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class="title">参考</span><span class="arrow end"></span></button><!----></section></li></ul><!--[--><!----><!--]--></aside><!--[--><main class="page" id="main-content"><!--[--><!----><nav class="breadcrumb disable"></nav><div class="page-title"><h1><!----></h1><div class="page-info"><!----><!----><!----><!----><span class="page-reading-time-info" aria-label="阅读时间"><svg xmlns="http://www.w3.org/2000/svg" class="icon timer-icon" viewBox="0 0 1024 1024" fill="currentColor" aria-label="timer icon"><path d="M799.387 122.15c4.402-2.978 7.38-7.897 7.38-13.463v-1.165c0-8.933-7.38-16.312-16.312-16.312H256.33c-8.933 0-16.311 7.38-16.311 16.312v1.165c0 5.825 2.977 10.874 7.637 13.592 4.143 194.44 97.22 354.963 220.201 392.763-122.204 37.542-214.893 196.511-220.2 389.397-4.661 5.049-7.638 11.651-7.638 19.03v5.825h566.49v-5.825c0-7.379-2.849-13.981-7.509-18.9-5.049-193.016-97.867-351.985-220.2-389.527 123.24-37.67 216.446-198.453 220.588-392.892zM531.16 450.445v352.632c117.674 1.553 211.787 40.778 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108.8-49.067 108.8-108.8v-192c0-59.733-49.067-108.8-108.8-108.8zM313.6 160h396.8v204.8H313.6V160zm396.8 704H313.6V620.8h396.8V864zM864 665.6c0 25.6-19.2 44.8-44.8 44.8h-44.8V588.8c0-17.067-14.933-32-32-32H281.6c-17.067 0-32 14.933-32 32v121.6h-44.8c-25.6 0-44.8-19.2-44.8-44.8v-192c0-25.6 19.2-44.8 44.8-44.8h614.4c25.6 0 44.8 19.2 44.8 44.8v192z"></path></svg></button></div><div class="toc-wrapper"><ul class="toc-list"><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V0.13.x/UDF-Library/Data-Repairing.html#数据修复" class="router-link-active router-link-exact-active toc-link level2">数据修复</a></li><ul class="toc-list"><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V0.13.x/UDF-Library/Data-Repairing.html#timestamprepair" class="router-link-active router-link-exact-active toc-link level3">TimestampRepair</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V0.13.x/UDF-Library/Data-Repairing.html#valuefill" class="router-link-active router-link-exact-active toc-link level3">ValueFill</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V0.13.x/UDF-Library/Data-Repairing.html#valuerepair" class="router-link-active router-link-exact-active toc-link level3">ValueRepair</a></li><!----><!--]--></ul><!--]--></ul></div><!--[--><!----><!--]--></aside></div><!----><div class="theme-hope-content"><!--

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--><h2 id="数据修复" tabindex="-1"><a class="header-anchor" href="#数据修复" aria-hidden="true">#</a> 数据修复</h2><h3 id="timestamprepair" tabindex="-1"><a class="header-anchor" href="#timestamprepair" aria-hidden="true">#</a> TimestampRepair</h3><h4 id="函数简介" tabindex="-1"><a class="header-anchor" href="#函数简介" aria-hidden="true">#</a> 函数简介</h4><p>本函数用于时间戳修复。根据给定的标准时间间隔，采用最小化修复代价的方法，通过对数据时间戳的微调，将原本时间戳间隔不稳定的数据修复为严格等间隔的数据。在未给定标准时间间隔的情况下，本函数将使用时间间隔的中位数 (median)、众数 (mode) 或聚类中心 (cluster) 来推算标准时间间隔。</p><p><strong>函数名：</strong> TIMESTAMPREPAIR</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>interval</code>: 标准时间间隔（单位是毫秒），是一个正整数。在缺省情况下，将根据指定的方法推算。</li><li><code>method</code>：推算标准时间间隔的方法，取值为 &#39;median&#39;, &#39;mode&#39; 或 &#39;cluster&#39;，仅在<code>interval</code>缺省时有效。在缺省情况下，将使用中位数方法进行推算。</li></ul><p><strong>输出序列：</strong> 输出单个序列，类型与输入序列相同。该序列是修复后的输入序列。</p><h4 id="使用示例" tabindex="-1"><a class="header-anchor" href="#使用示例" aria-hidden="true">#</a> 使用示例</h4><h5 id="指定标准时间间隔" tabindex="-1"><a class="header-anchor" href="#指定标准时间间隔" aria-hidden="true">#</a> 指定标准时间间隔</h5><p>在给定<code>interval</code>参数的情况下，本函数将按照指定的标准时间间隔进行修复。</p><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+
|                         Time|root.test.d2.s1|
+-----------------------------+---------------+
|2021-07-01T12:00:00.000+08:00|            1.0|
|2021-07-01T12:00:10.000+08:00|            2.0|
|2021-07-01T12:00:19.000+08:00|            3.0|
|2021-07-01T12:00:30.000+08:00|            4.0|
|2021-07-01T12:00:40.000+08:00|            5.0|
|2021-07-01T12:00:50.000+08:00|            6.0|
|2021-07-01T12:01:01.000+08:00|            7.0|
|2021-07-01T12:01:11.000+08:00|            8.0|
|2021-07-01T12:01:21.000+08:00|            9.0|
