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| <section id="execution-metrics"> |
| <span id="id1"></span><h1>Execution Metrics<a class="headerlink" href="#execution-metrics" title="Link to this heading">#</a></h1> |
| <section id="overview"> |
| <h2>Overview<a class="headerlink" href="#overview" title="Link to this heading">#</a></h2> |
| <p>When DataFusion executes a query it compiles the logical plan into a tree of |
| <em>physical plan operators</em> (e.g. <code class="docutils literal notranslate"><span class="pre">FilterExec</span></code>, <code class="docutils literal notranslate"><span class="pre">ProjectionExec</span></code>, |
| <code class="docutils literal notranslate"><span class="pre">HashAggregateExec</span></code>). Each operator can record runtime statistics while it |
| runs. These statistics are called <strong>execution metrics</strong>.</p> |
| <p>Typical metrics include:</p> |
| <ul class="simple"> |
| <li><p><strong>output_rows</strong> – number of rows produced by the operator</p></li> |
| <li><p><strong>elapsed_compute</strong> – total CPU time (nanoseconds) spent inside the operator</p></li> |
| <li><p><strong>spill_count</strong> – number of times the operator spilled data to disk</p></li> |
| <li><p><strong>spilled_bytes</strong> – total bytes written to disk during spills</p></li> |
| <li><p><strong>spilled_rows</strong> – total rows written to disk during spills</p></li> |
| </ul> |
| <p>Metrics are collected <em>per-partition</em>: DataFusion may execute each operator |
| in parallel across several partitions. The convenience properties on |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetricsSet</span></code></a> (e.g. <code class="docutils literal notranslate"><span class="pre">output_rows</span></code>, <code class="docutils literal notranslate"><span class="pre">elapsed_compute</span></code>) |
| automatically sum the named metric across <strong>all</strong> partitions, giving a single |
| aggregate value for the operator as a whole. You can also access the raw |
| per-partition <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a> objects via |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet.metrics" title="datafusion.MetricsSet.metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">metrics()</span></code></a>.</p> |
| </section> |
| <section id="when-are-metrics-available"> |
| <h2>When Are Metrics Available?<a class="headerlink" href="#when-are-metrics-available" title="Link to this heading">#</a></h2> |
| <p>Some operators (for example <code class="docutils literal notranslate"><span class="pre">DataSourceExec</span></code>) eagerly create a |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetricsSet</span></code></a> when the physical plan is built, so |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan.metrics" title="datafusion.ExecutionPlan.metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">metrics()</span></code></a> may return a set even before any |
| rows have been processed. However, metric <strong>values</strong> such as <code class="docutils literal notranslate"><span class="pre">output_rows</span></code> |
| are only meaningful <strong>after</strong> the DataFrame has been executed via one of the |
| terminal operations:</p> |
| <ul class="simple"> |
| <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">collect()</span></code></p></li> |
| <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">collect_partitioned()</span></code></p></li> |
| <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">execute_stream()</span></code> |
| (metrics are available once the stream has been fully consumed)</p></li> |
| <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">execute_stream_partitioned()</span></code> |
| (metrics are available once all partition streams have been fully consumed)</p></li> |
| </ul> |
| <p>Before execution, metric values will be <code class="docutils literal notranslate"><span class="pre">0</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <p><strong>display() does not populate metrics.</strong> |
| When a DataFrame is displayed in a notebook (e.g. via <code class="docutils literal notranslate"><span class="pre">display(df)</span></code> or |
| automatic <code class="docutils literal notranslate"><span class="pre">repr</span></code> output), DataFusion runs a <em>limited</em> internal execution |
| to fetch preview rows. This internal execution does <strong>not</strong> cache the |
| physical plan used, so <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan.collect_metrics" title="datafusion.ExecutionPlan.collect_metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">collect_metrics()</span></code></a> |
| will not reflect the display execution. To access metrics you must call |
| one of the terminal operations listed above.</p> |
| </div> |
| <p>If you call <code class="xref py py-meth docutils literal notranslate"><span class="pre">collect()</span></code> (or another terminal |
| operation) multiple times on the same DataFrame, each call creates a fresh |
| physical plan. Metrics from <code class="xref py py-meth docutils literal notranslate"><span class="pre">execution_plan()</span></code> |
| always reflect the <strong>most recent</strong> execution.</p> |
| </section> |
| <section id="reading-the-physical-plan-tree"> |
| <h2>Reading the Physical Plan Tree<a class="headerlink" href="#reading-the-physical-plan-tree" title="Link to this heading">#</a></h2> |
| <p><code class="xref py py-meth docutils literal notranslate"><span class="pre">execution_plan()</span></code> returns the root |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan" title="datafusion.ExecutionPlan"><code class="xref py py-class docutils literal notranslate"><span class="pre">ExecutionPlan</span></code></a> node of the physical plan tree. The tree |
| mirrors the operator pipeline: the root is typically a projection or |
| coalescing node; its children are filters, aggregates, scans, etc.</p> |
