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import{_ as n,O as l,P as t,ah as i,aW as e,Q as s,U as a}from"./framework-62ad666a.js";const r={},m=e(`<h1 id="data-matching" tabindex="-1"><a class="header-anchor" href="#data-matching" aria-hidden="true">#</a> Data Matching</h1><h2 id="cov" tabindex="-1"><a class="header-anchor" href="#cov" aria-hidden="true">#</a> Cov</h2><h3 id="usage" tabindex="-1"><a class="header-anchor" href="#usage" aria-hidden="true">#</a> Usage</h3><p>This function is used to calculate the population covariance.</p><p><strong>Name:</strong> COV</p><p><strong>Input Series:</strong> Only support two input series. The types are both INT32 / INT64 / FLOAT / DOUBLE.</p><p><strong>Output Series:</strong> Output a single series. The type is DOUBLE. There is only one data point in the series, whose timestamp is 0 and value is the population covariance.</p><p><strong>Note:</strong></p><ul><li>If a row contains missing points, null points or <code>NaN</code>, it will be ignored;</li><li>If all rows are ignored, <code>NaN</code> will be output.</li></ul><h3 id="examples" tabindex="-1"><a class="header-anchor" href="#examples" aria-hidden="true">#</a> Examples</h3><p>Input series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+---------------+
| Time|root.test.d2.s1|root.test.d2.s2|
+-----------------------------+---------------+---------------+
|2020-01-01T00:00:02.000+08:00| 100.0| 101.0|
|2020-01-01T00:00:03.000+08:00| 101.0| null|
|2020-01-01T00:00:04.000+08:00| 102.0| 101.0|
|2020-01-01T00:00:06.000+08:00| 104.0| 102.0|
|2020-01-01T00:00:08.000+08:00| 126.0| 102.0|
|2020-01-01T00:00:10.000+08:00| 108.0| 103.0|
|2020-01-01T00:00:12.000+08:00| null| 103.0|
|2020-01-01T00:00:14.000+08:00| 112.0| 104.0|
|2020-01-01T00:00:15.000+08:00| 113.0| null|
|2020-01-01T00:00:16.000+08:00| 114.0| 104.0|
|2020-01-01T00:00:18.000+08:00| 116.0| 105.0|
|2020-01-01T00:00:20.000+08:00| 118.0| 105.0|
|2020-01-01T00:00:22.000+08:00| 100.0| 106.0|
|2020-01-01T00:00:26.000+08:00| 124.0| 108.0|
|2020-01-01T00:00:28.000+08:00| 126.0| 108.0|
|2020-01-01T00:00:30.000+08:00| NaN| 108.0|
+-----------------------------+---------------+---------------+
</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></div><p>SQL for query:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> cov<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>d2
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>Output series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+-------------------------------------+
| Time|cov(root.test.d2.s1, root.test.d2.s2)|
+-----------------------------+-------------------------------------+
|1970-01-01T08:00:00.000+08:00| 12.291666666666666|
+-----------------------------+-------------------------------------+
</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="dtw" tabindex="-1"><a class="header-anchor" href="#dtw" aria-hidden="true">#</a> DTW</h2><h3 id="usage-1" tabindex="-1"><a class="header-anchor" href="#usage-1" aria-hidden="true">#</a> Usage</h3><p>This function is used to calculate the DTW distance between two input series.</p><p><strong>Name:</strong> DTW</p><p><strong>Input Series:</strong> Only support two input series. The types are both INT32 / INT64 / FLOAT / DOUBLE.</p><p><strong>Output Series:</strong> Output a single series. The type is DOUBLE. There is only one data point in the series, whose timestamp is 0 and value is the DTW distance.</p><p><strong>Note:</strong></p><ul><li>If a row contains missing points, null points or <code>NaN</code>, it will be ignored;</li><li>If all rows are ignored, <code>0</code> will be output.</li></ul><h3 id="examples-1" tabindex="-1"><a class="header-anchor" href="#examples-1" aria-hidden="true">#</a> Examples</h3><p>Input series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+---------------+
| Time|root.test.d2.s1|root.test.d2.s2|
+-----------------------------+---------------+---------------+
