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href="/zh/UserGuide/V1.1.x/Ecosystem-Integration/Spark-TsFile.html#system-requirements" class="router-link-active router-link-exact-active toc-link level3">System Requirements</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V1.1.x/Ecosystem-Integration/Spark-TsFile.html#快速开始" class="router-link-active router-link-exact-active toc-link level3">快速开始</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V1.1.x/Ecosystem-Integration/Spark-TsFile.html#数据类型对应" class="router-link-active router-link-exact-active toc-link level3">数据类型对应</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V1.1.x/Ecosystem-Integration/Spark-TsFile.html#模式推断" class="router-link-active router-link-exact-active toc-link level3">模式推断</a></li><!----><!--]--><!--[--><li class="toc-item"><a aria-current="page" href="/zh/UserGuide/V1.1.x/Ecosystem-Integration/Spark-TsFile.html#scala-api" 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 --><h2 id="spark-tsfile" tabindex="-1"><a class="header-anchor" href="#spark-tsfile" aria-hidden="true">#</a> Spark-TsFile</h2><h3 id="about-tsfile-spark-connector" tabindex="-1"><a class="header-anchor" href="#about-tsfile-spark-connector" aria-hidden="true">#</a> About TsFile-Spark-Connector</h3><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><h3 id="system-requirements" tabindex="-1"><a class="header-anchor" href="#system-requirements" aria-hidden="true">#</a> System Requirements</h3><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>1.0.0</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：<a href="https://github.com/apache/iotdb/tree/master/tsfile" target="_blank" rel="noopener noreferrer">https://github.com/apache/iotdb/tree/master/tsfile<span><svg class="external-link-icon" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" focusable="false" x="0px" y="0px" viewBox="0 0 100 100" width="15" height="15"><path fill="currentColor" d="M18.8,85.1h56l0,0c2.2,0,4-1.8,4-4v-32h-8v28h-48v-48h28v-8h-32l0,0c-2.2,0-4,1.8-4,4v56C14.8,83.3,16.6,85.1,18.8,85.1z"></path><polygon fill="currentColor" points="45.7,48.7 51.3,54.3 77.2,28.5 77.2,37.2 85.2,37.2 85.2,14.9 62.8,14.9 62.8,22.9 71.5,22.9"></polygon></svg><span class="external-link-icon-sr-only">open in new window</span></span></a> 注意：spark 版本目前仅支持 2.4.3, 其他版本可能存在不适配的问题，目前已知 2.4.7 的版本存在不适配的问题</p></blockquote><h3 id="快速开始" tabindex="-1"><a class="header-anchor" href="#快速开始" aria-hidden="true">#</a> 快速开始</h3><h4 id="本地模式" tabindex="-1"><a class="header-anchor" href="#本地模式" aria-hidden="true">#</a> 本地模式</h4><p>在本地模式下使用 TsFile-Spark-Connector 启动 Spark：</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>./&lt;spark-shell-path&gt;  --jars  tsfile-spark-connector.jar,tsfile-{version}-jar-with-dependencies.jar,hadoop-tsfile-{version}-jar-with-dependencies.jar
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><ul><li>&lt;spark-shell-path&gt;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 <a href="https://github.com/apache/iotdb/tree/master/tsfile%E3%80%82" target="_blank" rel="noopener noreferrer">https://github.com/apache/iotdb/tree/master/tsfile。<span><svg class="external-link-icon" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" focusable="false" x="0px" y="0px" viewBox="0 0 100 100" width="15" height="15"><path fill="currentColor" d="M18.8,85.1h56l0,0c2.2,0,4-1.8,4-4v-32h-8v28h-48v-48h28v-8h-32l0,0c-2.2,0-4,1.8-4,4v56C14.8,83.3,16.6,85.1,18.8,85.1z"></path><polygon fill="currentColor" points="45.7,48.7 51.3,54.3 77.2,28.5 77.2,37.2 85.2,37.2 85.2,14.9 62.8,14.9 62.8,22.9 71.5,22.9"></polygon></svg><span class="external-link-icon-sr-only">open in new window</span></span></a></li><li>获取到 dependency 包：<code>mvn clean package -DskipTests -P get-jar-with-dependencies</code></li></ul><h4 id="分布式模式" tabindex="-1"><a class="header-anchor" href="#分布式模式" aria-hidden="true">#</a> 分布式模式</h4><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-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>. /&lt;spark-shell-path&gt;   --jars  tsfile-spark-connector.jar,tsfile-{version}-jar-with-dependencies.jar,hadoop-tsfile-{version}-jar-with-dependencies.jar  --master spark://ip:7077
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>注意：</p><ul><li>&lt;spark-shell-path&gt;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 <a href="https://github.com/apache/iotdb/tree/master/tsfile%E3%80%82" target="_blank" rel="noopener noreferrer">https://github.com/apache/iotdb/tree/master/tsfile。