THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
Aggregation query
The main logic of the aggregation query is in AggregateExecutor
org.apache.iotdb.db.query.executor.AggregationExecutor
For aggregate queries without value filters, the results are obtained by the executeWithoutValueFilter() method and a dataSet is constructed. First use the groupAggregationsBySeries method to merge aggregate queries for the same time series. For example: if you need to calculate count(s1), sum(s2), count(s3), sum(s1), you need to calculate two aggregation values of s1, then the pathToAggrIndexesMap result will be: s1-> 0, 3; s2-> 1; s3-> 2.
Then you will get pathToAggrIndexesMap, where each entry is an aggregate query of series, so you can calculate its aggregate value aggregateResult by calling the aggregateOneSeries method. Before you finally create the result set, you need to restore its order to the order of the user query. Finally use the constructDataSet() method to create a result set and return it.
The aggregateOneSeries() method is explained in detail below. First create an IAggregateReader:
if (ascAggregateResultList != null && !ascAggregateResultList.isEmpty()) {
IAggregateReader seriesReader = new SeriesAggregateReader(
seriesPath, measurements, tsDataType, context, queryDataSource, timeFilter,
null, null, true);
aggregateFromReader(seriesReader, ascAggregateResultList);
}
if (descAggregateResultList != null && !descAggregateResultList.isEmpty()) {
IAggregateReader seriesReader = new SeriesAggregateReader(
seriesPath, measurements, tsDataType, context, queryDataSource, timeFilter,
null, null, false);
aggregateFromReader(seriesReader, descAggregateResultList);
}
For each entry (that is, series), first create an aggregate result AggregateResult for each aggregate query. Maintain a boolean array isCalculatedArray, corresponding to whether each AggregateResult has been calculated. Record the remaining number of functions to be calculated in remainingToCalculate. The array of boolean values and this count value will make some aggregate functions (such as FIRST_VALUE) not need to continue the entire loop process after obtaining the result.
Next, update AggregateResult according to the usage method of aggregateReader introduced in Section 5.2:
while (seriesReader.hasNextFile()) {
// cal by file statistics
if (seriesReader.canUseCurrentFileStatistics()) {
Statistics fileStatistics = seriesReader.currentFileStatistics();
remainingToCalculate =
aggregateStatistics(
aggregateResultList, isCalculatedArray, remainingToCalculate, fileStatistics);
if (remainingToCalculate == 0) {
return;
}
seriesReader.skipCurrentFile();
continue;
}
while (seriesReader.hasNextChunk()) {
// cal by chunk statistics
if (seriesReader.canUseCurrentChunkStatistics()) {
Statistics chunkStatistics = seriesReader.currentChunkStatistics();
remainingToCalculate =
aggregateStatistics(
aggregateResultList, isCalculatedArray, remainingToCalculate, chunkStatistics);
if (remainingToCalculate == 0) {
return;
}
seriesReader.skipCurrentChunk();
continue;
}
remainingToCalculate =
aggregatePages(
seriesReader, aggregateResultList, isCalculatedArray, remainingToCalculate);
if (remainingToCalculate == 0) {
return;
}
}
}
It should be noted that before updating each result, you need to first determine whether it has been calculated (using the isCalculatedArray array); after each update, call the hasFinalResult() method to update the boolean values in the array . If all values in the list are true, that is, the value of remainingToCalculate is 0, it proves that all aggregate function results have been calculated and can be returned.
for (int i = 0; i < aggregateResultList.size(); i++) {
if (!isCalculatedArray[i]) {
AggregateResult aggregateResult = aggregateResultList.get(i);
aggregateResult.updateResultFromStatistics(statistics);
if (aggregateResult.hasFinalResult()) {
isCalculatedArray[i] = true;
newRemainingToCalculate--;
if (newRemainingToCalculate == 0) {
return newRemainingToCalculate;
}
}
}
}
When using overlapedPageData to update, since each batch function result will traverse this batchData, you need to call theresetBatchData ()method to point the pointer to its starting position, so that the next function can traverse.
Aggregated query with value filter
For an aggregate query with a value filter, obtain the results through the executeWithoutValueFilter() method and build a dataSet. First create a timestampGenerator based on the expression, then create a SeriesReaderByTimestamp for each time series and place it in the readersOfSelectedSeries list; create an aggregate result for each query as AggregateResult, and place it in the aggregateResults list.
After initialization is complete, call the aggregateWithValueFilter() method to update the result:
while (timestampGenerator.hasNext()) {
// Generate timestamps
long[] timeArray = new long[aggregateFetchSize];
int timeArrayLength = 0;
for (int cnt = 0; cnt < aggregateFetchSize; cnt++) {
if (!timestampGenerator.hasNext()) {
break;
}
timeArray[timeArrayLength++] = timestampGenerator.next();
}
// Calculate aggregate results using timestamps
for (int i = 0; i < readersOfSelectedSeries.size(); i++) {
aggregateResults.get(i).updateResultUsingTimestamps(timeArray, timeArrayLength,
readersOfSelectedSeries.get(i));
}
}
Aggregated query with level
After aggregated query, we could also to count the total number of points of
each node at the given level in current Metadata Tree.
The logic is in the AggregationExecutor class.
In the beginning, get the final paths group by level and the origin path index to final path.
For example, we could get final path
root.sg1byroot.sg1.d1.s0,root.sg1.d2.s1andlevel=1.
Then, get the aggregated query result: RowRecord.
Finally, merge each RowRecord to NewRecord, which has fields like <final path, count>.
For example, we will get new RowRecord
<root.sg1,7>by<root.sg1.d1.s0, 3>, <root.sg1.d2.s1, 4>and level=1.
Attention:
only support count aggregation