|2021-07-01T12:01:31.000+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 class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="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"><pre class="language-sql"><code><span class="token keyword">select</span> timestamprepair<span class="token punctuation">(</span>s1<span class="token punctuation">,</span><span class="token string">&#39;interval&#39;</span><span class="token operator">=</span><span class="token string">&#39;10000&#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"><pre class="language-text"><code>+-----------------------------+----------------------------------------------------+
|                         Time|timestamprepair(root.test.d2.s1, &quot;interval&quot;=&quot;10000&quot;)|
+-----------------------------+----------------------------------------------------+
|2021-07-01T12:00:00.000+08:00|                                                 1.0|
|2021-07-01T12:00:10.000+08:00|                                                 2.0|
|2021-07-01T12:00:20.000+08:00|                                                 3.0|
|2021-07-01T12:00:30.000+08:00|                                                 4.0|
|2021-07-01T12:00:40.000+08:00|                                                 5.0|
|2021-07-01T12:00:50.000+08:00|                                                 6.0|
|2021-07-01T12:01:00.000+08:00|                                                 7.0|
|2021-07-01T12:01:10.000+08:00|                                                 8.0|
|2021-07-01T12:01:20.000+08:00|                                                 9.0|
|2021-07-01T12:01:30.000+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 class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="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><h5 id="自动推算标准时间间隔" tabindex="-1"><a class="header-anchor" href="#自动推算标准时间间隔" aria-hidden="true">#</a> 自动推算标准时间间隔</h5><p>如果<code>interval</code>参数没有给定，本函数将按照推算的标准时间间隔进行修复。</p><p>输入序列同上，用于查询的 SQL 语句如下：</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> timestamprepair<span class="token punctuation">(</span>s1<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"><pre class="language-text"><code>+-----------------------------+--------------------------------+
|                         Time|timestamprepair(root.test.d2.s1)|
+-----------------------------+--------------------------------+
|2021-07-01T12:00:00.000+08:00|                             1.0|
|2021-07-01T12:00:10.000+08:00|                             2.0|
|2021-07-01T12:00:20.000+08:00|                             3.0|
|2021-07-01T12:00:30.000+08:00|                             4.0|
|2021-07-01T12:00:40.000+08:00|                             5.0|
|2021-07-01T12:00:50.000+08:00|                             6.0|
|2021-07-01T12:01:00.000+08:00|                             7.0|
|2021-07-01T12:01:10.000+08:00|                             8.0|
|2021-07-01T12:01:20.000+08:00|                             9.0|
|2021-07-01T12:01:30.000+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 class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="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><h3 id="valuefill" tabindex="-1"><a class="header-anchor" href="#valuefill" aria-hidden="true">#</a> ValueFill</h3><h4 id="函数简介-1" tabindex="-1"><a class="header-anchor" href="#函数简介-1" aria-hidden="true">#</a> 函数简介</h4><p><strong>函数名：</strong> ValueFill</p><p><strong>输入序列：</strong> 单列时序数据，类型为INT32 / INT64 / FLOAT / DOUBLE</p><p><strong>参数：</strong></p><ul><li><code>method</code>: {&quot;mean&quot;, &quot;previous&quot;, &quot;linear&quot;, &quot;likelihood&quot;, &quot;AR&quot;, &quot;MA&quot;, &quot;SCREEN&quot;}, 默认为 &quot;linear&quot;。其中，“mean” 指使用均值填补的方法； “previous&quot; 指使用前值填补方法；“linear&quot; 指使用线性插值填补方法；“likelihood” 为基于速度的正态分布的极大似然估计方法；“AR” 指自回归的填补方法；“MA” 指滑动平均的填补方法；&quot;SCREEN&quot; 指约束填补方法；缺省情况下使用 “linear”。</li></ul><p><strong>输出序列：</strong> 填补后的单维序列。</p><p><strong>备注：</strong> AR 模型采用 AR(1)，时序列需满足自相关条件，否则将输出单个数据点 (0, 0.0).</p><h4 id="使用示例-1" tabindex="-1"><a class="header-anchor" href="#使用示例-1" aria-hidden="true">#</a> 使用示例</h4><h5 id="使用-linear-方法进行填补" tabindex="-1"><a class="header-anchor" href="#使用-linear-方法进行填补" aria-hidden="true">#</a> 使用 linear 方法进行填补</h5><p>当<code>method</code>缺省或取值为 &#39;linear&#39; 时，本函数将使用线性插值方法进行填补。</p><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+
|                         Time|root.test.d2.s1|
+-----------------------------+---------------+
|2020-01-01T00:00:02.000+08:00|            NaN|
|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|            NaN|
|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|            NaN|
|2020-01-01T00:00:22.000+08:00|            NaN|
