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Posted to jira@kafka.apache.org by GitBox <gi...@apache.org> on 2022/05/10 22:43:05 UTC
[GitHub] [kafka] mjsax commented on a diff in pull request #12135: KAFKA-13785: [7/N][Emit final] emit final for sliding window
mjsax commented on code in PR #12135:
URL: https://github.com/apache/kafka/pull/12135#discussion_r869501138
##########
streams/src/main/java/org/apache/kafka/streams/kstream/EmitStrategy.java:
##########
@@ -19,15 +19,52 @@
import org.apache.kafka.streams.kstream.internals.UnlimitedWindow;
import org.apache.kafka.streams.kstream.internals.emitstrategy.WindowCloseStrategy;
import org.apache.kafka.streams.kstream.internals.emitstrategy.WindowUpdateStrategy;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.HashMap;
+import java.util.Map;
/**
* This interface controls the strategy that can be used to control how we emit results in a processor.
*/
public interface EmitStrategy {
+ Logger log = LoggerFactory.getLogger(EmitStrategy.class);
+
enum StrategyType {
- ON_WINDOW_CLOSE,
- ON_WINDOW_UPDATE
+ ON_WINDOW_UPDATE(0, new WindowUpdateStrategy()),
+ ON_WINDOW_CLOSE(1, new WindowCloseStrategy());
+
+ private final short code;
+ private final EmitStrategy strategy;
+
+ private short code() {
+ return this.code;
+ }
+
+ private EmitStrategy strategy() {
+ return this.strategy;
+ }
+
+ StrategyType(final int code, final EmitStrategy strategy) {
+ this.code = (short) code;
+ this.strategy = strategy;
+ }
+
+ private final static Map<Short, EmitStrategy> TYPE_TO_STRATEGY = new HashMap<>();
+
+ static {
+ for (final StrategyType type : StrategyType.values()) {
+ if (TYPE_TO_STRATEGY.put(type.code(), type.strategy()) != null)
+ throw new IllegalStateException("Code " + type.code() + " for type " +
Review Comment:
Never seen anything like this before -- is it best practice to have a guard like this?
##########
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);
+
+ protected void maybeMeasureEmitFinalLatency(final Record<KIn, VIn> record, final long windowCloseTime) {
Review Comment:
Nit: Should we make this method `final` ?
##########
streams/src/main/java/org/apache/kafka/streams/kstream/EmitStrategy.java:
##########
@@ -19,15 +19,52 @@
import org.apache.kafka.streams.kstream.internals.UnlimitedWindow;
import org.apache.kafka.streams.kstream.internals.emitstrategy.WindowCloseStrategy;
import org.apache.kafka.streams.kstream.internals.emitstrategy.WindowUpdateStrategy;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.HashMap;
+import java.util.Map;
/**
* This interface controls the strategy that can be used to control how we emit results in a processor.
*/
public interface EmitStrategy {
+ Logger log = LoggerFactory.getLogger(EmitStrategy.class);
+
enum StrategyType {
- ON_WINDOW_CLOSE,
- ON_WINDOW_UPDATE
+ ON_WINDOW_UPDATE(0, new WindowUpdateStrategy()),
+ ON_WINDOW_CLOSE(1, new WindowCloseStrategy());
+
+ private final short code;
+ private final EmitStrategy strategy;
+
+ private short code() {
+ return this.code;
+ }
+
+ private EmitStrategy strategy() {
+ return this.strategy;
+ }
+
+ StrategyType(final int code, final EmitStrategy strategy) {
Review Comment:
Why are you using `int` here? Seems cleaner to use `short` ?
##########
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<>(
Review Comment:
Why do we init the `tupleForwarder` only for "emit on change" -- don't we also need the forwarder for "emit final" (and just _use_ it differently)?
In the original code, we setup `TimestampedTupleForwarder` w/ or w/o the `TimestampedCacheFlushListener` for both cases.
##########
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);
Review Comment:
What's the definition for this sensor? Wondering about the semantics given the current implemenation?
##########
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(
Review Comment:
Seems we use `tupleForwarded` for the "emit final" case here, but it seems it was not initialized (cf my commend above on `init()` method)?
##########
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) {
Review Comment:
It seems this method is called as a first step inside the implementation of `maybeForwardFinalResult` -- thus, I am wondering if we should not make it private and call inside `maybeMeasureEmitFinalLatency` ?
