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| <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>系统设计</span> <!----></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>应用概览</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>TsFile</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>查询引擎</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>元数据管理</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>存储引擎</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading open"><span>数据查询</span> <span class="arrow down"></span></p> <ul class="sidebar-links sidebar-group-items"><li><a href="/zh/SystemDesign/DataQuery/DataQuery.html" class="sidebar-link">数据查询</a></li><li><a href="/zh/SystemDesign/DataQuery/QueryFundamentals.html" class="sidebar-link">查询基础介绍</a></li><li><a href="/zh/SystemDesign/DataQuery/SeriesReader.html" class="sidebar-link">查询基础组件</a></li><li><a href="/zh/SystemDesign/DataQuery/RawDataQuery.html" class="sidebar-link">原始数据查询</a></li><li><a href="/zh/SystemDesign/DataQuery/AggregationQuery.html" class="sidebar-link">聚合查询</a></li><li><a href="/zh/SystemDesign/DataQuery/GroupByQuery.html" class="sidebar-link">降采样查询</a></li><li><a href="/zh/SystemDesign/DataQuery/LastQuery.html" class="sidebar-link">最近时间戳 Last 查询</a></li><li><a href="/zh/SystemDesign/DataQuery/AlignByDeviceQuery.html" class="sidebar-link">按设备对齐查询</a></li><li><a href="/zh/SystemDesign/DataQuery/FillFunction.html" class="sidebar-link">空值填充</a></li><li><a href="/zh/SystemDesign/DataQuery/GroupByFillQuery.html" aria-current="page" class="active sidebar-link">降采样补空值查询</a></li><li><a href="/zh/SystemDesign/DataQuery/OrderByTimeQuery.html" class="sidebar-link">按时间倒序查询</a></li></ul></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>工具</span> <span class="arrow right"></span></p> <!----></section></li><li><section class="sidebar-group collapsable depth-0"><p class="sidebar-heading"><span>连接器</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></ul> </aside> <main class="page"> <div class="content content__default"><h1 id="降采样补空值查询"><a href="#降采样补空值查询" class="header-anchor">#</a> 降采样补空值查询</h1> <p>GroupByFill 查询的主要逻辑在 <code>GroupByFillDataSet</code></p> <ul><li><code>org.apache.iotdb.db.query.dataset.groupby.GroupByFillDataSet</code></li></ul> <p>GroupByFill是对原降采样结果进行填充，目前仅支持使用前值填充的方式。</p> <ul><li>在Group By Fill中，Group by子句不支持滑动步长，否则抛异常</li> <li>Fill子句中仅能使用Previous和PREVIOUSUNTILLAST这两种插值方式，Linear不支持</li> <li>Previous和PREVIOUSUNTILLAST对fill的时间不做限制</li> <li>填充只针对last_value这一聚合函数，其他的函数不支持，如果其他函数的聚合值查询结果为null，依旧为null，不进行填充</li></ul> <h2 id="previousuntillast与previous填充的区别"><a href="#previousuntillast与previous填充的区别" class="header-anchor">#</a> PREVIOUSUNTILLAST与PREVIOUS填充的区别</h2> <p>Previous填充方式的语意没有变，只要前面有值，就可以拿过来填充； |
| PREVIOUSUNTILLAST考虑到在某些业务场景下，所填充的值的时间不能大于该时间序列last的时间戳（从业务角度考虑，取历史数据不能取未来历史数据） |
| 看下面的例子，或许更容易理解</p> <p>A点时间戳为1，B为5，C为20，D为30，N为8，M为38</p> <p>原始数据为<img src="https://user-images.githubusercontent.com/16079446/78784824-9f41ae00-79d8-11ea-9920-0825e081cae0.png" style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;"></p> <p><code>select temperature FROM root.ln.wf01.wt01 where time >= 1 and time <= 38</code></p> <table><thead><tr><th>Time</th> <th>root.ln.wf01.wt01.temperature</th></tr></thead> <tbody><tr><td>1</td> <td>21</td></tr> <tr><td>3</td> <td>23</td></tr> <tr><td>5</td> <td>25</td></tr> <tr><td>20</td> <td>26</td></tr> <tr><td>27</td> <td>29</td></tr> <tr><td>28</td> <td>30</td></tr> <tr><td>30</td> <td>40</td></tr></tbody></table> <p>当我们使用Previous插值方式时，即使D到M这一段是未来的数据，我们也会用D点的数据进行填充</p> <p><code>SELECT last_value(temperature) as last_temperature FROM root.ln.wf01.wt01 GROUP BY([8, 39), 5m) FILL (int32[previous])</code></p> <table><thead><tr><th>Time</th> <th>last_temperature</th></tr></thead> <tbody><tr><td>8</td> <td>25</td></tr> <tr><td>13</td> <td>25</td></tr> <tr><td>18</td> <td>26</td></tr> <tr><td>23</td> <td>29</td></tr> <tr><td>28</td> <td>40</td></tr> <tr><td>33</td> <td>40</td></tr> <tr><td>38</td> <td>40</td></tr></tbody></table> <p>当我们使用NONLASTPREVIOUS插值方式时，因为D到M这一段是未来的数据，我们不会进行插值，还是返回null</p> <p><code>SELECT last_value(temperature) as last_temperature FROM root.ln.wf01.wt01 GROUP BY([8, 39), 5m) FILL (int32[PREVIOUSUNTILLAST])</code></p> <table><thead><tr><th>Time</th> <th>last_temperature</th></tr></thead> <tbody><tr><td>8</td> <td>25</td></tr> <tr><td>13</td> <td>25</td></tr> <tr><td>18</td> <td>26</td></tr> <tr><td>23</td> <td>29</td></tr> <tr><td>28</td> <td>40</td></tr> <tr><td>33</td> <td>null</td></tr> <tr><td>38</td> <td>null</td></tr></tbody></table> <h2 id="核心查询逻辑"><a href="#核心查询逻辑" class="header-anchor">#</a> 核心查询逻辑</h2> <p>在<code>GroupByFillDataSet</code>中维护了两个主要变量</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>// the first value for each time series |
