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| <div class="section" id="pyspark-sql-dataframe-withwatermark"> |
| <h1>pyspark.sql.DataFrame.withWatermark<a class="headerlink" href="#pyspark-sql-dataframe-withwatermark" title="Permalink to this headline">¶</a></h1> |
| <dl class="py method"> |
| <dt id="pyspark.sql.DataFrame.withWatermark"> |
| <code class="sig-prename descclassname">DataFrame.</code><code class="sig-name descname">withWatermark</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">eventTime</span></em>, <em class="sig-param"><span class="n">delayThreshold</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/sql/dataframe.html#DataFrame.withWatermark"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.sql.DataFrame.withWatermark" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Defines an event time watermark for this <a class="reference internal" href="pyspark.sql.DataFrame.html#pyspark.sql.DataFrame" title="pyspark.sql.DataFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></a>. A watermark tracks a point |
| in time before which we assume no more late data is going to arrive.</p> |
| <dl class="simple"> |
| <dt>Spark will use this watermark for several purposes:</dt><dd><ul class="simple"> |
| <li><p>To know when a given time window aggregation can be finalized and thus can be emitted |
| when using output modes that do not allow updates.</p></li> |
| <li><p>To minimize the amount of state that we need to keep for on-going aggregations.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <p>The current watermark is computed by looking at the <cite>MAX(eventTime)</cite> seen across |
| all of the partitions in the query minus a user specified <cite>delayThreshold</cite>. Due to the cost |
| of coordinating this value across partitions, the actual watermark used is only guaranteed |
| to be at least <cite>delayThreshold</cite> behind the actual event time. In some cases we may still |
| process records that arrive more than <cite>delayThreshold</cite> late.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.1.0.</span></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl class="simple"> |
| <dt><strong>eventTime</strong><span class="classifier">str</span></dt><dd><p>the name of the column that contains the event time of the row.</p> |
| </dd> |
| <dt><strong>delayThreshold</strong><span class="classifier">str</span></dt><dd><p>the minimum delay to wait to data to arrive late, relative to the |
| latest record that has been processed in the form of an interval |
| (e.g. “1 minute” or “5 hours”).</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Notes</p> |
| <p>This API is evolving.</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">pyspark.sql.functions</span> <span class="kn">import</span> <span class="n">timestamp_seconds</span> |
| <span class="gp">>>> </span><span class="n">sdf</span><span class="o">.</span><span class="n">select</span><span class="p">(</span> |
| <span class="gp">... </span> <span class="s1">'name'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="n">timestamp_seconds</span><span class="p">(</span><span class="n">sdf</span><span class="o">.</span><span class="n">time</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">'time'</span><span class="p">))</span><span class="o">.</span><span class="n">withWatermark</span><span class="p">(</span><span class="s1">'time'</span><span class="p">,</span> <span class="s1">'10 minutes'</span><span class="p">)</span> |
| <span class="go">DataFrame[name: string, time: timestamp]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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