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

Example 1 with RecreateInMemoryData

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

the class AggregationParser method parse.

public static AggregationRuntime parse(AggregationDefinition aggregationDefinition, SiddhiAppContext siddhiAppContext, Map<String, AbstractDefinition> streamDefinitionMap, Map<String, AbstractDefinition> tableDefinitionMap, Map<String, AbstractDefinition> windowDefinitionMap, Map<String, AbstractDefinition> aggregationDefinitionMap, Map<String, Table> tableMap, Map<String, Window> windowMap, Map<String, AggregationRuntime> aggregationMap, SiddhiAppRuntimeBuilder siddhiAppRuntimeBuilder) {
    if (aggregationDefinition == null) {
        throw new SiddhiAppCreationException("AggregationDefinition instance is null. " + "Hence, can't create the siddhi app '" + siddhiAppContext.getName() + "'");
    }
    if (aggregationDefinition.getTimePeriod() == null) {
        throw new SiddhiAppCreationException("AggregationDefinition '" + aggregationDefinition.getId() + "'s timePeriod is null. " + "Hence, can't create the siddhi app '" + siddhiAppContext.getName() + "'", aggregationDefinition.getQueryContextStartIndex(), aggregationDefinition.getQueryContextEndIndex());
    }
    if (aggregationDefinition.getSelector() == null) {
        throw new SiddhiAppCreationException("AggregationDefinition '" + aggregationDefinition.getId() + "'s selection is not defined. " + "Hence, can't create the siddhi app '" + siddhiAppContext.getName() + "'", aggregationDefinition.getQueryContextStartIndex(), aggregationDefinition.getQueryContextEndIndex());
    }
    if (streamDefinitionMap.get(aggregationDefinition.getBasicSingleInputStream().getStreamId()) == null) {
        throw new SiddhiAppCreationException("Stream " + aggregationDefinition.getBasicSingleInputStream().getStreamId() + " has not been defined");
    }
    try {
        List<VariableExpressionExecutor> incomingVariableExpressionExecutors = new ArrayList<>();
        String aggregatorName = aggregationDefinition.getId();
        StreamRuntime streamRuntime = InputStreamParser.parse(aggregationDefinition.getBasicSingleInputStream(), siddhiAppContext, streamDefinitionMap, tableDefinitionMap, windowDefinitionMap, aggregationDefinitionMap, tableMap, windowMap, aggregationMap, incomingVariableExpressionExecutors, null, false, aggregatorName);
        // Get original meta for later use.
        MetaStreamEvent incomingMetaStreamEvent = (MetaStreamEvent) streamRuntime.getMetaComplexEvent();
        // Create new meta stream event.
        // This must hold the timestamp, group by attributes (if given) and the incremental attributes, in
        // onAfterWindowData array
        // Example format: AGG_TIMESTAMP, groupByAttribute1, groupByAttribute2, AGG_incAttribute1, AGG_incAttribute2
        // AGG_incAttribute1, AGG_incAttribute2 would have the same attribute names as in
        // finalListOfIncrementalAttributes
        // To enter data as onAfterWindowData
        incomingMetaStreamEvent.initializeAfterWindowData();
        List<ExpressionExecutor> incomingExpressionExecutors = new ArrayList<>();
        List<IncrementalAttributeAggregator> incrementalAttributeAggregators = new ArrayList<>();
        List<Variable> groupByVariableList = aggregationDefinition.getSelector().getGroupByList();
        boolean isProcessingOnExternalTime = aggregationDefinition.getAggregateAttribute() != null;
        // Expressions to get
        List<Expression> outputExpressions = new ArrayList<>();
        // final aggregate outputs. e.g avg = sum/count
        // Expression executors to get
        List<ExpressionExecutor> outputExpressionExecutors = new ArrayList<>();
        // final aggregate outputs. e.g avg = sum/count
        populateIncomingAggregatorsAndExecutors(aggregationDefinition, siddhiAppContext, tableMap, incomingVariableExpressionExecutors, aggregatorName, incomingMetaStreamEvent, incomingExpressionExecutors, incrementalAttributeAggregators, groupByVariableList, outputExpressions);
        int baseAggregatorBeginIndex = incomingMetaStreamEvent.getOutputData().size();
