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Xarray with Dask Arrays
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DataFrames: Groupby
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Score and Predict Large Datasets
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Batch Prediction with PyTorch
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Train Models on Large Datasets
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Incrementally Train Large Datasets
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Hyperparameter optimization with Dask
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Scale XGBoost
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Automate Machine Learning with TPOT
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Generalized Linear Models
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Singular Value Decomposition
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Handle Evolving Workflows
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Image Processing
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<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#Create-Random-array">
Create Random array
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#Persist-data-in-memory">
Persist data in memory
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#Further-Reading">
Further Reading
</a>
</li>
</ul>
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<div class="admonition-live-notebook admonition">
<p class="admonition-title">Live Notebook</p>
<p>You can run this notebook in a <a class="reference external" href="https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=lab/tree/array.ipynb">live session</a> <a class="reference external" href="https://mybinder.org/v2/gh/dask/dask-examples/main?urlpath=lab/tree/array.ipynb"><img alt="Binder" src="https://static.mybinder.org/badge_logo.svg" /></a> or view it <a class="reference external" href="https://github.com/dask/dask-examples/blob/main/array.ipynb">on Github</a>.</p>
</div>
<div class="section" id="Dask-Arrays">
<h1>Dask Arrays<a class="headerlink" href="#Dask-Arrays" title="Permalink to this headline">¶</a></h1>
<p><img alt="Dask arrays are blocked numpy arrays" src="_images/dask-array-black-text.svg" /></p>
<p>Dask arrays coordinate many Numpy arrays, arranged into chunks within a grid. They support a large subset of the Numpy API.</p>
<div class="section" id="Start-Dask-Client-for-Dashboard">
<h2>Start Dask Client for Dashboard<a class="headerlink" href="#Start-Dask-Client-for-Dashboard" title="Permalink to this headline">¶</a></h2>
<p>Starting the Dask Client is optional. It will provide a dashboard which is useful to gain insight on the computation.</p>
<p>The link to the dashboard will become visible when you create the client below. We recommend having it open on one side of your screen while using your notebook on the other side. This can take some effort to arrange your windows, but seeing them both at the same is very useful when learning.</p>
<div class="nbinput docutils container">
<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[1]:
</pre></div>
</div>
<div class="input_area highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">dask.distributed</span> <span class="kn">import</span> <span class="n">Client</span><span class="p">,</span> <span class="n">progress</span>
<span class="n">client</span> <span class="o">=</span> <span class="n">Client</span><span class="p">(</span><span class="n">processes</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">threads_per_worker</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span>
<span class="n">n_workers</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">memory_limit</span><span class="o">=</span><span class="s1">'2GB'</span><span class="p">)</span>
<span class="n">client</span>
</pre></div>
</div>
</div>
<div class="nboutput nblast docutils container">
<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[1]:
</pre></div>
</div>
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<div style="margin-left: 48px;">
<h3 style="margin-bottom: 0px;">Client</h3>
<p style="color: #9D9D9D; margin-bottom: 0px;">Client-d7513320-0ddf-11ed-9808-000d3a8f7959</p>
<table style="width: 100%; text-align: left;">
<tr>
<td style="text-align: left;"><strong>Connection method:</strong> Cluster object</td>
<td style="text-align: left;"><strong>Cluster type:</strong> distributed.LocalCluster</td>
</tr>
<tr>
<td style="text-align: left;">
<strong>Dashboard: </strong> <a href="http://10.1.1.64:8787/status" target="_blank">http://10.1.1.64:8787/status</a>
</td>
<td style="text-align: left;"></td>
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<summary style="margin-bottom: 20px;"><h3 style="display: inline;">Cluster Info</h3></summary>
<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output">
