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href="/zh/UserGuide/V1.0.x/Query-Data/Select-Expression.html" aria-label="选择表达式"><!---->选择表达式<!----></a></li><li><a class="route-link nav-link vp-sidebar-link vp-sidebar-page" href="/zh/UserGuide/V1.0.x/Query-Data/Last-Query.html" aria-label="最新点查询"><!---->最新点查询<!----></a></li><li><a class="route-link nav-link vp-sidebar-link vp-sidebar-page" href="/zh/UserGuide/V1.0.x/Query-Data/Align-By.html" aria-label="查询对齐模式"><!---->查询对齐模式<!----></a></li><li><a class="route-link nav-link vp-sidebar-link vp-sidebar-page" href="/zh/UserGuide/V1.0.x/Query-Data/Where-Condition.html" aria-label="查询过滤条件"><!---->查询过滤条件<!----></a></li><li><a class="route-link nav-link active vp-sidebar-link vp-sidebar-page active" href="/zh/UserGuide/V1.0.x/Query-Data/Group-By.html" aria-label="分段分组聚合"><!---->分段分组聚合<!----></a></li><li><a class="route-link nav-link vp-sidebar-link vp-sidebar-page" href="/zh/UserGuide/V1.0.x/Query-Data/Having-Condition.html" aria-label="聚合结果过滤"><!---->聚合结果过滤<!----></a></li><li><a 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class="vp-page-title"><h1><!---->分段分组聚合</h1><div class="page-info"><!----><!----><span class="page-date-info" aria-label="写作日期"><svg xmlns="http://www.w3.org/2000/svg" class="icon calendar-icon" viewBox="0 0 1024 1024" fill="currentColor" aria-label="calendar icon"><path d="M716.4 110.137c0-18.753-14.72-33.473-33.472-33.473-18.753 0-33.473 14.72-33.473 33.473v33.473h66.993v-33.473zm-334.87 0c0-18.753-14.72-33.473-33.473-33.473s-33.52 14.72-33.52 33.473v33.473h66.993v-33.473zm468.81 33.52H716.4v100.465c0 18.753-14.72 33.473-33.472 33.473a33.145 33.145 0 01-33.473-33.473V143.657H381.53v100.465c0 18.753-14.72 33.473-33.473 33.473a33.145 33.145 0 01-33.473-33.473V143.657H180.6A134.314 134.314 0 0046.66 277.595v535.756A134.314 134.314 0 00180.6 947.289h669.74a134.36 134.36 0 00133.94-133.938V277.595a134.314 134.314 0 00-133.94-133.938zm33.473 267.877H147.126a33.145 33.145 0 01-33.473-33.473c0-18.752 14.72-33.473 33.473-33.473h736.687c18.752 0 33.472 14.72 33.472 33.473a33.145 33.145 0 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220.588-392.892zM531.16 450.445v352.632c117.674 1.553 211.787 40.778 211.787 88.676H304.097c0-48.286 95.149-87.382 213.728-88.676V450.445c-93.077-3.107-167.901-81.297-167.901-177.093 0-8.803 6.99-15.793 15.793-15.793 8.803 0 15.794 6.99 15.794 15.793 0 80.261 63.69 145.635 142.01 145.635s142.011-65.374 142.011-145.635c0-8.803 6.99-15.793 15.794-15.793s15.793 6.99 15.793 15.793c0 95.019-73.789 172.82-165.96 177.093z"></path></svg><span>大约 17 分钟</span><meta property="timeRequired" content="PT17M"></span><!----><!----></div><hr></div><div class="vp-toc-placeholder"><aside id="toc"><!--[--><!----><!--]--><div class="vp-toc-header">此页内容<button type="button" class="print-button" title="打印"><svg xmlns="http://www.w3.org/2000/svg" class="icon print-icon" viewBox="0 0 1024 1024" fill="currentColor" aria-label="print icon"><path d="M819.2 364.8h-44.8V128c0-17.067-14.933-32-32-32H281.6c-17.067 0-32 14.933-32 32v236.8h-44.8C145.067 364.8 96 413.867 96 473.6v192c0 59.733 49.067 108.8 108.8 108.8h44.8V896c0 17.067 14.933 32 32 32h460.8c17.067 0 32-14.933 32-32V774.4h44.8c59.733 0 108.8-49.067 108.8-108.8v-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 class="arrow end"></div></div><div class="vp-toc-wrapper"><ul class="vp-toc-list"><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#时间区间分段聚合">时间区间分段聚合</a></li><li><ul class="vp-toc-list"><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#未指定滑动步长的时间区间分组聚合查询">未指定滑动步长的时间区间分组聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#指定滑动步长的时间区间分组聚合查询">指定滑动步长的时间区间分组聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#按照自然月份的时间区间分组聚合查询">按照自然月份的时间区间分组聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#左开右闭区间">左开右闭区间</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#与分组聚合混合使用">与分组聚合混合使用</a></li><!----><!--]--></ul></li><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#路径层级分组聚合">路径层级分组聚合</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#标签分组聚合">标签分组聚合</a></li><li><ul class="vp-toc-list"><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#单标签聚合查询">单标签聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#多标签聚合查询">多标签聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#基于时间区间的标签聚合查询">基于时间区间的标签聚合查询</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#标签聚合查询的限制">标签聚合查询的限制</a></li><!----><!--]--></ul></li><!--]--></ul><div class="vp-toc-marker" style="top:-1.7rem;"></div></div><!--[--><!----><!--]--></aside></div><!--[--><!----><!--]--><div class="theme-hope-content"><h1 id="分段分组聚合" tabindex="-1"><a class="header-anchor" href="#分段分组聚合"><span>分段分组聚合</span></a></h1><h2 id="时间区间分段聚合" tabindex="-1"><a class="header-anchor" href="#时间区间分段聚合"><span>时间区间分段聚合</span></a></h2><p>分段聚合是一种时序数据典型的查询方式，数据以高频进行采集，需要按照一定的时间间隔进行聚合计算，如计算每天的平均气温，需要将气温的序列按天进行分段，然后计算平均值。</p><p>在 IoTDB 中，聚合查询可以通过 <code>GROUP BY</code> 子句指定按照时间区间分段聚合。