api/compute.html">Compute Functions</a><input class="toctree-checkbox" id="toctree-checkbox-7" name="toctree-checkbox-7" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-7"><i class="fa-solid fa-chevron-down"></i></label><ul> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.negate_checked.html">pyarrow.compute.negate_checked</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.sqrt.html">pyarrow.compute.sqrt</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.sqrt_checked.html">pyarrow.compute.sqrt_checked</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.subtract_checked.html">pyarrow.compute.subtract_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.bit_wise_and.html">pyarrow.compute.bit_wise_and</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.bit_wise_not.html">pyarrow.compute.bit_wise_not</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.bit_wise_or.html">pyarrow.compute.bit_wise_or</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.bit_wise_xor.html">pyarrow.compute.bit_wise_xor</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.shift_left_checked.html">pyarrow.compute.shift_left_checked</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.shift_right_checked.html">pyarrow.compute.shift_right_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.ceil.html">pyarrow.compute.ceil</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.floor.html">pyarrow.compute.floor</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.round.html">pyarrow.compute.round</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.round_to_multiple.html">pyarrow.compute.round_to_multiple</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.trunc.html">pyarrow.compute.trunc</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.ln.html">pyarrow.compute.ln</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.ln_checked.html">pyarrow.compute.ln_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log10.html">pyarrow.compute.log10</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log10_checked.html">pyarrow.compute.log10_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log1p.html">pyarrow.compute.log1p</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log1p_checked.html">pyarrow.compute.log1p_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log2.html">pyarrow.compute.log2</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.log2_checked.html">pyarrow.compute.log2_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.logb.html">pyarrow.compute.logb</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.logb_checked.html">pyarrow.compute.logb_checked</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.acos_checked.html">pyarrow.compute.acos_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.asin.html">pyarrow.compute.asin</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.asin_checked.html">pyarrow.compute.asin_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.atan.html">pyarrow.compute.atan</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.atan2.html">pyarrow.compute.atan2</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.cos.html">pyarrow.compute.cos</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.cos_checked.html">pyarrow.compute.cos_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.sin.html">pyarrow.compute.sin</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.sin_checked.html">pyarrow.compute.sin_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.tan.html">pyarrow.compute.tan</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.tan_checked.html">pyarrow.compute.tan_checked</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.compute.equal.html">pyarrow.compute.equal</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.ipc.MessageReader.html">pyarrow.ipc.MessageReader</a></li> |
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| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.flight.FlightUnavailableError.html">pyarrow.flight.FlightUnavailableError</a></li> |
| <li class="toctree-l3"><a class="reference internal" href="generated/pyarrow.flight.FlightWriteSizeExceededError.html">pyarrow.flight.FlightWriteSizeExceededError</a></li> |
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| <section id="reading-and-writing-the-apache-orc-format"> |
| <span id="orc"></span><h1>Reading and Writing the Apache ORC Format<a class="headerlink" href="#reading-and-writing-the-apache-orc-format" title="Permalink to this heading">#</a></h1> |
| <p>The <a class="reference external" href="http://orc.apache.org/">Apache ORC</a> project provides a |
| standardized open-source columnar storage format for use in data analysis |
| systems. It was created originally for use in <a class="reference external" href="http://hadoop.apache.org/">Apache Hadoop</a> with systems like <a class="reference external" href="http://drill.apache.org">Apache Drill</a>, <a class="reference external" href="http://hive.apache.org">Apache Hive</a>, <a class="reference external" href="http://impala.apache.org">Apache |
| Impala</a>, and <a class="reference external" href="http://spark.apache.org">Apache Spark</a> adopting it as a shared standard for high |
| performance data IO.</p> |
| <p>Apache Arrow is an ideal in-memory representation layer for data that is being read |
| or written with ORC files.</p> |
| <section id="obtaining-pyarrow-with-orc-support"> |
| <h2>Obtaining pyarrow with ORC Support<a class="headerlink" href="#obtaining-pyarrow-with-orc-support" title="Permalink to this heading">#</a></h2> |
| <p>If you installed <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code> with pip or conda, it should be built with ORC |
| support bundled:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">pyarrow</span> <span class="kn">import</span> <span class="n">orc</span> |
| </pre></div> |
| </div> |
| <p>If you are building <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code> from source, you must use |
