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<h1>Source code for apache_beam.typehints.arrow_batching_microbenchmark</h1><div class="highlight"><pre>
<span></span><span class="c1">#</span>
<span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span>
<span class="c1"># contributor license agreements. See the NOTICE file distributed with</span>
<span class="c1"># this work for additional information regarding copyright ownership.</span>
<span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span>
<span class="c1"># (the &quot;License&quot;); you may not use this file except in compliance with</span>
<span class="c1"># the License. You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1">#</span>
<span class="sd">&quot;&quot;&quot;A microbenchmark for pyarrow batch creation.</span>
<span class="sd">This microbenchmark exercises the PyarrowBatchConverter.produce_batch method</span>
<span class="sd">for different batch sizes.</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">argparse</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span>
<span class="kn">from</span> <span class="nn">apache_beam.portability.api</span> <span class="kn">import</span> <span class="n">schema_pb2</span>
<span class="kn">from</span> <span class="nn">apache_beam.tools</span> <span class="kn">import</span> <span class="n">utils</span>
<span class="kn">from</span> <span class="nn">apache_beam.typehints.arrow_type_compatibility</span> <span class="kn">import</span> <span class="n">PyarrowBatchConverter</span>
<span class="kn">from</span> <span class="nn">apache_beam.typehints.arrow_type_compatibility</span> <span class="kn">import</span> <span class="n">beam_schema_from_arrow_schema</span>
<span class="kn">from</span> <span class="nn">apache_beam.typehints.schemas</span> <span class="kn">import</span> <span class="n">typing_from_runner_api</span>
<div class="viewcode-block" id="benchmark_produce_batch"><a class="viewcode-back" href="../../../apache_beam.typehints.arrow_batching_microbenchmark.html#apache_beam.typehints.arrow_batching_microbenchmark.benchmark_produce_batch">[docs]</a><span class="k">def</span> <span class="nf">benchmark_produce_batch</span><span class="p">(</span><span class="n">size</span><span class="p">):</span>
<span class="n">batch</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">Table</span><span class="o">.</span><span class="n">from_pydict</span><span class="p">({</span>
<span class="s1">&#39;foo&#39;</span><span class="p">:</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="p">),</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">int64</span><span class="p">()),</span>
<span class="s1">&#39;bar&#39;</span><span class="p">:</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">i</span> <span class="o">/</span> <span class="n">size</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="p">)],</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">float64</span><span class="p">()),</span>
<span class="s1">&#39;baz&#39;</span><span class="p">:</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">size</span><span class="p">)],</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">string</span><span class="p">()),</span>
<span class="p">})</span>
<span class="n">beam_schema</span> <span class="o">=</span> <span class="n">beam_schema_from_arrow_schema</span><span class="p">(</span><span class="n">batch</span><span class="o">.</span><span class="n">schema</span><span class="p">)</span>
<span class="n">element_type</span> <span class="o">=</span> <span class="n">typing_from_runner_api</span><span class="p">(</span>
<span class="n">schema_pb2</span><span class="o">.</span><span class="n">FieldType</span><span class="p">(</span><span class="n">row_type</span><span class="o">=</span><span class="n">schema_pb2</span><span class="o">.</span><span class="n">RowType</span><span class="p">(</span><span class="n">schema</span><span class="o">=</span><span class="n">beam_schema</span><span class="p">)))</span>
<span class="n">batch_converter</span> <span class="o">=</span> <span class="n">PyarrowBatchConverter</span><span class="o">.</span><span class="n">from_typehints</span><span class="p">(</span><span class="n">element_type</span><span class="p">,</span> <span class="n">pa</span><span class="o">.</span><span class="n">Table</span><span class="p">)</span>
<span class="n">elements</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">batch_converter</span><span class="o">.</span><span class="n">explode_batch</span><span class="p">(</span><span class="n">batch</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">_do_benchmark</span><span class="p">():</span>
<span class="n">_</span> <span class="o">=</span> <span class="n">batch_converter</span><span class="o">.</span><span class="n">produce_batch</span><span class="p">(</span><span class="n">elements</span><span class="p">)</span>
<span class="k">return</span> <span class="n">_do_benchmark</span></div>
<div class="viewcode-block" id="run_benchmark"><a class="viewcode-back" href="../../../apache_beam.typehints.arrow_batching_microbenchmark.html#apache_beam.typehints.arrow_batching_microbenchmark.run_benchmark">[docs]</a><span class="k">def</span> <span class="nf">run_benchmark</span><span class="p">(</span>
<span class="n">starting_point</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_runs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">num_elements_step</span><span class="o">=</span><span class="mi">300</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="n">suite</span> <span class="o">=</span> <span class="p">[</span>
<span class="n">utils</span><span class="o">.</span><span class="n">LinearRegressionBenchmarkConfig</span><span class="p">(</span>
<span class="n">benchmark_produce_batch</span><span class="p">,</span> <span class="n">starting_point</span><span class="p">,</span> <span class="n">num_elements_step</span><span class="p">,</span> <span class="n">num_runs</span><span class="p">)</span>
<span class="p">]</span>
<span class="k">return</span> <span class="n">utils</span><span class="o">.</span><span class="n">run_benchmarks</span><span class="p">(</span><span class="n">suite</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="n">verbose</span><span class="p">)</span></div>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>
<span class="n">logging</span><span class="o">.</span><span class="n">basicConfig</span><span class="p">()</span>
<span class="n">parser</span> <span class="o">=</span> <span class="n">argparse</span><span class="o">.</span><span class="n">ArgumentParser</span><span class="p">()</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--num_runs&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--starting_point&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--increment&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="n">parser</span><span class="o">.</span><span class="n">add_argument</span><span class="p">(</span><span class="s1">&#39;--verbose&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="nb">bool</span><span class="p">)</span>
<span class="n">options</span> <span class="o">=</span> <span class="n">parser</span><span class="o">.</span><span class="n">parse_args</span><span class="p">()</span>
<span class="n">run_benchmark</span><span class="p">(</span>
<span class="n">options</span><span class="o">.</span><span class="n">starting_point</span><span class="p">,</span>
<span class="n">options</span><span class="o">.</span><span class="n">num_runs</span><span class="p">,</span>
<span class="n">options</span><span class="o">.</span><span class="n">increment</span><span class="p">,</span>
<span class="n">options</span><span class="o">.</span><span class="n">verbose</span><span class="p">)</span>
</pre></div>
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