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| <section id="distinct-counting"> |
| <h1>Distinct Counting<a class="headerlink" href="#distinct-counting" title="Link to this heading"></a></h1> |
| <p>Distinct counting is one of the earliest tasks to which sketches were applied. The concept is simple: |
| Provide an estimate of the number of unique elements in a set of data. One of the earliest solutions came |
| from Flajolet and Martin in 1985 with their seminal work |
| <a class="reference external" href="http://db.cs.berkeley.edu/cs286/papers/flajoletmartin-jcss1985.pdf">Probabilistic counting Algorithms for Data Base Applications</a>.</p> |
| <p>The DataSketches library offers several types of distinct counting sketches, each with different properties.</p> |
| <blockquote> |
| <div><ul class="simple"> |
| <li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">hll_sketch</span></code>: Hyper Log Log, a well-known sketch for distinct counting but no longer state-of-the-art.</p></li> |
| <li><p><code class="xref py py-class docutils literal notranslate"><span class="pre">cpc_sketch</span></code>: Provides a better accuracy-space trade-off than HLL, but with a somewhat larger footprint while in-memory.</p></li> |
| <li><p><a class="reference internal" href="theta.html#datasketches.theta_sketch" title="datasketches.theta_sketch"><code class="xref py py-class docutils literal notranslate"><span class="pre">theta_sketch</span></code></a>: Theta sketch, a type of k-minimum value sketch, which provide good performance with intersection and set difference operations.</p></li> |
| <li><p><a class="reference internal" href="tuple.html#datasketches.tuple_sketch" title="datasketches.tuple_sketch"><code class="xref py py-class docutils literal notranslate"><span class="pre">tuple_sketch</span></code></a>: Tuple sketch, which is similar to a theta sketch but supports additional data stored with each key.</p></li> |
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| <li class="toctree-l1"><a class="reference internal" href="theta.html">Theta Sketch</a></li> |
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