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import{_ as n,o as e,c as s,e as i}from"./app-Bp5kEZWW.js";const a={},l=i(`<h1 id="异常检测" tabindex="-1"><a class="header-anchor" href="#异常检测"><span>异常检测</span></a></h1><h2 id="iqr" tabindex="-1"><a class="header-anchor" href="#iqr"><span>IQR</span></a></h2><h3 id="函数简介" tabindex="-1"><a class="header-anchor" href="#函数简介"><span>函数简介</span></a></h3><p>本函数用于检验超出上下四分位数1.5倍IQR的数据分布异常。</p><p><strong>函数名：</strong> IQR</p><p><strong>输入序列：</strong> 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE。</p><p><strong>参数：</strong></p><ul><li><code>method</code>：若设置为 &quot;batch&quot;，则将数据全部读入后检测；若设置为 &quot;stream&quot;，则需用户提供上下四分位数进行流式检测。默认为 &quot;batch&quot;。</li><li><code>q1</code>：使用流式计算时的下四分位数。</li><li><code>q3</code>：使用流式计算时的上四分位数。</li></ul><p><strong>输出序列</strong>：输出单个序列，类型为 DOUBLE。</p><p><strong>说明</strong>：$IQR=Q_3-Q_1$</p><h3 id="使用示例" tabindex="-1"><a class="header-anchor" href="#使用示例"><span>使用示例</span></a></h3><h4 id="全数据计算" tabindex="-1"><a class="header-anchor" href="#全数据计算"><span>全数据计算</span></a></h4><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+------------+
| Time|root.test.s1|
+-----------------------------+------------+
|1970-01-01T08:00:00.100+08:00| 0.0|
|1970-01-01T08:00:00.200+08:00| 0.0|
|1970-01-01T08:00:00.300+08:00| 1.0|
|1970-01-01T08:00:00.400+08:00| -1.0|
|1970-01-01T08:00:00.500+08:00| 0.0|
|1970-01-01T08:00:00.600+08:00| 0.0|
|1970-01-01T08:00:00.700+08:00| -2.0|
|1970-01-01T08:00:00.800+08:00| 2.0|
|1970-01-01T08:00:00.900+08:00| 0.0|
|1970-01-01T08:00:01.000+08:00| 0.0|
|1970-01-01T08:00:01.100+08:00| 1.0|
|1970-01-01T08:00:01.200+08:00| -1.0|
|1970-01-01T08:00:01.300+08:00| -1.0|
|1970-01-01T08:00:01.400+08:00| 1.0|
|1970-01-01T08:00:01.500+08:00| 0.0|
|1970-01-01T08:00:01.600+08:00| 0.0|
|1970-01-01T08:00:01.700+08:00| 10.0|
|1970-01-01T08:00:01.800+08:00| 2.0|
|1970-01-01T08:00:01.900+08:00| -2.0|
|1970-01-01T08:00:02.000+08:00| 0.0|
+-----------------------------+------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> iqr<span class="token punctuation">(</span>s1<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-----------------+
| Time|iqr(root.test.s1)|
+-----------------------------+-----------------+
|1970-01-01T08:00:01.700+08:00| 10.0|
+-----------------------------+-----------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h2 id="ksigma" tabindex="-1"><a class="header-anchor" href="#ksigma"><span>KSigma</span></a></h2><h3 id="函数简介-1" tabindex="-1"><a class="header-anchor" href="#函数简介-1"><span>函数简介</span></a></h3><p>本函数利用动态 K-Sigma 算法进行异常检测。在一个窗口内，与平均值的差距超过k倍标准差的数据将被视作异常并输出。</p><p><strong>函数名：</strong> KSIGMA</p><p><strong>输入序列：</strong> 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>参数：</strong></p><ul><li><code>k</code>：在动态 K-Sigma 算法中，分布异常的标准差倍数阈值，默认值为 3。</li><li><code>window</code>：动态 K-Sigma 算法的滑动窗口大小，默认值为 10000。</li></ul><p><strong>输出序列：</strong> 输出单个序列，类型与输入序列相同。</p><p><strong>提示：</strong> k 应大于 0，否则将不做输出。</p><h3 id="使用示例-1" tabindex="-1"><a class="header-anchor" href="#使用示例-1"><span>使用示例</span></a></h3><h4 id="指定k" tabindex="-1"><a class="header-anchor" href="#指定k"><span>指定k</span></a></h4><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------+
| Time|root.test.d1.s1|
+-----------------------------+---------------+
|2020-01-01T00:00:02.000+08:00| 0.0|
|2020-01-01T00:00:03.000+08:00| 50.0|