        List<Expression> finalBaseAggregators = getFinalBaseAggregators(siddhiAppContext, tableMap, incomingVariableExpressionExecutors, aggregatorName, incomingMetaStreamEvent, incomingExpressionExecutors, incrementalAttributeAggregators);
        StreamDefinition incomingOutputStreamDefinition = StreamDefinition.id("");
        incomingOutputStreamDefinition.setQueryContextStartIndex(aggregationDefinition.getQueryContextStartIndex());
        incomingOutputStreamDefinition.setQueryContextEndIndex(aggregationDefinition.getQueryContextEndIndex());
        MetaStreamEvent processedMetaStreamEvent = new MetaStreamEvent();
        for (Attribute attribute : incomingMetaStreamEvent.getOutputData()) {
            incomingOutputStreamDefinition.attribute(attribute.getName(), attribute.getType());
            processedMetaStreamEvent.addOutputData(attribute);
        }
        incomingMetaStreamEvent.setOutputDefinition(incomingOutputStreamDefinition);
        processedMetaStreamEvent.addInputDefinition(incomingOutputStreamDefinition);
        processedMetaStreamEvent.setOutputDefinition(incomingOutputStreamDefinition);
        // Executors of processing meta
        List<VariableExpressionExecutor> processVariableExpressionExecutors = new ArrayList<>();
        boolean groupBy = aggregationDefinition.getSelector().getGroupByList().size() != 0;
        List<ExpressionExecutor> processExpressionExecutors = constructProcessExpressionExecutors(siddhiAppContext, tableMap, aggregatorName, baseAggregatorBeginIndex, finalBaseAggregators, incomingOutputStreamDefinition, processedMetaStreamEvent, processVariableExpressionExecutors, groupBy);
        outputExpressionExecutors.addAll(outputExpressions.stream().map(expression -> ExpressionParser.parseExpression(expression, processedMetaStreamEvent, 0, tableMap, processVariableExpressionExecutors, siddhiAppContext, groupBy, 0, aggregatorName)).collect(Collectors.toList()));
        // Create group by key generator
        GroupByKeyGenerator groupByKeyGenerator = null;
        if (groupBy) {
            groupByKeyGenerator = new GroupByKeyGenerator(groupByVariableList, processedMetaStreamEvent, SiddhiConstants.UNKNOWN_STATE, tableMap, processVariableExpressionExecutors, siddhiAppContext, aggregatorName);
        }
        // Create new scheduler
        EntryValveExecutor entryValveExecutor = new EntryValveExecutor(siddhiAppContext);
        LockWrapper lockWrapper = new LockWrapper(aggregatorName);
        lockWrapper.setLock(new ReentrantLock());
        Scheduler scheduler = SchedulerParser.parse(siddhiAppContext.getScheduledExecutorService(), entryValveExecutor, siddhiAppContext);
        scheduler.init(lockWrapper, aggregatorName);
        scheduler.setStreamEventPool(new StreamEventPool(processedMetaStreamEvent, 10));
        QueryParserHelper.reduceMetaComplexEvent(incomingMetaStreamEvent);
        QueryParserHelper.reduceMetaComplexEvent(processedMetaStreamEvent);
        QueryParserHelper.updateVariablePosition(incomingMetaStreamEvent, incomingVariableExpressionExecutors);
        QueryParserHelper.updateVariablePosition(processedMetaStreamEvent, processVariableExpressionExecutors);
        List<TimePeriod.Duration> incrementalDurations = getSortedPeriods(aggregationDefinition.getTimePeriod());
        Map<TimePeriod.Duration, Table> aggregationTables = initDefaultTables(aggregatorName, incrementalDurations, processedMetaStreamEvent.getOutputStreamDefinition(), siddhiAppRuntimeBuilder, aggregationDefinition.getAnnotations(), groupByVariableList);
        int bufferSize = 0;
        Element element = AnnotationHelper.getAnnotationElement(SiddhiConstants.ANNOTATION_BUFFER_SIZE, null, aggregationDefinition.getAnnotations());
        if (element != null) {
            try {
                bufferSize = Integer.parseInt(element.getValue());
            } catch (NumberFormatException e) {
                throw new SiddhiAppCreationException(e.getMessage() + ": BufferSize must be an integer");
            }
        }
        if (bufferSize > 0) {
            TimePeriod.Duration rootDuration = incrementalDurations.get(0);
            if (rootDuration == TimePeriod.Duration.MONTHS || rootDuration == TimePeriod.Duration.YEARS) {
                throw new SiddhiAppCreationException("A buffer size greater than 0 can be provided, only when the " + "first duration value is seconds, minutes, hours or days");
