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| <div class="section" id="pyspark-sql-streaming-datastreamwriter-foreachbatch"> |
| <h1>pyspark.sql.streaming.DataStreamWriter.foreachBatch<a class="headerlink" href="#pyspark-sql-streaming-datastreamwriter-foreachbatch" title="Permalink to this headline">¶</a></h1> |
| <dl class="py method"> |
| <dt id="pyspark.sql.streaming.DataStreamWriter.foreachBatch"> |
| <code class="sig-prename descclassname">DataStreamWriter.</code><code class="sig-name descname">foreachBatch</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">func</span><span class="p">:</span> <span class="n">Callable[[DataFrame, int], None]</span></em><span class="sig-paren">)</span> → DataStreamWriter<a class="reference internal" href="../../../_modules/pyspark/sql/streaming/readwriter.html#DataStreamWriter.foreachBatch"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.sql.streaming.DataStreamWriter.foreachBatch" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Sets the output of the streaming query to be processed using the provided |
| function. This is supported only the in the micro-batch execution modes (that is, when the |
| trigger is not continuous). In every micro-batch, the provided function will be called in |
| every micro-batch with (i) the output rows as a DataFrame and (ii) the batch identifier. |
| The batchId can be used deduplicate and transactionally write the output |
| (that is, the provided Dataset) to external systems. The output DataFrame is guaranteed |
| to exactly same for the same batchId (assuming all operations are deterministic in the |
| query).</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 2.4.0.</span></p> |
| </div> |
| <p class="rubric">Notes</p> |
| <p>This API is evolving.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">time</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">readStream</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="s2">"rate"</span><span class="p">)</span><span class="o">.</span><span class="n">load</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">batch_df</span><span class="p">,</span> <span class="n">batch_id</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">batch_df</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span> |
| <span class="gp">...</span> |
| <span class="gp">>>> </span><span class="n">q</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">writeStream</span><span class="o">.</span><span class="n">foreachBatch</span><span class="p">(</span><span class="n">func</span><span class="p">)</span><span class="o">.</span><span class="n">start</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">time</span><span class="o">.</span><span class="n">sleep</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">q</span><span class="o">.</span><span class="n">stop</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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