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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 (v0.10.x)</span> <!----></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>开始</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>概述</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>概念</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>服务器端</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>客户端</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>操作指南</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 open"><span>生态集成</span> <span class="arrow down"></span></p> <ul class="sidebar-links sidebar-group-items"><li><a href="/zh/UserGuide/V0.10.x/Ecosystem Integration/Grafana.html" class="sidebar-link">Grafana</a></li><li><a href="/zh/UserGuide/V0.10.x/Ecosystem Integration/MapReduce TsFile.html" class="sidebar-link">MapReduce TsFile</a></li><li><a href="/zh/UserGuide/V0.10.x/Ecosystem Integration/Spark TsFile.html" class="active sidebar-link">Spark TsFile</a></li><li><a href="/zh/UserGuide/V0.10.x/Ecosystem Integration/Spark IoTDB.html" class="sidebar-link">Spark IoTDB</a></li><li><a href="/zh/UserGuide/V0.10.x/Ecosystem Integration/Hive TsFile.html" class="sidebar-link">Hive TsFile</a></li></ul></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>系统设计</span> <span class="arrow right"></span></p> <!----></section></li></ul> </aside> <main class="page"> <div class="content content__default"><h1 id="tsfile的spark连接器"><a href="#tsfile的spark连接器" class="header-anchor">#</a> TsFile的Spark连接器</h1> <h2 id="_1-about-tsfile-spark-connector"><a href="#_1-about-tsfile-spark-connector" class="header-anchor">#</a> 1. About TsFile-Spark-Connector</h2> <p>TsFile-Spark-Connector对Tsfile类型的外部数据源实现Spark的支持。 这使用户可以通过Spark读取，写入和查询Tsfile。</p> <p>使用此连接器，您可以</p> <ul><li>从本地文件系统或hdfs加载单个TsFile到Spark</li> <li>将本地文件系统或hdfs中特定目录中的所有文件加载到Spark中</li> <li>将数据从Spark写入TsFile</li></ul> <h2 id="_2-system-requirements"><a href="#_2-system-requirements" class="header-anchor">#</a> 2. System Requirements</h2> <table><thead><tr><th>Spark Version</th> <th>Scala Version</th> <th>Java Version</th> <th>TsFile</th></tr></thead> <tbody><tr><td><code>2.4.3</code></td> <td><code>2.11.8</code></td> <td><code>1.8</code></td> <td><code>0.10.0</code></td></tr></tbody></table> <blockquote><p>注意：有关如何下载和使用TsFile的更多信息，请参见以下链接：https://github.com/apache/incubator-iotdb/tree/master/tsfile</p></blockquote> <h2 id="_3-快速开始"><a href="#_3-快速开始" class="header-anchor">#</a> 3. 快速开始</h2> <h3 id="本地模式"><a href="#本地模式" class="header-anchor">#</a> 本地模式</h3> <p>在本地模式下使用TsFile-Spark-Connector启动Spark：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>./<spark-shell-path> --jars tsfile-spark-connector.jar,tsfile-0.10.1-jar-with-dependencies.jar |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><ul><li><spark-shell-path>是您的spark-shell的真实路径。</li> <li>多个jar包用逗号分隔，没有任何空格。</li> <li>有关如何获取TsFile的信息，请参见https://github.com/apache/incubator-iotdb/tree/master/tsfile。</li></ul> <h3 id="分布式模式"><a href="#分布式模式" class="header-anchor">#</a> 分布式模式</h3> <p>在分布式模式下使用TsFile-Spark-Connector启动Spark（即，Spark集群通过spark-shell连接）：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>. /<spark-shell-path> --jars tsfile-spark-connector.jar,tsfile-{version}-jar-with-dependencies.jar --master spark://ip:7077 |
