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    gitHub
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<ul><li>什么是TsFile的Hive连接器</li> <li>系统环境要求</li> <li>数据类型对应关系</li> <li>为Hive添加依赖jar包</li> <li>创建Tsfile-backed的Hive表</li> <li>从Tsfile-backed的Hive表中查询
<ul><li>选择查询语句示例</li> <li>聚合查询语句示例</li></ul></li> <li>后续工作</li></ul></li></ul> <h2 id="什么是tsfile的hive连接器"><a href="#什么是tsfile的hive连接器" class="header-anchor">#</a> 什么是TsFile的Hive连接器</h2> <p>TsFile的Hive连接器实现了对Hive读取外部Tsfile类型的文件格式的支持，
使用户能够通过Hive操作Tsfile。</p> <p>有了这个连接器，用户可以</p> <ul><li>将单个Tsfile文件加载进Hive，不论文件是存储在本地文件系统或者是HDFS中</li> <li>将某个特定目录下的所有文件加载进Hive，不论文件是存储在本地文件系统或者是HDFS中</li> <li>使用HQL查询tsfile</li> <li>到现在为止, 写操作在hive-connector中还没有被支持. 所以, HQL中的insert操作是不被允许的</li></ul> <h2 id="系统环境要求"><a href="#系统环境要求" class="header-anchor">#</a> 系统环境要求</h2> <table><thead><tr><th>Hadoop Version</th> <th>Hive Version</th> <th>Java Version</th> <th>TsFile</th></tr></thead> <tbody><tr><td><code>2.7.3</code> or <code>3.2.1</code></td> <td><code>2.3.6</code> or <code>3.1.2</code></td> <td><code>1.8</code></td> <td><code>0.10.0</code></td></tr></tbody></table> <blockquote><p>注意：关于如何下载和使用Tsfile, 请参考以下链接: <a href="https://github.com/apache/incubator-iotdb/tree/master/tsfile" target="_blank" rel="noopener noreferrer">https://github.com/apache/incubator-iotdb/tree/master/tsfile<svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" 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></a>。</p></blockquote> <h2 id="数据类型对应关系"><a href="#数据类型对应关系" class="header-anchor">#</a> 数据类型对应关系</h2> <table><thead><tr><th>TsFile 数据类型</th> <th>Hive 数据类型</th></tr></thead> <tbody><tr><td>BOOLEAN</td> <td>Boolean</td></tr> <tr><td>INT32</td> <td>INT</td></tr> <tr><td>INT64</td> <td>BIGINT</td></tr> <tr><td>FLOAT</td> <td>Float</td></tr> <tr><td>DOUBLE</td> <td>Double</td></tr> <tr><td>TEXT</td> <td>STRING</td></tr></tbody></table> <h2 id="为hive添加依赖jar包"><a href="#为hive添加依赖jar包" class="header-anchor">#</a> 为Hive添加依赖jar包</h2> <p>为了在Hive中使用Tsfile的hive连接器，我们需要把hive连接器的jar导入进hive。</p> <p>从 <a href="https://github.com/apache/incubator-iotdb" target="_blank" rel="noopener noreferrer">https://github.com/apache/incubator-iotdb<svg xmlns="http://www.w3.org/2000/svg" aria-hidden="true" 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></a>下载完iotdb后, 你可以使用 <code>mvn clean package -pl hive-connector -am -Dmaven.test.skip=true</code>命令得到一个 <code>hive-connector-X.X.X-SNAPSHOT-jar-with-dependencies.jar</code>。</p> <p>然后在hive的命令行中，使用<code>add jar XXX</code>命令添加依赖。例如:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>hive&gt; add jar /Users/hive/incubator-iotdb/hive-connector/target/hive-connector-0.10.0-SNAPSHOT-jar-with-dependencies.jar;

Added [/Users/hive/incubator-iotdb/hive-connector/target/hive-connector-0.10.0-SNAPSHOT-jar-with-dependencies.jar] to class path
Added resources: [/Users/hive/incubator-iotdb/hive-connector/target/hive-connector-0.10.0-SNAPSHOT-jar-with-dependencies.jar]
</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><h2 id="创建tsfile-backed的hive表"><a href="#创建tsfile-backed的hive表" class="header-anchor">#</a> 创建Tsfile-backed的Hive表</h2> <p>为了创建一个Tsfile-backed的表，需要将<code>serde</code>指定为<code>org.apache.iotdb.hive.TsFileSerDe</code>，
将<code>inputformat</code>指定为<code>org.apache.iotdb.hive.TSFHiveInputFormat</code>，
将<code>outputformat</code>指定为<code>org.apache.iotdb.hive.TSFHiveOutputFormat</code>。</p> <p>同时要提供一个只包含两个字段的Schema，这两个字段分别是<code>time_stamp</code>和<code>sensor_id</code>。
<code>time_stamp</code>代表的是时间序列的时间值，<code>sensor_id</code>是你想要从tsfile文件中提取出来分析的传感器名称，比如说<code>sensor_1</code>。