##########
streams/src/main/java/org/apache/kafka/streams/kstream/internals/KStreamWindowAggregate.java:
##########
@@ -248,80 +182,43 @@ public void process(final Record<KIn, VIn> record) {
}
}
- tryEmitFinalResult(record, windowCloseTime);
+ maybeMeasureEmitFinalLatency(record, windowCloseTime);
}
- private void tryEmitFinalResult(final Record<KIn, VIn> record, final long windowCloseTime) {
- if (emitStrategy.type() != StrategyType.ON_WINDOW_CLOSE) {
- return;
- }
-
- final long now = internalProcessorContext.currentSystemTimeMs();
- // Throttle emit frequency as an optimization, the tradeoff is that we need to remember the
- // window close time when we emitted last time so that we can restart from there in the next emit
- if (now < timeTracker.nextTimeToEmit) {
- return;
- }
-
- // 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();
-
- // Window close time has not progressed, there will be no windows to close hence no records to emit
- if (lastEmitWindowCloseTime != ConsumerRecord.NO_TIMESTAMP && lastEmitWindowCloseTime >= windowCloseTime) {
+ @Override
+ protected void maybeForwardFinalResult(final Record<KIn, VIn> record, final long windowCloseTime) {
+ if (!shouldEmitFinal(windowCloseTime)) {
return;
}
final long emitRangeUpperBoundInclusive = windowCloseTime - windows.size();
- // No window has ever closed and hence no need to emit any records
if (emitRangeUpperBoundInclusive < 0) {
+ // If emitRangeUpperBoundInclusive is 0, it means first window closes since windowEndTime
+ // is exclusive
return;
}
-
- // Set emitRangeLowerBoundInclusive to -1L if lastEmitWindowCloseTime was not set so that
- // we would fetch from 0L for the first time; otherwise set it to lastEmitWindowCloseTime - windows.size().
- //
- // Note if we get here, it means emitRangeUpperBoundInclusive > 0, which means windowCloseTime > windows.size(),
- // Because we always set lastEmitWindowCloseTime to windowCloseTime before, it means
- // lastEmitWindowCloseTime - windows.size() should always > 0
- // As a result, emitRangeLowerBoundInclusive is always >= 0
+ // Because we only get here when emitRangeUpperBoundInclusive > 0 which means closeTime > windows.size()
+ // Since we set lastEmitCloseTime to closeTime before storing to processor metadata
+ // lastEmitCloseTime - windows.size() is always > 0
+ // Set emitRangeLowerBoundInclusive to -1L if not set so that when we fetchAll, we fetch from 0L
final long emitRangeLowerBoundInclusive = lastEmitWindowCloseTime == ConsumerRecord.NO_TIMESTAMP ?
-1L : lastEmitWindowCloseTime - windows.size();
Review Comment:
The code up to here is basically identical, except the use of `window.size()` vs `window. timeDifferenceMs()` -- would it be worth to unify?
##########
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:
I though `fetchAndEmit` would take care of "emit final" -- what is this method about?
##########
streams/src/main/java/org/apache/kafka/streams/kstream/internals/KStreamSlidingWindowAggregate.java:
##########
@@ -467,13 +459,35 @@ private boolean rightWindowIsNotEmpty(final ValueAndTimestamp<VAgg> rightWinAgg,
return rightWinAgg != null && rightWinAgg.timestamp() > inputRecordTimestamp;
}
+ @Override
+ protected void maybeForwardFinalResult(final Record<KIn, VIn> record, final long windowCloseTime) {
+ if (!shouldEmitFinal(windowCloseTime)) {
+ return;
+ }
+
+ final long emitRangeUpperBoundExclusive = windowCloseTime - windows.timeDifferenceMs();
+
+ if (emitRangeUpperBoundExclusive <= 0) {
+ // Sliding window's start and end timestamps are inclusive, so
+ // the window is not closed if emitRangeUpperBoundExclusive is 0,
+ // and we shouldn't emit
+ return;
+ }
+
+ final long emitRangeLowerBoundInclusive = lastEmitWindowCloseTime == ConsumerRecord.NO_TIMESTAMP ?
+ 0L : lastEmitWindowCloseTime - windows.timeDifferenceMs();
Review Comment:
Should this be:
```
final long emitRangeLowerBoundInclusive = Math.max(0L, lastEmitWindowCloseTime - windows.timeDifferenceMs());
```
Otherwise, if `lastEmitWindowCloseTime < windows.timeDifferenceMs()` the result could still be negative?
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