用户可以指定聚合的时间间隔和滑动步长，相关参数如下：</p><ul><li>参数 1：时间轴显示时间窗口大小</li><li>参数 2：聚合窗口的大小（必须为正数）</li><li>参数 3：聚合窗口的滑动步长（可选，默认与聚合窗口大小相同）</li></ul><p>下图中指出了这三个参数的含义：</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/github/69109512-f808bc80-0ab2-11ea-9e4d-b2b2f58fb474.png"><p>接下来，我们给出几个典型例子：</p><h3 id="未指定滑动步长的时间区间分组聚合查询" tabindex="-1"><a class="header-anchor" href="#未指定滑动步长的时间区间分组聚合查询"><span>未指定滑动步长的时间区间分组聚合查询</span></a></h3><p>对应的 SQL 语句是：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span><span class="token punctuation">,</span> max_value<span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span>T00:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span>T23:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span><span class="token number">1</span>d<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>这条查询的含义是：</p><p>由于用户没有指定滑动步长，滑动步长将会被默认设置为跟时间间隔参数相同，也就是<code>1d</code>。</p><p>上面这个例子的第一个参数是显示窗口参数，决定了最终的显示范围是 [2017-11-01T00:00:00, 2017-11-07T23:00:00)。</p><p>上面这个例子的第二个参数是划分时间轴的时间间隔参数，将<code>1d</code>当作划分间隔，显示窗口参数的起始时间当作分割原点，时间轴即被划分为连续的时间间隔：[0,1d), [1d, 2d), [2d, 3d) 等等。</p><p>然后系统将会用 WHERE 子句中的时间和值过滤条件以及 GROUP BY 语句中的第一个参数作为数据的联合过滤条件，获得满足所有过滤条件的数据（在这个例子里是在 [2017-11-01T00:00:00, 2017-11-07 T23:00:00) 这个时间范围的数据），并把这些数据映射到之前分割好的时间轴中（这个例子里是从 2017-11-01T00:00:00 到 2017-11-07T23:00:00:00 的每一天）</p><p>每个时间间隔窗口内都有数据，SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+----------------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|max_value(root.ln.wf01.wt01.temperature)|
+-----------------------------+-------------------------------+----------------------------------------+
|2017-11-01T00:00:00.000+08:00|                           1440|                                    26.0|
|2017-11-02T00:00:00.000+08:00|                           1440|                                    26.0|
|2017-11-03T00:00:00.000+08:00|                           1440|                                   25.99|
|2017-11-04T00:00:00.000+08:00|                           1440|                                    26.0|
|2017-11-05T00:00:00.000+08:00|                           1440|                                    26.0|
|2017-11-06T00:00:00.000+08:00|                           1440|                                   25.99|
|2017-11-07T00:00:00.000+08:00|                           1380|                                    26.0|
+-----------------------------+-------------------------------+----------------------------------------+
Total line number = 7
It costs 0.024s
</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><h3 id="指定滑动步长的时间区间分组聚合查询" tabindex="-1"><a class="header-anchor" href="#指定滑动步长的时间区间分组聚合查询"><span>指定滑动步长的时间区间分组聚合查询</span></a></h3><p>对应的 SQL 语句是：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span><span class="token punctuation">,</span> max_value<span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</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">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span> <span class="token number">23</span>:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">3</span>h<span class="token punctuation">,</span> <span class="token number">1</span>d<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>这条查询的含义是：</p><p>由于用户指定了滑动步长为<code>1d</code>，GROUP BY 语句执行时将会每次把时间间隔往后移动一天的步长，而不是默认的 3 小时。</p><p>也就意味着，我们想要取从 2017-11-01 到 2017-11-07 每一天的凌晨 0 点到凌晨 3 点的数据。</p><p>上面这个例子的第一个参数是显示窗口参数，决定了最终的显示范围是 [2017-11-01T00:00:00, 2017-11-07T23:00:00)。</p><p>上面这个例子的第二个参数是划分时间轴的时间间隔参数，将<code>3h</code>当作划分间隔，显示窗口参数的起始时间当作分割原点，时间轴即被划分为连续的时间间隔：[2017-11-01T00:00:00, 2017-11-01T03:00:00), [2017-11-02T00:00:00, 2017-11-02T03:00:00), [2017-11-03T00:00:00, 2017-11-03T03:00:00) 等等。</p><p>上面这个例子的第三个参数是每次时间间隔的滑动步长。</p><p>然后系统将会用 WHERE 子句中的时间和值过滤条件以及 GROUP BY 语句中的第一个参数作为数据的联合过滤条件，获得满足所有过滤条件的数据（在这个例子里是在 [2017-11-01T00:00:00, 2017-11-07 T23:00:00) 这个时间范围的数据），并把这些数据映射到之前分割好的时间轴中（这个例子里是从 2017-11-01T00:00:00 到 2017-11-07T23:00:00:00 的每一天的凌晨 0 点到凌晨 3 点）</p><p>每个时间间隔窗口内都有数据，SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+----------------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|max_value(root.ln.wf01.wt01.temperature)|
+-----------------------------+-------------------------------+----------------------------------------+
|2017-11-01T00:00:00.000+08:00|                            180|                                   25.98|
|2017-11-02T00:00:00.000+08:00|                            180|                                   25.98|
|2017-11-03T00:00:00.000+08:00|                            180|                                   25.96|
|2017-11-04T00:00:00.000+08:00|                            180|                                   25.96|
|2017-11-05T00:00:00.000+08:00|                            180|                                    26.0|
|2017-11-06T00:00:00.000+08:00|                            180|                                   25.85|
|2017-11-07T00:00:00.000+08:00|                            180|                                   25.99|
+-----------------------------+-------------------------------+----------------------------------------+
Total line number = 7
It costs 0.006s