|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|          128.0|
+-----------------------------+---------------+
</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></div><p>用于查询的 SQL 语句：</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> valuefill<span class="token punctuation">(</span>s1<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"><pre class="language-text"><code>+-----------------------------+-----------------------+
|                         Time|valuefill(root.test.d2)|
+-----------------------------+-----------------------+
|2020-01-01T00:00:02.000+08:00|                    NaN|
|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|                  108.0|
|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|                  118.7|
|2020-01-01T00:00:22.000+08:00|                  121.3|
|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|                  128.0|
+-----------------------------+-----------------------+
</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></div><h5 id="使用-previous-方法进行填补" tabindex="-1"><a class="header-anchor" href="#使用-previous-方法进行填补" aria-hidden="true">#</a> 使用 previous 方法进行填补</h5><p>当<code>method</code>取值为 &#39;previous&#39; 时，本函数将使前值填补方法进行数值填补。</p><p>输入序列同上，用于查询的 SQL 语句如下：</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> valuefill<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;previous&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>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"><pre class="language-text"><code>+-----------------------------+-------------------------------------------+
|                         Time|valuefill(root.test.d2,&quot;method&quot;=&quot;previous&quot;)|
+-----------------------------+-------------------------------------------+
|2020-01-01T00:00:02.000+08:00|                                        NaN|
|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|                                      110.5|
|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|                                      116.0|
|2020-01-01T00:00:22.000+08:00|                                      116.0|
|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|                                      128.0|
+-----------------------------+-------------------------------------------+
</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></div><h3 id="valuerepair" tabindex="-1"><a class="header-anchor" href="#valuerepair" aria-hidden="true">#</a> ValueRepair</h3><h4 id="函数简介-2" tabindex="-1"><a class="header-anchor" href="#函数简介-2" aria-hidden="true">#</a> 函数简介</h4><p>本函数用于对时间序列的数值进行修复。目前，本函数支持两种修复方法：<strong>Screen</strong> 是一种基于速度阈值的方法，在最小改动的前提下使得所有的速度符合阈值要求；<strong>LsGreedy</strong> 是一种基于速度变化似然的方法，将速度变化建模为高斯分布，并采用贪心算法极大化似然函数。</p><p><strong>函数名：</strong> VALUEREPAIR</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>：修复时采用的方法，取值为 &#39;Screen&#39; 或 &#39;LsGreedy&#39;. 在缺省情况下，使用 Screen 方法进行修复。</li><li><code>minSpeed</code>：该参数仅在使用 Screen 方法时有效。当速度小于该值时会被视作数值异常点加以修复。在缺省情况下为中位数减去三倍绝对中位差。</li><li><code>maxSpeed</code>：该参数仅在使用 Screen 方法时有效。当速度大于该值时会被视作数值异常点加以修复。在缺省情况下为中位数加上三倍绝对中位差。</li><li><code>center</code>：该参数仅在使用 LsGreedy 方法时有效。对速度变化分布建立的高斯模型的中心。在缺省情况下为 0。</li><li><code>sigma</code> ：该参数仅在使用 LsGreedy 方法时有效。对速度变化分布建立的高斯模型的标准差。在缺省情况下为绝对中位差。</li></ul><p><strong>输出序列：</strong> 输出单个序列，类型与输入序列相同。该序列是修复后的输入序列。</p><p><strong>提示：</strong> 输入序列中的<code>NaN</code>在修复之前会先进行线性插值填补。</p><h4 id="使用示例-2" tabindex="-1"><a class="header-anchor" href="#使用示例-2" aria-hidden="true">#</a> 使用示例</h4><h5 id="使用-screen-方法进行修复" tabindex="-1"><a class="header-anchor" href="#使用-screen-方法进行修复" aria-hidden="true">#</a> 使用 Screen 方法进行修复</h5><p>当<code>method</code>缺省或取值为 &#39;Screen&#39; 时，本函数将使用 Screen 方法进行数值修复。</p><p>输入序列：</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+
|                         Time|root.test.d2.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|          100.0|
|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"><pre class="language-sql"><code><span class="token keyword">select</span> valuerepair<span class="token punctuation">(</span>s1<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"><pre class="language-text"><code>+-----------------------------+----------------------------+
|                         Time|valuerepair(root.test.d2.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|                       106.0|
