kafka KStreamSessionWindowAggregate 源码
kafka KStreamSessionWindowAggregate 代码
文件路径：/streams/src/main/java/org/apache/kafka/streams/kstream/internals/KStreamSessionWindowAggregate.java
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* 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,
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package org.apache.kafka.streams.kstream.internals;
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.Aggregator;
import org.apache.kafka.streams.kstream.EmitStrategy;
import org.apache.kafka.streams.kstream.Initializer;
import org.apache.kafka.streams.kstream.Merger;
import org.apache.kafka.streams.kstream.SessionWindows;
import org.apache.kafka.streams.kstream.Windowed;
import org.apache.kafka.streams.processor.api.ContextualProcessor;
import org.apache.kafka.streams.processor.api.Processor;
import org.apache.kafka.streams.processor.api.ProcessorContext;
import org.apache.kafka.streams.processor.api.Record;
import org.apache.kafka.streams.processor.api.RecordMetadata;
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.SessionStore;
import org.apache.kafka.streams.state.ValueAndTimestamp;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.ArrayList;
import java.util.List;
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.TaskMetrics.droppedRecordsSensor;
public class KStreamSessionWindowAggregate<KIn, VIn, VAgg> implements KStreamAggProcessorSupplier<KIn, VIn, Windowed<KIn>, VAgg> {
private static final Logger LOG = LoggerFactory.getLogger(KStreamSessionWindowAggregate.class);
private final String storeName;
private final SessionWindows windows;
private final Initializer<VAgg> initializer;
private final Aggregator<? super KIn, ? super VIn, VAgg> aggregator;
private final Merger<? super KIn, VAgg> sessionMerger;
private final EmitStrategy emitStrategy;
private boolean sendOldValues = false;
public KStreamSessionWindowAggregate(final SessionWindows windows,
final String storeName,
final EmitStrategy emitStrategy,
final Initializer<VAgg> initializer,
final Aggregator<? super KIn, ? super VIn, VAgg> aggregator,
final Merger<? super KIn, VAgg> sessionMerger) {
this.windows = windows;
this.storeName = storeName;
this.emitStrategy = emitStrategy;
this.initializer = initializer;
this.aggregator = aggregator;
this.sessionMerger = sessionMerger;
}
@Override
public Processor<KIn, VIn, Windowed<KIn>, Change<VAgg>> get() {
return new KStreamSessionWindowAggregateProcessor();
}
public SessionWindows windows() {
return windows;
}
@Override
public void enableSendingOldValues() {
sendOldValues = true;
}
private class KStreamSessionWindowAggregateProcessor extends
ContextualProcessor<KIn, VIn, Windowed<KIn>, Change<VAgg>> {
private SessionStore<KIn, VAgg> store;
private TimestampedTupleForwarder<Windowed<KIn>, VAgg> tupleForwarder;
private Sensor droppedRecordsSensor;
private Sensor emittedRecordsSensor;
private Sensor emitFinalLatencySensor;
private long lastEmitWindowCloseTime = ConsumerRecord.NO_TIMESTAMP;
private long observedStreamTime = ConsumerRecord.NO_TIMESTAMP;
private InternalProcessorContext<Windowed<KIn>, Change<VAgg>> internalProcessorContext;
private final Time time = Time.SYSTEM;
protected final KStreamImplJoin.TimeTracker timeTracker = new KStreamImplJoin.TimeTracker();
@Override
public void init(final ProcessorContext<Windowed<KIn>, Change<VAgg>> context) {
super.init(context);
internalProcessorContext = (InternalProcessorContext<Windowed<KIn>, Change<VAgg>>) context;
final StreamsMetricsImpl metrics = (StreamsMetricsImpl) context.metrics();
final String threadId = Thread.currentThread().getName();
final String processorName = internalProcessorContext.currentNode().name();
droppedRecordsSensor = droppedRecordsSensor(threadId, context.taskId().toString(), metrics);
emittedRecordsSensor = emittedRecordsSensor(threadId, context.taskId().toString(), processorName, metrics);