</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>滑动步长可以小于聚合窗口，此时聚合窗口之间有重叠时间（类似于一个滑动窗口）。</p><p>例如 SQL：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span><span class="token punctuation">,</span> max_value<span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</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">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span> <span class="token number">10</span>:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">4</span>h<span class="token punctuation">,</span> <span class="token number">2</span>h<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+----------------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|max_value(root.ln.wf01.wt01.temperature)|
+-----------------------------+-------------------------------+----------------------------------------+
|2017-11-01T00:00:00.000+08:00|                            180|                                   25.98|
|2017-11-01T02:00:00.000+08:00|                            180|                                   25.98|
|2017-11-01T04:00:00.000+08:00|                            180|                                   25.96|
|2017-11-01T06:00:00.000+08:00|                            180|                                   25.96|
|2017-11-01T08:00:00.000+08:00|                            180|                                    26.0|
+-----------------------------+-------------------------------+----------------------------------------+
Total line number = 5
It costs 0.006s
</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></div><h3 id="按照自然月份的时间区间分组聚合查询" tabindex="-1"><a class="header-anchor" href="#按照自然月份的时间区间分组聚合查询"><span>按照自然月份的时间区间分组聚合查询</span></a></h3><p>对应的 SQL 语句是：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">where</span> <span class="token keyword">time</span> <span class="token operator">&gt;</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span>T01:<span class="token number">00</span>:<span class="token number">00</span> <span class="token keyword">group</span> <span class="token keyword">by</span><span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span>T00:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">,</span> <span class="token number">2019</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span>T23:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">1</span>mo<span class="token punctuation">,</span> <span class="token number">2</span>mo<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>这条查询的含义是：</p><p>由于用户指定了滑动步长为<code>2mo</code>，GROUP BY 语句执行时将会每次把时间间隔往后移动 2 个自然月的步长，而不是默认的 1 个自然月。</p><p>也就意味着，我们想要取从 2017-11-01 到 2019-11-07 每 2 个自然月的第一个月的数据。</p><p>上面这个例子的第一个参数是显示窗口参数，决定了最终的显示范围是 [2017-11-01T00:00:00, 2019-11-07T23:00:00)。</p><p>起始时间为 2017-11-01T00:00:00，滑动步长将会以起始时间作为标准按月递增，取当月的 1 号作为时间间隔的起始时间。</p><p>上面这个例子的第二个参数是划分时间轴的时间间隔参数，将<code>1mo</code>当作划分间隔，显示窗口参数的起始时间当作分割原点，时间轴即被划分为连续的时间间隔：[2017-11-01T00:00:00, 2017-12-01T00:00:00), [2018-02-01T00:00:00, 2018-03-01T00:00:00), [2018-05-03T00:00:00, 2018-06-01T00:00:00) 等等。</p><p>上面这个例子的第三个参数是每次时间间隔的滑动步长。</p><p>然后系统将会用 WHERE 子句中的时间和值过滤条件以及 GROUP BY 语句中的第一个参数作为数据的联合过滤条件，获得满足所有过滤条件的数据（在这个例子里是在 [2017-11-01T00:00:00, 2019-11-07T23:00:00) 这个时间范围的数据），并把这些数据映射到之前分割好的时间轴中（这个例子里是从 2017-11-01T00:00:00 到 2019-11-07T23:00:00:00 的每两个自然月的第一个月）</p><p>每个时间间隔窗口内都有数据，SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|
+-----------------------------+-------------------------------+
|2017-11-01T00:00:00.000+08:00|                            259|
|2018-01-01T00:00:00.000+08:00|                            250|
|2018-03-01T00:00:00.000+08:00|                            259|
|2018-05-01T00:00:00.000+08:00|                            251|
|2018-07-01T00:00:00.000+08:00|                            242|
|2018-09-01T00:00:00.000+08:00|                            225|
|2018-11-01T00:00:00.000+08:00|                            216|
|2019-01-01T00:00:00.000+08:00|                            207|
|2019-03-01T00:00:00.000+08:00|                            216|
|2019-05-01T00:00:00.000+08:00|                            207|
|2019-07-01T00:00:00.000+08:00|                            199|
|2019-09-01T00:00:00.000+08:00|                            181|
|2019-11-01T00:00:00.000+08:00|                             60|
+-----------------------------+-------------------------------+
</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></div><p>对应的 SQL 语句是：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span><span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">10</span><span class="token operator">-</span><span class="token number">31</span>T00:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">,</span> <span class="token number">2019</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span>T23:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">1</span>mo<span class="token punctuation">,</span> <span class="token number">2</span>mo<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>这条查询的含义是：</p><p>由于用户指定了滑动步长为<code>2mo</code>，GROUP BY 语句执行时将会每次把时间间隔往后移动 2 个自然月的步长，而不是默认的 1 个自然月。</p><p>也就意味着，我们想要取从 2017-10-31 到 2019-11-07 每 2 个自然月的第一个月的数据。