表的名字可以是hive所支持的任何表名。</p> <p>需要提供一个路径供hive-connector从其中拉取最新的数据。</p> <p>这个路径必须是一个指定的文件夹，这个文件夹可以在你的本地文件系统上，也可以在HDFS上，如果你启动了Hadoop的话。
如果是本地文件系统，要以这样的形式<code>file:///data/data/sequence/root.baic2.WWS.leftfrontdoor/</code></p> <p>最后需要在<code>TBLPROPERTIES</code>里指明<code>device_id</code></p> <p>例如：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>CREATE EXTERNAL TABLE IF NOT EXISTS only_sensor_1(
  time_stamp TIMESTAMP,
  sensor_1 BIGINT)
ROW FORMAT SERDE 'org.apache.iotdb.hive.TsFileSerDe'
STORED AS
  INPUTFORMAT 'org.apache.iotdb.hive.TSFHiveInputFormat'
  OUTPUTFORMAT 'org.apache.iotdb.hive.TSFHiveOutputFormat'
LOCATION '/data/data/sequence/root.baic2.WWS.leftfrontdoor/'
TBLPROPERTIES ('device_id'='root.baic2.WWS.leftfrontdoor.plc1');
</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>在这个例子里，我们从<code>/data/data/sequence/root.baic2.WWS.leftfrontdoor/</code>中拉取<code>root.baic2.WWS.leftfrontdoor.plc1.sensor_1</code>的数据。
这个表可能产生如下描述：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>hive&gt; describe only_sensor_1;
OK
time_stamp          	timestamp              	from deserializer
sensor_1            	bigint              	from deserializer
Time taken: 0.053 seconds, Fetched: 2 row(s)
</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><p>到目前为止, Tsfile-backed的表已经可以像hive中其他表一样被操作了。</p> <h2 id="从tsfile-backed的hive表中查询"><a href="#从tsfile-backed的hive表中查询" class="header-anchor">#</a> 从Tsfile-backed的Hive表中查询</h2> <p>在做任何查询之前，我们需要通过如下命令，在hive中设置<code>hive.input.format</code>：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>hive&gt; set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
</code></pre> <div class="line-numbers-wrapper"><span class="line-number">1</span><br></div></div><p>现在，我们已经在hive中有了一个名为<code>only_sensor_1</code>的外部表。
我们可以使用HQL做任何查询来分析其中的数据。</p> <p>例如:</p> <h3 id="选择查询语句示例"><a href="#选择查询语句示例" class="header-anchor">#</a> 选择查询语句示例</h3> <div class="language- line-numbers-mode"><pre class="language-text"><code>hive&gt; select * from only_sensor_1 limit 10;
OK
1	1000000
2	1000001
3	1000002
4	1000003
5	1000004
6	1000005
7	1000006
8	1000007
9	1000008
10	1000009
Time taken: 1.464 seconds, Fetched: 10 row(s)
</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><h3 id="聚合查询语句示例"><a href="#聚合查询语句示例" class="header-anchor">#</a> 聚合查询语句示例</h3> <div class="language- line-numbers-mode"><pre class="language-text"><code>hive&gt; select count(*) from only_sensor_1;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = jackietien_20191016202416_d1e3e233-d367-4453-b39a-2aac9327a3b6
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=&lt;number&gt;
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=&lt;number&gt;
In order to set a constant number of reducers:
  set mapreduce.job.reduces=&lt;number&gt;
Job running in-process (local Hadoop)
2019-10-16 20:24:18,305 Stage-1 map = 0%,  reduce = 0%
2019-10-16 20:24:27,443 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_local867757288_0002
MapReduce Jobs Launched:
Stage-Stage-1:  HDFS Read: 0 HDFS Write: 0 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
1000000
Time taken: 11.334 seconds, Fetched: 1 row(s)
</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></div></div><h2 id="后续工作"><a href="#后续工作" class="header-anchor">#</a> 后续工作</h2> <p>我们现在仅支持查询操作，写操作的支持还在开发中...</p></div> <div class="page-nav"><p class="inner"><span class="prev">
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      Disclaimer: Apache IoTDB (incubating) is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
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