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| GitHub |
| <span><svg 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" class="icon outbound"><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="sr-only">(opens new window)</span></span></a></nav> <ul class="sidebar-links"><li><section class="sidebar-group depth-0"><p class="sidebar-heading"><span>IoTDB用户手册 (V0.12.x)</span> <!----></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>IoTDB简介</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>快速上手</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>数据模式与概念</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>SQL命令行终端(CLI)</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>权限管理</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading open"><span>IoTDB-SQL 语言</span> <span class="arrow down"></span></p> <ul class="sidebar-links sidebar-group-items"><li><a href="/zh/UserGuide/V0.12.x/IoTDB-SQL-Language/DDL-Data-Definition-Language.html" class="sidebar-link">数据定义语言（DDL）</a></li><li><a href="/zh/UserGuide/V0.12.x/IoTDB-SQL-Language/DML-Data-Manipulation-Language.html" aria-current="page" class="active sidebar-link">数据操作语言（DML）</a></li><li><a href="/zh/UserGuide/V0.12.x/IoTDB-SQL-Language/Maintenance-Command.html" class="sidebar-link">运维命令</a></li></ul></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>应用编程接口</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>用户定义函数(UDF)</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>通信服务协议</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>系统工具</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>端云协同</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>系统集成</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>集群搭建</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>常见问题</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>附录</span> <span class="arrow right"></span></p> <!----></section></li></ul> </aside> <main class="page"> <div class="content content__default"><h2 id="数据操作语言-dml"><a href="#数据操作语言-dml" class="header-anchor">#</a> 数据操作语言（DML）</h2> <h3 id="数据写入"><a href="#数据写入" class="header-anchor">#</a> 数据写入</h3> <p>IoTDB为用户提供多种插入实时数据的方式，例如在<a href="/zh/UserGuide/V0.12.x/CLI/Command-Line-Interface.html">Cli/Shell工具</a>中直接输入插入数据的INSERT语句，或使用Java API（标准<a href="/zh/UserGuide/V0.12.x/API/Programming-JDBC.html">Java JDBC</a>接口）单条或批量执行插入数据的INSERT语句。</p> <p>本节主要为您介绍实时数据接入的INSERT语句在场景中的实际使用示例，有关INSERT SQL语句的详细语法请参见本文<a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">INSERT语句</a>节。</p> <h4 id="使用insert语句"><a href="#使用insert语句" class="header-anchor">#</a> 使用INSERT语句</h4> <p>使用INSERT语句可以向指定的已经创建的一条或多条时间序列中插入数据。对于每一条数据，均由一个时间戳类型的时间戳和一个数值或布尔值、字符串类型的传感器采集值组成。</p> <p>在本节的场景实例下，以其中的两个时间序列<code>root.ln.wf02.wt02.status</code>和<code>root.ln.wf02.wt02.hardware</code>为例 ，它们的数据类型分别为BOOLEAN和TEXT。</p> <p>单列数据插入示例代码如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB > insert into root.ln.wf02.wt02(timestamp,status) values(1,true) |
| IoTDB > insert into root.ln.wf02.wt02(timestamp,hardware) values(1, "v1") |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>以上示例代码将长整型的timestamp以及值为true的数据插入到时间序列<code>root.ln.wf02.wt02.status</code>中和将长整型的timestamp以及值为”v1”的数据插入到时间序列<code>root.ln.wf02.wt02.hardware</code>中。执行成功后会返回执行时间，代表数据插入已完成。</p> <blockquote><p>注意：在IoTDB中，TEXT类型的数据单双引号都可以来表示,上面的插入语句是用的是双引号表示TEXT类型数据，下面的示例将使用单引号表示TEXT类型数据。</p></blockquote> <p>INSERT语句还可以支持在同一个时间点下多列数据的插入，同时向2时间点插入上述两个时间序列的值，多列数据插入示例代码如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB > insert into root.ln.wf02.wt02(timestamp, status, hardware) VALUES (2, false, 'v2') |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>插入数据后我们可以使用SELECT语句简单查询已插入的数据。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB > select * from root.ln.wf02 where time < 3 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果如图所示。由查询结果可以看出，单列、多列数据的插入操作正确执行。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------------------+------------------------+ |
| | Time|root.ln.wf02.wt02.hardware|root.ln.wf02.wt02.status| |
| +-----------------------------+--------------------------+------------------------+ |
| |1970-01-01T08:00:00.001+08:00| v1| true| |
| |1970-01-01T08:00:00.002+08:00| v2| false| |
| +-----------------------------+--------------------------+------------------------+ |
| Total line number = 2 |
| It costs 0.170s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br></div></div><h3 id="数据查询"><a href="#数据查询" class="header-anchor">#</a> 数据查询</h3> <h4 id="时间条件过滤查询"><a href="#时间条件过滤查询" class="header-anchor">#</a> 时间条件过滤查询</h4> <p>本节主要介绍时间切片查询的相关示例，主要使用的是<a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">IoTDB SELECT语句</a>。同时，您也可以使用<a href="/zh/UserGuide/V0.12.x/API/Programming-JDBC.html">Java JDBC</a>标准接口来执行相关的查询语句。</p> <ul><li>根据一个时间区间选择一列数据</li></ul> <p>SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select temperature from root.ln.wf01.wt01 where time < 2017-11-01T00:08:00.000 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>其含义为：</p> <p>被选择的设备为ln集团wf01子站wt01设备；被选择的时间序列为温度传感器（temperature）；该语句要求选择出该设备在“2017-11-01T00:08:00.000”（此处可以使用多种时间格式，详情可参看<a href="/zh/UserGuide/V0.12.x/Data-Concept/Data-Model-and-Terminology.html">2.1节</a>）时间点以前的所有温度传感器的值。</p> <p>该SQL语句的执行结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.temperature| |
| +-----------------------------+-----------------------------+ |
| |2017-11-01T00:00:00.000+08:00| 25.96| |
| |2017-11-01T00:01:00.000+08:00| 24.36| |
| |2017-11-01T00:02:00.000+08:00| 20.09| |
| |2017-11-01T00:03:00.000+08:00| 20.18| |
| |2017-11-01T00:04:00.000+08:00| 21.13| |
| |2017-11-01T00:05:00.000+08:00| 22.72| |
| |2017-11-01T00:06:00.000+08:00| 20.71| |
| |2017-11-01T00:07:00.000+08:00| 21.45| |
| +-----------------------------+-----------------------------+ |
| Total line number = 8 |
| It costs 0.026s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br></div></div><ul><li>根据一个时间区间选择多列数据</li></ul> <p>SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status, temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>其含义为：</p> <p>被选择的设备为ln集团wf01子站wt01设备；被选择的时间序列为供电状态（status）和温度传感器（temperature）；该语句要求选择出“2017-11-01T00:05:00.000”至“2017-11-01T00:12:00.000”之间的所选时间序列的值。</p> <p>该SQL语句的执行结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| |2017-11-01T00:08:00.000+08:00| false| 22.58| |
| |2017-11-01T00:09:00.000+08:00| false| 20.98| |
| |2017-11-01T00:10:00.000+08:00| true| 25.52| |
| |2017-11-01T00:11:00.000+08:00| false| 22.91| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 6 |
| It costs 0.018s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br></div></div><ul><li>按照多个时间区间选择同一设备的多列数据</li></ul> <p>IoTDB支持在一次查询中指定多个时间区间条件，用户可以根据需求随意组合时间区间条件。例如，</p> <p>SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where (time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000) or (time >= 2017-11-01T16:35:00.000 and time <= 2017-11-01T16:37:00.000); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>其含义为：</p> <p>被选择的设备为ln集团wf01子站wt01设备；被选择的时间序列为“供电状态（status）”和“温度传感器（temperature）”；该语句指定了两个不同的时间区间，分别为“2017-11-01T00:05:00.000至2017-11-01T00:12:00.000”和“2017-11-01T16:35:00.000至2017-11-01T16:37:00.000”；该语句要求选择出满足任一时间区间的被选时间序列的值。</p> <p>该SQL语句的执行结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| |2017-11-01T00:08:00.000+08:00| false| 22.58| |
| |2017-11-01T00:09:00.000+08:00| false| 20.98| |
| |2017-11-01T00:10:00.000+08:00| true| 25.52| |
| |2017-11-01T00:11:00.000+08:00| false| 22.91| |
| |2017-11-01T16:35:00.000+08:00| true| 23.44| |
| |2017-11-01T16:36:00.000+08:00| false| 21.98| |
| |2017-11-01T16:37:00.000+08:00| false| 21.93| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 9 |
| It costs 0.018s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br></div></div><ul><li>按照多个时间区间选择不同设备的多列数据</li></ul> <p>该系统支持在一次查询中选择任意列的数据，也就是说，被选择的列可以来源于不同的设备。例如，SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select wf01.wt01.status,wf02.wt02.hardware from root.ln where (time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000) or (time >= 2017-11-01T16:35:00.000 and time <= 2017-11-01T16:37:00.000); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>其含义为：</p> <p>被选择的时间序列为“ln集团wf01子站wt01设备的供电状态”以及“ln集团wf02子站wt02设备的硬件版本”；该语句指定了两个时间区间，分别为“2017-11-01T00:05:00.000至2017-11-01T00:12:00.000”和“2017-11-01T16:35:00.000至2017-11-01T16:37:00.000”；该语句要求选择出满足任意时间区间的被选时间序列的值。</p> <p>该SQL语句的执行结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+--------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf02.wt02.hardware| |