|2020-01-01T00:00:04.000+08:00| 100.0|
|2020-01-01T00:00:06.000+08:00| 150.0|
|2020-01-01T00:00:08.000+08:00| 200.0|
|2020-01-01T00:00:10.000+08:00| 200.0|
|2020-01-01T00:00:14.000+08:00| 200.0|
|2020-01-01T00:00:15.000+08:00| 200.0|
|2020-01-01T00:00:16.000+08:00| 200.0|
|2020-01-01T00:00:18.000+08:00| 200.0|
|2020-01-01T00:00:20.000+08:00| 150.0|
|2020-01-01T00:00:22.000+08:00| 100.0|
|2020-01-01T00:00:26.000+08:00| 50.0|
|2020-01-01T00:00:28.000+08:00| 0.0|
|2020-01-01T00:00:30.000+08:00| NaN|
+-----------------------------+---------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> ksigma<span class="token punctuation">(</span>s1<span class="token punctuation">,</span><span class="token string">&quot;k&quot;</span><span class="token operator">=</span><span class="token string">&quot;1.0&quot;</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d1 <span class="token keyword">where</span> <span class="token keyword">time</span> <span class="token operator">&lt;=</span> <span class="token number">2020</span><span class="token operator">-</span><span class="token number">01</span><span class="token operator">-</span><span class="token number">01</span> <span class="token number">00</span>:<span class="token number">00</span>:<span class="token number">30</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------------------------+
|Time |ksigma(root.test.d1.s1,&quot;k&quot;=&quot;3.0&quot;)|
+-----------------------------+---------------------------------+
|2020-01-01T00:00:02.000+08:00| 0.0|
|2020-01-01T00:00:03.000+08:00| 50.0|
|2020-01-01T00:00:26.000+08:00| 50.0|
|2020-01-01T00:00:28.000+08:00| 0.0|
+-----------------------------+---------------------------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h2 id="lof" tabindex="-1"><a class="header-anchor" href="#lof"><span>LOF</span></a></h2><h3 id="函数简介-2" tabindex="-1"><a class="header-anchor" href="#函数简介-2"><span>函数简介</span></a></h3><p>本函数使用局部离群点检测方法用于查找序列的密度异常。将根据提供的第k距离数及局部离群点因子(lof)阈值，判断输入数据是否为离群点，即异常，并输出各点的 LOF 值。</p><p><strong>函数名：</strong> LOF</p><p><strong>输入序列：</strong> 多个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>参数：</strong></p><ul><li><code>method</code>:使用的检测方法。默认为 default，以高维数据计算。设置为 series，将一维时间序列转换为高维数据计算。</li><li><code>k</code>:使用第k距离计算局部离群点因子.默认为 3。</li><li><code>window</code>:每次读取数据的窗口长度。默认为 10000.</li><li><code>windowsize</code>:使用series方法时，转化高维数据的维数，即单个窗口的大小。默认为 5。</li></ul><p><strong>输出序列：</strong> 输出单时间序列，类型为DOUBLE。</p><p><strong>提示：</strong> 不完整的数据行会被忽略，不参与计算，也不标记为离群点。</p><h3 id="使用示例-2" tabindex="-1"><a class="header-anchor" href="#使用示例-2"><span>使用示例</span></a></h3><h4 id="默认参数" tabindex="-1"><a class="header-anchor" href="#默认参数"><span>默认参数</span></a></h4><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------+---------------+
| Time|root.test.d1.s1|root.test.d1.s2|
+-----------------------------+---------------+---------------+
|1970-01-01T08:00:00.100+08:00| 0.0| 0.0|
|1970-01-01T08:00:00.200+08:00| 0.0| 1.0|
|1970-01-01T08:00:00.300+08:00| 1.0| 1.0|
|1970-01-01T08:00:00.400+08:00| 1.0| 0.0|
|1970-01-01T08:00:00.500+08:00| 0.0| -1.0|
|1970-01-01T08:00:00.600+08:00| -1.0| -1.0|
|1970-01-01T08:00:00.700+08:00| -1.0| 0.0|
|1970-01-01T08:00:00.800+08:00| 2.0| 2.0|
|1970-01-01T08:00:00.900+08:00| 0.0| null|
