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| <section id="concepts"> |
| <span id="user-guide-concepts"></span><h1>Concepts<a class="headerlink" href="#concepts" title="Link to this heading">¶</a></h1> |
| <p>In this section, we will cover a basic example to introduce a few key concepts. We will use the |
| 2021 Yellow Taxi Trip Records (<a class="reference external" href="https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2021-01.parquet">download</a>), |
| from the <a class="reference external" href="https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page">TLC Trip Record Data</a>.</p> |
| <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">1</span><span class="p">]:</span> <span class="kn">from</span><span class="w"> </span><span class="nn">datafusion</span><span class="w"> </span><span class="kn">import</span> <span class="n">SessionContext</span><span class="p">,</span> <span class="n">col</span><span class="p">,</span> <span class="n">lit</span><span class="p">,</span> <span class="n">functions</span> <span class="k">as</span> <span class="n">f</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">2</span><span class="p">]:</span> <span class="n">ctx</span> <span class="o">=</span> <span class="n">SessionContext</span><span class="p">()</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">3</span><span class="p">]:</span> <span class="n">df</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">read_parquet</span><span class="p">(</span><span class="s2">"yellow_tripdata_2021-01.parquet"</span><span class="p">)</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">4</span><span class="p">]:</span> <span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span> |
| <span class="o">...</span><span class="p">:</span> <span class="s2">"trip_distance"</span><span class="p">,</span> |
| <span class="o">...</span><span class="p">:</span> <span class="n">col</span><span class="p">(</span><span class="s2">"total_amount"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"total"</span><span class="p">),</span> |
| <span class="o">...</span><span class="p">:</span> <span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">lit</span><span class="p">(</span><span class="mf">100.0</span><span class="p">)</span> <span class="o">*</span> <span class="n">col</span><span class="p">(</span><span class="s2">"tip_amount"</span><span class="p">)</span> <span class="o">/</span> <span class="n">col</span><span class="p">(</span><span class="s2">"total_amount"</span><span class="p">),</span> <span class="n">lit</span><span class="p">(</span><span class="mi">1</span><span class="p">)))</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"tip_percent"</span><span class="p">),</span> |
| <span class="o">...</span><span class="p">:</span> <span class="p">)</span> |
| <span class="o">...</span><span class="p">:</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">5</span><span class="p">]:</span> <span class="n">df</span><span class="o">.</span><span class="n">show</span><span class="p">()</span> |
| <span class="n">DataFrame</span><span class="p">()</span> |
| <span class="o">+---------------+-------+-------------+</span> |
| <span class="o">|</span> <span class="n">trip_distance</span> <span class="o">|</span> <span class="n">total</span> <span class="o">|</span> <span class="n">tip_percent</span> <span class="o">|</span> |
| <span class="o">+---------------+-------+-------------+</span> |
| <span class="o">|</span> <span class="mf">2.1</span> <span class="o">|</span> <span class="mf">11.8</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.2</span> <span class="o">|</span> <span class="mf">4.3</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">14.7</span> <span class="o">|</span> <span class="mf">51.95</span> <span class="o">|</span> <span class="mf">16.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">10.6</span> <span class="o">|</span> <span class="mf">36.35</span> <span class="o">|</span> <span class="mf">16.6</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">4.94</span> <span class="o">|</span> <span class="mf">24.36</span> <span class="o">|</span> <span class="mf">16.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.6</span> <span class="o">|</span> <span class="mf">14.15</span> <span class="o">|</span> <span class="mf">16.6</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">4.1</span> <span class="o">|</span> <span class="mf">17.3</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">5.7</span> <span class="o">|</span> <span class="mf">21.8</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">9.1</span> <span class="o">|</span> <span class="mf">28.8</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">2.7</span> <span class="o">|</span> <span class="mf">18.95</span> <span class="o">|</span> <span class="mf">16.6</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">6.11</span> <span class="o">|</span> <span class="mf">24.3</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.21</span> <span class="o">|</span> <span class="mf">10.79</span> <span class="o">|</span> <span class="mf">23.1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">7.4</span> <span class="o">|</span> <span class="mf">33.92</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.7</span> <span class="o">|</span> <span class="mf">14.16</span> <span class="o">|</span> <span class="mf">16.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.81</span> <span class="o">|</span> <span class="mf">8.3</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.01</span> <span class="o">|</span> <span class="mf">10.3</span> <span class="o">|</span> <span class="mf">9.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.73</span> <span class="o">|</span> <span class="mf">12.09</span> <span class="o">|</span> <span class="mf">23.1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.17</span> <span class="o">|</span> <span class="mf">12.36</span> <span class="o">|</span> <span class="mf">16.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.78</span> <span class="o">|</span> <span class="mf">9.96</span> <span class="o">|</span> <span class="mf">16.7</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.66</span> <span class="o">|</span> <span class="mf">12.3</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">+---------------+-------+-------------+</span> |
| </pre></div> |
| </div> |
| <section id="session-context"> |
| <h2>Session Context<a class="headerlink" href="#session-context" title="Link to this heading">¶</a></h2> |