            }
            if (!isProcessingOnExternalTime) {
                throw new SiddhiAppCreationException("Buffer size cannot be specified when events are aggregated " + "based on event arrival time.");
            // Buffer size is used to process out of order events. However, events would never be out of
            // order if they are processed based on event arrival time.
            }
        } else if (bufferSize < 0) {
            throw new SiddhiAppCreationException("Expected a positive integer as the buffer size, but found " + bufferSize + " as the provided value");
        }
        boolean ignoreEventsOlderThanBuffer = false;
        element = AnnotationHelper.getAnnotationElement(SiddhiConstants.ANNOTATION_IGNORE_EVENTS_OLDER_THAN_BUFFER, null, aggregationDefinition.getAnnotations());
        if (element != null) {
            if (element.getValue().equalsIgnoreCase("true")) {
                ignoreEventsOlderThanBuffer = true;
            } else if (!element.getValue().equalsIgnoreCase("false")) {
                throw new SiddhiAppCreationException("IgnoreEventsOlderThanBuffer value must " + "be true or false");
            }
        }
        Map<TimePeriod.Duration, IncrementalExecutor> incrementalExecutorMap = buildIncrementalExecutors(isProcessingOnExternalTime, processedMetaStreamEvent, processExpressionExecutors, groupByKeyGenerator, bufferSize, ignoreEventsOlderThanBuffer, incrementalDurations, aggregationTables, siddhiAppContext, aggregatorName);
        // Recreate in-memory data from tables
        RecreateInMemoryData recreateInMemoryData = new RecreateInMemoryData(incrementalDurations, aggregationTables, incrementalExecutorMap, siddhiAppContext, processedMetaStreamEvent, tableMap, windowMap, aggregationMap);
        IncrementalExecutor rootIncrementalExecutor = incrementalExecutorMap.get(incrementalDurations.get(0));
        rootIncrementalExecutor.setScheduler(scheduler);
        // Connect entry valve to root incremental executor
        entryValveExecutor.setNextExecutor(rootIncrementalExecutor);
        QueryParserHelper.initStreamRuntime(streamRuntime, incomingMetaStreamEvent, lockWrapper, aggregatorName);
        LatencyTracker latencyTrackerFind = null;
        LatencyTracker latencyTrackerInsert = null;
        ThroughputTracker throughputTrackerFind = null;
        ThroughputTracker throughputTrackerInsert = null;
        if (siddhiAppContext.getStatisticsManager() != null) {
            latencyTrackerFind = QueryParserHelper.createLatencyTracker(siddhiAppContext, aggregationDefinition.getId(), SiddhiConstants.METRIC_INFIX_WINDOWS, SiddhiConstants.METRIC_TYPE_FIND);
            latencyTrackerInsert = QueryParserHelper.createLatencyTracker(siddhiAppContext, aggregationDefinition.getId(), SiddhiConstants.METRIC_INFIX_WINDOWS, SiddhiConstants.METRIC_TYPE_INSERT);
            throughputTrackerFind = QueryParserHelper.createThroughputTracker(siddhiAppContext, aggregationDefinition.getId(), SiddhiConstants.METRIC_INFIX_WINDOWS, SiddhiConstants.METRIC_TYPE_FIND);
            throughputTrackerInsert = QueryParserHelper.createThroughputTracker(siddhiAppContext, aggregationDefinition.getId(), SiddhiConstants.METRIC_INFIX_WINDOWS, SiddhiConstants.METRIC_TYPE_INSERT);
        }
        streamRuntime.setCommonProcessor(new IncrementalAggregationProcessor(rootIncrementalExecutor, incomingExpressionExecutors, processedMetaStreamEvent, latencyTrackerInsert, throughputTrackerInsert, siddhiAppContext));
        List<ExpressionExecutor> baseExecutors = cloneExpressionExecutors(processExpressionExecutors);
        ExpressionExecutor timestampExecutor = baseExecutors.remove(0);
        return new AggregationRuntime(aggregationDefinition, incrementalExecutorMap, aggregationTables, ((SingleStreamRuntime) streamRuntime), entryValveExecutor, incrementalDurations, siddhiAppContext, baseExecutors, timestampExecutor, processedMetaStreamEvent, outputExpressionExecutors, latencyTrackerFind, throughputTrackerFind, recreateInMemoryData);
    } catch (Throwable t) {
        ExceptionUtil.populateQueryContext(t, aggregationDefinition, siddhiAppContext);
        throw t;
    }
}