</p><p>与上述示例不同的是起始时间为 2017-10-31T00:00:00，滑动步长将会以起始时间作为标准按月递增，取当月的 31 号（即最后一天）作为时间间隔的起始时间。若起始时间设置为 30 号，滑动步长会将时间间隔的起始时间设置为当月 30 号，若不存在则为最后一天。</p><p>上面这个例子的第一个参数是显示窗口参数，决定了最终的显示范围是 [2017-10-31T00:00:00, 2019-11-07T23:00:00)。</p><p>上面这个例子的第二个参数是划分时间轴的时间间隔参数，将<code>1mo</code>当作划分间隔，显示窗口参数的起始时间当作分割原点，时间轴即被划分为连续的时间间隔：[2017-10-31T00:00:00, 2017-11-31T00:00:00), [2018-02-31T00:00:00, 2018-03-31T00:00:00), [2018-05-31T00:00:00, 2018-06-31T00:00:00) 等等。</p><p>上面这个例子的第三个参数是每次时间间隔的滑动步长。</p><p>然后系统将会用 WHERE 子句中的时间和值过滤条件以及 GROUP BY 语句中的第一个参数作为数据的联合过滤条件，获得满足所有过滤条件的数据（在这个例子里是在 [2017-10-31T00:00:00, 2019-11-07T23:00:00) 这个时间范围的数据），并把这些数据映射到之前分割好的时间轴中（这个例子里是从 2017-10-31T00:00:00 到 2019-11-07T23:00:00:00 的每两个自然月的第一个月）</p><p>每个时间间隔窗口内都有数据，SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|
+-----------------------------+-------------------------------+
|2017-10-31T00:00:00.000+08:00|                            251|
|2017-12-31T00:00:00.000+08:00|                            250|
|2018-02-28T00:00:00.000+08:00|                            259|
|2018-04-30T00:00:00.000+08:00|                            250|
|2018-06-30T00:00:00.000+08:00|                            242|
|2018-08-31T00:00:00.000+08:00|                            225|
|2018-10-31T00:00:00.000+08:00|                            216|
|2018-12-31T00:00:00.000+08:00|                            208|
|2019-02-28T00:00:00.000+08:00|                            216|
|2019-04-30T00:00:00.000+08:00|                            208|
|2019-06-30T00:00:00.000+08:00|                            199|
|2019-08-31T00:00:00.000+08:00|                            181|
|2019-10-31T00:00:00.000+08:00|                             69|
+-----------------------------+-------------------------------+
</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></div><h3 id="左开右闭区间" tabindex="-1"><a class="header-anchor" href="#左开右闭区间"><span>左开右闭区间</span></a></h3><p>每个区间的结果时间戳为区间右端点，对应的 SQL 语句是：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">(</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span>T00:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span>T23:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">]</span><span class="token punctuation">,</span><span class="token number">1</span>d<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>这条查询语句的时间区间是左开右闭的，结果中不会包含时间点 2017-11-01 的数据，但是会包含时间点 2017-11-07 的数据。</p><p>SQL 执行后的结果集如下所示：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------------+
|                         Time|count(root.ln.wf01.wt01.status)|
+-----------------------------+-------------------------------+
|2017-11-02T00:00:00.000+08:00|                           1440|
|2017-11-03T00:00:00.000+08:00|                           1440|
|2017-11-04T00:00:00.000+08:00|                           1440|
|2017-11-05T00:00:00.000+08:00|                           1440|
|2017-11-06T00:00:00.000+08:00|                           1440|
|2017-11-07T00:00:00.000+08:00|                           1440|
|2017-11-07T23:00:00.000+08:00|                           1380|
+-----------------------------+-------------------------------+
Total line number = 7
It costs 0.004s
</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><h3 id="与分组聚合混合使用" tabindex="-1"><a class="header-anchor" href="#与分组聚合混合使用"><span>与分组聚合混合使用</span></a></h3><p>通过定义 LEVEL 来统计指定层级下的数据点个数。</p><p>例如：</p><p>统计降采样后的数据点个数</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">(</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">01</span>T00:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span>T23:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">]</span><span class="token punctuation">,</span><span class="token number">1</span>d<span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token keyword">level</span><span class="token operator">=</span><span class="token number">1</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>结果：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------+
|                         Time|COUNT(root.ln.*.*.status)|
+-----------------------------+-------------------------+
|2017-11-02T00:00:00.000+08:00|                     1440|
|2017-11-03T00:00:00.000+08:00|                     1440|
|2017-11-04T00:00:00.000+08:00|                     1440|
|2017-11-05T00:00:00.000+08:00|                     1440|
|2017-11-06T00:00:00.000+08:00|                     1440|
|2017-11-07T00:00:00.000+08:00|                     1440|
|2017-11-07T23:00:00.000+08:00|                     1380|
+-----------------------------+-------------------------+
Total line number = 7
It costs 0.006s