|1970-01-01T08:00:00.001+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.002+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.003+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.004+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.005+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.006+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.007+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.008+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.009+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.010+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.011+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.012+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.013+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.014+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.015+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.016+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.017+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.018+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.019+08:00| 1.0| 2.0|
|1970-01-01T08:00:00.020+08:00| 1.0| 2.0|
+-----------------------------+---------------+---------------+
</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>SQL for query:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> dtw<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>d2
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>Output series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+-------------------------------------+
| Time|dtw(root.test.d2.s1, root.test.d2.s2)|
+-----------------------------+-------------------------------------+
|1970-01-01T08:00:00.000+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></div><h2 id="pearson" tabindex="-1"><a class="header-anchor" href="#pearson" aria-hidden="true">#</a> Pearson</h2><h3 id="usage-2" tabindex="-1"><a class="header-anchor" href="#usage-2" aria-hidden="true">#</a> Usage</h3><p>This function is used to calculate the Pearson Correlation Coefficient.</p><p><strong>Name:</strong> PEARSON</p><p><strong>Input Series:</strong> Only support two input series. The types are both INT32 / INT64 / FLOAT / DOUBLE.</p><p><strong>Output Series:</strong> Output a single series. The type is DOUBLE. There is only one data point in the series, whose timestamp is 0 and value is the Pearson Correlation Coefficient.</p><p><strong>Note:</strong></p><ul><li>If a row contains missing points, null points or <code>NaN</code>, it will be ignored;</li><li>If all rows are ignored, <code>NaN</code> will be output.</li></ul><h3 id="examples-2" tabindex="-1"><a class="header-anchor" href="#examples-2" aria-hidden="true">#</a> Examples</h3><p>Input series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+---------------+
| Time|root.test.d2.s1|root.test.d2.s2|
+-----------------------------+---------------+---------------+
|2020-01-01T00:00:02.000+08:00| 100.0| 101.0|
|2020-01-01T00:00:03.000+08:00| 101.0| null|
|2020-01-01T00:00:04.000+08:00| 102.0| 101.0|
|2020-01-01T00:00:06.000+08:00| 104.0| 102.0|
|2020-01-01T00:00:08.000+08:00| 126.0| 102.0|
|2020-01-01T00:00:10.000+08:00| 108.0| 103.0|
|2020-01-01T00:00:12.000+08:00| null| 103.0|
|2020-01-01T00:00:14.000+08:00| 112.0| 104.0|
|2020-01-01T00:00:15.000+08:00| 113.0| null|
|2020-01-01T00:00:16.000+08:00| 114.0| 104.0|
|2020-01-01T00:00:18.000+08:00| 116.0| 105.0|
|2020-01-01T00:00:20.000+08:00| 118.0| 105.0|
|2020-01-01T00:00:22.000+08:00| 100.0| 106.0|
|2020-01-01T00:00:26.000+08:00| 124.0| 108.0|
|2020-01-01T00:00:28.000+08:00| 126.0| 108.0|
|2020-01-01T00:00:30.000+08:00| NaN| 108.0|
+-----------------------------+---------------+---------------+
</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></div><p>SQL for query:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> pearson<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>d2
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>Output series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+-----------------------------------------+
| Time|pearson(root.test.d2.s1, root.test.d2.s2)|
+-----------------------------+-----------------------------------------+
|1970-01-01T08:00:00.000+08:00| 0.5630881927754872|
+-----------------------------+-----------------------------------------+