| <code class="docutils literal notranslate"><span class="pre">-DARROW_ORC=ON</span></code> when compiling the C++ libraries and enable the ORC |
| extensions when building <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code>. See the <a class="reference internal" href="../developers/python.html#python-development"><span class="std std-ref">Python Development</span></a> page for more details.</p> |
| </section> |
| <section id="reading-and-writing-single-files"> |
| <h2>Reading and Writing Single Files<a class="headerlink" href="#reading-and-writing-single-files" title="Permalink to this heading">#</a></h2> |
| <p>The functions <a class="reference internal" href="generated/pyarrow.orc.read_table.html#pyarrow.orc.read_table" title="pyarrow.orc.read_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">read_table()</span></code></a> and <a class="reference internal" href="generated/pyarrow.orc.write_table.html#pyarrow.orc.write_table" title="pyarrow.orc.write_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">write_table()</span></code></a> |
| read and write the <a class="reference internal" href="data.html#data-table"><span class="std std-ref">pyarrow.Table</span></a> object, respectively.</p> |
| <p>Let’s look at a simple table:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> |
| <span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span> |
| |
| <span class="gp">>>> </span><span class="n">table</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">table</span><span class="p">(</span> |
| <span class="gp">... </span> <span class="p">{</span> |
| <span class="gp">... </span> <span class="s1">'one'</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="mf">2.5</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="s1">'two'</span><span class="p">:</span> <span class="p">[</span><span class="s1">'foo'</span><span class="p">,</span> <span class="s1">'bar'</span><span class="p">,</span> <span class="s1">'baz'</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="s1">'three'</span><span class="p">:</span> <span class="p">[</span><span class="kc">True</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">]</span> |
| <span class="gp">... </span> <span class="p">}</span> |
| <span class="gp">... </span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>We write this to ORC format with <code class="docutils literal notranslate"><span class="pre">write_table</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">pyarrow</span> <span class="kn">import</span> <span class="n">orc</span> |
| <span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="s1">'example.orc'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>This creates a single ORC file. In practice, an ORC dataset may consist |
| of many files in many directories. We can read a single file back with |
| <code class="docutils literal notranslate"><span class="pre">read_table</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">table2</span> <span class="o">=</span> <span class="n">orc</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s1">'example.orc'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>You can pass a subset of columns to read, which can be much faster than reading |
| the whole file (due to the columnar layout):</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s1">'example.orc'</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">'one'</span><span class="p">,</span> <span class="s1">'three'</span><span class="p">])</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">one: double</span> |
| <span class="go">three: bool</span> |
| <span class="go">----</span> |
| <span class="go">one: [[-1,nan,2.5]]</span> |
| <span class="go">three: [[true,false,true]]</span> |
| </pre></div> |
| </div> |
| <p>We need not use a string to specify the origin of the file. It can be any of:</p> |
| <ul class="simple"> |
| <li><p>A file path as a string</p></li> |
| <li><p>A Python file object</p></li> |
| <li><p>A pathlib.Path object</p></li> |
| <li><p>A <a class="reference internal" href="memory.html#io-native-file"><span class="std std-ref">NativeFile</span></a> from PyArrow</p></li> |
| </ul> |
| <p>In general, a Python file object will have the worst read performance, while a |
| string file path or an instance of <a class="reference internal" href="generated/pyarrow.NativeFile.html#pyarrow.NativeFile" title="pyarrow.NativeFile"><code class="xref py py-class docutils literal notranslate"><span class="pre">NativeFile</span></code></a> (especially memory |
| maps) will perform the best.</p> |
| <p>We can also read partitioned datasets with multiple ORC files through the |
| <code class="xref py py-mod docutils literal notranslate"><span class="pre">pyarrow.dataset</span></code> interface.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p><a class="reference internal" href="dataset.html#dataset"><span class="std std-ref">Documentation for datasets</span></a>.</p> |
| </div> |
| <section id="orc-file-writing-options"> |
| <h3>ORC file writing options<a class="headerlink" href="#orc-file-writing-options" title="Permalink to this heading">#</a></h3> |
| <p><a class="reference internal" href="generated/pyarrow.orc.write_table.html#pyarrow.orc.write_table" title="pyarrow.orc.write_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">write_table()</span></code></a> has a number of options to |
| control various settings when writing an ORC file.</p> |
| <ul class="simple"> |
| <li><p><code class="docutils literal notranslate"><span class="pre">file_version</span></code>, the ORC format version to use. <code class="docutils literal notranslate"><span class="pre">'0.11'</span></code> ensures |
| compatibility with older readers, while <code class="docutils literal notranslate"><span class="pre">'0.12'</span></code> is the newer one.</p></li> |
| <li><p><code class="docutils literal notranslate"><span class="pre">stripe_size</span></code>, to control the approximate size of data within a column |
| stripe. This currently defaults to 64MB.</p></li> |