</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>加上滑动 Step 的降采样后的结果也可以汇总</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span>wf01<span class="token punctuation">.</span>wt01 <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</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">00</span><span class="token punctuation">,</span> <span class="token number">2017</span><span class="token operator">-</span><span class="token number">11</span><span class="token operator">-</span><span class="token number">07</span> <span class="token number">23</span>:<span class="token number">00</span>:<span class="token number">00</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">3</span>h<span class="token punctuation">,</span> <span class="token number">1</span>d<span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token keyword">level</span><span class="token operator">=</span><span class="token number">1</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+-------------------------+
|                         Time|COUNT(root.ln.*.*.status)|
+-----------------------------+-------------------------+
|2017-11-01T00:00:00.000+08:00|                      180|
|2017-11-02T00:00:00.000+08:00|                      180|
|2017-11-03T00:00:00.000+08:00|                      180|
|2017-11-04T00:00:00.000+08:00|                      180|
|2017-11-05T00:00:00.000+08:00|                      180|
|2017-11-06T00:00:00.000+08:00|                      180|
|2017-11-07T00:00:00.000+08:00|                      180|
+-----------------------------+-------------------------+
Total line number = 7
It costs 0.004s
</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><h2 id="路径层级分组聚合" tabindex="-1"><a class="header-anchor" href="#路径层级分组聚合"><span>路径层级分组聚合</span></a></h2><p>在时间序列层级结构中，分层聚合查询用于<strong>对某一层级下同名的序列进行聚合查询</strong>。</p><ul><li>使用 <code>GROUP BY LEVEL = INT</code> 来指定需要聚合的层级，并约定 <code>ROOT</code> 为第 0 层。若统计 &quot;root.ln&quot; 下所有序列则需指定 level 为 1。</li><li>分层聚合查询支持使用所有内置聚合函数。对于 <code>sum</code>，<code>avg</code>，<code>min_value</code>， <code>max_value</code>， <code>extreme</code> 五种聚合函数，需保证所有聚合的时间序列数据类型相同。其他聚合函数没有此限制。</li></ul><p><strong>示例1：</strong> 不同 database 下均存在名为 status 的序列， 如 &quot;root.ln.wf01.wt01.status&quot;, &quot;root.ln.wf02.wt02.status&quot;, 以及 &quot;root.sgcc.wf03.wt01.status&quot;, 如果需要统计不同 database 下 status 序列的数据点个数，使用以下查询：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token keyword">level</span> <span class="token operator">=</span> <span class="token number">1</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>运行结果为：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-------------------------+---------------------------+
|count(root.ln.*.*.status)|count(root.sgcc.*.*.status)|
+-------------------------+---------------------------+
|                    20160|                      10080|
+-------------------------+---------------------------+
Total line number = 1
It costs 0.003s
</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></div><p><strong>示例2：</strong> 统计不同设备下 status 序列的数据点个数，可以规定 level = 3，</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token keyword">level</span> <span class="token operator">=</span> <span class="token number">3</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>运行结果为：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+---------------------------+---------------------------+
|count(root.*.*.wt01.status)|count(root.*.*.wt02.status)|
+---------------------------+---------------------------+
|                      20160|                      10080|
+---------------------------+---------------------------+
Total line number = 1
It costs 0.003s
</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></div><p>注意，这时会将 database <code>ln</code> 和 <code>sgcc</code> 下名为 <code>wt01</code> 的设备视为同名设备聚合在一起。</p><p><strong>示例3：</strong> 统计不同 database 下的不同设备中 status 序列的数据点个数，可以使用以下查询：</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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token keyword">status</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token keyword">level</span> <span class="token operator">=</span> <span class="token number">1</span><span class="token punctuation">,</span> <span class="token number">3</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>运行结果为：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+----------------------------+----------------------------+------------------------------+
|count(root.ln.*.wt01.status)|count(root.ln.*.wt02.status)|count(root.sgcc.*.wt01.status)|
+----------------------------+----------------------------+------------------------------+
|                       10080|                       10080|                         10080|
+----------------------------+----------------------------+------------------------------+
Total line number = 1
It costs 0.003s
</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></div><p><strong>示例4：</strong> 查询所有序列下温度传感器 temperature 的最大值，可以使用下列查询语句：</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> max_value<span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token keyword">level</span> <span class="token operator">=</span> <span class="token number">0</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>运行结果：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+---------------------------------+
|max_value(root.*.*.*.temperature)|
+---------------------------------+
|                             26.0|
+---------------------------------+
Total line number = 1
