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| <div class="section" id="pyspark-sql-functions-monotonically-increasing-id"> |
| <h1>pyspark.sql.functions.monotonically_increasing_id<a class="headerlink" href="#pyspark-sql-functions-monotonically-increasing-id" title="Permalink to this headline">¶</a></h1> |
| <dl class="py function"> |
| <dt id="pyspark.sql.functions.monotonically_increasing_id"> |
| <code class="sig-prename descclassname">pyspark.sql.functions.</code><code class="sig-name descname">monotonically_increasing_id</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyspark/sql/functions.html#monotonically_increasing_id"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.sql.functions.monotonically_increasing_id" title="Permalink to this definition">¶</a></dt> |
| <dd><p>A column that generates monotonically increasing 64-bit integers.</p> |
| <p>The generated ID is guaranteed to be monotonically increasing and unique, but not consecutive. |
| The current implementation puts the partition ID in the upper 31 bits, and the record number |
| within each partition in the lower 33 bits. The assumption is that the data frame has |
| less than 1 billion partitions, and each partition has less than 8 billion records.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 1.6.0.</span></p> |
| </div> |
| <p class="rubric">Notes</p> |
| <p>The function is non-deterministic because its result depends on partition IDs.</p> |
| <p>As an example, consider a <code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code> with two partitions, each with 3 records. |
| This expression would return the following IDs: |
| 0, 1, 2, 8589934592 (1L << 33), 8589934593, 8589934594.</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df0</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">mapPartitions</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="p">[(</span><span class="mi">1</span><span class="p">,),</span> <span class="p">(</span><span class="mi">2</span><span class="p">,),</span> <span class="p">(</span><span class="mi">3</span><span class="p">,)])</span><span class="o">.</span><span class="n">toDF</span><span class="p">([</span><span class="s1">'col1'</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">df0</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="n">monotonically_increasing_id</span><span class="p">()</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s1">'id'</span><span class="p">))</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span> |
| <span class="go">[Row(id=0), Row(id=1), Row(id=2), Row(id=8589934592), Row(id=8589934593), Row(id=8589934594)]</span> |
| </pre></div> |
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