| <p>The <code class="docutils literal notranslate"><span class="pre">operator_name</span></code> string returned by |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan.collect_metrics" title="datafusion.ExecutionPlan.collect_metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">collect_metrics()</span></code></a> is the <em>display</em> name of |
| the node, for example <code class="docutils literal notranslate"><span class="pre">"FilterExec:</span> <span class="pre">column1@0</span> <span class="pre">></span> <span class="pre">1"</span></code>. This is the same string |
| you would see when calling <code class="docutils literal notranslate"><span class="pre">plan.display()</span></code>.</p> |
| </section> |
| <section id="aggregated-vs-per-partition-metrics"> |
| <h2>Aggregated vs Per-Partition Metrics<a class="headerlink" href="#aggregated-vs-per-partition-metrics" title="Link to this heading">#</a></h2> |
| <p>DataFusion executes each operator across one or more <strong>partitions</strong> in |
| parallel. The <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetricsSet</span></code></a> convenience properties |
| (<code class="docutils literal notranslate"><span class="pre">output_rows</span></code>, <code class="docutils literal notranslate"><span class="pre">elapsed_compute</span></code>, etc.) automatically <strong>sum</strong> the named |
| metric across all partitions, giving a single aggregate value.</p> |
| <p>To inspect individual partitions — for example to detect data skew where one |
| partition processes far more rows than others — iterate over the raw |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a> objects:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">metric</span> <span class="ow">in</span> <span class="n">metrics_set</span><span class="o">.</span><span class="n">metrics</span><span class="p">():</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" partition=</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">partition</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">=</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>The <code class="docutils literal notranslate"><span class="pre">partition</span></code> property is a 0-based index (<code class="docutils literal notranslate"><span class="pre">0</span></code>, <code class="docutils literal notranslate"><span class="pre">1</span></code>, …) identifying |
| which parallel slot processed this metric. It is <code class="docutils literal notranslate"><span class="pre">None</span></code> for metrics that |
| apply globally (not tied to a specific partition).</p> |
| </section> |
| <section id="available-metrics"> |
| <h2>Available Metrics<a class="headerlink" href="#available-metrics" title="Link to this heading">#</a></h2> |
| <p>The following metrics are directly accessible as properties on |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetricsSet</span></code></a>:</p> |
| <div class="pst-scrollable-table-container"><table class="table"> |
| <thead> |
| <tr class="row-odd"><th class="head"><p>Property</p></th> |
| <th class="head"><p>Description</p></th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">output_rows</span></code></p></td> |
| <td><p>Number of rows emitted by the operator (summed across partitions).</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">elapsed_compute</span></code></p></td> |
| <td><p>Wall-clock CPU time <strong>in nanoseconds</strong> spent inside the operator’s compute loop, excluding I/O wait. Useful for identifying which operators are most expensive (summed across partitions).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">spill_count</span></code></p></td> |
| <td><p>Number of spill-to-disk events triggered by memory pressure. This is a unitless count of events, not a measure of data volume (summed across partitions).</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">spilled_bytes</span></code></p></td> |
| <td><p>Total bytes written to disk during spill events (summed across partitions).</p></td> |
| </tr> |
| <tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">spilled_rows</span></code></p></td> |
| <td><p>Total rows written to disk during spill events (summed across partitions).</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <p>Any metric not listed above can be accessed via |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet.sum_by_name" title="datafusion.MetricsSet.sum_by_name"><code class="xref py py-meth docutils literal notranslate"><span class="pre">sum_by_name()</span></code></a>, or by iterating over the raw |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a> objects returned by |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet.metrics" title="datafusion.MetricsSet.metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">metrics()</span></code></a>.</p> |
| </section> |
| <section id="labels"> |
| <h2>Labels<a class="headerlink" href="#labels" title="Link to this heading">#</a></h2> |
| <p>A <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a> may carry <em>labels</em>: key/value pairs that |
| provide additional context. Labels are operator-specific; most metrics have |
| an empty label dict.</p> |
| <p>Some operators tag their metrics with labels to distinguish variants. For |
| example, a <code class="docutils literal notranslate"><span class="pre">HashAggregateExec</span></code> may record separate <code class="docutils literal notranslate"><span class="pre">output_rows</span></code> metrics |
| for intermediate and final output:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">metric</span> <span class="ow">in</span> <span class="n">metrics_set</span><span class="o">.</span><span class="n">metrics</span><span class="p">():</span> |
| <span class="nb">print</span><span class="p">(</span><span class="n">metric</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">metric</span><span class="o">.</span><span class="n">labels</span><span class="p">())</span> |
| <span class="c1"># output_rows {'output_type': 'final'}</span> |
| <span class="c1"># output_rows {'output_type': 'intermediate'}</span> |
| </pre></div> |
| </div> |
