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  if (hasCachedTimeInterval) {
    return true;
  }

  curStartTime = usedIndex * slidingStep + startTime;
  usedIndex++;
  if (curStartTime &lt; endTime) {
    hasCachedTimeInterval = true;
    curEndTime = Math.min(curStartTime + interval, endTime);
    return true;
  } else {
    return false;
  }
}
</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><h2 id="downsampling-query-without-value-filter"><a href="#downsampling-query-without-value-filter" class="header-anchor">#</a> Downsampling query without value filter</h2> <p>The downsampling query logic without value filter is mainly in the <code>GroupByWithoutValueFilterDataSet</code> class, which inherits<code>GroupByEngineDataSet</code>.</p> <p>This class has the following key fields:</p> <ul><li><p>private Map &lt;Path, GroupByExecutor&gt; pathExecutors classifies aggregate functions for the same <code>Path</code> and encapsulates them as<code>GroupByExecutor</code>,
<code>GroupByExecutor</code> encapsulates the data calculation logic and method of each Path, which will be described later</p></li> <li><p>private TimeRange timeRange encapsulates the time interval of each calculation into an object, which is used to determine whether Statistics can directly participate in the calculation</p></li> <li><p>private Filter timeFilter Generates a user-defined query interval as a Filter object, which is used to filter the available files, chunks, and pages.</p></li></ul> <p>First, in the initialization <code>initGroupBy()</code> method, the <code>timeFilter</code> is calculated based on the expression, and <code>GroupByExecutor</code> is generated for each <code>path</code>.</p> <p>First, in the initialization <code>initGroupBy()</code> method, the <code>timeFilter</code> is calculated based on the expression, and <code>GroupByExecutor</code> is generated for each <code>path</code>.
The following method is used to convert the result list into a RowRecord. Note that when there are no results in the list, add <code>null</code> to the RowRecord:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>for (AggregateResult res : fields) {
  if (res == null) {
    record.addField(null);
    continue;
  }
  record.addField(res.getResult(), res.getResultDataType());
}
</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><h3 id="groupbyexecutor"><a href="#groupbyexecutor" class="header-anchor">#</a> GroupByExecutor</h3> <p>Encapsulating the calculation method of all aggregate functions under the same path, this class has the following key fields:</p> <ul><li>private IAggregateReader reader  the <code>SeriesAggregateReader</code> used to read the current <code>Path</code> data</li> <li>private BatchData preCachedData Every time the data read from <code>Reader</code> is a batch, and it is likely to exceed the current time period. This <code>BatchData</code> will be cached for next use</li> <li>private List&lt;Pair&lt;AggregateResult, Integer&gt;&gt; results stores all aggregation methods in the current <code>Path</code>, for example: <code>select count(a), sum(a), avg(b)</code>, <code>count</code> and <code>sum</code> can be stored together.
The <code>Integer</code> on the right is used to convert the result set to the order of the user query before converting it to RowRecord.</li></ul> <h4 id="main-method"><a href="#main-method" class="header-anchor">#</a> Main method</h4> <div class="language- line-numbers-mode"><pre class="language-text"><code>//Read data from the reader and calculate the main method of this class.
private List&lt;Pair&lt;AggregateResult, Integer&gt;&gt; calcResult() throws IOException, QueryProcessException;

//Add aggregation operation for current path
private void addAggregateResult(AggregateResult aggrResult, int index);

//Determine whether the current path has completed all aggregation calculations
private boolean isEndCalc();

//Calculate results from BatchData that did not run out of cache last calculation
private boolean calcFromCacheData() throws IOException;

//Calculation using BatchData
private void calcFromBatch(BatchData batchData) throws IOException;

//Calculate results directly using Page or Chunk's Statistics
private void calcFromStatistics(Statistics statistics) throws QueryProcessException;

//Clear all calculation results
private void resetAggregateResults();

//Iterate through and calculate the data in the page
private boolean readAndCalcFromPage() throws IOException, QueryProcessException;

</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></div></div><p>In <code>GroupByExecutor</code>, because different aggregate functions of the same path use the same data, the entry method <code>calcResult</code> is responsible for reading all the data of the <code>Path</code>.
The retrieved data then calls the <code>calcFromBatch</code> method to complete the calculation of <code>BatchData</code> through all the aggregate functions.</p> <p>The <code>calcResult</code> method returns all AggregateResult under the current Path and the position of the current aggregated value in the user query order. Its main logic is:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>//Calculate the data left over from the last time, and end the calculation if you can get the results directly
if (calcFromCacheData()) {
    return results;
}

//Because a chunk contains multiple pages, the page of the current chunk must be used up before the next chunk is opened.
if (readAndCalcFromPage()) {
    return results;
}