| +-----------------------------+------------------------+--------------------------+ |
| |2017-11-01T00:06:00.000+08:00| false| v1| |
| |2017-11-01T00:07:00.000+08:00| false| v1| |
| |2017-11-01T00:08:00.000+08:00| false| v1| |
| |2017-11-01T00:09:00.000+08:00| false| v1| |
| |2017-11-01T00:10:00.000+08:00| true| v2| |
| |2017-11-01T00:11:00.000+08:00| false| v1| |
| |2017-11-01T16:35:00.000+08:00| true| v2| |
| |2017-11-01T16:36:00.000+08:00| false| v1| |
| |2017-11-01T16:37:00.000+08:00| false| v1| |
| +-----------------------------+------------------------+--------------------------+ |
| Total line number = 9 |
| It costs 0.014s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br></div></div><h4 id="其他结果对齐方式"><a href="#其他结果对齐方式" class="header-anchor">#</a> 其他结果对齐方式</h4> <ul><li>根据时间降序返回 |
| IoTDB 在 0.11 版本开始支持 'order by time' 语句, 用于对结果按照时间进行降序展示。例如，SQL语句为：</li></ul> <div class="language-sql line-numbers-mode"><pre class="language-sql"><code><span class="token keyword">select</span> <span class="token operator">*</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>ln <span class="token keyword">where</span> <span class="token keyword">time</span> <span class="token operator">></span> <span class="token number">1</span> <span class="token keyword">order</span> <span class="token keyword">by</span> <span class="token keyword">time</span> <span class="token keyword">desc</span> <span class="token keyword">limit</span> <span class="token number">10</span><span class="token punctuation">;</span> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>语句执行的结果为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------------------+------------------------+-----------------------------+------------------------+ |
| | Time|root.ln.wf02.wt02.hardware|root.ln.wf02.wt02.status|root.ln.wf01.wt01.temperature|root.ln.wf01.wt01.status| |
| +-----------------------------+--------------------------+------------------------+-----------------------------+------------------------+ |
| |2017-11-07T23:59:00.000+08:00| v1| false| 21.07| false| |
| |2017-11-07T23:58:00.000+08:00| v1| false| 22.93| false| |
| |2017-11-07T23:57:00.000+08:00| v2| true| 24.39| true| |
| |2017-11-07T23:56:00.000+08:00| v2| true| 24.44| true| |
| |2017-11-07T23:55:00.000+08:00| v2| true| 25.9| true| |
| |2017-11-07T23:54:00.000+08:00| v1| false| 22.52| false| |
| |2017-11-07T23:53:00.000+08:00| v2| true| 24.58| true| |
| |2017-11-07T23:52:00.000+08:00| v1| false| 20.18| false| |
| |2017-11-07T23:51:00.000+08:00| v1| false| 22.24| false| |
| |2017-11-07T23:50:00.000+08:00| v2| true| 23.7| true| |
| +-----------------------------+--------------------------+------------------------+-----------------------------+------------------------+ |
| Total line number = 10 |
| It costs 0.016s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br></div></div><p>更多语法请参照 <a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">SQL REFERENCE</a>.</p> <ul><li>IoTDB支持另外两种结果返回形式: 按设备时间对齐 'align by device' 和 时序不对齐 'disable align'.</li></ul> <p>'align by device' 对齐方式下，设备ID会单独作为一列出现。在 select 子句中写了多少列，最终结果就会有该列数+2 （时间列和设备名字列）。SQL形如:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.* where time <= 2017-11-01T00:01:00 align by device |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------+-----------+------+--------+ |
| | Time| Device|temperature|status|hardware| |
| +-----------------------------+-----------------+-----------+------+--------+ |
| |2017-11-01T00:00:00.000+08:00|root.ln.wf01.wt01| 25.96| true| null| |
| |2017-11-01T00:01:00.000+08:00|root.ln.wf01.wt01| 24.36| true| null| |
| |1970-01-01T08:00:00.001+08:00|root.ln.wf02.wt02| null| true| v1| |
| |1970-01-01T08:00:00.002+08:00|root.ln.wf02.wt02| null| false| v2| |
| |2017-11-01T00:00:00.000+08:00|root.ln.wf02.wt02| null| true| v2| |
| |2017-11-01T00:01:00.000+08:00|root.ln.wf02.wt02| null| true| v2| |
| +-----------------------------+-----------------+-----------+------+--------+ |
| Total line number = 6 |
| It costs 0.012s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br></div></div><p>'disable align' 意味着每条时序就有 2 列存在。Disable Align只能用于查询语句句尾，不能用于聚合查询、Fill语句、Group by或Group by device语句，但可用于Limit语句。结果显示若无数据显示为空白。</p> <p>SQL形如:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.* where time <= 2017-11-01T00:01:00 disable align |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------------------+-----------------------------+------------------------+-----------------------------+-----------------------------+-----------------------------+------------------------+ |
| | Time|root.ln.wf02.wt02.hardware| Time|root.ln.wf02.wt02.status| Time|root.ln.wf01.wt01.temperature| Time|root.ln.wf01.wt01.status| |
| +-----------------------------+--------------------------+-----------------------------+------------------------+-----------------------------+-----------------------------+-----------------------------+------------------------+ |
| |1970-01-01T08:00:00.001+08:00| v1|1970-01-01T08:00:00.001+08:00| true|2017-11-01T00:00:00.000+08:00| 25.96|2017-11-01T00:00:00.000+08:00| true| |
| |1970-01-01T08:00:00.002+08:00| v2|1970-01-01T08:00:00.002+08:00| false|2017-11-01T00:01:00.000+08:00| 24.36|2017-11-01T00:01:00.000+08:00| true| |
| |2017-11-01T00:00:00.000+08:00| v2|2017-11-01T00:00:00.000+08:00| true| null| null| null| null| |
| |2017-11-01T00:01:00.000+08:00| v2|2017-11-01T00:01:00.000+08:00| true| null| null| null| null| |
| +-----------------------------+--------------------------+-----------------------------+------------------------+-----------------------------+-----------------------------+-----------------------------+------------------------+ |
| Total line number = 4 |
| It costs 0.018s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br></div></div><p>更多语法请参照<a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">SQL REFERENCE</a>。</p> <h4 id="结果空值过滤"><a href="#结果空值过滤" class="header-anchor">#</a> 结果空值过滤</h4> <ul><li>如果结果集中，任意一列为null，则过滤掉该行；即获得的结果集不包含任何空值</li></ul> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.* where time <= 2017-11-01T00:01:00 WITHOUT NULL ANY |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><ul><li>在降采样查询中，如果结果集的某一行所有列都为null，则过滤掉该行；即获得的结果集不包含所有值都为null的行</li></ul> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.* where time <= 2017-11-01T00:01:00 WITHOUT NULL ALL |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><h4 id="聚合函数"><a href="#聚合函数" class="header-anchor">#</a> 聚合函数</h4> <p>本章节主要介绍聚合查询的相关示例， |
| 主要使用的是IoTDB SELECT语句的聚合查询函数。</p> <ul><li>统计总点数</li></ul> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-------------------------------+ |
| |count(root.ln.wf01.wt01.status)| |
| +-------------------------------+ |
| | 10080| |
| +-------------------------------+ |
| Total line number = 1 |
| It costs 0.016s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><h4 id="时间区间分组聚合"><a href="#时间区间分组聚合" class="header-anchor">#</a> 时间区间分组聚合</h4> <p>本章节主要介绍时间区间分组聚合查询的相关示例， |
| 主要使用的是IoTDB SELECT语句的<a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">GROUP BY子句</a>， |
| 该子句是IoTDB中用于根据用户给定划分条件对结果集进行划分，并对已划分的结果集进行聚合计算的语句。 |
| IoTDB支持根据时间间隔和自定义的滑动步长（默认值与时间间隔相同，自定义的值必须大于等于时间间隔）对结果集进行划分，默认结果按照时间升序排列。 |
| 同时，您也可以使用Java JDBC标准接口来执行相关的查询语句。</p> <p>GROUP BY语句为用户提供三类指定参数：</p> <ul><li>参数1：时间轴显示时间窗参数</li> <li>参数2：划分时间轴的时间间隔参数（必须为正数）</li> <li>参数3：滑动步长（可选参数，默认值与时间间隔相同，自定义的值必须大于等于时间间隔）</li></ul> <p>三类参数的实际含义已经在下图中指出，这三类参数里，第三个参数是可选的。 |
| 接下来，我们将给出三种典型的降频聚合查询的例子： |
| 滑动步长未指定， |
| 指定滑动步长， |