| private Object[] previousValue; |
| // last timestamp for each time series |
| private long[] lastTimeArray; |
| </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><h3 id="previousvalue"><a href="#previousvalue" class="header-anchor">#</a> <code>previousValue</code></h3> <p><code>previousValue</code>这个变量维护了当前时间窗口的前一个降采样值，在<code>GroupByFillDataSet</code>构造函数中调用了<code>initPreviousParis</code>方法对其进行初始化。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code> private void initPreviousParis(QueryContext context, GroupByFillPlan groupByFillPlan) |
| throws StorageEngineException, IOException, QueryProcessException { |
| previousValue = new Object[paths.size()]; |
| for (int i = 0; i < paths.size(); i++) { |
| Path path = paths.get(i); |
| TSDataType dataType = dataTypes.get(i); |
| IFill fill = new PreviousFill(dataType, groupByEngineDataSet.getStartTime(), -1L); |
| fill.constructReaders(path, groupByFillPlan.getAllMeasurementsInDevice(path.getDevice()), context); |
| |
| TimeValuePair timeValuePair = fill.getFillResult(); |
| if (timeValuePair == null || timeValuePair.getValue() == null) { |
| previousValue[i] = null; |
| } else { |
| previousValue[i] = timeValuePair.getValue().getValue(); |
| } |
| } |
| } |
| </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><code>initPreviousParis</code>方法主要为每个时间序列构造了一个单点补空值查询，<code>queryTime</code>设置为降采样时间窗口的起始值，<code>beforeRange</code>不作限制。</p> <h3 id="lasttimearray"><a href="#lasttimearray" class="header-anchor">#</a> <code>lastTimeArray</code></h3> <p><code>lastTimeArray</code>这个变量维护了每个时间序列的最近时间戳值，主要用于<code>PREVIOUSUNTILLAST</code>这一填充方式，在<code>GroupByFillDataSet</code>构造函数中调用了<code>initLastTimeArray</code>方法对其进行初始化。</p> <div class="language- line-numbers-mode"><pre class="language-text"><code> private void initLastTimeArray(QueryContext context) |
| throws IOException, StorageEngineException, QueryProcessException { |
| lastTimeArray = new long[paths.size()]; |
| Arrays.fill(lastTimeArray, Long.MAX_VALUE); |
| for (int i = 0; i < paths.size(); i++) { |
| TimeValuePair lastTimeValuePair = |
| LastQueryExecutor.calculateLastPairForOneSeries(paths.get(i), dataTypes.get(i), context); |
| if (lastTimeValuePair.getValue() != null) { |
| lastTimeArray[i] = lastTimeValuePair.getTimestamp(); |
| } |
| } |
| } |
| </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><code>initPreviousParis</code>方法主要为每个时间序列构造了一个最近时间戳 Last 查询</p> <h3 id="填充过程"><a href="#填充过程" class="header-anchor">#</a> 填充过程</h3> <p>填充过程在<code>nextWithoutConstraint</code>方法中完成，主要逻辑如下：</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>protected RowRecord nextWithoutConstraint() throws IOException { |
| |
| // 首先通过groupByEngineDataSet，获得原始的降采样查询结果行 |
| RowRecord rowRecord = groupByEngineDataSet.nextWithoutConstraint(); |
| |
| // 接下来对每个时间序列判断需不需要填充 |
| for (int i = 0; i < paths.size(); i++) { |
| Field field = rowRecord.getFields().get(i); |
| // 当前值为null，需要进行填充 |
| if (field.getDataType() == null) { |
| // 当前一个值不为null 并且 (填充方式不是PREVIOUSUNTILLAST 或者 当前时间小于改时间序列的最近时间戳) |
| if (previousValue[i] != null |
| && (!((PreviousFill) fillTypes.get(dataTypes.get(i))).isUntilLast() |
| || rowRecord.getTimestamp() <= lastTimeArray[i])) { |
| rowRecord.getFields().set(i, Field.getField(previousValue[i], dataTypes.get(i))); |
| } |
| } else { |
| // 当前值不为null，不需要填充，用当前值更新previousValue数组 |
| previousValue[i] = field.getObjectValue(field.getDataType()); |
| } |
| } |
| return rowRecord; |
| } |
| </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></div></div></div> <div class="page-nav"><p class="inner"><span class="prev"> |
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