</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="ptnsym" tabindex="-1"><a class="header-anchor" href="#ptnsym" aria-hidden="true">#</a> PtnSym</h2><h3 id="usage-3" tabindex="-1"><a class="header-anchor" href="#usage-3" aria-hidden="true">#</a> Usage</h3><p>This function is used to find all symmetric subseries in the input whose degree of symmetry is less than the threshold. The degree of symmetry is calculated by DTW. The smaller the degree, the more symmetrical the series is.</p><p><strong>Name:</strong> PATTERNSYMMETRIC</p><p><strong>Input Series:</strong> Only support a single input series. The type is INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>Parameter:</strong></p><ul><li><code>window</code>: The length of the symmetric subseries. It&#39;s a positive integer and the default value is 10.</li><li><code>threshold</code>: The threshold of the degree of symmetry. It&#39;s non-negative. Only the subseries whose degree of symmetry is below it will be output. By default, all subseries will be output.</li></ul><p><strong>Output Series:</strong> Output a single series. The type is DOUBLE. Each data point in the output series corresponds to a symmetric subseries. The output timestamp is the starting timestamp of the subseries and the output value is the degree of symmetry.</p><h3 id="example" tabindex="-1"><a class="header-anchor" href="#example" aria-hidden="true">#</a> Example</h3><p>Input series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+
| Time|root.test.d1.s4|
+-----------------------------+---------------+
|2021-01-01T12:00:00.000+08:00| 1.0|
|2021-01-01T12:00:01.000+08:00| 2.0|
|2021-01-01T12:00:02.000+08:00| 3.0|
|2021-01-01T12:00:03.000+08:00| 2.0|
|2021-01-01T12:00:04.000+08:00| 1.0|
|2021-01-01T12:00:05.000+08:00| 1.0|
|2021-01-01T12:00:06.000+08:00| 1.0|
|2021-01-01T12:00:07.000+08:00| 1.0|
|2021-01-01T12:00:08.000+08:00| 2.0|
|2021-01-01T12:00:09.000+08:00| 3.0|
|2021-01-01T12:00:10.000+08:00| 2.0|
|2021-01-01T12:00:11.000+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></div><p>SQL for query:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> ptnsym<span class="token punctuation">(</span>s4<span class="token punctuation">,</span> <span class="token string">&#39;window&#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&#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>d1
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>Output series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+------------------------------------------------------+
| Time|ptnsym(root.test.d1.s4, &quot;window&quot;=&quot;5&quot;, &quot;threshold&quot;=&quot;0&quot;)|
+-----------------------------+------------------------------------------------------+
|2021-01-01T12:00:00.000+08:00| 0.0|
|2021-01-01T12:00:07.000+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></div><h2 id="xcorr" tabindex="-1"><a class="header-anchor" href="#xcorr" aria-hidden="true">#</a> XCorr</h2><h3 id="usage-4" tabindex="-1"><a class="header-anchor" href="#usage-4" aria-hidden="true">#</a> Usage</h3><p>This function is used to calculate the cross correlation function of given two time series. For discrete time series, cross correlation is given by</p>`,64),c=s("p",{class:"katex-block"},[s("span",{class:"katex-display"},[s("span",{class:"katex"},[s("span",{class:"katex-mathml"},[s("math",{xmlns:"http://www.w3.org/1998/Math/MathML",display:"block"},[s("semantics",null,[s("mrow",null,[s("mi",null,"C"),s("mi",null,"R"),s("mo",{stretchy:"false"},"("),s("mi",null,"n"),s("mo",{stretchy:"false"},")"),s("mo",null,"="),s("mfrac",null,[s("mn",null,"1"),s("mi",null,"N")]),s("munderover",null,[s("mo",null,"∑"),s("mrow",null,[s("mi",null,"m"),s("mo",null,"="),s("mn",null,"1")]),s("mi",null,"N")]),s("msub",null,[s("mi",null,"S"),s("mn",null,"1")]),s("mo",{stretchy:"false"},"["),s("mi",null,"m"),s("mo",{stretchy:"false"},"]"),s("msub",null,[s("mi",null,"S"),s("mn",null,"2")]),s("mo",{stretchy:"false"},"["),s("mi",null,"m"),s("mo",null,"+"),s("mi",null,"n"),s("mo",{stretchy:"false"},"]")]),s("annotation",{encoding:"application/x-tex"}," CR(n) = \\frac{1}{N} \\sum_{m=1}^N S_1[m]S_2[m+n] ")])])]),s("span",{class:"katex-html","aria-hidden":"true"},[s("span",{class:"base"},[s("span",{class:"strut",style:{height:"1em","vertical-align":"-0.25em"}}),s("span",{class:"mord mathnormal",style:{"margin-right":"0.00773em"}},"CR"),s("span",{class:"mopen"},"("),s("span",{class:"mord mathnormal"},"n"),s("span",{class:"mclose"},")"),s("span",{class:"mspace",style:{"margin-right":"0.2778em"}}),s("span",{class:"mrel"},"="),s("span",{class:"mspace",style:{"margin-right":"0.2778em"}})]),s("span",{class:"base"},[s("span",{class:"strut",style:{height:"3.0954em","vertical-align":"-1.2671em"}}),s("span",{class:"mord"},[s("span",{class:"mopen