+-----------------------------+---------------+---------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> lof<span class="token punctuation">(</span>s1<span class="token punctuation">,</span>s2<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d1 <span class="token keyword">where</span> <span class="token keyword">time</span><span class="token operator">&lt;</span><span class="token number">1000</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------------+
| Time|lof(root.test.d1.s1, root.test.d1.s2)|
+-----------------------------+-------------------------------------+
|1970-01-01T08:00:00.100+08:00| 3.8274824267668244|
|1970-01-01T08:00:00.200+08:00| 3.0117631741126156|
|1970-01-01T08:00:00.300+08:00| 2.838155437762879|
|1970-01-01T08:00:00.400+08:00| 3.0117631741126156|
|1970-01-01T08:00:00.500+08:00| 2.73518261244453|
|1970-01-01T08:00:00.600+08:00| 2.371440975708148|
|1970-01-01T08:00:00.700+08:00| 2.73518261244453|
|1970-01-01T08:00:00.800+08:00| 1.7561416374270742|
+-----------------------------+-------------------------------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h4 id="诊断一维时间序列" tabindex="-1"><a class="header-anchor" href="#诊断一维时间序列"><span>诊断一维时间序列</span></a></h4><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------+
| Time|root.test.d1.s1|
+-----------------------------+---------------+
|1970-01-01T08:00:00.100+08:00| 1.0|
|1970-01-01T08:00:00.200+08:00| 2.0|
|1970-01-01T08:00:00.300+08:00| 3.0|
|1970-01-01T08:00:00.400+08:00| 4.0|
|1970-01-01T08:00:00.500+08:00| 5.0|
|1970-01-01T08:00:00.600+08:00| 6.0|
|1970-01-01T08:00:00.700+08:00| 7.0|
|1970-01-01T08:00:00.800+08:00| 8.0|
|1970-01-01T08:00:00.900+08:00| 9.0|
|1970-01-01T08:00:01.000+08:00| 10.0|
|1970-01-01T08:00:01.100+08:00| 11.0|
|1970-01-01T08:00:01.200+08:00| 12.0|
|1970-01-01T08:00:01.300+08:00| 13.0|
|1970-01-01T08:00:01.400+08:00| 14.0|
|1970-01-01T08:00:01.500+08:00| 15.0|
|1970-01-01T08:00:01.600+08:00| 16.0|
|1970-01-01T08:00:01.700+08:00| 17.0|
|1970-01-01T08:00:01.800+08:00| 18.0|
|1970-01-01T08:00:01.900+08:00| 19.0|
|1970-01-01T08:00:02.000+08:00| 20.0|
+-----------------------------+---------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> lof<span class="token punctuation">(</span>s1<span class="token punctuation">,</span> <span class="token string">&quot;method&quot;</span><span class="token operator">=</span><span class="token string">&quot;series&quot;</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d1 <span class="token keyword">where</span> <span class="token keyword">time</span><span class="token operator">&lt;</span><span class="token number">1000</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+--------------------+
| Time|lof(root.test.d1.s1)|
+-----------------------------+--------------------+
|1970-01-01T08:00:00.100+08:00| 3.77777777777778|
|1970-01-01T08:00:00.200+08:00| 4.32727272727273|
|1970-01-01T08:00:00.300+08:00| 4.85714285714286|
|1970-01-01T08:00:00.400+08:00| 5.40909090909091|
|1970-01-01T08:00:00.500+08:00| 5.94999999999999|
|1970-01-01T08:00:00.600+08:00| 6.43243243243243|
|1970-01-01T08:00:00.700+08:00| 6.79999999999999|
|1970-01-01T08:00:00.800+08:00| 7.0|
|1970-01-01T08:00:00.900+08:00| 7.0|
|1970-01-01T08:00:01.000+08:00| 6.79999999999999|
|1970-01-01T08:00:01.100+08:00| 6.43243243243243|
|1970-01-01T08:00:01.200+08:00| 5.94999999999999|
|1970-01-01T08:00:01.300+08:00| 5.40909090909091|
|1970-01-01T08:00:01.400+08:00| 4.85714285714286|
