Examples with IncrementalDataAggregator org.wso2.siddhi.core.aggregation.IncrementalDataAggregator used on opensource projects

Example 1 with IncrementalDataAggregator

use of org.wso2.siddhi.core.aggregation.IncrementalDataAggregator in project siddhi by wso2.

the class IncrementalAggregateCompileCondition method find.

public StreamEvent find(StateEvent matchingEvent, AggregationDefinition aggregationDefinition, Map<TimePeriod.Duration, IncrementalExecutor> incrementalExecutorMap, Map<TimePeriod.Duration, Table> aggregationTables, List<TimePeriod.Duration> incrementalDurations, List<ExpressionExecutor> baseExecutors, ExpressionExecutor timestampExecutor, List<ExpressionExecutor> outputExpressionExecutors, SiddhiAppContext siddhiAppContext) {
    ComplexEventChunk<StreamEvent> complexEventChunkToHoldWithinMatches = new ComplexEventChunk<>(true);
    // Retrieve per value
    String perValueAsString = perExpressionExecutor.execute(matchingEvent).toString();
    TimePeriod.Duration perValue = TimePeriod.Duration.valueOf(perValueAsString.toUpperCase());
    if (!incrementalExecutorMap.keySet().contains(perValue)) {
        throw new SiddhiAppRuntimeException("The aggregate values for " + perValue.toString() + " granularity cannot be provided since aggregation definition " + aggregationDefinition.getId() + " does not contain " + perValue.toString() + " duration");
    }
    Table tableForPerDuration = aggregationTables.get(perValue);
    Long[] startTimeEndTime = (Long[]) startTimeEndTimeExpressionExecutor.execute(matchingEvent);
    if (startTimeEndTime == null) {
        throw new SiddhiAppRuntimeException("Start and end times for within duration cannot be retrieved");
    }
    complexEventPopulater.populateComplexEvent(matchingEvent.getStreamEvent(0), startTimeEndTime);
    // Get all the aggregates within the given duration, from table corresponding to "per" duration
    StreamEvent withinMatchFromPersistedEvents = tableForPerDuration.find(matchingEvent, withinTableCompiledConditions.get(perValue));
    complexEventChunkToHoldWithinMatches.add(withinMatchFromPersistedEvents);
    // Optimization step.
    // Get the newest and oldest event timestamps from in-memory, and
    // check whether at least one of those timestamps fall out of the given time range. If that's the case,
    // there's no need to iterate through in-memory data.
    long oldestInMemoryEventTimestamp = getOldestInMemoryEventTimestamp(incrementalExecutorMap, incrementalDurations, perValue);
    long newestInMemoryEventTimestamp = getNewestInMemoryEventTimestamp(incrementalExecutorMap, incrementalDurations, perValue);
    if (requiresAggregatingInMemoryData(newestInMemoryEventTimestamp, oldestInMemoryEventTimestamp, startTimeEndTime)) {
        IncrementalDataAggregator incrementalDataAggregator = new IncrementalDataAggregator(incrementalDurations, perValue, baseExecutors, timestampExecutor, tableMetaStreamEvent, siddhiAppContext);
        // Aggregate in-memory data and create an event chunk out of it
        ComplexEventChunk<StreamEvent> aggregatedInMemoryEventChunk = incrementalDataAggregator.aggregateInMemoryData(incrementalExecutorMap);
        // Get the in-memory aggregate data, which is within given duration
        StreamEvent withinMatchFromInMemory = ((Operator) inMemoryStoreCompileCondition).find(matchingEvent, aggregatedInMemoryEventChunk, tableEventCloner);
        complexEventChunkToHoldWithinMatches.add(withinMatchFromInMemory);
    }
    // Get the final event chunk from the data which is within given duration. This event chunk contains the values
    // in the select clause of an aggregate definition.
    ComplexEventChunk<StreamEvent> aggregateSelectionComplexEventChunk = createAggregateSelectionEventChunk(complexEventChunkToHoldWithinMatches, outputExpressionExecutors);
    // Execute the on compile condition
    return ((Operator) onCompiledCondition).find(matchingEvent, aggregateSelectionComplexEventChunk, aggregateEventCloner);
}