It costs 0.013s
</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></div><p><strong>示例5：</strong> 上面的查询都是针对某一个传感器，特别地，<strong>如果想要查询某一层级下所有传感器拥有的总数据点数，则需要显式规定测点为 <code>*</code></strong></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> <span class="token function">count</span><span class="token punctuation">(</span><span class="token operator">*</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">group</span> <span class="token keyword">by</span> <span class="token keyword">level</span> <span class="token operator">=</span> <span class="token number">2</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>运行结果：</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+----------------------+----------------------+
|count(root.*.wf01.*.*)|count(root.*.wf02.*.*)|
+----------------------+----------------------+
|                 20160|                 20160|
+----------------------+----------------------+
Total line number = 1
It costs 0.013s
</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></div><h2 id="标签分组聚合" tabindex="-1"><a class="header-anchor" href="#标签分组聚合"><span>标签分组聚合</span></a></h2><p>IoTDB 支持通过 <code>GROUP BY TAGS</code> 语句根据时间序列中定义的标签的键值做聚合查询。</p><p>我们先在 IoTDB 中写入如下示例数据，稍后会以这些数据为例介绍标签聚合查询。</p><p>这些是某工厂 <code>factory1</code> 在多个城市的多个车间的设备温度数据， 时间范围为 [1000, 10000)。</p><p>时间序列路径中的设备一级是设备唯一标识。城市信息 <code>city</code> 和车间信息 <code>workshop</code> 则被建模在该设备时间序列的标签中。<br> 其中，设备 <code>d1</code>、<code>d2</code> 在 <code>Beijing</code> 的 <code>w1</code> 车间， <code>d3</code>、<code>d4</code> 在 <code>Beijing</code> 的 <code>w2</code> 车间，<code>d5</code>、<code>d6</code> 在 <code>Shanghai</code> 的 <code>w1</code> 车间，<code>d7</code> 在 <code>Shanghai</code> 的 <code>w2</code> 车间。<br><code>d8</code> 和 <code>d9</code> 设备目前处于调试阶段，还未被分配到具体的城市和车间，所以其相应的标签值为空值。</p><div class="language-sql line-numbers-mode" data-ext="sql" data-title="sql"><pre class="language-sql"><code><span class="token keyword">create</span> <span class="token keyword">database</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d1<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Beijing<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w1<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d2<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Beijing<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w1<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d3<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Beijing<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w2<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d4<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Beijing<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w2<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d5<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Shanghai<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w1<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d6<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Shanghai<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w1<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d7<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span> tags<span class="token punctuation">(</span>city<span class="token operator">=</span>Shanghai<span class="token punctuation">,</span> workshop<span class="token operator">=</span>w2<span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d8<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span><span class="token punctuation">;</span>
<span class="token keyword">create</span> timeseries root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d9<span class="token punctuation">.</span>temperature <span class="token keyword">with</span> datatype<span class="token operator">=</span><span class="token keyword">FLOAT</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d1<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">104.0</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d1<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">104.2</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d1<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">103.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d1<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">104.1</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d2<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">104.4</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d2<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">103.7</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d2<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">103.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d2<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">102.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d3<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">103.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d3<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">103.8</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d3<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">102.7</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d3<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">106.