//If the remaining data is calculated, open a new chunk to continue the calculation.
while (reader.hasNextChunk()) {
    Statistics chunkStatistics = reader.currentChunkStatistics();
      // Determine if Statistics is available and perform calculations
       ....
      // Skip current chunk
      reader.skipCurrentChunk();
      // End calculation if all results have been obtained
      if (isEndCalc()) {
        return true;
      }
      continue;
    }
    //If you cannot use chunkStatistics, you need to use page data to calculate
    if (readAndCalcFromPage()) {
      return results;
    }
}
</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></div></div><p>The <code>readAndCalcFromPage</code> method is to obtain the page data from the currently opened chunk and calculate the aggregate result.  Returns true when all calculations are completed, otherwise returns false.  The main logic:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>while (reader.hasNextPage()) {
    Statistics pageStatistics = reader.currentPageStatistics();
    //PageStatistics can only be used if the page does not intersect with other pages
    if (pageStatistics != null) {
        // Determine if Statistics is available and perform calculations
        ....
        // Skip current page
        reader.skipCurrentPage();
        // End calculation if all results have been obtained
        if (isEndCalc()) {
          return true;
        }
        continue;
      }
    }
    // When Statistics is not available, you can only fetch all data for calculation
    BatchData batchData = reader.nextPage();
    if (batchData == null || !batchData.hasCurrent()) {
      continue;
    }
    // If the page just opened exceeds the time range, the data retrieved is cached and the calculation is directly ended.
    if (batchData.currentTime() &gt;= curEndTime) {
      preCachedData = batchData;
      return true;
    }
    //Perform calculations
    calcFromBatch(batchData);
    ...
}

</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></div></div><p>The <code>calcFromBatch</code> method is to traverse all the aggregate functions to calculate the retrieved BatchData. The main logic is:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>for (Pair&lt;AggregateResult, Integer&gt; result : results) {
    //If a function has already been calculated, it will not be calculated, such as the minimum calculation.
    if (result.left.isCalculatedAggregationResult()) {
      continue;
    }
    // Perform calculations
    ....
}
//Determine if the data in the current batchdata can still be used next time, if it can be added to the cache
if (batchData.getMaxTimestamp() &gt;= curEndTime) {
    preCachedData = batchData;
}
</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><h2 id="aggregated-query-with-value-filter"><a href="#aggregated-query-with-value-filter" class="header-anchor">#</a> Aggregated query with value filter</h2> <p>The downsampling query logic with value filtering conditions is mainly in the <code>GroupByWithValueFilterDataSet</code> class, which inherits <code>GroupByEngineDataSet</code>.</p> <p>This class has the following key fields:</p> <ul><li>private List&lt;IReaderByTimestamp&gt; allDataReaderList</li> <li>private GroupByPlan groupByTimePlan</li> <li>private TimeGenerator timestampGenerator</li> <li>private long timestamp is used to cache timestamp for the next group by partition</li> <li>private boolean hasCachedTimestamp used to determine whether there is a timestamp cache for the next group by partition</li> <li>private int timeStampFetchSize is the size of the group by calculating the batch</li></ul> <p>First, in the initialization <code>initGroupBy ()</code>method, create a <code>timestampGenerator</code> based on the expression; then create a <code>SeriesReaderByTimestamp</code> for each time series and place it in the <code>allDataReaderList</code> list. After initialization is complete, call the <code>nextWithoutConstraint ()</code>method to update the result.  If timestamp is cached for the next group by partition and the time meets the requirements, add it to <code>timestampArray</code>, otherwise return the <code>aggregateResultList</code> result directly; if timestamp is not cached for the next group by partition, use <code>timestampGenerator</code> to traverse:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>while (timestampGenerator.hasNext()) {
  // Call constructTimeArrayForOneCal () method to get a list of timestamp
  timeArrayLength = constructTimeArrayForOneCal(timestampArray, timeArrayLength);

  // Call the updateResultUsingTimestamps () method to calculate the aggregate result using the timestamp list
  for (int i = 0; i &lt; paths.size(); i++) {
    aggregateResultList.get(i).updateResultUsingTimestamps(
        timestampArray, timeArrayLength, allDataReaderList.get(i));
  }

  timeArrayLength = 0;
  // Determine if it is over
  if (timestamp &gt;= curEndTime) {
    hasCachedTimestamp = true;
    break;
  }
}
</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>The <code>constructTimeArrayForOneCal ()</code>method traverses timestampGenerator to build a list of timestamps:</p> <div class="language- line-numbers-mode"><pre class="language-text"><code>for (int cnt = 1; cnt &lt; timeStampFetchSize &amp;&amp; timestampGenerator.hasNext(); cnt++) {
  timestamp = timestampGenerator.next();
  if (timestamp &lt; curEndTime) {
    timestampArray[timeArrayLength++] = timestamp;
  } else {
    hasCachedTimestamp = true;
    break;
  }
}
</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="aggregated-query-with-level"><a href="#aggregated-query-with-level" class="header-anchor">#</a> Aggregated query with level</h2> <p>After down-frequency query, we could also to count the total number of points of</p> <p>each node at the given level in current Metadata Tree.</p> <p>The logic is in the <code>GroupByTimeDataSet</code> class.</p> <ol><li><p>In the beginning, get the final paths group by level and the origin path index to final path.</p> <blockquote><p>For example, we could get final path <code>root.sg1</code> by <code>root.sg1.d1.s0,root.sg1.d2.s1</code> and <code>level=1</code>.</p></blockquote></li> <li><p>Then, get the down-frequency query result: RowRecord.</p></li> <li><p>Finally, merge each RowRecord to NewRecord, which has fields like &lt;final path, count&gt;.</p> <blockquote><p>For example, we will get new RowRecord <code>&lt;root.sg1,7&gt;</code> by <code>&lt;root.sg1.d1.s0, 3&gt;, &lt;root.sg1.d2.s1, 4&gt;</code> and level=1.</p></blockquote></li></ol> <blockquote><p>Attention:</p> <ol><li>only support count aggregation</li> <li>root's level == 0</li></ol></blockquote></div> <div class="page-nav"><p class="inner"><span class="prev">
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