<span><svg class="external-link-icon" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" focusable="false" x="0px" y="0px" viewBox="0 0 100 100" width="15" height="15"><path fill="currentColor" d="M18.8,85.1h56l0,0c2.2,0,4-1.8,4-4v-32h-8v28h-48v-48h28v-8h-32l0,0c-2.2,0-4,1.8-4,4v56C14.8,83.3,16.6,85.1,18.8,85.1z"></path><polygon fill="currentColor" points="45.7,48.7 51.3,54.3 77.2,28.5 77.2,37.2 85.2,37.2 85.2,14.9 62.8,14.9 62.8,22.9 71.5,22.9"></polygon></svg><span class="external-link-icon-sr-only">open in new window</span></span></a></li></ul><h3 id="数据类型对应" tabindex="-1"><a class="header-anchor" href="#数据类型对应" aria-hidden="true">#</a> 数据类型对应</h3><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><h3 id="模式推断" tabindex="-1"><a class="header-anchor" href="#模式推断" aria-hidden="true">#</a> 模式推断</h3><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><table><thead><tr><th>名称</th><th>类型</th><th>编码</th></tr></thead><tbody><tr><td>状态</td><td>Boolean</td><td>PLAIN</td></tr><tr><td>温度</td><td>Float</td><td>RLE</td></tr><tr><td>硬件</td><td>Text</td><td>PLAIN</td></tr></tbody></table><p>TsFile 中的现有数据如下：</p><ul><li>d1:root.ln.wf01.wt01</li><li>d2:root.ln.wf02.wt02</li></ul><table><thead><tr><th style="text-align:left;">time</th><th style="text-align:left;">d1.status</th><th style="text-align:left;">time</th><th style="text-align:left;">d1.temperature</th><th style="text-align:left;">time</th><th style="text-align:left;">d2.hardware</th><th style="text-align:left;">time</th><th style="text-align:left;">d2.status</th></tr></thead><tbody><tr><td style="text-align:left;">1</td><td style="text-align:left;">True</td><td style="text-align:left;">1</td><td style="text-align:left;">2.2</td><td style="text-align:left;">2</td><td style="text-align:left;">&quot;aaa&quot;</td><td style="text-align:left;">1</td><td style="text-align:left;">True</td></tr><tr><td style="text-align:left;">3</td><td style="text-align:left;">True</td><td style="text-align:left;">2</td><td style="text-align:left;">2.2</td><td style="text-align:left;">4</td><td style="text-align:left;">&quot;bbb&quot;</td><td style="text-align:left;">2</td><td style="text-align:left;">False</td></tr><tr><td style="text-align:left;">5</td><td style="text-align:left;">False</td><td style="text-align:left;">3</td><td style="text-align:left;">2.1</td><td style="text-align:left;">6</td><td style="text-align:left;">&quot;ccc&quot;</td><td style="text-align:left;">4</td><td style="text-align:left;">True</td></tr></tbody></table><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><h3 id="scala-api" tabindex="-1"><a class="header-anchor" href="#scala-api" aria-hidden="true">#</a> Scala API</h3><p>注意：请记住预先分配必要的读写权限。</p><ul><li>示例 1：从本地文件系统读取</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;test.tsfile&quot;</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">&quot;test.tsfile&quot;</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" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><ul><li>示例 2：从 hadoop 文件系统读取</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><ul><li>示例 3：从特定目录读取</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/usr/hadoop&quot;</span><span class="token punctuation">)</span>
 df<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></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><ul><li>示例 4：广泛形式的查询</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</span><span class="token punctuation">)</span>
 df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">&quot;tsfile_table&quot;</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">&quot;select * from tsfile_table where `device_1.sensor_1`&gt;0 and `device_1.sensor_2` &lt; 22&quot;</span><span class="token punctuation">)</span>
 newDf<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</span><span class="token punctuation">)</span>
 df<span class="token punctuation">.</span>createOrReplaceTempView<span class="token punctuation">(</span><span class="token string">&quot;tsfile_table&quot;</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">&quot;select count(*) from tsfile_table&quot;</span><span class="token punctuation">)</span>
 newDf<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><ul><li>示例 5：缩小形式的查询</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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">&quot;tsfile_table&quot;</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">&quot;select * from tsfile_table where device_name = &#39;root.ln.wf02.wt02&#39; and temperature &gt; 5&quot;</span><span class="token punctuation">)</span>
 newDf<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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">&quot;tsfile_table&quot;</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">&quot;select count(*) from tsfile_table&quot;</span><span class="token punctuation">)</span>
 newDf<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><ul><li>例 6：写宽格式</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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">&quot;hdfs://localhost:9000/output&quot;</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">&quot;hdfs://localhost:9000/output&quot;</span><span class="token punctuation">)</span>
 newDf<span class="token punctuation">.</span>show