| </code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>注意：</p> <ul><li><spark-shell-path>是您的spark-shell的真实路径。</li> <li>多个jar包用逗号分隔，没有任何空格。</li> <li>有关如何获取TsFile的信息，请参见https://github.com/apache/incubator-iotdb/tree/master/tsfile。</li></ul> <h2 id="_4-数据类型对应"><a href="#_4-数据类型对应" class="header-anchor">#</a> 4. 数据类型对应</h2> <table><thead><tr><th>TsFile数据类型</th> <th>SparkSQL数据类型</th></tr></thead> <tbody><tr><td>BOOLEAN</td> <td>BooleanType</td></tr> <tr><td>INT32</td> <td>IntegerType</td></tr> <tr><td>INT64</td> <td>LongType</td></tr> <tr><td>FLOAT</td> <td>FloatType</td></tr> <tr><td>DOUBLE</td> <td>DoubleType</td></tr> <tr><td>TEXT</td> <td>StringType</td></tr></tbody></table> <h2 id="_5-模式推断"><a href="#_5-模式推断" class="header-anchor">#</a> 5. 模式推断</h2> <p>显示TsFile的方式取决于架构。 以以下TsFile结构为例：TsFile模式中有三个度量：状态，温度和硬件。 这三种测量的基本信息如下：</p> <center><table style="text-align:center;"><tr><th colspan="2">名称</th><th colspan="2">类型</th><th colspan="2">编码</th></tr> <tr><td colspan="2">状态</td><td colspan="2">Boolean</td><td colspan="2">PLAIN</td></tr> <tr><td colspan="2">温度</td><td colspan="2">Float</td><td colspan="2">RLE</td></tr> <tr><td colspan="2">硬件</td><td colspan="2">Text</td><td colspan="2">PLAIN</td></tr></table></center> <p>TsFile中的现有数据如下：</p> <center><table style="text-align:center;"><tr><th colspan="4">device:root.ln.wf01.wt01</th><th colspan="4">device:root.ln.wf02.wt02</th></tr> <tr><th colspan="2">status</th><th colspan="2">temperature</th><th colspan="2">hardware</th><th colspan="2">status</th></tr> <tr><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th></tr> <tr><td>1</td><td>True</td><td>1</td><td>2.2</td><td>2</td><td>"aaa"</td><td>1</td><td>True</td></tr> <tr><td>3</td><td>True</td><td>2</td><td>2.2</td><td>4</td><td>"bbb"</td><td>2</td><td>False</td></tr> <tr><td>5</td><td> False </td><td>3</td><td>2.1</td><td>6</td><td>"ccc"</td><td>4</td><td>True</td></tr></table></center> <p>相应的SparkSQL表如下：</p> <table><thead><tr><th>time</th> <th>root.ln.wf02.wt02.temperature</th> <th>root.ln.wf02.wt02.status</th> <th>root.ln.wf02.wt02.hardware</th> <th>root.ln.wf01.wt01.temperature</th> <th>root.ln.wf01.wt01.status</th> <th>root.ln.wf01.wt01.hardware</th></tr></thead> <tbody><tr><td>1</td> <td>null</td> <td>true</td> <td>null</td> <td>2.2</td> <td>true</td> <td>null</td></tr> <tr><td>2</td> <td>null</td> <td>false</td> <td>aaa</td> <td>2.2</td> <td>null</td> <td>null</td></tr> <tr><td>3</td> <td>null</td> <td>null</td> <td>null</td> <td>2.1</td> <td>true</td> <td>null</td></tr> <tr><td>4</td> <td>null</td> <td>true</td> <td>bbb</td> <td>null</td> <td>null</td> <td>null</td></tr> <tr><td>5</td> <td>null</td> <td>null</td> <td>null</td> <td>null</td> <td>false</td> <td>null</td></tr> <tr><td>6</td> <td>null</td> <td>null</td> <td>ccc</td> <td>null</td> <td>null</td> <td>null</td></tr></tbody></table> <p>您还可以使用如下所示的窄表形式：（您可以参阅第6部分，了解如何使用窄表形式）</p> <table><thead><tr><th>time</th> <th>device_name</th> <th>status</th> <th>hardware</th> <th>temperature</th></tr></thead> <tbody><tr><td>1</td> <td>root.ln.wf02.wt01</td> <td>true</td> <td>null</td> <td>2.2</td></tr> <tr><td>1</td> <td>root.ln.wf02.wt02</td> <td>true</td> <td>null</td> <td>null</td></tr> <tr><td>2</td> <td>root.ln.wf02.wt01</td> <td>null</td> <td>null</td> <td>2.2</td></tr> <tr><td>2</td> <td>root.ln.wf02.wt02</td> <td>false</td> <td>aaa</td> <td>null</td></tr> <tr><td>3</td> <td>root.ln.wf02.wt01</td> <td>true</td> <td>null</td> <td>2.1</td></tr> <tr><td>4</td> <td>root.ln.wf02.wt02</td> <td>true</td> <td>bbb</td> <td>null</td></tr> <tr><td>5</td> <td>root.ln.wf02.wt01</td> <td>false</td> <td>null</td> <td>null</td></tr> <tr><td>6</td> <td>root.ln.wf02.wt02</td> <td>null</td> <td>ccc</td> <td>null</td></tr></tbody></table> <h2 id="_6-scala-api"><a href="#_6-scala-api" class="header-anchor">#</a> 6. Scala API</h2> <p>注意：请记住预先分配必要的读写权限。</p> <h3 id="示例1-从本地文件系统读取"><a href="#示例1-从本地文件系统读取" class="header-anchor">#</a> 示例1：从本地文件系统读取</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> wide_df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"test.tsfile"</span><span class="token punctuation">)</span> |
| wide_df<span class="token punctuation">.</span>show |
| |
| <span class="token keyword">val</span> narrow_df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"test.tsfile"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| narrow_df<span class="token punctuation">.</span>show |