| <p>When summing by name (via <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet.output_rows" title="datafusion.MetricsSet.output_rows"><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_rows</span></code></a> or |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet.sum_by_name" title="datafusion.MetricsSet.sum_by_name"><code class="xref py py-meth docutils literal notranslate"><span class="pre">sum_by_name()</span></code></a>), <strong>all</strong> metrics with that |
| name are summed regardless of labels. To filter by label, iterate over the |
| raw <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">Metric</span></code></a> objects directly.</p> |
| </section> |
| <section id="end-to-end-example"> |
| <h2>End-to-End Example<a class="headerlink" href="#end-to-end-example" title="Link to this heading">#</a></h2> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></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="n">ctx</span> <span class="o">=</span> <span class="n">SessionContext</span><span class="p">()</span> |
| <span class="n">ctx</span><span class="o">.</span><span class="n">sql</span><span class="p">(</span><span class="s2">"CREATE TABLE sales AS VALUES (1, 100), (2, 200), (3, 50)"</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">sql</span><span class="p">(</span><span class="s2">"SELECT * FROM sales WHERE column1 > 1"</span><span class="p">)</span> |
| |
| <span class="c1"># Execute the query — this populates the metrics</span> |
| <span class="n">results</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">collect</span><span class="p">()</span> |
| |
| <span class="c1"># Retrieve the physical plan with metrics</span> |
| <span class="n">plan</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">execution_plan</span><span class="p">()</span> |
| |
| <span class="c1"># Walk every operator and print its metrics</span> |
| <span class="k">for</span> <span class="n">operator_name</span><span class="p">,</span> <span class="n">ms</span> <span class="ow">in</span> <span class="n">plan</span><span class="o">.</span><span class="n">collect_metrics</span><span class="p">():</span> |
| <span class="k">if</span> <span class="n">ms</span><span class="o">.</span><span class="n">output_rows</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">operator_name</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" output_rows = </span><span class="si">{</span><span class="n">ms</span><span class="o">.</span><span class="n">output_rows</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span> |
| <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">" elapsed_compute = </span><span class="si">{</span><span class="n">ms</span><span class="o">.</span><span class="n">elapsed_compute</span><span class="si">}</span><span class="s2"> ns"</span><span class="p">)</span> |
| |
| <span class="c1"># Access raw per-partition metrics</span> |
| <span class="k">for</span> <span class="n">operator_name</span><span class="p">,</span> <span class="n">ms</span> <span class="ow">in</span> <span class="n">plan</span><span class="o">.</span><span class="n">collect_metrics</span><span class="p">():</span> |
| <span class="k">for</span> <span class="n">metric</span> <span class="ow">in</span> <span class="n">ms</span><span class="o">.</span><span class="n">metrics</span><span class="p">():</span> |
| <span class="nb">print</span><span class="p">(</span> |
| <span class="sa">f</span><span class="s2">" partition=</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">partition</span><span class="si">}</span><span class="s2"> "</span> |
| <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">=</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2"> "</span> |
| <span class="sa">f</span><span class="s2">"labels=</span><span class="si">{</span><span class="n">metric</span><span class="o">.</span><span class="n">labels</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="api-reference"> |
| <h2>API Reference<a class="headerlink" href="#api-reference" title="Link to this heading">#</a></h2> |
| <ul class="simple"> |
| <li><p><a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan" title="datafusion.ExecutionPlan"><code class="xref py py-class docutils literal notranslate"><span class="pre">datafusion.ExecutionPlan</span></code></a> — physical plan node</p></li> |
| <li><p><a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan.collect_metrics" title="datafusion.ExecutionPlan.collect_metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">datafusion.ExecutionPlan.collect_metrics()</span></code></a> — walk the tree and |
| return <code class="docutils literal notranslate"><span class="pre">(operator_name,</span> <span class="pre">MetricsSet)</span></code> pairs</p></li> |
| <li><p><a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.ExecutionPlan.metrics" title="datafusion.ExecutionPlan.metrics"><code class="xref py py-meth docutils literal notranslate"><span class="pre">datafusion.ExecutionPlan.metrics()</span></code></a> — return the |
| <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetricsSet</span></code></a> for a single node</p></li> |
| <li><p><a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.MetricsSet" title="datafusion.MetricsSet"><code class="xref py py-class docutils literal notranslate"><span class="pre">datafusion.MetricsSet</span></code></a> — aggregated metrics for one operator</p></li> |
| <li><p><a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.Metric" title="datafusion.Metric"><code class="xref py py-class docutils literal notranslate"><span class="pre">datafusion.Metric</span></code></a> — a single per-partition metric value</p></li> |
| </ul> |
| </section> |
| </section> |
| |
| |
| </article> |
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| <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#overview">Overview</a></li> |
| <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#when-are-metrics-available">When Are Metrics Available?</a></li> |
| <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#reading-the-physical-plan-tree">Reading the Physical Plan Tree</a></li> |
| <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#aggregated-vs-per-partition-metrics">Aggregated vs Per-Partition Metrics</a></li> |
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