guozhangwang commented on code in PR #12135: URL: https://github.com/apache/kafka/pull/12135#discussion_r872603611
########## streams/src/main/java/org/apache/kafka/streams/kstream/internals/AbstractKStreamTimeWindowAggregateProcessor.java: ########## @@ -0,0 +1,170 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.kafka.streams.kstream.internals; + +import static org.apache.kafka.streams.StreamsConfig.InternalConfig.EMIT_INTERVAL_MS_KSTREAMS_WINDOWED_AGGREGATION; +import static org.apache.kafka.streams.processor.internals.metrics.ProcessorNodeMetrics.emitFinalLatencySensor; +import static org.apache.kafka.streams.processor.internals.metrics.ProcessorNodeMetrics.emittedRecordsSensor; +import static org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl.maybeMeasureLatency; +import static org.apache.kafka.streams.processor.internals.metrics.TaskMetrics.droppedRecordsSensor; + +import org.apache.kafka.clients.consumer.ConsumerRecord; +import org.apache.kafka.common.metrics.Sensor; +import org.apache.kafka.common.utils.Time; +import org.apache.kafka.streams.KeyValue; +import org.apache.kafka.streams.StreamsConfig; +import org.apache.kafka.streams.kstream.EmitStrategy; +import org.apache.kafka.streams.kstream.EmitStrategy.StrategyType; +import org.apache.kafka.streams.kstream.Window; +import org.apache.kafka.streams.kstream.Windowed; +import org.apache.kafka.streams.kstream.internals.KStreamImplJoin.TimeTracker; +import org.apache.kafka.streams.processor.api.ContextualProcessor; +import org.apache.kafka.streams.processor.api.ProcessorContext; +import org.apache.kafka.streams.processor.api.Record; +import org.apache.kafka.streams.processor.internals.InternalProcessorContext; +import org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl; +import org.apache.kafka.streams.state.KeyValueIterator; +import org.apache.kafka.streams.state.TimestampedWindowStore; +import org.apache.kafka.streams.state.ValueAndTimestamp; + +public abstract class AbstractKStreamTimeWindowAggregateProcessor<KIn, VIn, VAgg> extends ContextualProcessor<KIn, VIn, Windowed<KIn>, Change<VAgg>> { + + private final Time time = Time.SYSTEM; + private final String storeName; + private final EmitStrategy emitStrategy; + private final boolean sendOldValues; + protected final TimeTracker timeTracker = new TimeTracker(); + + private TimestampedTupleForwarder<Windowed<KIn>, VAgg> tupleForwarder; + protected TimestampedWindowStore<KIn, VAgg> windowStore; + protected Sensor droppedRecordsSensor; + protected Sensor emittedRecordsSensor; + protected Sensor emitFinalLatencySensor; + protected long lastEmitWindowCloseTime = ConsumerRecord.NO_TIMESTAMP; + protected InternalProcessorContext<Windowed<KIn>, Change<VAgg>> internalProcessorContext; + + protected AbstractKStreamTimeWindowAggregateProcessor(final String storeName, + final EmitStrategy emitStrategy, + final boolean sendOldValues) { + this.storeName = storeName; + this.emitStrategy = emitStrategy; + this.sendOldValues = sendOldValues; + } + + @Override + public void init(final ProcessorContext<Windowed<KIn>, Change<VAgg>> context) { + super.init(context); + internalProcessorContext = (InternalProcessorContext<Windowed<KIn>, Change<VAgg>>) context; + final StreamsMetricsImpl metrics = internalProcessorContext.metrics(); + final String threadId = Thread.currentThread().getName(); + droppedRecordsSensor = droppedRecordsSensor(threadId, context.taskId().toString(), metrics); + emittedRecordsSensor = emittedRecordsSensor(threadId, context.taskId().toString(), + internalProcessorContext.currentNode().name(), metrics); + emitFinalLatencySensor = emitFinalLatencySensor(threadId, context.taskId().toString(), + internalProcessorContext.currentNode().name(), metrics); + windowStore = context.getStateStore(storeName); + + if (emitStrategy.type() == StrategyType.ON_WINDOW_CLOSE) { + // Restore last emit close time for ON_WINDOW_CLOSE strategy + final Long lastEmitTime = internalProcessorContext.processorMetadataForKey(storeName); + if (lastEmitTime != null) { + lastEmitWindowCloseTime = lastEmitTime; + } + final long emitInterval = StreamsConfig.InternalConfig.getLong( + context.appConfigs(), + EMIT_INTERVAL_MS_KSTREAMS_WINDOWED_AGGREGATION, + 1000L + ); + timeTracker.setEmitInterval(emitInterval); + } else { + tupleForwarder = new TimestampedTupleForwarder<>( + windowStore, + context, + new TimestampedCacheFlushListener<>(context), + sendOldValues); + } + } + + protected void maybeForwardUpdate(final Record<KIn, VIn> record, + final Window window, + final VAgg oldAgg, + final VAgg newAgg, + final long newTimestamp) { + if (emitStrategy.type() == StrategyType.ON_WINDOW_CLOSE) { + return; + } else if (tupleForwarder == null) { + throw new IllegalStateException("Emit strategy type is " + emitStrategy.type() + " but flush listener is not initialized."); + } + + tupleForwarder.maybeForward( + record.withKey(new Windowed<>(record.key(), window)) + .withValue(new Change<>(newAgg, sendOldValues ? oldAgg : null)) + .withTimestamp(newTimestamp)); + } + + protected boolean shouldEmitFinal(final long closeTime) { + if (emitStrategy.type() != StrategyType.ON_WINDOW_CLOSE) { + return false; + } + + final long now = internalProcessorContext.currentSystemTimeMs(); + // Throttle emit frequency + if (now < timeTracker.nextTimeToEmit) { + return false; + } + + // Schedule next emit time based on now to avoid the case that if system time jumps a lot, + // this can be triggered every time + timeTracker.nextTimeToEmit = now; + timeTracker.advanceNextTimeToEmit(); + + // Only EMIT if the window close time does progress + return lastEmitWindowCloseTime == ConsumerRecord.NO_TIMESTAMP || lastEmitWindowCloseTime < closeTime; + } + + protected void fetchAndEmit(final Record<KIn, VIn> record, + final long closeTime, + final long emitRangeLowerBoundInclusive, + final long emitRangeUpperBoundInclusive) { + final long startMs = time.milliseconds(); + + final KeyValueIterator<Windowed<KIn>, ValueAndTimestamp<VAgg>> windowToEmit = windowStore + .fetchAll(emitRangeLowerBoundInclusive, emitRangeUpperBoundInclusive); + + int emittedCount = 0; + while (windowToEmit.hasNext()) { + emittedCount++; + final KeyValue<Windowed<KIn>, ValueAndTimestamp<VAgg>> kv = windowToEmit.next(); + tupleForwarder.maybeForward( + record.withKey(kv.key) + .withValue(new Change<>(kv.value.value(), null)) + .withTimestamp(kv.value.timestamp()) + .withHeaders(record.headers())); + } + emittedRecordsSensor.record(emittedCount); + emitFinalLatencySensor.record(time.milliseconds() - startMs); + + lastEmitWindowCloseTime = closeTime; + internalProcessorContext.addProcessorMetadataKeyValue(storeName, closeTime); + } + + abstract protected void maybeForwardFinalResult(final Record<KIn, VIn> record, final long windowCloseTime); Review Comment: The instantiated `maybeForwardFinalResult` for time / sliding windows has a slight different validation check before calling `fetchAndEmit`. -- This is an automated message from the Apache Git Service. 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