| </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="示例2-从hadoop文件系统读取"><a href="#示例2-从hadoop文件系统读取" class="header-anchor">#</a> 示例2：从hadoop文件系统读取</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> wide_df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">)</span> |
| wide_df<span class="token punctuation">.</span>show |
| |
| <span class="token keyword">val</span> narrow_df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| narrow_df<span class="token punctuation">.</span>show |
| </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="示例3-从特定目录读取"><a href="#示例3-从特定目录读取" class="header-anchor">#</a> 示例3：从特定目录读取</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/usr/hadoop"</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>show |
| </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>注1：现在不支持目录中所有TsFile的全局时间排序。</p> <p>注2：具有相同名称的度量应具有相同的架构。</p> <h3 id="示例4-广泛形式的查询"><a href="#示例4-广泛形式的查询" class="header-anchor">#</a> 示例4：广泛形式的查询</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">"tsfile_table"</span><span class="token punctuation">)</span> |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>sql<span class="token punctuation">(</span><span class="token string">"select * from tsfile_table where `device_1.sensor_1`>0 and `device_1.sensor_2` < 22"</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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></div></div><div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">"tsfile_table"</span><span class="token punctuation">)</span> |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>sql<span class="token punctuation">(</span><span class="token string">"select count(*) from tsfile_table"</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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></div></div><h3 id="示例5-缩小形式的查询"><a href="#示例5-缩小形式的查询" class="header-anchor">#</a> 示例5：缩小形式的查询</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">"tsfile_table"</span><span class="token punctuation">)</span> |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>sql<span class="token punctuation">(</span><span class="token string">"select * from tsfile_table where device_name = 'root.ln.wf02.wt02' and temperature > 5"</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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></div></div><div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">"tsfile_table"</span><span class="token punctuation">)</span> |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>sql<span class="token punctuation">(</span><span class="token string">"select count(*) from tsfile_table"</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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></div></div><h3 id="例6-写宽格式"><a href="#例6-写宽格式" class="header-anchor">#</a> 例6：写宽格式</h3> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token comment">// we only support wide_form table to write</span> |
| <span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>show |
| df<span class="token punctuation">.</span>write<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/output"</span><span class="token punctuation">)</span> |
| |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/output"</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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><h2 id="例6-写窄格式"><a href="#例6-写窄格式" class="header-anchor">#</a> 例6：写窄格式</h2> <div class="language-scala line-numbers-mode"><pre class="language-scala"><code><span class="token comment">// we only support wide_form table to write</span> |
| <span class="token keyword">import</span> <span class="token namespace">org<span class="token punctuation">.</span>apache<span class="token punctuation">.</span>iotdb<span class="token punctuation">.</span>spark<span class="token punctuation">.</span>tsfile<span class="token punctuation">.</span></span>_ |
| |