| 带值过滤条件。</p> <img src="https://user-images.githubusercontent.com/16079446/69109512-f808bc80-0ab2-11ea-9e4d-b2b2f58fb474.png" style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;"> <ul><li>未指定滑动步长的降频聚合查询</li></ul> <p>对应的SQL语句是:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status), max_value(temperature) from root.ln.wf01.wt01 group by ([2017-11-01T00:00:00, 2017-11-07T23:00:00),1d); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></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- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></div></div><ul><li>指定滑动步长的时间区间分组聚合查询</li></ul> <p>对应的SQL语句是:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status), max_value(temperature) from root.ln.wf01.wt01 group by ([2017-11-01 00:00:00, 2017-11-07 23:00:00), 3h, 1d); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></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- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></div></div><ul><li>按照自然月份的时间区间分组聚合查询</li></ul> <p>对应的SQL语句是:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01 where time > 2017-11-01T01:00:00 group by([2017-11-01T00:00:00, 2019-11-07T23:00:00), 1mo, 2mo); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></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- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br><span class="line-number">17</span><br></div></div><p>对应的SQL语句是:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01 group by([2017-10-31T00:00:00, 2019-11-07T23:00:00), 1mo, 2mo); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></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- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br><span class="line-number">17</span><br></div></div><ul><li>左开右闭区间</li></ul> <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- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01 group by ((2017-11-01T00:00:00, 2017-11-07T23:00:00],1d); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></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- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></div></div><h4 id="路径层级分组聚合"><a href="#路径层级分组聚合" class="header-anchor">#</a> 路径层级分组聚合</h4> <p>在时间序列层级结构中，分层聚合查询用于对某一层级进行聚合查询。 |
| 这里使用LEVEL来统计指定层级下的聚合范围，该语句约定root为第0层序列，若统计"root.ln"下所有序列则需指定level为1。</p> <p>例如：在"root.ln.wf01"下存在多个子序列：wt01，wt02，wt03等均有名为status的序列， |
| 如果需要统计这些子序列的status包含的点个数，使用以下查询:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.* group by level=2 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>运行结果为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+----------------------------+ |
| |count(root.ln.wf01.*.status)| |
| +----------------------------+ |
| | 10080| |
| +----------------------------+ |
| Total line number = 1 |
| It costs 0.003s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>假设此时添加两条序列，"root.ln.wf01.wt01.temperature" and "root.ln.wf02.wt01.temperature"。 |
| 需要同时查询"root.ln.*.*.temperature"在第二层级的count聚合结果和sum聚合结果，可以使用下列查询语句：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(temperature), sum(temperature) from root.ln.*.* group by level=2 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>运行结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+---------------------------------+---------------------------------+-------------------------------+-------------------------------+ |
| |count(root.ln.wf02.*.temperature)|count(root.ln.wf01.*.temperature)|sum(root.ln.wf02.*.temperature)|sum(root.ln.wf01.*.temperature)| |
| +---------------------------------+---------------------------------+-------------------------------+-------------------------------+ |
| | 8| 4| 228.0| 91.83000183105469| |
| +---------------------------------+---------------------------------+-------------------------------+-------------------------------+ |
| Total line number = 1 |
| It costs 0.013s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>若统计"root.ln.*.*"下第一层级的count聚合结果和sum聚合结果，则设置level=1即可:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(temperature), sum(temperature) from root.ln.*.* group by level=1 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>运行结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+------------------------------+----------------------------+ |
| |count(root.ln.*.*.temperature)|sum(root.ln.*.*.temperature)| |
| +------------------------------+----------------------------+ |
| | 12| 319.8300018310547| |
| +------------------------------+----------------------------+ |
| Total line number = 1 |
| It costs 0.013s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>分层聚合查询也可被用于其他聚合函数，当前所支持的聚合函数为：count, sum, avg, last_value, first_value, min_time, max_time, min_value, max_value, extreme</p> <p>对于sum, avg, min_value, max_value, extreme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。</p> <h4 id="时间区间和路径层级分组聚合查询"><a href="#时间区间和路径层级分组聚合查询" class="header-anchor">#</a> 时间区间和路径层级分组聚合查询</h4> <p>除此之外，还可以通过定义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- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01 group by ((2017-11-01T00:00:00, 2017-11-07T23:00:00],1d), level=1; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></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- line-numbers-mode"><pre class="language-text"><code>select count(status) from root.ln.wf01.wt01 group by ([0,20),2ms,3ms), level=1; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><div class="language- line-numbers-mode"><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-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></div></div><h4 id="最新点查询"><a href="#最新点查询" class="header-anchor">#</a> 最新点查询</h4> <p>SQL语法：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select last <Path> [COMMA <Path>]* from < PrefixPath > [COMMA < PrefixPath >]* <WhereClause> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>其含义是：查询时间序列prefixPath.path中最近时间戳的数据</p> <p><WhereClause>中当前只支持含有'>'或'>='的时间过滤条件，任何其他过滤条件都将会返回异常。</p> <p>结果集为三列的结构</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+----+----------+-----+----+ |
| |Time|timeseries|value|type| |
| +----+----------+-----+----+ |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br></div></div><p>示例 1：查询 root.ln.wf01.wt01.status 的最新数据点</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select last status from root.ln.wf01.wt01 |
| +-----------------------------+------------------------+-----+-------+ |
| | Time| timeseries|value| type| |
| +-----------------------------+------------------------+-----+-------+ |
| |2017-11-07T23:59:00.000+08:00|root.ln.wf01.wt01.status|false|BOOLEAN| |
| +-----------------------------+------------------------+-----+-------+ |
| Total line number = 1 |
| It costs 0.000s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br></div></div><p>示例 2：查询 root.ln.wf01.wt01 下 status，temperature 时间戳大于等于2017-11-07T23:50:00的最新数据点。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select last status, temperature from root.ln.wf01.wt01 where time >= 2017-11-07T23:50:00 |
| +-----------------------------+-----------------------------+---------+-------+ |
| | Time| timeseries| value| type| |
| +-----------------------------+-----------------------------+---------+-------+ |
| |2017-11-07T23:59:00.000+08:00| root.ln.wf01.wt01.status| false|BOOLEAN| |
| |2017-11-07T23:59:00.000+08:00|root.ln.wf01.wt01.temperature|21.067368| DOUBLE| |
| +-----------------------------+-----------------------------+---------+-------+ |
| Total line number = 2 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br></div></div><h3 id="模糊查询"><a href="#模糊查询" class="header-anchor">#</a> 模糊查询</h3> <p>模糊查询分为Like语句和Regexp语句，都可以支持对Text类型的数据进行模糊匹配</p> <p>Like语句：</p> <p>示例 1：查询 <code>root.sg.device</code> 下 <code>value</code> 含有<code>'cc'</code>的数据。 |
| <code>%</code> 表示任意0个或多个字符。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select * from root.sg.device where value like '%cc%' |
| +-----------------------------+--------------------+ |
| | Time|root.sg.device.value| |
| +-----------------------------+--------------------+ |
| |2017-11-07T23:59:00.000+08:00| aabbccdd| |
| |2017-11-07T23:59:00.000+08:00| cc| |
| +-----------------------------+--------------------+ |
| Total line number = 2 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br></div></div><p>示例 2：查询 <code>root.sg.device</code> 下 <code>value</code> 中间为 <code>'b'</code>、前后为任意单个字符的数据。 |
| <code>_</code> 表示任意单个字符。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select * from root.sg.device where value like '_b_' |
| +-----------------------------+--------------------+ |
| | Time|root.sg.device.value| |
| +-----------------------------+--------------------+ |
| |2017-11-07T23:59:00.000+08:00| abc| |
| +-----------------------------+--------------------+ |
| Total line number = 1 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br></div></div><p>Regexp语句：</p> <p>需要传入的过滤条件为 Java 标准库风格的正则表达式</p> <p>示例 1：查询 root.sg.device 下 value 值为26个英文字符组成的字符串</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select * from root.sg.device where value regexp '^[A-Za-z]+$' |
| +-----------------------------+--------------------+ |
| | Time|root.sg.device.value| |
| +-----------------------------+--------------------+ |
| |2017-11-07T23:59:00.000+08:00| aabbccdd| |
| |2017-11-07T23:59:00.000+08:00| cc| |
| +-----------------------------+--------------------+ |
