mjsax commented on a change in pull request #9039:
URL: https://github.com/apache/kafka/pull/9039#discussion_r466032804



##########
File path: 
streams/src/main/java/org/apache/kafka/streams/kstream/internals/KStreamSlidingWindowAggregate.java
##########
@@ -0,0 +1,389 @@
+/*
+ * 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 org.apache.kafka.clients.consumer.ConsumerRecord;
+import org.apache.kafka.common.metrics.Sensor;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.kstream.Aggregator;
+import org.apache.kafka.streams.kstream.Initializer;
+import org.apache.kafka.streams.kstream.Window;
+import org.apache.kafka.streams.kstream.Windowed;
+import org.apache.kafka.streams.kstream.SlidingWindows;
+import org.apache.kafka.streams.processor.AbstractProcessor;
+import org.apache.kafka.streams.processor.Processor;
+import org.apache.kafka.streams.processor.ProcessorContext;
+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;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import java.time.Instant;
+import java.util.HashSet;
+import static 
org.apache.kafka.streams.processor.internals.metrics.TaskMetrics.droppedRecordsSensorOrLateRecordDropSensor;
+import static 
org.apache.kafka.streams.processor.internals.metrics.TaskMetrics.droppedRecordsSensorOrSkippedRecordsSensor;
+import static org.apache.kafka.streams.state.ValueAndTimestamp.getValueOrNull;
+
+public class KStreamSlidingWindowAggregate<K, V, Agg> implements 
KStreamAggProcessorSupplier<K, Windowed<K>, V, Agg> {
+    private final Logger log = LoggerFactory.getLogger(getClass());
+
+    private final String storeName;
+    private final SlidingWindows windows;
+    private final Initializer<Agg> initializer;
+    private final Aggregator<? super K, ? super V, Agg> aggregator;
+
+    private boolean sendOldValues = false;
+
+    public KStreamSlidingWindowAggregate(final SlidingWindows windows,
+                                          final String storeName,
+                                          final Initializer<Agg> initializer,
+                                          final Aggregator<? super K, ? super 
V, Agg> aggregator) {
+        this.windows = windows;
+        this.storeName = storeName;
+        this.initializer = initializer;
+        this.aggregator = aggregator;
+    }
+
+    @Override
+    public Processor<K, V> get() {
+        return new KStreamSlidingWindowAggregateProcessor();
+    }
+
+    public SlidingWindows windows() {
+        return windows;
+    }
+
+    @Override
+    public void enableSendingOldValues() {
+        sendOldValues = true;
+    }
+
+    private class KStreamSlidingWindowAggregateProcessor extends 
AbstractProcessor<K, V> {
+        private TimestampedWindowStore<K, Agg> windowStore;
+        private TimestampedTupleForwarder<Windowed<K>, Agg> tupleForwarder;
+        private StreamsMetricsImpl metrics;
+        private InternalProcessorContext internalProcessorContext;
+        private Sensor lateRecordDropSensor;
+        private Sensor droppedRecordsSensor;
+        private long observedStreamTime = ConsumerRecord.NO_TIMESTAMP;
+        private boolean reverseIteratorImplemented = false;
+
+        @SuppressWarnings("unchecked")
+        @Override
+        public void init(final ProcessorContext context) {
+            super.init(context);
+            internalProcessorContext = (InternalProcessorContext) context;
+            metrics = internalProcessorContext.metrics();
+            final String threadId = Thread.currentThread().getName();
+            lateRecordDropSensor = droppedRecordsSensorOrLateRecordDropSensor(
+                    threadId,
+                    context.taskId().toString(),
+                    internalProcessorContext.currentNode().name(),
+                    metrics
+            );
+            //catch unsupported operation error
+            droppedRecordsSensor = 
droppedRecordsSensorOrSkippedRecordsSensor(threadId, 
context.taskId().toString(), metrics);
+            windowStore = (TimestampedWindowStore<K, Agg>) 
context.getStateStore(storeName);
+            tupleForwarder = new TimestampedTupleForwarder<>(
+                    windowStore,
+                    context,
+                    new TimestampedCacheFlushListener<>(context),
+                    sendOldValues);
+        }
+
+        @Override
+        public void process(final K key, final V value) {
+            if (reverseIteratorImplemented) {
+                processReverse(key, value);
+            } else {
+                processInOrder(key, value);
+            }
+        }
+
+        @SuppressWarnings("checkstyle:LineLength")
+        public void processReverse(final K key, final V value) {
+            if (key == null) {
+                log.warn(
+                        "Skipping record due to null key. value=[{}] 
topic=[{}] partition=[{}] offset=[{}]",
+                        value, context().topic(), context().partition(), 
context().offset()
+                );
+                droppedRecordsSensor.record();
+                return;
+            }
+
+            final long timestamp = context().timestamp();
+            observedStreamTime = Math.max(observedStreamTime, timestamp);

Review comment:
       Thanks for confirming. Let keep this issue out for this PR than.




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