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</div>
<div style="margin-left: 48px;">
<h3 style="margin-bottom: 0px; margin-top: 0px;">LocalCluster</h3>
<p style="color: #9D9D9D; margin-bottom: 0px;">eced48ba</p>
<table style="width: 100%; text-align: left;">
<tr>
<td style="text-align: left;">
<strong>Dashboard:</strong> <a href="http://10.1.1.64:8787/status" target="_blank">http://10.1.1.64:8787/status</a>
</td>
<td style="text-align: left;">
<strong>Workers:</strong> 1
</td>
</tr>
<tr>
<td style="text-align: left;">
<strong>Total threads:</strong> 4
</td>
<td style="text-align: left;">
<strong>Total memory:</strong> 1.86 GiB
</td>
</tr>
<tr>
<td style="text-align: left;"><strong>Status:</strong> running</td>
<td style="text-align: left;"><strong>Using processes:</strong> False</td>
</tr>
</table>
<details>
<summary style="margin-bottom: 20px;">
<h3 style="display: inline;">Scheduler Info</h3>
</summary>
<div style="">
<div>
<div style="width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;"> </div>
<div style="margin-left: 48px;">
<h3 style="margin-bottom: 0px;">Scheduler</h3>
<p style="color: #9D9D9D; margin-bottom: 0px;">Scheduler-245cbcab-5c52-43bc-bcad-524a2981a5bf</p>
<table style="width: 100%; text-align: left;">
<tr>
<td style="text-align: left;">
<strong>Comm:</strong> inproc://10.1.1.64/6152/1
</td>
<td style="text-align: left;">
<strong>Workers:</strong> 1
</td>
</tr>
<tr>
<td style="text-align: left;">
<strong>Dashboard:</strong> <a href="http://10.1.1.64:8787/status" target="_blank">http://10.1.1.64:8787/status</a>
</td>
<td style="text-align: left;">
<strong>Total threads:</strong> 4
</td>
</tr>
<tr>
<td style="text-align: left;">
<strong>Started:</strong> Just now
</td>
<td style="text-align: left;">
<strong>Total memory:</strong> 1.86 GiB
</td>
</tr>
</table>
</div>
</div>
<details style="margin-left: 48px;">
<summary style="margin-bottom: 20px;">
<h3 style="display: inline;">Workers</h3>
</summary>
<div style="margin-bottom: 20px;">
<div style="width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;"> </div>
<div style="margin-left: 48px;">
<details>
<summary>
<h4 style="margin-bottom: 0px; display: inline;">Worker: 0</h4>
</summary>
<table style="width: 100%; text-align: left;">
<tr>
<td style="text-align: left;">
<strong>Comm: </strong> inproc://10.1.1.64/6152/4
</td>
<td style="text-align: left;">
<strong>Total threads: </strong> 4
</td>
</tr>
<tr>
<td style="text-align: left;">
<strong>Dashboard: </strong> <a href="http://10.1.1.64:36121/status" target="_blank">http://10.1.1.64:36121/status</a>
</td>
<td style="text-align: left;">
<strong>Memory: </strong> 1.86 GiB
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</tr>
<tr>
<td style="text-align: left;">
<strong>Nanny: </strong> None
</td>
<td style="text-align: left;"></td>
</tr>
<tr>
<td colspan="2" style="text-align: left;">
<strong>Local directory: </strong> /home/runner/work/dask-examples/dask-examples/dask-worker-space/worker-94bm6jfp
</td>
</tr>
</table>
</details>
</div>
</div>
</details>
</div>
</details>
</div>
</div>
</details>
</div>
</div></div>
</div>
</div>
<div class="section" id="Create-Random-array">
<h2>Create Random array<a class="headerlink" href="#Create-Random-array" title="Permalink to this headline">¶</a></h2>
<p>This creates a 10000x10000 array of random numbers, represented as many numpy arrays of size 1000x1000 (or smaller if the array cannot be divided evenly). In this case there are 100 (10x10) numpy arrays of size 1000x1000.</p>
<div class="nbinput docutils container">
<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[2]:
</pre></div>
</div>
<div class="input_area highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">dask.array</span> <span class="k">as</span> <span class="nn">da</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">((</span><span class="mi">10000</span><span class="p">,</span> <span class="mi">10000</span><span class="p">),</span> <span class="n">chunks</span><span class="o">=</span><span class="p">(</span><span class="mi">1000</span><span class="p">,</span> <span class="mi">1000</span><span class="p">))</span>
<span class="n">x</span>
</pre></div>
</div>
</div>
<div class="nboutput nblast docutils container">
<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[2]:
</pre></div>
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<div class="output_area rendered_html docutils container">
<table>
<tr>
<td>
<table>
<thead>
<tr>
<td> </td>
<th> Array </th>
<th> Chunk </th>
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</thead>
<tbody>
<tr>
<th> Bytes </th>
<td> 762.94 MiB </td>
<td> 7.63 MiB </td>
</tr>
<tr>
<th> Shape </th>
<td> (10000, 10000) </td>
<td> (1000, 1000) </td>
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<th> Count </th>
<td> 100 Tasks </td>
<td> 100 Chunks </td>
</tr>
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