| Total line number = 2 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br></div></div><p>示例 2：查询 root.sg.device 下 value 值为26个小写英文字符组成的字符串 且时间大于100的</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select * from root.sg.device where value regexp '^[a-z]+$' and time > 100 |
| +-----------------------------+--------------------+ |
| | Time|root.sg.device.value| |
| +-----------------------------+--------------------+ |
| |2017-11-07T23:59:00.000+08:00| aabbccdd| |
| |2017-11-07T23:59:00.000+08:00| cc| |
| +-----------------------------+--------------------+ |
| Total line number = 2 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br></div></div><p>常见的正则匹配举例：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>长度为3-20的所有字符：^.{3,20}$ |
| 大写英文字符：^[A-Z]+$ |
| 数字和英文字符：^[A-Za-z0-9]+$ |
| 以a开头的：^a.* |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br></div></div><p>更多语法请参照 <a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">SQL REFERENCE</a>.</p> <h3 id="空值填充"><a href="#空值填充" class="header-anchor">#</a> 空值填充</h3> <p>在IoTDB的实际使用中，当进行时间序列的查询操作时，可能会出现在某些时间点值为null的情况，这会妨碍用户进行进一步的分析。 为了更好地反映数据更改的程度，用户希望可以自动填充缺失值。 因此，IoTDB系统引入了自动填充功能。</p> <p>自动填充功能是指对单列或多列执行时间序列查询时，根据用户指定的方法和有效时间范围填充空值。 如果查询点的值不为null，则填充功能将不起作用。</p> <blockquote><p>注意：在当前版本中，IoTDB为用户提供两种方法：Previous 和Linear。 Previous 方法用前一个值填充空白。 Linear方法通过线性拟合来填充空白。 并且填充功能只能在执行时间点查询时使用。</p></blockquote> <ul><li>填充功能</li></ul> <ul><li>Previous功能</li></ul> <p>当查询的时间戳值为空时，将使用前一个时间戳的值来填充空白。 形式化的先前方法如下（有关详细语法，请参见第7.1.3.6节）：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select <path> from <prefixPath> where time = <T> fill(<data_type>[previous, <before_range>], …) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>表3-4给出了所有参数的详细说明。</p> <center>**表3-4previous填充参数列表** |
| <table><thead><tr><th style="text-align:left;">参数名称（不区分大小写）</th> <th style="text-align:left;">解释</th></tr></thead> <tbody><tr><td style="text-align:left;">path, prefixPath</td> <td style="text-align:left;">查询路径； 必填项</td></tr> <tr><td style="text-align:left;">T</td> <td style="text-align:left;">查询时间戳（只能指定一个）； 必填项</td></tr> <tr><td style="text-align:left;">data_type</td> <td style="text-align:left;">填充方法使用的数据类型。 可选值是int32，int64，float，double，boolean，text; 可选字段</td></tr> <tr><td style="text-align:left;">before_range</td> <td style="text-align:left;">表示前一种方法的有效时间范围。 当[T-before _range，T]范围内的值存在时，前一种方法将起作用。 如果未指定before_range，则before_range会使用默认值default_fill_interval; -1表示无穷大； 可选字段</td></tr></tbody></table></center> <p>在这里，我们举一个使用先前方法填充空值的示例。 SQL语句如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select temperature from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float[previous, 1m]) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>由于时间根目录root.sgcc.wf03.wt01.temperature在2017-11-01T16：37：50.000为空，因此系统使用以前的时间戳2017-11-01T16：37：00.000（且时间戳位于[2017-11-01T16:36:50.000, 2017-11-01T16:37:50.000]范围）进行填充和显示。</p> <p>在<a href="https://github.com/thulab/iotdb/files/4438687/OtherMaterial-Sample.Data.txt" target="_blank" rel="noopener noreferrer">样例数据中<span><svg 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" class="icon outbound"><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="sr-only">(opens new window)</span></span></a>, 该语句的执行结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------------------+ |
| | Time|root.sgcc.wf03.wt01.temperature| |
| +-----------------------------+-------------------------------+ |
| |2017-11-01T16:37:50.000+08:00| 21.93| |
| +-----------------------------+-------------------------------+ |
| Total line number = 1 |
| It costs 0.016s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>值得注意的是，如果在指定的有效时间范围内没有值，系统将不会填充空值，如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> select temperature from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float[previous, 1s]) |
| +-----------------------------+-------------------------------+ |
| | Time|root.sgcc.wf03.wt01.temperature| |
| +-----------------------------+-------------------------------+ |
| |2017-11-01T16:37:50.000+08:00| null| |
| +-----------------------------+-------------------------------+ |
| Total line number = 1 |
| It costs 0.004s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br></div></div><ul><li>Linear方法</li></ul> <p>当查询的时间戳值为空时，将使用前一个和下一个时间戳的值来填充空白。 形式化线性方法如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select <path> from <prefixPath> where time = <T> fill(<data_type>[linear, <before_range>, <after_range>]…) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>表3-5中给出了所有参数的详细说明。</p> <center>**表3-5线性填充参数列表** |
| <table><thead><tr><th style="text-align:left;">参数名称（不区分大小写）</th> <th style="text-align:left;">解释</th></tr></thead> <tbody><tr><td style="text-align:left;">path, prefixPath</td> <td style="text-align:left;">查询路径； 必填项</td></tr> <tr><td style="text-align:left;">T</td> <td style="text-align:left;">查询时间戳（只能指定一个）； 必填项</td></tr> <tr><td style="text-align:left;">data_type</td> <td style="text-align:left;">填充方法使用的数据类型。 可选值是int32，int64，float，double，boolean，text; 可选字段</td></tr> <tr><td style="text-align:left;">before_range, after_range</td> <td style="text-align:left;">表示线性方法的有效时间范围。 当[T-before_range，T + after_range]范围内的值存在时，前一种方法将起作用。 如果未明确指定before_range和after_range，则使用default_fill_interval。 -1表示无穷大； 可选字段</td></tr></tbody></table></center> <p>需要注意的是一旦时间序列在查询时间戳T时刻存在有效值，线性填充就会使用这个值作为结果返回。 |
| 除此之外，如果在[T-before_range，T]或[T, T + after_range]两个范围中任意一个范围内不存在有效填充值，则线性填充返回null值。</p> <p>在这里，我们举一个使用线性方法填充空值的示例。 SQL语句如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select temperature from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float [linear, 1m, 1m]) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>由于时间根目录root.sgcc.wf03.wt01.temperature在2017-11-01T16:37:50.000为空，因此系统使用以前的时间戳2017-11-01T16:37:00.000（且时间戳位于[2017-11-01T16:36:50.000, 2017-11-01T16:37:50.000]时间范围）及其值21.927326，下一个时间戳记2017-11-01T16:38:00.000（且时间戳记位于[2017-11-01T16:37:50.000, 2017-11-01T16:38:50.000]时间范围）及其值25.311783以执行线性拟合计算：</p> <p>21.927326 +（25.311783-21.927326）/ 60s * 50s = 24.747707</p> <p>在 <a href="https://github.com/thulab/iotdb/files/4438687/OtherMaterial-Sample.Data.txt" target="_blank" rel="noopener noreferrer">样例数据<span><svg 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" class="icon outbound"><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="sr-only">(opens new window)</span></span></a>, 该语句的执行结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------------------+ |
| | Time|root.sgcc.wf03.wt01.temperature| |
| +-----------------------------+-------------------------------+ |
| |2017-11-01T16:37:50.000+08:00| 24.746666| |
| +-----------------------------+-------------------------------+ |
| Total line number = 1 |
| It costs 0.017s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><ul><li>Value方法</li></ul> <p>当查询的时间戳值为空时，将使用给定的值来填充空白。 特定值填充方法如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select <path> from <prefixPath> where time = <T> fill(<data_type>[constant]…) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>表3-6中给出了所有参数的详细说明。</p> <center>**表3-6特定值填充参数列表** |
| <table><thead><tr><th style="text-align:left;">参数名称（不区分大小写）</th> <th style="text-align:left;">解释</th></tr></thead> <tbody><tr><td style="text-align:left;">path, prefixPath</td> <td style="text-align:left;">查询路径； 必填项</td></tr> <tr><td style="text-align:left;">T</td> <td style="text-align:left;">查询时间戳（只能指定一个）； 必填项</td></tr> <tr><td style="text-align:left;">data_type</td> <td style="text-align:left;">填充方法使用的数据类型。 可选值是int32，int64，float，double，boolean，text; 可选字段</td></tr> <tr><td style="text-align:left;">constant</td> <td style="text-align:left;">给定的填充值</td></tr></tbody></table></center> <p>需要注意的是一旦时间序列在查询时间戳T时刻存在有效值，特定值填充就会使用这个值作为结果返回。</p> <p>在这里，我们举一个使用特定值方法填充空值的示例。 SQL语句如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select temperature from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float [2.0]) |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>由于时间根目录root.sgcc.wf03.wt01.temperature在2017-11-01T16:37:50.000为空，因此使用给定的值2.0进行填充：</p> <p>在 <a href="https://github.com/thulab/iotdb/files/4438687/OtherMaterial-Sample.Data.txt" target="_blank" rel="noopener noreferrer">样例数据<span><svg 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" class="icon outbound"><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="sr-only">(opens new window)</span></span></a>, 该语句的执行结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------------------+ |
| | Time|root.sgcc.wf03.wt01.temperature| |
| +-----------------------------+-------------------------------+ |