|1970-01-01T08:00:01.500+08:00| 4.32727272727273|
|1970-01-01T08:00:01.600+08:00| 3.77777777777778|
+-----------------------------+--------------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h2 id="missdetect" tabindex="-1"><a class="header-anchor" href="#missdetect"><span>MissDetect</span></a></h2><h3 id="函数简介-3" tabindex="-1"><a class="header-anchor" href="#函数简介-3"><span>函数简介</span></a></h3><p>本函数用于检测数据中的缺失异常。在一些数据中，缺失数据会被线性插值填补，在数据中出现完美的线性片段，且这些片段往往长度较大。本函数通过在数据中发现这些完美线性片段来检测缺失异常。</p><p><strong>函数名：</strong> MISSDETECT</p><p><strong>输入序列：</strong> 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE。</p><p><strong>参数：</strong></p><ul><li><code>minlen</code>：被标记为异常的完美线性片段的最小长度，是一个大于等于 10 的整数，默认值为 10。</li></ul><p><strong>输出序列：</strong> 输出单个序列，类型为 BOOLEAN，即该数据点是否为缺失异常。</p><p><strong>提示：</strong> 数据中的<code>NaN</code>将会被忽略。</p><h3 id="使用示例-3" tabindex="-1"><a class="header-anchor" href="#使用示例-3"><span>使用示例</span></a></h3><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------+
| Time|root.test.d2.s2|
+-----------------------------+---------------+
|2021-07-01T12:00:00.000+08:00| 0.0|
|2021-07-01T12:00:01.000+08:00| 1.0|
|2021-07-01T12:00:02.000+08:00| 0.0|
|2021-07-01T12:00:03.000+08:00| 1.0|
|2021-07-01T12:00:04.000+08:00| 0.0|
|2021-07-01T12:00:05.000+08:00| 0.0|
|2021-07-01T12:00:06.000+08:00| 0.0|
|2021-07-01T12:00:07.000+08:00| 0.0|
|2021-07-01T12:00:08.000+08:00| 0.0|
|2021-07-01T12:00:09.000+08:00| 0.0|
|2021-07-01T12:00:10.000+08:00| 0.0|
|2021-07-01T12:00:11.000+08:00| 0.0|
|2021-07-01T12:00:12.000+08:00| 0.0|
|2021-07-01T12:00:13.000+08:00| 0.0|
|2021-07-01T12:00:14.000+08:00| 0.0|
|2021-07-01T12:00:15.000+08:00| 0.0|
|2021-07-01T12:00:16.000+08:00| 1.0|
|2021-07-01T12:00:17.000+08:00| 0.0|
|2021-07-01T12:00:18.000+08:00| 1.0|
|2021-07-01T12:00:19.000+08:00| 0.0|
|2021-07-01T12:00:20.000+08:00| 1.0|
+-----------------------------+---------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的SQL语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> missdetect<span class="token punctuation">(</span>s2<span class="token punctuation">,</span><span class="token string">&#39;minlen&#39;</span><span class="token operator">=</span><span class="token string">&#39;10&#39;</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d2
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+------------------------------------------+
| Time|missdetect(root.test.d2.s2, &quot;minlen&quot;=&quot;10&quot;)|
+-----------------------------+------------------------------------------+
|2021-07-01T12:00:00.000+08:00| false|
|2021-07-01T12:00:01.000+08:00| false|
|2021-07-01T12:00:02.000+08:00| false|
|2021-07-01T12:00:03.000+08:00| false|
|2021-07-01T12:00:04.000+08:00| true|
|2021-07-01T12:00:05.000+08:00| true|
|2021-07-01T12:00:06.000+08:00| true|
|2021-07-01T12:00:07.000+08:00| true|
|2021-07-01T12:00:08.000+08:00| true|
|2021-07-01T12:00:09.000+08:00| true|
|2021-07-01T12:00:10.000+08:00| true|
|2021-07-01T12:00:11.000+08:00| true|
|2021-07-01T12:00:12.000+08:00| true|
|2021-07-01T12:00:13.000+08:00| true|
|2021-07-01T12:00:14.000+08:00| true|
|2021-07-01T12:00:15.000+08:00| true|
|2021-07-01T12:00:16.000+08:00| false|
|2021-07-01T12:00:17.000+08:00| false|
|2021-07-01T12:00:18.000+08:00| false|
|2021-07-01T12:00:19.000+08:00| false|
|2021-07-01T12:00:20.000+08:00| false|