Example 2 with RecreateInMemoryData

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

the class RecreateInMemoryData method recreateInMemoryData.

public void recreateInMemoryData() {
    if (incrementalExecutorMap.get(incrementalDurations.get(0)).getNextEmitTime() != -1) {
        // created. Hence this method does not have to be executed.
        return;
    }
    Event[] events;
    Long latestEventTimestamp = null;
    // Get all events from table corresponding to max duration
    Table tableForMaxDuration = aggregationTables.get(incrementalDurations.get(incrementalDurations.size() - 1));
    StoreQuery storeQuery = StoreQuery.query().from(InputStore.store(tableForMaxDuration.getTableDefinition().getId())).select(Selector.selector().orderBy(Expression.variable("AGG_TIMESTAMP")));
    StoreQueryRuntime storeQueryRuntime = StoreQueryParser.parse(storeQuery, siddhiAppContext, tableMap, windowMap, aggregationMap);
    // Get latest event timestamp in tableForMaxDuration
    events = storeQueryRuntime.execute();
    if (events != null) {
        latestEventTimestamp = (Long) events[events.length - 1].getData(0);
    }
    for (int i = incrementalDurations.size() - 1; i > 0; i--) {
        TimePeriod.Duration recreateForDuration = incrementalDurations.get(i);
        IncrementalExecutor incrementalExecutor = incrementalExecutorMap.get(recreateForDuration);
        // Get the table previous to the duration for which we need to recreate (e.g. if we want to recreate
        // for minute duration, take the second table [provided that aggregation is done for seconds])
        Table recreateFromTable = aggregationTables.get(incrementalDurations.get(i - 1));
        storeQuery = StoreQuery.query().from(InputStore.store(recreateFromTable.getTableDefinition().getId())).select(Selector.selector().orderBy(Expression.variable("AGG_TIMESTAMP")));
        storeQueryRuntime = StoreQueryParser.parse(storeQuery, siddhiAppContext, tableMap, windowMap, aggregationMap);
        events = storeQueryRuntime.execute();
        if (events != null) {
            long referenceToNextLatestEvent = (Long) events[events.length - 1].getData(0);
            String timeZoneOfNextLatestEvent = events[events.length - 1].getData(1).toString();
            if (latestEventTimestamp != null) {
                List<Event> eventsNewerThanLatestEventOfRecreateForDuration = new ArrayList<>();
                for (Event event : events) {
                    // After getting the events from recreateFromTable, get the time bucket it belongs to,
                    // if each of these events were in the recreateForDuration. This helps to identify the events,
                    // which must be processed in-memory for recreateForDuration.
                    long timeBucketForNextDuration = IncrementalTimeConverterUtil.getStartTimeOfAggregates((Long) event.getData(0), recreateForDuration, event.getData(1).toString());
                    if (timeBucketForNextDuration > latestEventTimestamp) {
                        eventsNewerThanLatestEventOfRecreateForDuration.add(event);
                    }
                }
                events = eventsNewerThanLatestEventOfRecreateForDuration.toArray(new Event[eventsNewerThanLatestEventOfRecreateForDuration.size()]);
            }
            latestEventTimestamp = referenceToNextLatestEvent;
            ComplexEventChunk<StreamEvent> complexEventChunk = new ComplexEventChunk<>(false);
            for (Event event : events) {
                StreamEvent streamEvent = streamEventPool.borrowEvent();
                streamEvent.setOutputData(event.getData());
                complexEventChunk.add(streamEvent);
            }
            incrementalExecutor.execute(complexEventChunk);
            if (i == 1) {
                TimePeriod.Duration rootDuration = incrementalDurations.get(0);
                IncrementalExecutor rootIncrementalExecutor = incrementalExecutorMap.get(rootDuration);
                long emitTimeOfLatestEventInTable = IncrementalTimeConverterUtil.getNextEmitTime(latestEventTimestamp, rootDuration, timeZoneOfNextLatestEvent);
                rootIncrementalExecutor.setValuesForInMemoryRecreateFromTable(true, emitTimeOfLatestEventInTable);
            }
        }
    }
}