| |2017-11-01T16:37:50.000+08:00| 2.0 | |
| +-----------------------------+-------------------------------+ |
| Total line number = 1 |
| It costs 0.007s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>数据类型和填充方法之间的对应关系</p> <p>数据类型和支持的填充方法如表3-6所示。</p> <center>**表3-6数据类型和支持的填充方法** |
| <table><thead><tr><th style="text-align:left;">数据类型</th> <th style="text-align:left;">支持的填充方法</th></tr></thead> <tbody><tr><td style="text-align:left;">boolean</td> <td style="text-align:left;">previous, value</td></tr> <tr><td style="text-align:left;">int32</td> <td style="text-align:left;">previous, linear, value</td></tr> <tr><td style="text-align:left;">int64</td> <td style="text-align:left;">previous, linear, value</td></tr> <tr><td style="text-align:left;">float</td> <td style="text-align:left;">previous, linear, value</td></tr> <tr><td style="text-align:left;">double</td> <td style="text-align:left;">previous, linear, value</td></tr> <tr><td style="text-align:left;">text</td> <td style="text-align:left;">previous, value</td></tr></tbody></table></center> <blockquote><p>注意：应在Fill语句中至少指定一种填充方法。</p></blockquote> <ul><li>时间区间分组聚合查询补空值</li></ul> <p>时间区间分组聚合出的各个时间段的结果，支持使用前值补空。</p> <p>不允许设置滑动步长，默认为聚合时间区间，实际为定长采样。现在只支持 last_value 聚合函数。</p> <p>目前不支持线性插值补空值。</p> <p>PREVIOUS 和 PREVIOUSUNTILLAST 的区别</p> <ul><li>PREVIOUS：只要空值前边有值，就会用其填充空值。</li> <li>PREVIOUSUNTILLAST：不会填充此序列最新点后的空值</li></ul> <p>首先我们检查一下root.ln.wf01.wt01.temperature在时间2017-11-07T23:50:00以后的值</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> SELECT temperature FROM root.ln.wf01.wt01 where time >= 2017-11-07T23:50:00 |
| +-----------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.temperature| |
| +-----------------------------+-----------------------------+ |
| |2017-11-07T23:50:00.000+08:00| 23.7| |
| |2017-11-07T23:51:00.000+08:00| 22.24| |
| |2017-11-07T23:52:00.000+08:00| 20.18| |
| |2017-11-07T23:53:00.000+08:00| 24.58| |
| |2017-11-07T23:54:00.000+08:00| 22.52| |
| |2017-11-07T23:55:00.000+08:00| 25.9| |
| |2017-11-07T23:56:00.000+08:00| 24.44| |
| |2017-11-07T23:57:00.000+08:00| 24.39| |
| |2017-11-07T23:58:00.000+08:00| 22.93| |
| |2017-11-07T23:59:00.000+08:00| 21.07| |
| +-----------------------------+-----------------------------+ |
| Total line number = 10 |
| It costs 0.002s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br><span class="line-number">17</span><br></div></div><p>我们发现root.ln.wf01.wt01.temperature的最后时间和值是2017-11-07T23:59:00和21.07。</p> <p>SQL 示例:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>SELECT last_value(temperature) FROM root.ln.wf01.wt01 GROUP BY([2017-11-07T23:50:00, 2017-11-08T00:01:00),1m) FILL (float[PREVIOUSUNTILLAST]); |
| SELECT last_value(temperature) FROM root.ln.wf01.wt01 GROUP BY([2017-11-07T23:50:00, 2017-11-08T00:01:00),1m) FILL (float[PREVIOUS]); |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------------------------------+ |
| | Time|last_value(root.ln.wf01.wt01.temperature)| |
| +-----------------------------+-----------------------------------------+ |
| |2017-11-07T23:50:00.000+08:00| 23.7| |
| |2017-11-07T23:51:00.000+08:00| 22.24| |
| |2017-11-07T23:52:00.000+08:00| 20.18| |
| |2017-11-07T23:53:00.000+08:00| 24.58| |
| |2017-11-07T23:54:00.000+08:00| 22.52| |
| |2017-11-07T23:55:00.000+08:00| 25.9| |
| |2017-11-07T23:56:00.000+08:00| 24.44| |
| |2017-11-07T23:57:00.000+08:00| 24.39| |
| |2017-11-07T23:58:00.000+08:00| 22.93| |
| |2017-11-07T23:59:00.000+08:00| 21.07| |
| |2017-11-08T00:00:00.000+08:00| null| |
| +-----------------------------+-----------------------------------------+ |
| Total line number = 11 |
| It costs 0.005s |
| |
| +-----------------------------+-----------------------------------------+ |
| | Time|last_value(root.ln.wf01.wt01.temperature)| |
| +-----------------------------+-----------------------------------------+ |
| |2017-11-07T23:50:00.000+08:00| 23.7| |
| |2017-11-07T23:51:00.000+08:00| 22.24| |
| |2017-11-07T23:52:00.000+08:00| 20.18| |
| |2017-11-07T23:53:00.000+08:00| 24.58| |
| |2017-11-07T23:54:00.000+08:00| 22.52| |
| |2017-11-07T23:55:00.000+08:00| 25.9| |
| |2017-11-07T23:56:00.000+08:00| 24.44| |
| |2017-11-07T23:57:00.000+08:00| 24.39| |
| |2017-11-07T23:58:00.000+08:00| 22.93| |
| |2017-11-07T23:59:00.000+08:00| 21.07| |
| |2017-11-08T00:00:00.000+08:00| 21.07| |
| +-----------------------------+-----------------------------------------+ |
| Total line number = 11 |
| It costs 0.006s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br><span class="line-number">17</span><br><span class="line-number">18</span><br><span class="line-number">19</span><br><span class="line-number">20</span><br><span class="line-number">21</span><br><span class="line-number">22</span><br><span class="line-number">23</span><br><span class="line-number">24</span><br><span class="line-number">25</span><br><span class="line-number">26</span><br><span class="line-number">27</span><br><span class="line-number">28</span><br><span class="line-number">29</span><br><span class="line-number">30</span><br><span class="line-number">31</span><br><span class="line-number">32</span><br><span class="line-number">33</span><br><span class="line-number">34</span><br><span class="line-number">35</span><br></div></div><p>解释:</p> <p>使用 PREVIOUSUNTILLAST 将不会填充2017-11-07T23:59:00以后的值。</p> <h4 id="limit-offset"><a href="#limit-offset" class="header-anchor">#</a> LIMIT & OFFSET</h4> <p>IoTDB提供 <a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">LIMIT/SLIMIT</a> 子句和 <a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">OFFSET/SOFFSET</a> 子句，以使用户可以更好地控制查询结果。使用LIMIT和SLIMIT子句可让用户控制查询结果的行数和列数， |
| 并且使用OFFSET和SOFFSET子句允许用户设置结果显示的起始位置。</p> <p>请注意，按组查询不支持LIMIT和OFFSET。</p> <p>本章主要介绍查询结果的行和列控制的相关示例。你还可以使用 <a href="/zh/UserGuide/V0.12.x/API/Programming-JDBC.html">Java JDBC</a> 标准接口执行查询。</p> <ul><li>查询结果的行控制</li></ul> <p>通过使用LIMIT和OFFSET子句，用户可以以与行相关的方式控制查询结果。 我们将通过以下示例演示如何使用LIMIT和OFFSET子句。</p> <ul><li>示例1：基本的LIMIT子句</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status, temperature from root.ln.wf01.wt01 limit 10 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 选择的时间序列是“状态”和“温度”。 SQL语句要求返回查询结果的前10行。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:00:00.000+08:00| true| 25.96| |
| |2017-11-01T00:01:00.000+08:00| true| 24.36| |
| |2017-11-01T00:02:00.000+08:00| false| 20.09| |
| |2017-11-01T00:03:00.000+08:00| false| 20.18| |
| |2017-11-01T00:04:00.000+08:00| false| 21.13| |
| |2017-11-01T00:05:00.000+08:00| false| 22.72| |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| |2017-11-01T00:08:00.000+08:00| false| 22.58| |
| |2017-11-01T00:09:00.000+08:00| false| 20.98| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 10 |
| It costs 0.000s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br></div></div><ul><li>示例2：带OFFSET的LIMIT子句</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status, temperature from root.ln.wf01.wt01 limit 5 offset 3 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 选择的时间序列是“状态”和“温度”。 SQL语句要求返回查询结果的第3至7行（第一行编号为0行）。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:03:00.000+08:00| false| 20.18| |
| |2017-11-01T00:04:00.000+08:00| false| 21.13| |
| |2017-11-01T00:05:00.000+08:00| false| 22.72| |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 5 |
| It costs 0.342s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br></div></div><ul><li>示例3：LIMIT子句与WHERE子句结合</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time< 2017-11-01T00:12:00.000 limit 5 offset 3 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 选择的时间序列是“状态”和“温度”。 SQL语句要求返回时间“ 2017-11-01T00：05：00.000”和“ 2017-11-01T00：12：00.000”之间的状态和温度传感器值的第3至4行（第一行） 编号为第0行）。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:03:00.000+08:00| false| 20.18| |
| |2017-11-01T00:04:00.000+08:00| false| 21.13| |
| |2017-11-01T00:05:00.000+08:00| false| 22.72| |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 5 |
| It costs 0.000s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br></div></div><ul><li>示例4：LIMIT子句与GROUP BY子句组合</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select count(status), max_value(temperature) from root.ln.wf01.wt01 group by ([2017-11-01T00:00:00, 2017-11-07T23:00:00),1d) limit 4 offset 3 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>SQL语句子句要求返回查询结果的第3至6行（第一行编号为0行）。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------------------+----------------------------------------+ |
| | Time|count(root.ln.wf01.wt01.status)|max_value(root.ln.wf01.wt01.temperature)| |