| <p>The first statement group creates a <a class="reference internal" href="../autoapi/datafusion/context/index.html#datafusion.context.SessionContext" title="datafusion.context.SessionContext"><code class="xref py py-class docutils literal notranslate"><span class="pre">SessionContext</span></code></a>.</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># create a context</span> |
| <span class="n">ctx</span> <span class="o">=</span> <span class="n">datafusion</span><span class="o">.</span><span class="n">SessionContext</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <p>A Session Context is the main interface for executing queries with DataFusion. It maintains the state |
| of the connection between a user and an instance of the DataFusion engine. Additionally it provides |
| the following functionality:</p> |
| <ul class="simple"> |
| <li><p>Create a DataFrame from a data source.</p></li> |
| <li><p>Register a data source as a table that can be referenced from a SQL query.</p></li> |
| <li><p>Execute a SQL query</p></li> |
| </ul> |
| </section> |
| <section id="dataframe"> |
| <h2>DataFrame<a class="headerlink" href="#dataframe" title="Link to this heading">¶</a></h2> |
| <p>The second statement group creates a <code class="code docutils literal notranslate"><span class="pre">DataFrame</span></code>,</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Create a DataFrame from a file</span> |
| <span class="n">df</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">read_parquet</span><span class="p">(</span><span class="s2">"yellow_tripdata_2021-01.parquet"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>A DataFrame refers to a (logical) set of rows that share the same column names, similar to a <a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html">Pandas DataFrame</a>. |
| DataFrames are typically created by calling a method on <a class="reference internal" href="../autoapi/datafusion/context/index.html#datafusion.context.SessionContext" title="datafusion.context.SessionContext"><code class="xref py py-class docutils literal notranslate"><span class="pre">SessionContext</span></code></a>, such as <code class="code docutils literal notranslate"><span class="pre">read_csv</span></code>, and can then be modified by |
| calling the transformation methods, such as <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.filter" title="datafusion.dataframe.DataFrame.filter"><code class="xref py py-func docutils literal notranslate"><span class="pre">filter()</span></code></a>, <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.select" title="datafusion.dataframe.DataFrame.select"><code class="xref py py-func docutils literal notranslate"><span class="pre">select()</span></code></a>, <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.aggregate" title="datafusion.dataframe.DataFrame.aggregate"><code class="xref py py-func docutils literal notranslate"><span class="pre">aggregate()</span></code></a>, |
| and <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.limit" title="datafusion.dataframe.DataFrame.limit"><code class="xref py py-func docutils literal notranslate"><span class="pre">limit()</span></code></a> to build up a query definition.</p> |
| <p>For more details on working with DataFrames, including visualization options and conversion to other formats, see <a class="reference internal" href="dataframe/index.html"><span class="doc">DataFrames</span></a>.</p> |
| </section> |
| <section id="expressions"> |
| <h2>Expressions<a class="headerlink" href="#expressions" title="Link to this heading">¶</a></h2> |
| <p>The third statement uses <code class="code docutils literal notranslate"><span class="pre">Expressions</span></code> to build up a query definition. You can find |
| explanations for what the functions below do in the user documentation for |
| <a class="reference internal" href="../autoapi/datafusion/index.html#datafusion.col" title="datafusion.col"><code class="xref py py-func docutils literal notranslate"><span class="pre">col()</span></code></a>, <a class="reference internal" href="../autoapi/datafusion/index.html#datafusion.lit" title="datafusion.lit"><code class="xref py py-func docutils literal notranslate"><span class="pre">lit()</span></code></a>, <a class="reference internal" href="../autoapi/datafusion/functions/index.html#datafusion.functions.round" title="datafusion.functions.round"><code class="xref py py-func docutils literal notranslate"><span class="pre">round()</span></code></a>, |
| and <a class="reference internal" href="../autoapi/datafusion/expr/index.html#datafusion.expr.Expr.alias" title="datafusion.expr.Expr.alias"><code class="xref py py-func docutils literal notranslate"><span class="pre">alias()</span></code></a>.</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span> |
| <span class="s2">"trip_distance"</span><span class="p">,</span> |
| <span class="n">col</span><span class="p">(</span><span class="s2">"total_amount"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"total"</span><span class="p">),</span> |
| <span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">lit</span><span class="p">(</span><span class="mf">100.0</span><span class="p">)</span> <span class="o">*</span> <span class="n">col</span><span class="p">(</span><span class="s2">"tip_amount"</span><span class="p">)</span> <span class="o">/</span> <span class="n">col</span><span class="p">(</span><span class="s2">"total_amount"</span><span class="p">),</span> <span class="n">lit</span><span class="p">(</span><span class="mi">1</span><span class="p">)))</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"tip_percent"</span><span class="p">),</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Finally the <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.show" title="datafusion.dataframe.DataFrame.show"><code class="xref py py-func docutils literal notranslate"><span class="pre">show()</span></code></a> method converts the logical plan |
| represented by the DataFrame into a physical plan and execute it, collecting all results and |
| displaying them to the user. It is important to note that DataFusion performs lazy evaluation |
| of the DataFrame. Until you call a method such as <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.show" title="datafusion.dataframe.DataFrame.show"><code class="xref py py-func docutils literal notranslate"><span class="pre">show()</span></code></a> |
| or <a class="reference internal" href="../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.collect" title="datafusion.dataframe.DataFrame.collect"><code class="xref py py-func docutils literal notranslate"><span class="pre">collect()</span></code></a>, DataFusion will not perform the query.</p> |
| </section> |
| </section> |
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