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| <div class="section" id="pyspark-sql-functions-session-window"> |
| <h1>pyspark.sql.functions.session_window<a class="headerlink" href="#pyspark-sql-functions-session-window" title="Permalink to this headline">¶</a></h1> |
| <dl class="py function"> |
| <dt id="pyspark.sql.functions.session_window"> |
| <code class="sig-prename descclassname">pyspark.sql.functions.</code><code class="sig-name descname">session_window</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">timeColumn</span><span class="p">:</span> <span class="n">ColumnOrName</span></em>, <em class="sig-param"><span class="n">gapDuration</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>pyspark.sql.column.Column<span class="p">, </span>str<span class="p">]</span></span></em><span class="sig-paren">)</span> → pyspark.sql.column.Column<a class="reference internal" href="../../../_modules/pyspark/sql/functions.html#session_window"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.sql.functions.session_window" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Generates session window given a timestamp specifying column. |
| Session window is one of dynamic windows, which means the length of window is varying |
| according to the given inputs. The length of session window is defined as “the timestamp |
| of latest input of the session + gap duration”, so when the new inputs are bound to the |
| current session window, the end time of session window can be expanded according to the new |
| inputs. |
| Windows can support microsecond precision. Windows in the order of months are not supported. |
| For a streaming query, you may use the function <cite>current_timestamp</cite> to generate windows on |
| processing time. |
| gapDuration is provided as strings, e.g. ‘1 second’, ‘1 day 12 hours’, ‘2 minutes’. Valid |
| interval strings are ‘week’, ‘day’, ‘hour’, ‘minute’, ‘second’, ‘millisecond’, ‘microsecond’. |
| It could also be a Column which can be evaluated to gap duration dynamically based on the |
| input row. |
| The output column will be a struct called ‘session_window’ by default with the nested columns |
| ‘start’ and ‘end’, where ‘start’ and ‘end’ will be of <a class="reference internal" href="pyspark.sql.types.TimestampType.html#pyspark.sql.types.TimestampType" title="pyspark.sql.types.TimestampType"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyspark.sql.types.TimestampType</span></code></a>.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 3.2.0.</span></p> |
| </div> |
| <div class="versionchanged"> |
| <p><span class="versionmodified changed">Changed in version 3.4.0: </span>Supports Spark Connect.</p> |
| </div> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>timeColumn</strong><span class="classifier"><a class="reference internal" href="pyspark.sql.Column.html#pyspark.sql.Column" title="pyspark.sql.Column"><code class="xref py py-class docutils literal notranslate"><span class="pre">Column</span></code></a> or str</span></dt><dd><p>The column name or column to use as the timestamp for windowing by time. |
| The time column must be of TimestampType or TimestampNTZType.</p> |
| </dd> |
| <dt><strong>gapDuration</strong><span class="classifier"><a class="reference internal" href="pyspark.sql.Column.html#pyspark.sql.Column" title="pyspark.sql.Column"><code class="xref py py-class docutils literal notranslate"><span class="pre">Column</span></code></a> or str</span></dt><dd><p>A Python string literal or column specifying the timeout of the session. It could be |
| static value, e.g. <cite>10 minutes</cite>, <cite>1 second</cite>, or an expression/UDF that specifies gap |
| duration dynamically based on the input row.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt><a class="reference internal" href="pyspark.sql.Column.html#pyspark.sql.Column" title="pyspark.sql.Column"><code class="xref py py-class docutils literal notranslate"><span class="pre">Column</span></code></a></dt><dd><p>the column for computed results.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">createDataFrame</span><span class="p">([(</span><span class="s2">"2016-03-11 09:00:07"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)])</span><span class="o">.</span><span class="n">toDF</span><span class="p">(</span><span class="s2">"date"</span><span class="p">,</span> <span class="s2">"val"</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">w</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="n">session_window</span><span class="p">(</span><span class="s2">"date"</span><span class="p">,</span> <span class="s2">"5 seconds"</span><span class="p">))</span><span class="o">.</span><span class="n">agg</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="s2">"val"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"sum"</span><span class="p">))</span> |
| <span class="gp">>>> </span><span class="n">w</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="n">w</span><span class="o">.</span><span class="n">session_window</span><span class="o">.</span><span class="n">start</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="s2">"string"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"start"</span><span class="p">),</span> |
| <span class="gp">... </span> <span class="n">w</span><span class="o">.</span><span class="n">session_window</span><span class="o">.</span><span class="n">end</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="s2">"string"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"end"</span><span class="p">),</span> <span class="s2">"sum"</span><span class="p">)</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span> |
| <span class="go">[Row(start='2016-03-11 09:00:07', end='2016-03-11 09:00:12', sum=1)]</span> |
| <span class="gp">>>> </span><span class="n">w</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">groupBy</span><span class="p">(</span><span class="n">session_window</span><span class="p">(</span><span class="s2">"date"</span><span class="p">,</span> <span class="n">lit</span><span class="p">(</span><span class="s2">"5 seconds"</span><span class="p">)))</span><span class="o">.</span><span class="n">agg</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="s2">"val"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"sum"</span><span class="p">))</span> |
| <span class="gp">>>> </span><span class="n">w</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="n">w</span><span class="o">.</span><span class="n">session_window</span><span class="o">.</span><span class="n">start</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="s2">"string"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"start"</span><span class="p">),</span> |
| <span class="gp">... </span> <span class="n">w</span><span class="o">.</span><span class="n">session_window</span><span class="o">.</span><span class="n">end</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="s2">"string"</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"end"</span><span class="p">),</span> <span class="s2">"sum"</span><span class="p">)</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span> |
| <span class="go">[Row(start='2016-03-11 09:00:07', end='2016-03-11 09:00:12', sum=1)]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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