| +-----------------------------+-------------------------------+----------------------------------------+ |
| |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 = 4 |
| It costs 0.016s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br></div></div><p>值得注意的是，由于当前的FILL子句只能在某个时间点填充时间序列的缺失值，也就是说，FILL子句的执行结果恰好是一行，因此LIMIT和OFFSET不会是 与FILL子句结合使用，否则将提示错误。 例如，执行以下SQL语句：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select temperature from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float[previous, 1m]) limit 10 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>SQL语句将不会执行，并且相应的错误提示如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>Msg: 401: Error occured while parsing SQL to physical plan: line 1:101 mismatched input 'limit' expecting {<EOF>, SLIMIT, SOFFSET, GROUP, DISABLE, ALIGN} |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><ul><li>查询结果的列控制</li></ul> <p>通过使用SLIMIT和SOFFSET子句，用户可以与列相关的方式控制查询结果。 我们将通过以下示例演示如何使用SLIMIT和SOFFSET子句。</p> <ul><li>示例1：基本的SLIMIT子句</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 slimit 1 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 所选时间序列是该设备下的第二列，即温度。 SQL语句要求在"2017-11-01T00:05:00.000"和"2017-11-01T00:12:00.000"的时间点之间选择温度传感器值。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.temperature| |
| +-----------------------------+-----------------------------+ |
| |2017-11-01T00:06:00.000+08:00| 20.71| |
| |2017-11-01T00:07:00.000+08:00| 21.45| |
| |2017-11-01T00:08:00.000+08:00| 22.58| |
| |2017-11-01T00:09:00.000+08:00| 20.98| |
| |2017-11-01T00:10:00.000+08:00| 25.52| |
| |2017-11-01T00:11:00.000+08:00| 22.91| |
| +-----------------------------+-----------------------------+ |
| Total line number = 6 |
| It costs 0.000s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br></div></div><ul><li>示例2：带SOFFSET的SLIMIT子句</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 slimit 1 soffset 1 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 所选时间序列是该设备下的第一列，即电源状态。 SQL语句要求在" 2017-11-01T00:05:00.000"和"2017-11-01T00:12:00.000"的时间点之间选择状态传感器值。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+ |
| | Time|root.ln.wf01.wt01.status| |
| +-----------------------------+------------------------+ |
| |2017-11-01T00:06:00.000+08:00| false| |
| |2017-11-01T00:07:00.000+08:00| false| |
| |2017-11-01T00:08:00.000+08:00| false| |
| |2017-11-01T00:09:00.000+08:00| false| |
| |2017-11-01T00:10:00.000+08:00| true| |
| |2017-11-01T00:11:00.000+08:00| false| |
| +-----------------------------+------------------------+ |
| Total line number = 6 |
| It costs 0.003s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br></div></div><ul><li>示例3：SLIMIT子句与GROUP BY子句结合</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select max_value(*) from root.ln.wf01.wt01 group by ([2017-11-01T00:00:00, 2017-11-07T23:00:00),1d) slimit 1 soffset 1 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------------------------+ |
| | Time|max_value(root.ln.wf01.wt01.status)| |
| +-----------------------------+-----------------------------------+ |
| |2017-11-01T00:00:00.000+08:00| true| |
| |2017-11-02T00:00:00.000+08:00| true| |
| |2017-11-03T00:00:00.000+08:00| true| |
| |2017-11-04T00:00:00.000+08:00| true| |
| |2017-11-05T00:00:00.000+08:00| true| |
| |2017-11-06T00:00:00.000+08:00| true| |
| |2017-11-07T00:00:00.000+08:00| true| |
| +-----------------------------+-----------------------------------+ |
| Total line number = 7 |
| It costs 0.000s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br></div></div><ul><li>示例4：SLIMIT子句与FILL子句结合</li></ul> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.sgcc.wf03.wt01 where time = 2017-11-01T16:37:50.000 fill(float[previous, 1m]) slimit 1 soffset 1 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------------------+ |
| | Time|root.sgcc.wf03.wt01.status| |
| +-----------------------------+--------------------------+ |
| |2017-11-01T16:35:00.000+08:00| true| |
| +-----------------------------+--------------------------+ |
| Total line number = 1 |
| It costs 0.007s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><ul><li>控制查询结果的行和列</li></ul> <p>除了对查询结果进行行或列控制之外，IoTDB还允许用户控制查询结果的行和列。 这是同时包含LIMIT子句和SLIMIT子句的完整示例。</p> <p>SQL语句是：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select * from root.ln.wf01.wt01 limit 10 offset 100 slimit 2 soffset 0 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>意思是：</p> <p>所选设备为ln组wf01工厂wt01设备； 所选时间序列是此设备下的第0列至第1列（第一列编号为第0列）。 SQL语句子句要求返回查询结果的第100至109行（第一行编号为0行）。</p> <p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-----------------------------+------------------------+ |
| | Time|root.ln.wf01.wt01.temperature|root.ln.wf01.wt01.status| |
| +-----------------------------+-----------------------------+------------------------+ |
| |2017-11-01T01:40:00.000+08:00| 21.19| false| |
| |2017-11-01T01:41:00.000+08:00| 22.79| false| |
| |2017-11-01T01:42:00.000+08:00| 22.98| false| |
| |2017-11-01T01:43:00.000+08:00| 21.52| false| |
| |2017-11-01T01:44:00.000+08:00| 23.45| true| |
| |2017-11-01T01:45:00.000+08:00| 24.06| true| |
| |2017-11-01T01:46:00.000+08:00| 22.6| false| |
| |2017-11-01T01:47:00.000+08:00| 23.78| true| |
| |2017-11-01T01:48:00.000+08:00| 24.72| true| |
| |2017-11-01T01:49:00.000+08:00| 24.68| true| |
| +-----------------------------+-----------------------------+------------------------+ |
| Total line number = 10 |
| It costs 0.009s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br><span class="line-number">13</span><br><span class="line-number">14</span><br><span class="line-number">15</span><br><span class="line-number">16</span><br></div></div><h4 id="别名"><a href="#别名" class="header-anchor">#</a> 别名</h4> <p>由于 IoTDB 独特的数据模型，在每个传感器前都附带有设备等诸多额外信息。有时，我们只针对某个具体设备查询，而这些前缀信息频繁显示造成了冗余，影响了结果集的显示与分析。这时我们可以使用 IoTDB 提供的 AS 函数，将查询中出现的时间序列给定一个别名。</p> <p>例如：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select s1 as temperature, s2 as speed from root.ln.wf01.wt01; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>则结果集将显示为：</p> <table><thead><tr><th>Time</th> <th>temperature</th> <th>speed</th></tr></thead> <tbody><tr><td>...</td> <td>...</td> <td>...</td></tr></tbody></table> <h4 id="内置函数"><a href="#内置函数" class="header-anchor">#</a> 内置函数</h4> <p>时间序列生成函数可接受若干原始时间序列作为输入，产生一列时间序列输出。与聚合函数不同的是，时间序列生成函数的结果集带有时间戳列。</p> <p>所有的时间序列生成函数都可以接受 * 作为输入，都可以与原始查询混合进行。</p> <ul><li>数学函数</li></ul> <p>目前IoTDB支持下列数学函数，这些数学函数的行为与这些函数在Java Math标准库中对应实现的行为一致。</p> <table><thead><tr><th>函数名</th> <th>输入序列类型</th> <th>输出序列类型</th> <th>Java标准库中的对应实现</th></tr></thead> <tbody><tr><td>SIN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#sin(double)</td></tr> <tr><td>COS</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#cos(double)</td></tr> <tr><td>TAN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#tan(double)</td></tr> <tr><td>ASIN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#asin(double)</td></tr> <tr><td>ACOS</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#acos(double)</td></tr> <tr><td>ATAN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#atan(double)</td></tr> <tr><td>DEGREES</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#toDegrees(double)</td></tr> <tr><td>RADIANS</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#toRadians(double)</td></tr> <tr><td>ABS</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>与输入序列的实际类型一致</td> <td>Math#abs(int) / Math#abs(long) /Math#abs(float) /Math#abs(double)</td></tr> <tr><td>SIGN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#signum(double)</td></tr> <tr><td>CEIL</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#ceil(double)</td></tr> <tr><td>FLOOR</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#floor(double)</td></tr> <tr><td>ROUND</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#rint(double)</td></tr> <tr><td>EXP</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#exp(double)</td></tr> <tr><td>LN</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#log(double)</td></tr> <tr><td>LOG10</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#log10(double)</td></tr> <tr><td>SQRT</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>Math#sqrt(double)</td></tr></tbody></table> <p>例如：</p> <div class="language-sql line-numbers-mode"><pre class="language-sql"><code><span class="token keyword">select</span> s1<span class="token punctuation">,</span> sin<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> cos<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> tan<span class="token punctuation">(</span>s1<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>sg1<span class="token punctuation">.</span>d1 <span class="token keyword">limit</span> <span class="token number">5</span> <span class="token keyword">offset</span> <span class="token number">1000</span><span class="token punctuation">;</span> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------+-------------------+--------------------+-------------------+ |