 </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><ul><li>例 7：写窄格式</li></ul><div class="language-scala line-numbers-mode" data-ext="scala"><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">&quot;hdfs://localhost:9000/test.tsfile&quot;</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">&quot;hdfs://localhost:9000/output&quot;</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">&quot;hdfs://localhost:9000/output&quot;</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" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>附录 A：模式推断的旧设计</p><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><table><thead><tr><th>名称</th><th>类型</th><th>编码</th></tr></thead><tbody><tr><td>状态</td><td>Boolean</td><td>PLAIN</td></tr><tr><td>温度</td><td>Float</td><td>RLE</td></tr><tr><td>硬件</td><td>Text</td><td>PLAIN</td></tr></tbody></table><p>文件中的现有数据如下：</p><ul><li>delta_object1: root.ln.wf01.wt01</li><li>delta_object2: root.ln.wf02.wt02</li><li>delta_object3: :root.sgcc.wf03.wt01</li></ul><table><thead><tr><th style="text-align:left;">time</th><th style="text-align:left;">delta_object1.status</th><th style="text-align:left;">time</th><th style="text-align:left;">delta_object1.temperature</th><th style="text-align:left;">time</th><th style="text-align:left;">delta_object2.hardware</th><th style="text-align:left;">time</th><th style="text-align:left;">delta_object2.status</th><th style="text-align:left;">time</th><th style="text-align:left;">delta_object3.status</th><th style="text-align:left;">time</th><th style="text-align:left;">delta_object3.temperature</th></tr></thead><tbody><tr><td style="text-align:left;">1</td><td style="text-align:left;">True</td><td style="text-align:left;">1</td><td style="text-align:left;">2.2</td><td style="text-align:left;">2</td><td style="text-align:left;">&quot;aaa&quot;</td><td style="text-align:left;">1</td><td style="text-align:left;">True</td><td style="text-align:left;">2</td><td style="text-align:left;">True</td><td style="text-align:left;">3</td><td style="text-align:left;">3.3</td></tr><tr><td style="text-align:left;">3</td><td style="text-align:left;">True</td><td style="text-align:left;">2</td><td style="text-align:left;">2.2</td><td style="text-align:left;">4</td><td style="text-align:left;">&quot;bbb&quot;</td><td style="text-align:left;">2</td><td style="text-align:left;">False</td><td style="text-align:left;">3</td><td style="text-align:left;">True</td><td style="text-align:left;">6</td><td style="text-align:left;">6.6</td></tr><tr><td style="text-align:left;">5</td><td style="text-align:left;">False</td><td style="text-align:left;">3</td><td style="text-align:left;">2.1</td><td style="text-align:left;">6</td><td style="text-align:left;">&quot;ccc&quot;</td><td style="text-align:left;">4</td><td style="text-align:left;">True</td><td style="text-align:left;">4</td><td style="text-align:left;">True</td><td style="text-align:left;">8</td><td style="text-align:left;">8.8</td></tr><tr><td style="text-align:left;">7</td><td style="text-align:left;">True</td><td style="text-align:left;">4</td><td style="text-align:left;">2.0</td><td style="text-align:left;">8</td><td style="text-align:left;">&quot;ddd&quot;</td><td style="text-align:left;">5</td><td style="text-align:left;">False</td><td style="text-align:left;">6</td><td style="text-align:left;">True</td><td style="text-align:left;">9</td><td style="text-align:left;">9.9</td></tr></tbody></table><p>有两种显示方法：</p><ul><li>默认方式</li></ul><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><table><thead><tr><th>time(LongType)</th><th>delta_object(StringType)</th><th>status(BooleanType)</th><th>temperature(FloatType)</th><th>hardware(StringType)</th></tr></thead><tbody><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>&quot;aaa&quot;</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>&quot;bbb&quot;</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>&quot;ccc&quot;</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>&quot;ddd&quot;</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></tbody></table><ul><li>展开 delta_object 列</li></ul><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><table><thead><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></thead><tbody><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>&quot;aaa&quot;</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>&quot;bbb&quot;</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>&quot;ccc&quot;</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>&quot;ddd&quot;</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></tbody></table><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><p>附录 B：旧注</p><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><!----><footer class="page-meta"><div class="meta-item edit-link"><a href="https://github.com/apache/iotdb/edit/rel/1.1/docs/zh/UserGuide/Ecosystem-Integration/Spark-TsFile.md" rel="noopener noreferrer" target="_blank" aria-label="发现错误？在 GitHub 上编辑此页" class="nav-link label"><!--[--><svg xmlns="http://www.w3.org/2000/svg" class="icon edit-icon" viewBox="0 0 1024 1024" fill="currentColor" aria-label="edit icon"><path d="M430.818 653.65a60.46 60.46 0 0 1-50.96-93.281l71.69-114.012 7.773-10.365L816.038 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