|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|                       128.0|
+-----------------------------+----------------------------+
</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></div><h5 id="使用-lsgreedy-方法进行修复" tabindex="-1"><a class="header-anchor" href="#使用-lsgreedy-方法进行修复" aria-hidden="true">#</a> 使用 LsGreedy 方法进行修复</h5><p>当<code>method</code>取值为 &#39;LsGreedy&#39; 时，本函数将使用 LsGreedy 方法进行数值修复。</p><p>输入序列同上，用于查询的 SQL 语句如下：</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> valuerepair<span class="token punctuation">(</span>s1<span class="token punctuation">,</span><span class="token string">&#39;method&#39;</span><span class="token operator">=</span><span class="token string">&#39;LsGreedy&#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"><pre class="language-text"><code>+-----------------------------+-------------------------------------------------+
|                         Time|valuerepair(root.test.d2.s1, &quot;method&quot;=&quot;LsGreedy&quot;)|
+-----------------------------+-------------------------------------------------+
|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|                                            106.0|
|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|                                            128.0|
+-----------------------------+-------------------------------------------------+
</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></div></div><!----><footer class="page-meta"><div class="meta-item edit-link"><a href="https://github.com/apache/iotdb/edit/rel/0.13/docs/zh/UserGuide/UDF-Library/Data-Repairing.md" rel="noopener noreferrer" target="_blank" aria-label="发现错误？在 GitHub 上编辑此页" class="nav-link label"><!--[--><svg xmlns="http://www.w3.org/2000/svg" class="icon edit-icon" viewBox="0 0 1024 1024" fill="currentColor" aria-label="edit icon"><path d="M430.818 653.65a60.46 60.46 0 0 1-50.96-93.281l71.69-114.012 7.773-10.365L816.038 80.138A60.46 60.46 0 0 1 859.225 62a60.46 60.46 0 0 1 43.186 18.138l43.186 43.186a60.46 60.46 0 0 1 0 86.373L588.879 565.55l-8.637 8.637-117.466 68.234a60.46 60.46 0 0 1-31.958 11.229z"></path><path d="M728.802 962H252.891A190.883 190.883 0 0 1 62.008 771.98V296.934a190.883 190.883 0 0 1 190.883-192.61h267.754a60.46 60.46 0 0 1 0 120.92H252.891a69.962 69.962 0 0 0-69.098 69.099V771.98a69.962 69.962 0 0 0 69.098 69.098h475.911A69.962 69.962 0 0 0 797.9 771.98V503.363a60.46 60.46 0 1 1 120.922 0V771.98A190.883 190.883 0 0 1 728.802 962z"></path></svg><!--]-->发现错误？在 GitHub 上编辑此页<span><svg class="external-link-icon" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" focusable="false" x="0px" y="0px" viewBox="0 0 100 100" width="15" height="15"><path fill="currentColor" d="M18.8,85.1h56l0,0c2.2,0,4-1.8,4-4v-32h-8v28h-48v-48h28v-8h-32l0,0c-2.2,0-4,1.8-4,4v56C14.8,83.3,16.6,85.1,18.8,85.1z"></path><polygon fill="currentColor" points="45.7,48.7 51.3,54.3 77.2,28.5 77.2,37.2 85.2,37.2 85.2,14.9 62.8,14.9 62.8,22.9 71.5,22.9"></polygon></svg><span class="external-link-icon-sr-only">open in new window</span></span><!----></a></div><div class="meta-item git-info"><!----><!----></div></footer><nav class="page-nav"><a href="/zh/UserGuide/V0.13.x/UDF-Library/Data-Quality.html" class="nav-link prev" aria-label="数据质量"><div class="hint"><span class="arrow start"></span>上一页</div><div class="link"><!---->数据质量</div></a><a href="/zh/UserGuide/V0.13.x/UDF-Library/Series-Discovery.html" class="nav-link next" aria-label="序列发现"><div class="hint">下一页<span class="arrow end"></span></div><div class="link">序列发现<!----></div></a></nav><!----><!----><!--]--></main><!--]--><footer style="padding-bottom:2rem;"><span id="doc-version" style="display:none;">rel/0.13</span><p style="text-align:center;color:#909399;font-size:12px;margin:0 30px;">Copyright © 2023 The Apache Software Foundation.<br> Apache and the Apache feather logo are trademarks of The Apache Software Foundation</p><p style="text-align:center;margin-top:10px;color:#909399;font-size:12px;margin:0 30px;"><strong>Have a question?</strong> Connect with us on QQ, WeChat, or Slack. <a href="https://github.com/apache/iotdb/issues/1995">Join the community</a> now.</p><p style="text-align:center;margin-top:10px;color:#909399;font-size:12px;margin:0 30px;"> We use <a href="https://analytics.google.com">Google Analytics</a> to collect anonymous, aggregated usage information. </p></footer></div><!--]--><!--]--><!----><!--]--></div>
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