| <span class="token keyword">val</span> df <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/test.tsfile"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| df<span class="token punctuation">.</span>show |
| df<span class="token punctuation">.</span>write<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/output"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| |
| <span class="token keyword">val</span> newDf <span class="token operator">=</span> spark<span class="token punctuation">.</span>read<span class="token punctuation">.</span>tsfile<span class="token punctuation">(</span><span class="token string">"hdfs://localhost:9000/output"</span><span class="token punctuation">,</span> <span class="token boolean">true</span><span class="token punctuation">)</span> |
| newDf<span class="token punctuation">.</span>show |
| </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><h2 id="附录a-模式推断的旧设计"><a href="#附录a-模式推断的旧设计" class="header-anchor">#</a> 附录A：模式推断的旧设计</h2> <p>显示TsFile的方式与TsFile Schema有关。 以以下TsFile结构为例：TsFile架构中有三个度量：状态，温度和硬件。 这三个度量的基本信息如下：</p> <center><table style="text-align:center;"><tr><th colspan="2">名称</th><th colspan="2">类型</th><th colspan="2">编码</th></tr> <tr><td colspan="2">状态</td><td colspan="2">Boolean</td><td colspan="2">PLAIN</td></tr> <tr><td colspan="2">温度</td><td colspan="2">Float</td><td colspan="2">RLE</td></tr> <tr><td colspan="2">硬件</td><td colspan="2">Text</td><td colspan="2">PLAIN</td></tr></table> <span>测量的基本信息</span></center> <p>文件中的现有数据如下：</p> <center><table style="text-align:center;"><tr><th colspan="4">delta\_object:root.ln.wf01.wt01</th><th colspan="4">delta\_object:root.ln.wf02.wt02</th><th colspan="4">delta\_object:root.sgcc.wf03.wt01</th></tr> <tr><th colspan="2">status</th><th colspan="2">temperature</th><th colspan="2">hardware</th><th colspan="2">status</th><th colspan="2">status</th><th colspan="2">temperature</th></tr> <tr><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th><th>time</th><th>value</th></tr> <tr><td>1</td><td>True</td><td>1</td><td>2.2</td><td>2</td><td>"aaa"</td><td>1</td><td>True</td><td>2</td><td>True</td><td>3</td><td>3.3</td></tr> <tr><td>3</td><td>True</td><td>2</td><td>2.2</td><td>4</td><td>"bbb"</td><td>2</td><td>False</td><td>3</td><td>True</td><td>6</td><td>6.6</td></tr> <tr><td>5</td><td> False </td><td>3</td><td>2.1</td><td>6</td><td>"ccc"</td><td>4</td><td>True</td><td>4</td><td>True</td><td>8</td><td>8.8</td></tr> <tr><td>7</td><td> True </td><td>4</td><td>2.0</td><td>8</td><td>"ddd"</td><td>5</td><td>False</td><td>6</td><td>True</td><td>9</td><td>9.9</td></tr></table> <span>一组时间序列数据</span></center> <p>有两种显示方法：</p> <h4 id="默认方式"><a href="#默认方式" class="header-anchor">#</a> 默认方式</h4> <p>将创建两列来存储设备的完整路径：time（LongType）和delta_object（StringType）。</p> <ul><li><code>time</code>：时间戳记，LongType</li> <li><code>delta_object</code>：Delta_object ID，StringType</li></ul> <p>接下来，为每个度量创建一列以存储特定数据。 SparkSQL表结构如下：</p> <center><table style="text-align:center;"><tr><th>time(LongType)</th><th> delta\_object(StringType)</th><th>status(BooleanType)</th><th>temperature(FloatType)</th><th>hardware(StringType)</th></tr> <tr><td>1</td><td> root.ln.wf01.wt01 </td><td>True</td><td>2.2</td><td>null</td></tr> <tr><td>1</td><td> root.ln.wf02.wt02 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>2</td><td> root.ln.wf01.wt01 </td><td>null</td><td>2.2</td><td>null</td></tr> <tr><td>2</td><td> root.ln.wf02.wt02 </td><td>False</td><td>null</td><td>"aaa"</td></tr> <tr><td>2</td><td> root.sgcc.wf03.wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>3</td><td> root.ln.wf01.wt01 </td><td>True</td><td>2.1</td><td>null</td></tr> <tr><td>3</td><td> root.sgcc.wf03.wt01 </td><td>True</td><td>3.3</td><td>null</td></tr> <tr><td>4</td><td> root.ln.wf01.wt01 </td><td>null</td><td>2.0</td><td>null</td></tr> <tr><td>4</td><td> root.ln.wf02.wt02 </td><td>True</td><td>null</td><td>"bbb"</td></tr> <tr><td>4</td><td> root.sgcc.wf03.wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> root.ln.wf01.wt01 </td><td>False</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> root.ln.wf02.wt02 </td><td>False</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> root.sgcc.wf03.wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>6</td><td> root.ln.wf02.wt02 </td><td>null</td><td>null</td><td>"ccc"</td></tr> <tr><td>6</td><td> root.sgcc.wf03.wt01 </td><td>null</td><td>6.6</td><td>null</td></tr> <tr><td>7</td><td> root.ln.wf01.wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>8</td><td> root.ln.wf02.wt02 </td><td>null</td><td>null</td><td>"ddd"</td></tr> <tr><td>8</td><td> root.sgcc.wf03.wt01 </td><td>null</td><td>8.8</td><td>null</td></tr> <tr><td>9</td><td> root.sgcc.wf03.wt01 </td><td>null</td><td>9.9</td><td>null</td></tr></table></center> <h4 id="展开delta-object列"><a href="#展开delta-object列" class="header-anchor">#</a> 展开delta_object列</h4> <p>通过“。”将设备列展开为多个列，忽略根目录“root”。方便进行更丰富的聚合操作。如果用户想使用这种显示方式，需要在表创建语句中设置参数“delta_object_name”(参考本手册5.1节中的示例5)，在本例中，将参数“delta_object_name”设置为“root.device.turbine”。路径层的数量必须是一对一的。此时，除了“根”层之外，为设备路径的每一层创建一列。列名是参数中的名称，值是设备相应层的名称。接下来，将为每个度量创建一个列来存储特定的数据。</p> <p>那么SparkSQL表结构如下:</p> <center><table style="text-align:center;"><tr><th>time(LongType)</th><th> group(StringType)</th><th> field(StringType)</th><th> device(StringType)</th><th>status(BooleanType)</th><th>temperature(FloatType)</th><th>hardware(StringType)</th></tr> <tr><td>1</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>True</td><td>2.2</td><td>null</td></tr> <tr><td>1</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>2</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>null</td><td>2.2</td><td>null</td></tr> <tr><td>2</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>False</td><td>null</td><td>"aaa"</td></tr> <tr><td>2</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>3</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>True</td><td>2.1</td><td>null</td></tr> <tr><td>3</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>True</td><td>3.3</td><td>null</td></tr> <tr><td>4</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>null</td><td>2.0</td><td>null</td></tr> <tr><td>4</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>True</td><td>null</td><td>"bbb"</td></tr> <tr><td>4</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>False</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>False</td><td>null</td><td>null</td></tr> <tr><td>5</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>6</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>null</td><td>null</td><td>"ccc"</td></tr> <tr><td>6</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>null</td><td>6.6</td><td>null</td></tr> <tr><td>7</td><td> ln </td><td> wf01 </td><td> wt01 </td><td>True</td><td>null</td><td>null</td></tr> <tr><td>8</td><td> ln </td><td> wf02 </td><td> wt02 </td><td>null</td><td>null</td><td>"ddd"</td></tr> <tr><td>8</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>null</td><td>8.8</td><td>null</td></tr> <tr><td>9</td><td> sgcc </td><td> wf03 </td><td> wt01 </td><td>null</td><td>9.9</td><td>null</td></tr></table></center> <p>TsFile-Spark-Connector可以通过SparkSQL在SparkSQL中以表的形式显示一个或多个tsfile。它还允许用户指定一个目录或使用通配符来匹配多个目录。如果有多个tsfile，那么所有tsfile中的度量值的并集将保留在表中，并且具有相同名称的度量值在默认情况下具有相同的数据类型。注意，如果存在名称相同但数据类型不同的情况，TsFile-Spark-Connector将不能保证结果的正确性。</p> <p>写入过程是将数据aframe写入一个或多个tsfile。默认情况下，需要包含两个列:time和delta_object。其余的列用作测量。如果用户希望将第二个表结构写回TsFile，可以设置“delta_object_name”参数(请参阅本手册5.1节的5.1节)。</p> <h2 id="附录b-旧注"><a href="#附录b-旧注" class="header-anchor">#</a> 附录B：旧注</h2> <p>注意：检查Spark根目录中的jar软件包，并将libthrift-0.9.2.jar和libfb303-0.9.2.jar分别替换为libthrift-0.9.1.jar和libfb303-0.9.1.jar。</p></div> <div class="page-nav"><p class="inner"><span class="prev"> |
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