| | Time| root.sg1.d1.s1|sin(root.sg1.d1.s1)| cos(root.sg1.d1.s1)|tan(root.sg1.d1.s1)| |
| +-----------------------------+-------------------+-------------------+--------------------+-------------------+ |
| |2020-12-10T17:11:49.037+08:00|7360723084922759782| 0.8133527237573284| 0.5817708713544664| 1.3980636773094157| |
| |2020-12-10T17:11:49.038+08:00|4377791063319964531|-0.8938962705202537| 0.4482738644511651| -1.994085181866842| |
| |2020-12-10T17:11:49.039+08:00|7972485567734642915| 0.9627757585308978|-0.27030138509681073|-3.5618602479083545| |
| |2020-12-10T17:11:49.040+08:00|2508858212791964081|-0.6073417341629443| -0.7944406950452296| 0.7644897069734913| |
| |2020-12-10T17:11:49.041+08:00|2817297431185141819|-0.8419358900502509| -0.5395775727782725| 1.5603611649667768| |
| +-----------------------------+-------------------+-------------------+--------------------+-------------------+ |
| Total line number = 5 |
| It costs 0.008s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br></div></div><ul><li>字符串函数</li></ul> <p>目前IoTDB支持下列字符串处理函数：</p> <table><thead><tr><th>函数名</th> <th>输入序列类型</th> <th>必要的属性参数</th> <th>输出序列类型</th> <th>功能描述</th></tr></thead> <tbody><tr><td>STRING_CONTAINS</td> <td>TEXT</td> <td><code>s</code>: 待搜寻的字符串</td> <td>BOOLEAN</td> <td>判断字符串中是否存在<code>s</code></td></tr> <tr><td>STRING_MATCHES</td> <td>TEXT</td> <td><code>regex</code>: Java标准库风格的正则表达式</td> <td>BOOLEAN</td> <td>判断字符串是否能够被正则表达式<code>regex</code>匹配</td></tr></tbody></table> <p>例如：</p> <div class="language-sql line-numbers-mode"><pre class="language-sql"><code><span class="token keyword">select</span> s1<span class="token punctuation">,</span> string_contains<span class="token punctuation">(</span>s1<span class="token punctuation">,</span> <span class="token string">"s"</span><span class="token operator">=</span><span class="token string">"warn"</span><span class="token punctuation">)</span><span class="token punctuation">,</span> string_matches<span class="token punctuation">(</span>s1<span class="token punctuation">,</span> <span class="token string">"regex"</span><span class="token operator">=</span><span class="token string">"[^\\s]+37229"</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>sg1<span class="token punctuation">.</span>d4<span class="token punctuation">;</span> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------+-------------------------------------------+------------------------------------------------------+ |
| | Time|root.sg1.d4.s1|string_contains(root.sg1.d4.s1, "s"="warn")|string_matches(root.sg1.d4.s1, "regex"="[^\\s]+37229")| |
| +-----------------------------+--------------+-------------------------------------------+------------------------------------------------------+ |
| |1970-01-01T08:00:00.001+08:00| warn:-8721| true| false| |
| |1970-01-01T08:00:00.002+08:00| error:-37229| false| true| |
| |1970-01-01T08:00:00.003+08:00| warn:1731| true| false| |
| +-----------------------------+--------------+-------------------------------------------+------------------------------------------------------+ |
| Total line number = 3 |
| It costs 0.007s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br></div></div><ul><li>选择函数</li></ul> <p>目前IoTDB支持如下选择函数：</p> <table><thead><tr><th>函数名</th> <th>输入序列类型</th> <th>必要的属性参数</th> <th>输出序列类型</th> <th>功能描述</th></tr></thead> <tbody><tr><td>TOP_K</td> <td>INT32 / INT64 / FLOAT / DOUBLE / TEXT</td> <td><code>k</code>: 最多选择的数据点数，必须大于0小于等于1000</td> <td>与输入序列的实际类型一致</td> <td>返回某时间序列中值最大的<code>k</code>个数据点。若多于<code>k</code>个数据点的值并列最大，则返回时间戳最小的数据点。</td></tr> <tr><td>BOTTOM_K</td> <td>INT32 / INT64 / FLOAT / DOUBLE / TEXT</td> <td><code>k</code>: 最多选择的数据点数，必须大于0小于等于1000</td> <td>与输入序列的实际类型一致</td> <td>返回某时间序列中值最小的<code>k</code>个数据点。若多于<code>k</code>个数据点的值并列最小，则返回时间戳最小的数据点。</td></tr></tbody></table> <p>例如：</p> <div class="language-sql line-numbers-mode"><pre class="language-sql"><code><span class="token keyword">select</span> s1<span class="token punctuation">,</span> top_k<span class="token punctuation">(</span>s1<span class="token punctuation">,</span> <span class="token string">"k"</span><span class="token operator">=</span><span class="token string">"2"</span><span class="token punctuation">)</span><span class="token punctuation">,</span> bottom_k<span class="token punctuation">(</span>s1<span class="token punctuation">,</span> <span class="token string">"k"</span><span class="token operator">=</span><span class="token string">"2"</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>sg1<span class="token punctuation">.</span>d2 <span class="token keyword">where</span> <span class="token keyword">time</span> <span class="token operator">></span> <span class="token number">2020</span><span class="token operator">-</span><span class="token number">12</span><span class="token operator">-</span><span class="token number">10</span>T20:<span class="token number">36</span>:<span class="token number">15.530</span><span class="token operator">+</span><span class="token number">08</span>:<span class="token number">00</span><span class="token punctuation">;</span> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+--------------------+------------------------------+---------------------------------+ |
| | Time| root.sg1.d2.s1|top_k(root.sg1.d2.s1, "k"="2")|bottom_k(root.sg1.d2.s1, "k"="2")| |
| +-----------------------------+--------------------+------------------------------+---------------------------------+ |
| |2020-12-10T20:36:15.531+08:00| 1531604122307244742| 1531604122307244742| null| |
| |2020-12-10T20:36:15.532+08:00|-7426070874923281101| null| null| |
| |2020-12-10T20:36:15.533+08:00|-7162825364312197604| -7162825364312197604| null| |
| |2020-12-10T20:36:15.534+08:00|-8581625725655917595| null| -8581625725655917595| |
| |2020-12-10T20:36:15.535+08:00|-7667364751255535391| null| -7667364751255535391| |
| +-----------------------------+--------------------+------------------------------+---------------------------------+ |
| Total line number = 5 |
| It costs 0.006s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br></div></div><ul><li>趋势计算函数</li></ul> <p>目前IoTDB支持如下趋势计算函数：</p> <table><thead><tr><th>函数名</th> <th>输入序列类型</th> <th>输出序列类型</th> <th>功能描述</th></tr></thead> <tbody><tr><td>TIME_DIFFERENCE</td> <td>INT32 / INT64 / FLOAT / DOUBLE / BOOLEAN / TEXT</td> <td>INT64</td> <td>统计序列中某数据点的时间戳与前一数据点时间戳的差。范围内第一个数据点没有对应的结果输出。</td></tr> <tr><td>DIFFERENCE</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>与输入序列的实际类型一致</td> <td>统计序列中某数据点的值与前一数据点的值的差。范围内第一个数据点没有对应的结果输出。</td></tr> <tr><td>NON_NEGATIVE_DIFFERENCE</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>与输入序列的实际类型一致</td> <td>统计序列中某数据点的值与前一数据点的值的差的绝对值。范围内第一个数据点没有对应的结果输出。</td></tr> <tr><td>DERIVATIVE</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>统计序列中某数据点相对于前一数据点的变化率，数量上等同于 DIFFERENCE / TIME_DIFFERENCE。范围内第一个数据点没有对应的结果输出。</td></tr> <tr><td>NON_NEGATIVE_DERIVATIVE</td> <td>INT32 / INT64 / FLOAT / DOUBLE</td> <td>DOUBLE</td> <td>统计序列中某数据点相对于前一数据点的变化率的绝对值，数量上等同于 NON_NEGATIVE_DIFFERENCE / TIME_DIFFERENCE。范围内第一个数据点没有对应的结果输出。</td></tr></tbody></table> <p>例如：</p> <div class="language-sql line-numbers-mode"><pre class="language-sql"><code><span class="token keyword">select</span> s1<span class="token punctuation">,</span> time_difference<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> difference<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> non_negative_difference<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> derivative<span class="token punctuation">(</span>s1<span class="token punctuation">)</span><span class="token punctuation">,</span> non_negative_derivative<span class="token punctuation">(</span>s1<span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>sg1<span class="token punctuation">.</span>d1 <span class="token keyword">limit</span> <span class="token number">5</span> <span class="token keyword">offset</span> <span class="token number">1000</span><span class="token punctuation">;</span> |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>结果：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+-------------------+-------------------------------+--------------------------+---------------------------------------+--------------------------+---------------------------------------+ |