+-----------------------------+------------------------------------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h2 id="range" tabindex="-1"><a class="header-anchor" href="#range"><span>Range</span></a></h2><h3 id="函数简介-4" tabindex="-1"><a class="header-anchor" href="#函数简介-4"><span>函数简介</span></a></h3><p>本函数用于查找时间序列的范围异常。将根据提供的上界与下界，判断输入数据是否越界，即异常，并输出所有异常点为新的时间序列。</p><p><strong>函数名：</strong> RANGE</p><p><strong>输入序列：</strong> 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>参数：</strong></p><ul><li><code>lower_bound</code>:范围异常检测的下界。</li><li><code>upper_bound</code>:范围异常检测的上界。</li></ul><p><strong>输出序列：</strong> 输出单个序列，类型与输入序列相同。</p><p><strong>提示：</strong> 应满足<code>upper_bound</code>大于<code>lower_bound</code>，否则将不做输出。</p><h3 id="使用示例-4" tabindex="-1"><a class="header-anchor" href="#使用示例-4"><span>使用示例</span></a></h3><h4 id="指定上界与下界" tabindex="-1"><a class="header-anchor" href="#指定上界与下界"><span>指定上界与下界</span></a></h4><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+---------------+
| Time|root.test.d1.s1|
+-----------------------------+---------------+
|2020-01-01T00:00:02.000+08:00| 100.0|
|2020-01-01T00:00:03.000+08:00| 101.0|
|2020-01-01T00:00:04.000+08:00| 102.0|
|2020-01-01T00:00:06.000+08:00| 104.0|
|2020-01-01T00:00:08.000+08:00| 126.0|
|2020-01-01T00:00:10.000+08:00| 108.0|
|2020-01-01T00:00:14.000+08:00| 112.0|
|2020-01-01T00:00:15.000+08:00| 113.0|
|2020-01-01T00:00:16.000+08:00| 114.0|
|2020-01-01T00:00:18.000+08:00| 116.0|
|2020-01-01T00:00:20.000+08:00| 118.0|
|2020-01-01T00:00:22.000+08:00| 120.0|
|2020-01-01T00:00:26.000+08:00| 124.0|
|2020-01-01T00:00:28.000+08:00| 126.0|
|2020-01-01T00:00:30.000+08:00| NaN|
+-----------------------------+---------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> range<span class="token punctuation">(</span>s1<span class="token punctuation">,</span><span class="token string">&quot;lower_bound&quot;</span><span class="token operator">=</span><span class="token string">&quot;101.0&quot;</span><span class="token punctuation">,</span><span class="token string">&quot;upper_bound&quot;</span><span class="token operator">=</span><span class="token string">&quot;125.0&quot;</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d1 <span class="token keyword">where</span> <span class="token keyword">time</span> <span class="token operator">&lt;=</span> <span class="token number">2020</span><span class="token operator">-</span><span class="token number">01</span><span class="token operator">-</span><span class="token number">01</span> <span class="token number">00</span>:<span class="token number">00</span>:<span class="token number">30</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+------------------------------------------------------------------+
|Time |range(root.test.d1.s1,&quot;lower_bound&quot;=&quot;101.0&quot;,&quot;upper_bound&quot;=&quot;125.0&quot;)|
+-----------------------------+------------------------------------------------------------------+
|2020-01-01T00:00:02.000+08:00| 100.0|
|2020-01-01T00:00:28.000+08:00| 126.0|