| </ul> |
| <p>See the <a class="reference internal" href="generated/pyarrow.orc.write_table.html#pyarrow.orc.write_table" title="pyarrow.orc.write_table"><code class="xref py py-func docutils literal notranslate"><span class="pre">write_table()</span></code></a> docstring for more details.</p> |
| </section> |
| </section> |
| <section id="finer-grained-reading-and-writing"> |
| <h2>Finer-grained Reading and Writing<a class="headerlink" href="#finer-grained-reading-and-writing" title="Permalink to this heading">#</a></h2> |
| <p><code class="docutils literal notranslate"><span class="pre">read_table</span></code> uses the <a class="reference internal" href="generated/pyarrow.orc.ORCFile.html#pyarrow.orc.ORCFile" title="pyarrow.orc.ORCFile"><code class="xref py py-class docutils literal notranslate"><span class="pre">ORCFile</span></code></a> class, which has other features:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">orc_file</span> <span class="o">=</span> <span class="n">orc</span><span class="o">.</span><span class="n">ORCFile</span><span class="p">(</span><span class="s1">'example.orc'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">orc_file</span><span class="o">.</span><span class="n">metadata</span> |
| |
| <span class="go">-- metadata --</span> |
| <span class="gp">>>> </span><span class="n">orc_file</span><span class="o">.</span><span class="n">schema</span> |
| <span class="go">one: double</span> |
| <span class="go">two: string</span> |
| <span class="go">three: bool</span> |
| <span class="gp">>>> </span><span class="n">orc_file</span><span class="o">.</span><span class="n">nrows</span> |
| <span class="go">3</span> |
| </pre></div> |
| </div> |
| <p>See the <a class="reference internal" href="generated/pyarrow.orc.ORCFile.html#pyarrow.orc.ORCFile" title="pyarrow.orc.ORCFile"><code class="xref py py-class docutils literal notranslate"><span class="pre">ORCFile</span></code></a> docstring for more details.</p> |
| <p>As you can learn more in the <a class="reference external" href="https://orc.apache.org/specification/">Apache ORC format</a>, an ORC file consists of |
| multiple stripes. <code class="docutils literal notranslate"><span class="pre">read_table</span></code> will read all of the stripes and |
| concatenate them into a single table. You can read individual stripes with |
| <code class="docutils literal notranslate"><span class="pre">read_stripe</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">orc_file</span><span class="o">.</span><span class="n">nstripes</span> |
| <span class="go">1</span> |
| <span class="gp">>>> </span><span class="n">orc_file</span><span class="o">.</span><span class="n">read_stripe</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> |
| <span class="go">pyarrow.RecordBatch</span> |
| <span class="go">one: double</span> |
| <span class="go">two: string</span> |
| <span class="go">three: bool</span> |
| </pre></div> |
| </div> |
| <p>We can write an ORC file using <code class="docutils literal notranslate"><span class="pre">ORCWriter</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">with</span> <span class="n">orc</span><span class="o">.</span><span class="n">ORCWriter</span><span class="p">(</span><span class="s1">'example2.orc'</span><span class="p">)</span> <span class="k">as</span> <span class="n">writer</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="n">writer</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">table</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="compression"> |
| <h2>Compression<a class="headerlink" href="#compression" title="Permalink to this heading">#</a></h2> |
| <p>The data pages within a column in a row group can be compressed after the |
| encoding passes (dictionary, RLE encoding). In PyArrow we don’t use compression |
| by default, but Snappy, ZSTD, Gzip/Zlib, and LZ4 are also supported:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="n">where</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'uncompressed'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="n">where</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'gzip'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="n">where</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'zstd'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">orc</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">,</span> <span class="n">where</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'snappy'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Snappy generally results in better performance, while Gzip may yield smaller |
| files.</p> |
| </section> |
| <section id="reading-from-cloud-storage"> |
| <h2>Reading from cloud storage<a class="headerlink" href="#reading-from-cloud-storage" title="Permalink to this heading">#</a></h2> |
| <p>In addition to local files, pyarrow supports other filesystems, such as cloud |
| filesystems, through the <code class="docutils literal notranslate"><span class="pre">filesystem</span></code> keyword:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">pyarrow</span> <span class="kn">import</span> <span class="n">fs</span> |
| |
| <span class="gp">>>> </span><span class="n">s3</span> <span class="o">=</span> <span class="n">fs</span><span class="o">.</span><span class="n">S3FileSystem</span><span class="p">(</span><span class="n">region</span><span class="o">=</span><span class="s2">"us-east-2"</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">table</span> <span class="o">=</span> <span class="n">orc</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s2">"bucket/object/key/prefix"</span><span class="p">,</span> <span class="n">filesystem</span><span class="o">=</span><span class="n">s3</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p><a class="reference internal" href="filesystems.html#filesystem"><span class="std std-ref">Documentation for filesystems</span></a>.</p> |
| </div> |
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