Examples with DataPointValueTime com.infiniteautomation.mango.rest.latest.model.pointValue.DataPointValueTime used on opensource projects

Example 1 with DataPointValueTime

use of com.infiniteautomation.mango.rest.latest.model.pointValue.DataPointValueTime in project ma-modules-public by infiniteautomation.

the class MultiDataPointStatisticsQuantizerStream method finish.

@Override
public void finish(PointValueTimeWriter writer) throws QueryCancelledException, IOException {
    if (info.isSingleArray() && voMap.size() > 1) {
        // Fast forward to end to fill any gaps at the end and stream out data in time
        BucketCalculator bc;
        if (this.info.getTimePeriod() == null) {
            bc = new BucketsBucketCalculator(ZonedDateTime.ofInstant(Instant.ofEpochMilli(lastFullPeriodToMillis), info.getZoneId()), info.getTo(), 1);
        } else {
            bc = new TimePeriodBucketCalculator(ZonedDateTime.ofInstant(Instant.ofEpochMilli(lastFullPeriodToMillis), info.getZoneId()), info.getTo(), TimePeriodType.convertFrom(this.info.getTimePeriod().getType()), this.info.getTimePeriod().getPeriods());
        }
        Instant currentPeriodTo = bc.getStartTime().toInstant();
        Instant end = bc.getEndTime().toInstant();
        while (currentPeriodTo.isBefore(end)) {
            long nextTo = currentPeriodTo.toEpochMilli();
            for (DataPointStatisticsQuantizer<?> quant : this.quantizerMap.values()) {
                quant.fastForward(nextTo);
            }
            currentPeriodTo = bc.getNextPeriodTo().toInstant();
        }
        for (DataPointStatisticsQuantizer<?> quant : this.quantizerMap.values()) {
            if (!quant.isDone())
                quant.done();
        }
        // TODO This is likely not necessary
        Iterator<Long> it = this.periodStats.keySet().iterator();
        while (it.hasNext()) {
            List<DataPointValueTime> entries = this.periodStats.get(it.next());
            writePeriodStats(entries);
            it.remove();
        }
    } else {
        // The last data point may not have been done() as well as any with 0 data
        if (currentDataPointId != -1) {
            DataPointStatisticsQuantizer<?> quant = this.quantizerMap.get(currentDataPointId);
            if (!quant.isDone()) {
                quant.done();
            }
        }
        // For any with 0 data TODO Check for is open?
        for (DataPointStatisticsQuantizer<?> q : this.quantizerMap.values()) {
            if (!q.isDone()) {
                q.done();
            }
        }
    }
    super.finish(writer);
}

Example 2 with DataPointValueTime

use of com.infiniteautomation.mango.rest.latest.model.pointValue.DataPointValueTime in project ma-modules-public by infiniteautomation.

the class MultiDataPointDefaultRollupStatisticsQuantizerStream method streamData.

@Override
public void streamData(PointValueTimeWriter writer) throws IOException, QueryCancelledException {
    if (!useSimplify) {
        super.streamData(writer);
        return;
    }
    createQuantizerMap();
    Collection<? extends DataPointVO> vos = new ArrayList<>(voMap.values());
    if (info.isSingleArray()) {
        dao.wideBookendQueryCombined(vos, info.getFromMillis(), info.getToMillis(), null, this);
    } else {
        dao.wideBookendQueryPerPoint(vos, info.getFromMillis(), info.getToMillis(), null, this);
    }
    // Fast forward to end to fill any gaps at the end
    for (DataPointStatisticsQuantizer<?> quant : this.quantizerMap.values()) {
        if (!quant.isDone())
            quant.done();
    }
    boolean singleArray = info.isSingleArray() && voMap.size() > 1;
    // Process the data into lists per data point, limit and simplify if necessary.
    Map<DataPointVO, List<DataPointValueTime>> processed = process(singleArray ? null : info.getLimit());
    if (singleArray) {
        // Combine into single array
        List<DataPointValueTime> values = new ArrayList<>();
        Iterator<DataPointVO> it = processed.keySet().iterator();
        while (it.hasNext()) {
            values.addAll(processed.get(it.next()));
        }
        // Sort by time
        Collections.sort(values);
        // Limit entire list
        if (info.getLimit() != null)
            values = values.subList(0, info.getLimit());
        // Reset current time and write out
        if (values.size() > 0) {
            long currentTime = values.get(0).getTime();
            List<DataPointValueTime> currentValues = new ArrayList<>();
            for (DataPointValueTime value : values) {
                if (currentTime == value.getTime())
                    currentValues.add(value);
                else {
                    if (currentValues.size() > 0) {
                        writer.writeDataPointValues(currentValues, currentValues.get(0).getTime());
                        currentValues.clear();
                    }
                    currentTime = value.getTime();
                    currentValues.add(value);
                }
            }
            // Finish the current values
            if (currentValues.size() > 0)
                writer.writeDataPointValues(currentValues, currentValues.get(0).getTime());
        }
    } else {
        Iterator<DataPointVO> it = processed.keySet().iterator();
        while (it.hasNext()) {
            DataPointVO key = it.next();
            List<DataPointValueTime> values = processed.get(key);
            if (!info.isSingleArray())
                this.writer.writeStartArray(key.getXid());
            for (DataPointValueTime value : values) {
                writer.writeDataPointValue(value);
                count++;
            }
            if (!info.isSingleArray())
                writer.writeEndArray();
        }
    }
}

Example 3 with DataPointValueTime

use of com.infiniteautomation.mango.rest.latest.model.pointValue.DataPointValueTime in project ma-modules-public by infiniteautomation.

the class MultiDataPointDefaultRollupStatisticsQuantizerStream method process.

/**
 * Process the data into lists per data point, simplify if necessary
 */
private Map<DataPointVO, List<DataPointValueTime>> process(Integer limit) {
    Map<DataPointVO, List<DataPointValueTime>> processed = new LinkedHashMap<>();
    for (DataPointVO vo : voMap.values()) {
        List<DataPointStatisticsGenerator> generators = valueMap.get(vo.getId());
        List<DataPointValueTime> values = new ArrayList<>();
        if (generators.get(0).getGenerator() instanceof NoStatisticsGenerator) {
            // Iterate and combine into an array
            for (DataPointStatisticsGenerator gen : generators) {
                NoStatisticsGenerator noGen = (NoStatisticsGenerator) gen.getGenerator();
                for (IValueTime value : noGen.getValues()) {
                    values.add(new DataPointVOPointValueTimeBookend(vo, (IdPointValueTime) value));
                }
            }
        } else {
            for (DataPointStatisticsGenerator generator : generators) {
                values.add(new DataPointRollupPeriodValue(generator, RollupEnum.convertTo(vo.getRollup())));
            }
        }
        if (values.size() > 0) {
            // As the other endpoints, limit before simplification
            if (limit != null)
                values = values.subList(0, limit);
            if (vo.isSimplifyDataSets()) {
                if (vo.getSimplifyType() == DataPointVO.SimplifyTypes.TARGET)
                    values = SimplifyUtility.simplify(null, vo.getSimplifyTarget(), true, true, values);
                else
                    values = SimplifyUtility.simplify(vo.getSimplifyTolerance(), null, true, true, values);
            }
            processed.put(vo, values);
        }
    }
    return processed;
}