+-----------------------------+------------------------------------------------------------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><h2 id="twosidedfilter" tabindex="-1"><a class="header-anchor" href="#twosidedfilter"><span>TwoSidedFilter</span></a></h2><h3 id="函数简介-5" tabindex="-1"><a class="header-anchor" href="#函数简介-5"><span>函数简介</span></a></h3><p>本函数基于双边窗口检测法对输入序列中的异常点进行过滤。</p><p><strong>函数名：</strong> TWOSIDEDFILTER</p><p><strong>输出序列：</strong> 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>输出序列：</strong> 输出单个序列，类型与输入相同，是输入序列去除异常点后的结果。</p><p><strong>参数：</strong></p><ul><li><code>len</code>：双边窗口检测法中的窗口大小，取值范围为正整数，默认值为 5.如当<code>len</code>=3 时，算法向前、向后各取长度为3的窗口，在窗口中计算异常度。</li><li><code>threshold</code>：异常度的阈值，取值范围为(0,1)，默认值为 0.3。阈值越高，函数对于异常度的判定标准越严格。</li></ul><h3 id="使用示例-5" tabindex="-1"><a class="header-anchor" href="#使用示例-5"><span>使用示例</span></a></h3><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+------------+
| Time|root.test.s0|
+-----------------------------+------------+
|1970-01-01T08:00:00.000+08:00| 2002.0|
|1970-01-01T08:00:01.000+08:00| 1946.0|
|1970-01-01T08:00:02.000+08:00| 1958.0|
|1970-01-01T08:00:03.000+08:00| 2012.0|
|1970-01-01T08:00:04.000+08:00| 2051.0|
|1970-01-01T08:00:05.000+08:00| 1898.0|
|1970-01-01T08:00:06.000+08:00| 2014.0|
|1970-01-01T08:00:07.000+08:00| 2052.0|
|1970-01-01T08:00:08.000+08:00| 1935.0|
|1970-01-01T08:00:09.000+08:00| 1901.0|
|1970-01-01T08:00:10.000+08:00| 1972.0|
|1970-01-01T08:00:11.000+08:00| 1969.0|
|1970-01-01T08:00:12.000+08:00| 1984.0|
|1970-01-01T08:00:13.000+08:00| 2018.0|
|1970-01-01T08:00:37.000+08:00| 1484.0|
|1970-01-01T08:00:38.000+08:00| 1055.0|
|1970-01-01T08:00:39.000+08:00| 1050.0|
|1970-01-01T08:01:05.000+08:00| 1023.0|
|1970-01-01T08:01:06.000+08:00| 1056.0|
|1970-01-01T08:01:07.000+08:00| 978.0|
|1970-01-01T08:01:08.000+08:00| 1050.0|
|1970-01-01T08:01:09.000+08:00| 1123.0|
|1970-01-01T08:01:10.000+08:00| 1150.0|
|1970-01-01T08:01:11.000+08:00| 1034.0|
|1970-01-01T08:01:12.000+08:00| 950.0|
|1970-01-01T08:01:13.000+08:00| 1059.0|
+-----------------------------+------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">select</span> TwoSidedFilter<span class="token punctuation">(</span>s0<span class="token punctuation">,</span> <span class="token string">&#39;len&#39;</span><span class="token operator">=</span><span class="token string">&#39;5&#39;</span><span class="token punctuation">,</span> <span class="token string">&#39;threshold&#39;</span><span class="token operator">=</span><span class="token string">&#39;0.3&#39;</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+------------+
| Time|root.test.s0|
+-----------------------------+------------+
|1970-01-01T08:00:00.000+08:00| 2002.0|
|1970-01-01T08:00:01.000+08:00| 1946.0|
|1970-01-01T08:00:02.000+08:00| 1958.0|
|1970-01-01T08:00:03.000+08:00| 2012.0|
|1970-01-01T08:00:04.000+08:00| 2051.0|
|1970-01-01T08:00:05.000+08:00| 1898.0|
|1970-01-01T08:00:06.000+08:00| 2014.0|
|1970-01-01T08:00:07.000+08:00| 2052.0|
|1970-01-01T08:00:08.000+08:00| 1935.0|
|1970-01-01T08:00:09.000+08:00| 1901.0|
|1970-01-01T08:00:10.000+08:00| 1972.0|
|1970-01-01T08:00:11.000+08:00| 1969.0|
|1970-01-01T08:00:12.000+08:00| 1984.0|
|1970-01-01T08:00:13.000+08:00| 2018.0|
|1970-01-01T08:01:05.000+08:00| 1023.0|
|1970-01-01T08:01:06.000+08:00| 1056.0|
|1970-01-01T08:01:07.000+08:00| 978.0|
|1970-01-01T08:01:08.000+08:00| 1050.0|
|1970-01-01T08:01:09.000+08:00| 1123.0|
|1970-01-01T08:01:10.000+08:00| 1150.0|
|1970-01-01T08:01:11.000+08:00| 1034.0|
|1970-01-01T08:01:12.000+08:00| 950.0|
|1970-01-01T08:01:13.000+08:00| 1059.0|
+-----------------------------+------------+