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d4<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">103.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d4<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">102.7</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d4<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">106.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d5<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">112.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d5<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">113.0</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d6<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">113.9</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d6<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">113.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d6<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">112.7</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d6<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">112.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d7<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">101.2</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d7<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">99.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d7<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">100.1</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d7<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">99.8</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d8<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">50.0</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d8<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">52.1</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d8<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">5000</span><span class="token punctuation">,</span> <span class="token number">50.1</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d8<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">7000</span><span class="token punctuation">,</span> <span class="token number">50.5</span><span class="token punctuation">)</span><span class="token punctuation">;</span>

<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d9<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">50.3</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
<span class="token keyword">insert</span> <span class="token keyword">into</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span>d9<span class="token punctuation">(</span><span class="token keyword">time</span><span class="token punctuation">,</span> temperature<span class="token punctuation">)</span> <span class="token keyword">values</span><span class="token punctuation">(</span><span class="token number">3000</span><span class="token punctuation">,</span> <span class="token number">52.1</span><span class="token punctuation">)</span><span class="token punctuation">;</span>
</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 class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="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="单标签聚合查询" tabindex="-1"><a class="header-anchor" href="#单标签聚合查询"><span>单标签聚合查询</span></a></h3><p>用户想统计该工厂每个地区的设备的温度的平均值，可以使用如下查询语句</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> <span class="token function">AVG</span><span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">FROM</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">GROUP</span> <span class="token keyword">BY</span> TAGS<span class="token punctuation">(</span>city<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>该查询会将具有同一个 <code>city</code> 标签值的时间序列的所有满足查询条件的点做平均值计算，计算结果如下</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+--------+------------------+
|    city|  avg(temperature)|
+--------+------------------+
| Beijing|104.04666697184244|
|Shanghai|107.85000076293946|
|    NULL| 50.84999910990397|
+--------+------------------+
Total line number = 3
It costs 0.231s
</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>从结果集中可以看到，和时间区间聚合、按层次聚合相比，标签聚合的查询结果的不同点是：</p><ol><li>标签聚合查询的聚合结果不会再做去星号展开，而是将多个时间序列的数据作为一个整体进行聚合计算。</li><li>标签聚合查询除了输出聚合结果列，还会输出聚合标签的键值列。该列的列名为聚合指定的标签键，列的值则为所有查询的时间序列中出现的该标签的值。<br> 如果某些时间序列未设置该标签，则在键值列中有一行单独的 <code>NULL</code> ，代表未设置标签的所有时间序列数据的聚合结果。</li></ol><h3 id="多标签聚合查询" tabindex="-1"><a class="header-anchor" href="#多标签聚合查询"><span>多标签聚合查询</span></a></h3><p>除了基本的单标签聚合查询外，还可以按顺序指定多个标签进行聚合计算。</p><p>例如，用户想统计每个城市的每个车间内设备的平均温度。但因为各个城市的车间名称有可能相同，所以不能直接按照 <code>workshop</code> 做标签聚合。必须要先按照城市，再按照车间处理。</p><p>SQL 语句如下</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> <span class="token function">avg</span><span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">FROM</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">GROUP</span> <span class="token keyword">BY</span> TAGS<span class="token punctuation">(</span>city<span class="token punctuation">,</span> workshop<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>查询结果如下</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+--------+--------+------------------+