| | Time| root.sg1.d1.s1|time_difference(root.sg1.d1.s1)|difference(root.sg1.d1.s1)|non_negative_difference(root.sg1.d1.s1)|derivative(root.sg1.d1.s1)|non_negative_derivative(root.sg1.d1.s1)| |
| +-----------------------------+-------------------+-------------------------------+--------------------------+---------------------------------------+--------------------------+---------------------------------------+ |
| |2020-12-10T17:11:49.037+08:00|7360723084922759782| 1| -8431715764844238876| 8431715764844238876| -8.4317157648442388E18| 8.4317157648442388E18| |
| |2020-12-10T17:11:49.038+08:00|4377791063319964531| 1| -2982932021602795251| 2982932021602795251| -2.982932021602795E18| 2.982932021602795E18| |
| |2020-12-10T17:11:49.039+08:00|7972485567734642915| 1| 3594694504414678384| 3594694504414678384| 3.5946945044146785E18| 3.5946945044146785E18| |
| |2020-12-10T17:11:49.040+08:00|2508858212791964081| 1| -5463627354942678834| 5463627354942678834| -5.463627354942679E18| 5.463627354942679E18| |
| |2020-12-10T17:11:49.041+08:00|2817297431185141819| 1| 308439218393177738| 308439218393177738| 3.0843921839317773E17| 3.0843921839317773E17| |
| +-----------------------------+-------------------+-------------------------------+--------------------------+---------------------------------------+--------------------------+---------------------------------------+ |
| Total line number = 5 |
| It costs 0.014s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br></div></div><ul><li>自定义序列生成函数</li></ul> <p>请参考 <a href="/zh/UserGuide/V0.12.x/UDF/UDF-User-Defined-Function.html">UDF (用户定义函数)</a>。</p> <h4 id="错误处理"><a href="#错误处理" class="header-anchor">#</a> 错误处理</h4> <p>当LIMIT / SLIMIT的参数N / SN超过结果集的大小时，IoTDB将按预期返回所有结果。 例如，原始SQL语句的查询结果由六行组成，我们通过LIMIT子句选择前100行：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 limit 100 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+-----------------------------+------------------------+-----------------------------+ |
| | Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +-----------------------------+------------------------+-----------------------------+ |
| |2017-11-01T00:06:00.000+08:00| false| 20.71| |
| |2017-11-01T00:07:00.000+08:00| false| 21.45| |
| |2017-11-01T00:08:00.000+08:00| false| 22.58| |
| |2017-11-01T00:09:00.000+08:00| false| 20.98| |
| |2017-11-01T00:10:00.000+08:00| true| 25.52| |
| |2017-11-01T00:11:00.000+08:00| false| 22.91| |
| +-----------------------------+------------------------+-----------------------------+ |
| Total line number = 6 |
| It costs 0.005s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br><span class="line-number">8</span><br><span class="line-number">9</span><br><span class="line-number">10</span><br><span class="line-number">11</span><br><span class="line-number">12</span><br></div></div><p>当LIMIT / SLIMIT子句的参数N / SN超过允许的最大值（N / SN的类型为int32）时，系统将提示错误。 例如，执行以下SQL语句：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 limit 1234567890123456789 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>SQL语句将不会执行，并且相应的错误提示如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>Msg: 303: check metadata error: Out of range. LIMIT <N>: N should be Int32. |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>当LIMIT / LIMIT子句的参数N / SN不是正整数时，系统将提示错误。 例如，执行以下SQL语句：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 limit 13.1 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>SQL语句将不会执行，并且相应的错误提示如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>Msg: 401: line 1:129 mismatched input '.' expecting {<EOF>, SLIMIT, OFFSET, SOFFSET, GROUP, DISABLE, ALIGN} |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>当LIMIT子句的参数OFFSET超过结果集的大小时，IoTDB将返回空结果集。 例如，执行以下SQL语句：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>select status,temperature from root.ln.wf01.wt01 where time > 2017-11-01T00:05:00.000 and time < 2017-11-01T00:12:00.000 limit 2 offset 6 |
| |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><p>结果如下所示：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>+----+------------------------+-----------------------------+ |
| |Time|root.ln.wf01.wt01.status|root.ln.wf01.wt01.temperature| |
| +----+------------------------+-----------------------------+ |
| +----+------------------------+-----------------------------+ |
| Empty set. |
| It costs 0.005s |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br></div></div><h3 id="数据删除"><a href="#数据删除" class="header-anchor">#</a> 数据删除</h3> <p>用户使用<a href="/zh/UserGuide/V0.12.x/Appendix/SQL-Reference.html">DELETE语句</a>可以删除指定的时间序列中符合时间删除条件的数据。在删除数据时，用户可以选择需要删除的一个或多个时间序列、时间序列的前缀、时间序列带*路径对某一个时间区间内的数据进行删除。</p> <p>在JAVA编程环境中，您可以使用JDBC API单条或批量执行DELETE语句。</p> <h4 id="单传感器时间序列值删除"><a href="#单传感器时间序列值删除" class="header-anchor">#</a> 单传感器时间序列值删除</h4> <p>以测控ln集团为例，存在这样的使用场景：</p> <p>wf02子站的wt02设备在2017-11-01 16:26:00之前的供电状态出现多段错误，且无法分析其正确数据，错误数据影响了与其他设备的关联分析。此时，需要将此时间段前的数据删除。进行此操作的SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02.status where time<=2017-11-01T16:26:00; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>如果我们仅仅想要删除2017年内的在2017-11-01 16:26:00之前的数据，可以使用以下SQL:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02.status where time>=2017-01-01T00:00:00 and time<=2017-11-01T16:26:00; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>IoTDB 支持删除一个时间序列任何一个时间范围内的所有时序点，用户可以使用以下SQL语句指定需要删除的时间范围：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02.status where time < 10 |
| delete from root.ln.wf02.wt02.status where time <= 10 |
| delete from root.ln.wf02.wt02.status where time < 20 and time > 10 |
| delete from root.ln.wf02.wt02.status where time <= 20 and time >= 10 |
| delete from root.ln.wf02.wt02.status where time > 20 |
| delete from root.ln.wf02.wt02.status where time >= 20 |
| delete from root.ln.wf02.wt02.status where time = 20 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br><span class="line-number">4</span><br><span class="line-number">5</span><br><span class="line-number">6</span><br><span class="line-number">7</span><br></div></div><p>需要注意，当前的删除语句不支持where子句后的时间范围为多个由OR连接成的时间区间。如下删除语句将会解析出错：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02.status where time > 4 or time < 0 |
| Msg: 303: Check metadata error: For delete statement, where clause can only contain atomic |
| expressions like : time > XXX, time <= XXX, or two atomic expressions connected by 'AND' |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br><span class="line-number">3</span><br></div></div><p>如果delete语句中未指定where子句，则会删除时间序列中的所有数据。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.status |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><h4 id="多传感器时间序列值删除"><a href="#多传感器时间序列值删除" class="header-anchor">#</a> 多传感器时间序列值删除</h4> <p>当ln集团wf02子站的wt02设备在2017-11-01 16:26:00之前的供电状态和设备硬件版本都需要删除，此时可以使用含义更广的<a href="/zh/UserGuide/V0.12.x/Data-Concept/Data-Model-and-Terminology.html">前缀路径或带<code>*</code>路径</a>进行删除操作，进行此操作的SQL语句为：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02 where time <= 2017-11-01T16:26:00; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>或</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>delete from root.ln.wf02.wt02.* where time <= 2017-11-01T16:26:00; |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>需要注意的是，当删除的路径不存在时，IoTDB会提示路径不存在，无法删除数据，如下所示。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>IoTDB> delete from root.ln.wf03.wt02.status where time < now() |
| Msg: TimeSeries does not exist and its data cannot be deleted |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br><span class="line-number">2</span><br></div></div><h4 id="删除时间分区-实验性功能"><a href="#删除时间分区-实验性功能" class="header-anchor">#</a> 删除时间分区 (实验性功能)</h4> <p>您可以通过如下语句来删除某一个存储组下的指定时间分区:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>DELETE PARTITION root.ln 0,1,2 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>上例中的0,1,2为待删除时间分区的id，您可以通过查看IoTDB的数据文件夹找到它，或者可以通过计算<code>timestamp / partitionInterval</code>(向下取整), |
| 手动地将一个时间戳转换为对应的id，其中的<code>partitionInterval</code>可以在IoTDB的配置文件中找到（如果您使用的版本支持时间分区）。</p> <p>请注意该功能目前只是实验性的，如果您不是开发者，使用时请务必谨慎。</p></div> <div class="page-nav"><p class="inner"><span class="prev"> |
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