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div>`,107),d=[l];function t(r,c){return e(),s("div",null,d)}const o=n(a,[["render",t],["__file","Anomaly-Detection.html.vue"]]),u=JSON.parse('{"path":"/zh/UserGuide/V1.0.x/Operators-Functions/Anomaly-Detection.html","title":"异常检测","lang":"zh-CN","frontmatter":{"description":"异常检测 IQR 函数简介 本函数用于检验超出上下四分位数1.5倍IQR的数据分布异常。 函数名： IQR 输入序列： 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE。 参数： method：若设置为 \\"batch\\"，则将数据全部读入后检测；若设置为 \\"stream\\"，则需用户提供上下四分位数进行流式检测。默认...","head":[["link",{"rel":"alternate","hreflang":"en-us","href":"https://iotdb.apache.org/UserGuide/V1.0.x/Operators-Functions/Anomaly-Detection.html"}],["meta",{"property":"og:url","content":"https://iotdb.apache.org/zh/UserGuide/V1.0.x/Operators-Functions/Anomaly-Detection.html"}],["meta",{"property":"og:site_name","content":"IoTDB Website"}],["meta",{"property":"og:title","content":"异常检测"}],["meta",{"property":"og:description","content":"异常检测 IQR 函数简介 本函数用于检验超出上下四分位数1.5倍IQR的数据分布异常。 函数名： IQR 输入序列： 仅支持单个输入序列，类型为 INT32 / INT64 / FLOAT / DOUBLE。 参数： method：若设置为 \\"batch\\"，则将数据全部读入后检测；若设置为 \\"stream\\"，则需用户提供上下四分位数进行流式检测。默认..."}],["meta",{"property":"og:type","content":"article"}],["meta",{"property":"og:locale","content":"zh-CN"}],["meta",{"property":"og:locale:alternate","content":"en-US"}],["meta",{"property":"og:updated_time","content":"2023-07-10T03:11:17.000Z"}],["meta",{"property":"article:modified_time","content":"2023-07-10T03:11:17.000Z"}],["script",{"type":"application/ld+json"},"{\\"@context\\":\\"https://schema.org\\",\\"@type\\":\\"Article\\",\\"headline\\":\\"异常检测\\",\\"image\\":[\\"\\"],\\"dateModified\\":\\"2023-07-10T03:11:17.000Z\\",\\"author\\":[]}"]]},"headers":[{"level":2,"title":"IQR","slug":"iqr","link":"#iqr","children":[{"level":3,"title":"函数简介","slug":"函数简介","link":"#函数简介","children":[]},{"level":3,"title":"使用示例","slug":"使用示例","link":"#使用示例","children":[]}]},{"level":2,"title":"KSigma","slug":"ksigma","link":"#ksigma","children":[{"level":3,"title":"函数简介","slug":"函数简介-1","link":"#函数简介-1","children":[]},{"level":3,"title":"使用示例","slug":"使用示例-1","link":"#使用示例-1","children":[]}]},{"level":2,"title":"LOF","slug":"lof","link":"#lof","children":[{"level":3,"title":"函数简介","slug":"函数简介-2","link":"#函数简介-2","children":[]},{"level":3,"title":"使用示例","slug":"使用示例-2","link":"#使用示例-2","children":[]}]},{"level":2,"title":"MissDetect","slug":"missdetect","link":"#missdetect","children":[{"level":3,"title":"函数简介","slug":"函数简介-3","link":"#函数简介-3","children":[]},{"level":3,"title":"使用示例","slug":"使用示例-3","link":"#使用示例-3","children":[]}]},{"level":2,"title":"Range","slug":"range","link":"#range","children":[{"level":3,"title":"函数简介","slug":"函数简介-4","link":"#函数简介-4","children":[]},{"level":3,"title":"使用示例","slug":"使用示例-4","link":"#使用示例-4","children":[]}]},{"level":2,"title":"TwoSidedFilter","slug":"twosidedfilter","link":"#twosidedfilter","children":[{"level":3,"title":"函数简介","slug":"函数简介-5","link":"#函数简介-5","children":[]},{"level":3,"title":"使用示例","slug":"使用示例-5","link":"#使用示例-5","children":[]}]}],"git":{"createdTime":1688958677000,"updatedTime":1688958677000,"contributors":[{"name":"CritasWang","email":"critas@outlook.com","commits":1}]},"readingTime":{"minutes":10.32,"words":3097},"filePathRelative":"zh/UserGuide/V1.0.x/Operators-Functions/Anomaly-Detection.md","localizedDate":"2023年7月10日","autoDesc":true}');export{o as comp,u as data};