|    city|workshop|  avg(temperature)|
+--------+--------+------------------+
|    NULL|    NULL| 50.84999910990397|
|Shanghai|      w1|113.01666768391927|
| Beijing|      w2| 104.4000004359654|
|Shanghai|      w2|100.10000038146973|
| Beijing|      w1|103.73750019073486|
+--------+--------+------------------+
Total line number = 5
It costs 0.027s
</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></div><p>从结果集中可以看到，和单标签聚合相比，多标签聚合的查询结果会根据指定的标签顺序，输出相应标签的键值列。</p><h3 id="基于时间区间的标签聚合查询" tabindex="-1"><a class="header-anchor" href="#基于时间区间的标签聚合查询"><span>基于时间区间的标签聚合查询</span></a></h3><p>按照时间区间聚合是时序数据库中最常用的查询需求之一。IoTDB 在基于时间区间的聚合基础上，支持进一步按照标签进行聚合查询。</p><p>例如，用户想统计时间 <code>[1000, 10000)</code> 范围内，每个城市每个车间中的设备每 5 秒内的平均温度。</p><p>SQL 语句如下</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> <span class="token function">AVG</span><span class="token punctuation">(</span>temperature<span class="token punctuation">)</span> <span class="token keyword">FROM</span> root<span class="token punctuation">.</span>factory1<span class="token punctuation">.</span><span class="token operator">*</span><span class="token operator">*</span> <span class="token keyword">GROUP</span> <span class="token keyword">BY</span> <span class="token punctuation">(</span><span class="token punctuation">[</span><span class="token number">1000</span><span class="token punctuation">,</span> <span class="token number">10000</span><span class="token punctuation">)</span><span class="token punctuation">,</span> <span class="token number">5</span>s<span class="token punctuation">)</span><span class="token punctuation">,</span> TAGS<span class="token punctuation">(</span>city<span class="token punctuation">,</span> workshop<span class="token punctuation">)</span><span class="token punctuation">;</span>
</code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>查询结果如下</p><div class="language-text line-numbers-mode" data-ext="text" data-title="text"><pre class="language-text"><code>+-----------------------------+--------+--------+------------------+
|                         Time|    city|workshop|  avg(temperature)|
+-----------------------------+--------+--------+------------------+
|1970-01-01T08:00:01.000+08:00|    NULL|    NULL| 50.91999893188476|
|1970-01-01T08:00:01.000+08:00|Shanghai|      w1|113.20000076293945|
|1970-01-01T08:00:01.000+08:00| Beijing|      w2|             103.4|
|1970-01-01T08:00:01.000+08:00|Shanghai|      w2| 100.1999994913737|
|1970-01-01T08:00:01.000+08:00| Beijing|      w1|103.81666692097981|
|1970-01-01T08:00:06.000+08:00|    NULL|    NULL|              50.5|
|1970-01-01T08:00:06.000+08:00|Shanghai|      w1| 112.6500015258789|
|1970-01-01T08:00:06.000+08:00| Beijing|      w2| 106.9000015258789|
|1970-01-01T08:00:06.000+08:00|Shanghai|      w2| 99.80000305175781|
|1970-01-01T08:00:06.000+08:00| Beijing|      w1|             103.5|
+-----------------------------+--------+--------+------------------+
</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>和标签聚合相比，基于时间区间的标签聚合的查询会首先按照时间区间划定聚合范围，在时间区间内部再根据指定的标签顺序，进行相应数据的聚合计算。在输出的结果集中，会包含一列时间列，该时间列值的含义和时间区间聚合查询的相同。</p><h3 id="标签聚合查询的限制" tabindex="-1"><a class="header-anchor" href="#标签聚合查询的限制"><span>标签聚合查询的限制</span></a></h3><p>由于标签聚合功能仍然处于开发阶段，目前有如下未实现功能。</p><blockquote><ol><li>暂不支持 <code>HAVING</code> 子句过滤查询结果。</li><li>暂不支持结果按照标签值排序。</li><li>暂不支持 <code>LIMIT</code>，<code>OFFSET</code>，<code>SLIMIT</code>，<code>SOFFSET</code>。</li><li>暂不支持 <code>ALIGN BY DEVICE</code>。</li><li>暂不支持聚合函数内部包含表达式，例如 <code>count(s+1)</code>。</li><li>不支持值过滤条件聚合，和分层聚合查询行为保持一致。</li></ol></blockquote></div><!--[--><!----><!--]--><footer class="vp-page-meta"><div class="vp-meta-item edit-link"><a href="https://github.com/apache/iotdb-docs/edit/main/src/zh/UserGuide/V1.0.x/Query-Data/Group-By.md" rel="noopener noreferrer" target="_blank" aria-label="发现错误？在 GitHub 上编辑此页" class="nav-link vp-meta-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="vp-meta-item git-info"><div class="update-time"><span class="vp-meta-label">上次编辑于: </span><!----></div><!----></div></footer><nav class="vp-page-nav"><a class="route-link nav-link prev" href="/zh/UserGuide/V1.0.x/Query-Data/Where-Condition.html" aria-label="查询过滤条件"><div class="hint"><span class="arrow start"></span>上一页</div><div class="link"><!---->查询过滤条件</div></a><a class="route-link nav-link next" href="/zh/UserGuide/V1.0.x/Query-Data/Having-Condition.html" aria-label="聚合结果过滤"><div class="hint">下一页<span class="arrow end"></span></div><div class="link">聚合结果过滤<!----></div></a></nav><!----><!--[--><!----><!--]--><!--]--></main><!--]--><footer style="padding-bottom:2rem;"><span id="doc-version" style="display:none;">rel/1.0</span><p style="text-align:center;color:#909399;font-size:12px;margin:0 30px;">Copyright © 2024 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></footer></div><!--]--><!--]--><!--[--><!----><!--]--><!--]--></div>
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