nulldelimiter"}),s("span",{class:"mfrac"},[s("span",{class:"vlist-t vlist-t2"},[s("span",{class:"vlist-r"},[s("span",{class:"vlist",style:{height:"1.3214em"}},[s("span",{style:{top:"-2.314em"}},[s("span",{class:"pstrut",style:{height:"3em"}}),s("span",{class:"mord"},[s("span",{class:"mord mathnormal",style:{"margin-right":"0.10903em"}},"N")])]),s("span",{style:{top:"-3.23em"}},[s("span",{class:"pstrut",style:{height:"3em"}}),s("span",{class:"frac-line",style:{"border-bottom-width":"0.04em"}})]),s("span",{style:{top:"-3.677em"}},[s("span",{class:"pstrut",style:{height:"3em"}}),s("span",{class:"mord"},[s("span",{class:"mord"},"1")])])]),s("span",{class:"vlist-s"},"​")]),s("span",{class:"vlist-r"},[s("span",{class:"vlist",style:{height:"0.686em"}},[s("span")])])])]),s("span",{class:"mclose nulldelimiter"})]),s("span",{class:"mspace",style:{"margin-right":"0.1667em"}}),s("span",{class:"mop op-limits"},[s("span",{class:"vlist-t vlist-t2"},[s("span",{class:"vlist-r"},[s("span",{class:"vlist",style:{height:"1.8283em"}},[s("span",{style:{top:"-1.8829em","margin-left":"0em"}},[s("span",{class:"pstrut",style:{height:"3.05em"}}),s("span",{class:"sizing reset-size6 size3 mtight"},[s("span",{class:"mord mtight"},[s("span",{class:"mord mathnormal mtight"},"m"),s("span",{class:"mrel 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mtight"},"2")])])]),s("span",{class:"vlist-s"},"​")]),s("span",{class:"vlist-r"},[s("span",{class:"vlist",style:{height:"0.15em"}},[s("span")])])])])]),s("span",{class:"mopen"},"["),s("span",{class:"mord mathnormal"},"m"),s("span",{class:"mclose"},"]"),s("span",{class:"mpunct"},","),s("span",{class:"mspace"}," "),s("span",{class:"mspace",style:{"margin-right":"0.1667em"}}),s("span",{class:"mord mathnormal"},"i"),s("span",{class:"mord mathnormal",style:{"margin-right":"0.10764em"}},"f"),s("span",{class:"mspace"}," "),s("span",{class:"mord mathnormal"},"i"),s("span",{class:"mspace",style:{"margin-right":"0.2778em"}}),s("span",{class:"mrel"},">"),s("span",{class:"mspace",style:{"margin-right":"0.2778em"}})]),s("span",{class:"base"},[s("span",{class:"strut",style:{height:"0.6833em"}}),s("span",{class:"mord mathnormal",style:{"margin-right":"0.10903em"}},"N")])])])])],-1),v=e(`<p><strong>Note:</strong></p><ul><li><code>null</code> and <code>NaN</code> values in the input series will be ignored and treated as 0.</li></ul><h3 id="examples-3" tabindex="-1"><a class="header-anchor" href="#examples-3" aria-hidden="true">#</a> Examples</h3><p>Input series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+---------------+
| Time|root.test.d1.s1|root.test.d1.s2|
+-----------------------------+---------------+---------------+
|2020-01-01T00:00:01.000+08:00| null| 6|
|2020-01-01T00:00:02.000+08:00| 2| 7|
|2020-01-01T00:00:03.000+08:00| 3| NaN|
|2020-01-01T00:00:04.000+08:00| 4| 9|
|2020-01-01T00:00:05.000+08:00| 5| 10|
+-----------------------------+---------------+---------------+
</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></div><p>SQL for query:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> xcorr<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">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">05</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>Output series:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------------------------------+
| Time|xcorr(root.test.d1.s1, root.test.d1.s2)|
+-----------------------------+---------------------------------------+
|1970-01-01T08:00:00.001+08:00| 0.0|
|1970-01-01T08:00:00.002+08:00| 4.0|
|1970-01-01T08:00:00.003+08:00| 9.6|
|1970-01-01T08:00:00.004+08:00| 13.4|
|1970-01-01T08:00:00.005+08:00| 20.0|
|1970-01-01T08:00:00.006+08:00| 15.6|
|1970-01-01T08:00:00.007+08:00| 9.2|
|1970-01-01T08:00:00.008+08:00| 11.8|
|1970-01-01T08:00:00.009+08:00| 6.0|
+-----------------------------+---------------------------------------+
</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></div>`,9);function b(y,T){return l(),t("div",null,[i(`
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`),m,c,p,o,d,u,h,g,v])}const x=n(r,[["render",b],["__file","Data-Matching.html.vue"]]);export{x as default};