emitFinalLatencySensor = emitFinalLatencySensor(threadId, context.taskId().toString(), processorName, metrics);
store = context.getStateStore(storeName);
if (emitStrategy.type() == EmitStrategy.StrategyType.ON_WINDOW_CLOSE) {
// Restore last emit close time for ON_WINDOW_CLOSE strategy
final Long lastEmitWindowCloseTime = internalProcessorContext.processorMetadataForKey(storeName);
if (lastEmitWindowCloseTime != null) {
this.lastEmitWindowCloseTime = lastEmitWindowCloseTime;
}
final long emitInterval = StreamsConfig.InternalConfig.getLong(
context.appConfigs(),
EMIT_INTERVAL_MS_KSTREAMS_WINDOWED_AGGREGATION,
1000L
);
timeTracker.setEmitInterval(emitInterval);
tupleForwarder = new TimestampedTupleForwarder<>(context, sendOldValues);
} else {
tupleForwarder = new TimestampedTupleForwarder<>(
store,
context,
new SessionCacheFlushListener<>(context),
sendOldValues);
}
}
@Override
public void process(final Record<KIn, VIn> record) {
// if the key is null, we do not need proceed aggregating
// the record with the table
if (record.key() == null) {
logSkippedRecordForNullKey();
return;
}
final long timestamp = record.timestamp();
observedStreamTime = Math.max(observedStreamTime, timestamp);
final long windowCloseTime = observedStreamTime - windows.gracePeriodMs() - windows.inactivityGap();
final List<KeyValue<Windowed<KIn>, VAgg>> merged = new ArrayList<>();
final SessionWindow newSessionWindow = new SessionWindow(timestamp, timestamp);
SessionWindow mergedWindow = newSessionWindow;
VAgg agg = initializer.apply();
try (
final KeyValueIterator<Windowed<KIn>, VAgg> iterator = store.findSessions(
record.key(),
timestamp - windows.inactivityGap(),
timestamp + windows.inactivityGap()
)
) {
while (iterator.hasNext()) {
final KeyValue<Windowed<KIn>, VAgg> next = iterator.next();
merged.add(next);
agg = sessionMerger.apply(record.key(), agg, next.value);
mergedWindow = mergeSessionWindow(mergedWindow, (SessionWindow) next.key.window());
}
}
if (mergedWindow.end() < windowCloseTime) {
logSkippedRecordForExpiredWindow(timestamp, windowCloseTime, mergedWindow);
} else {
if (!mergedWindow.equals(newSessionWindow)) {
for (final KeyValue<Windowed<KIn>, VAgg> session : merged) {
store.remove(session.key);
maybeForwardUpdate(session.key, session.value, null);
}
}
agg = aggregator.apply(record.key(), record.value(), agg);
final Windowed<KIn> sessionKey = new Windowed<>(record.key(), mergedWindow);
store.put(sessionKey, agg);
maybeForwardUpdate(sessionKey, null, agg);
}
maybeForwardFinalResult(record, windowCloseTime);
}
private void maybeForwardUpdate(final Windowed<KIn> windowedkey,
final VAgg oldAgg,
final VAgg newAgg) {
if (emitStrategy.type() == EmitStrategy.StrategyType.ON_WINDOW_CLOSE) {
return;
}
// Update the sent record timestamp to the window end time if possible
final long newTimestamp = windowedkey.window().end();
tupleForwarder.maybeForward(new Record<>(windowedkey, new Change<>(newAgg, sendOldValues ? oldAgg : null), newTimestamp));
}
// TODO: consolidate SessionWindow with TimeWindow to merge common functions
private void maybeForwardFinalResult(final Record<KIn, VIn> record, final long windowCloseTime) {
if (shouldEmitFinal(windowCloseTime)) {
final long emitRangeUpperBound = emitRangeUpperBound(windowCloseTime);
// if the upper bound is smaller than 0, then there's no window closed ever;
// and we can skip range fetching
if (emitRangeUpperBound >= 0) {
final long emitRangeLowerBound = emitRangeLowerBound();
if (shouldRangeFetch(emitRangeLowerBound, emitRangeUpperBound)) {
fetchAndEmit(record, windowCloseTime, emitRangeLowerBound, emitRangeUpperBound);
}
}
}
}
private boolean shouldEmitFinal(final long windowCloseTime) {
if (emitStrategy.type() != EmitStrategy.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 < windowCloseTime;
}
private long emitRangeLowerBound() {
return Math.max(0L, lastEmitWindowCloseTime);
}
private long emitRangeUpperBound(final long windowCloseTime) {
// Session window's start and end timestamps are inclusive, so
// we should minus 1 for the inclusive closed window-end upper bound
return windowCloseTime - 1;
}
private boolean shouldRangeFetch(final long emitRangeLowerBound, final long emitRangeUpperBound) {
// since a session window could be a single point (i.e. [t, t]),
// we need to range fetch and emit even if the upper and lower bound are the same
return emitRangeUpperBound >= emitRangeLowerBound;
}
private void fetchAndEmit(final Record<KIn, VIn> record,
final long windowCloseTime,
final long emitRangeLowerBound,
final long emitRangeUpperBound) {
final long startMs = time.milliseconds();
// Only time ordered (indexed) session store should have implemented
// this function, otherwise a not-supported exception would throw
final KeyValueIterator<Windowed<KIn>, VAgg> windowToEmit = store
.findSessions(emitRangeLowerBound, emitRangeUpperBound);
int emittedCount = 0;
while (windowToEmit.hasNext()) {
emittedCount++;
final KeyValue<Windowed<KIn>, VAgg> kv = windowToEmit.next();
tupleForwarder.maybeForward(
record.withKey(kv.key)
.withValue(new Change<>(kv.value, null))
// set the timestamp as the window end timestamp
.withTimestamp(kv.key.window().end())
.withHeaders(record.headers()));
}
emittedRecordsSensor.record(emittedCount);
emitFinalLatencySensor.record(time.milliseconds() - startMs);
lastEmitWindowCloseTime = windowCloseTime;
internalProcessorContext.addProcessorMetadataKeyValue(storeName, windowCloseTime);
}
private void logSkippedRecordForNullKey() {
if (context().recordMetadata().isPresent()) {
final RecordMetadata recordMetadata = context().recordMetadata().get();
LOG.warn(
"Skipping record due to null key. "
+ "topic=[{}] partition=[{}] offset=[{}]",
recordMetadata.topic(), recordMetadata.partition(), recordMetadata.offset()
);
} else {
LOG.warn(
"Skipping record due to null key. Topic, partition, and offset not known."
);
}
droppedRecordsSensor.record();
}
private void logSkippedRecordForExpiredWindow(final long timestamp,
final long windowExpire,
final SessionWindow window) {
final String windowString = "[" + window.start() + "," + window.end() + "]";
if (context().recordMetadata().isPresent()) {
final RecordMetadata recordMetadata = context().recordMetadata().get();
LOG.warn("Skipping record for expired window. " +
"topic=[{}] " +
"partition=[{}] " +
"offset=[{}] " +
"timestamp=[{}] " +
"window={} " +
"expiration=[{}] " +
"streamTime=[{}]",
recordMetadata.topic(),
recordMetadata.partition(),
recordMetadata.offset(),
timestamp,
windowString,
windowExpire,
observedStreamTime
);
} else {
LOG.warn("Skipping record for expired window. Topic, partition, and offset not known. " +
"timestamp=[{}] " +
"window={} " +
"expiration=[{}] " +
"streamTime=[{}]",
timestamp,
windowString,
windowExpire,
observedStreamTime
);
}
droppedRecordsSensor.record();
}
}
private SessionWindow mergeSessionWindow(final SessionWindow one, final SessionWindow two) {
final long start = Math.min(one.start(), two.start());
final long end = Math.max(one.end(), two.end());
return new SessionWindow(start, end);
}
@Override
public KTableValueGetterSupplier<Windowed<KIn>, VAgg> view() {
return new KTableValueGetterSupplier<Windowed<KIn>, VAgg>() {
@Override
public KTableValueGetter<Windowed<KIn>, VAgg> get() {
return new KTableSessionWindowValueGetter();
}
@Override
public String[] storeNames() {
return new String[]{storeName};
}
};
}
private class KTableSessionWindowValueGetter implements KTableValueGetter<Windowed<KIn>, VAgg> {
private SessionStore<KIn, VAgg> store;
@Override
public void init(final ProcessorContext<?, ?> context) {
store = context.getStateStore(storeName);
}
@Override
public ValueAndTimestamp<VAgg> get(final Windowed<KIn> key) {
return ValueAndTimestamp.make(
store.fetchSession(key.key(), key.window().start(), key.window().end()),
key.window().end());
}
}
}
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