Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3150#discussion_r96818876
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/DataSetSessionWindowAggregateReduceGroupFunction.scala
---
@@ -0,0 +1,179 @@
+/*
+ * 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.flink.table.runtime.aggregate
+
+import java.lang.Iterable
+
+import org.apache.flink.api.common.functions.RichGroupReduceFunction
+import org.apache.flink.types.Row
+import org.apache.flink.configuration.Configuration
+import org.apache.flink.util.{Collector, Preconditions}
+
+import scala.collection.JavaConversions._
+import org.apache.flink.streaming.api.windowing.windows.TimeWindow
+
+/**
+ * It wraps the aggregate logic inside of
+ * [[org.apache.flink.api.java.operators.GroupReduceOperator]]. It is
used for Session time-window
+ * on batch.
+ * Note:
+ * This can handle two input types:
+ * 1. when partial aggregate is not supported, the input data structure
of reduce is
+ * |groupKey1|groupKey2|sum1|count1|sum2|count2|rowTime|
+ * 2. when partial aggregate is supported, the input data structure of
reduce is
+ * |groupKey1|groupKey2|sum1|count1|sum2|count2|windowStart|windowEnd|
+ *
+ * @param aggregates The aggregate functions.
+ * @param groupKeysMapping The index mapping of group keys between
intermediate aggregate Row
+ * and output Row.
+ * @param aggregateMapping The index mapping between aggregate function
list and aggregated value
+ * index in output Row.
+ * @param intermediateRowArity The intermediate row field count.
+ * @param finalRowArity The output row field count.
+ * @param finalRowWindowStartPos The relative window-start field position.
+ * @param finalRowWindowEndPos The relative window-end field position.
+ * @param gap Session time window gap.
+ */
+class DataSetSessionWindowAggregateReduceGroupFunction(
+ aggregates: Array[Aggregate[_ <: Any]],
+ groupKeysMapping: Array[(Int, Int)],
+ aggregateMapping: Array[(Int, Int)],
+ intermediateRowArity: Int,
+ finalRowArity: Int,
+ finalRowWindowStartPos: Option[Int],
+ finalRowWindowEndPos: Option[Int],
+ gap:Long)
+ extends RichGroupReduceFunction[Row, Row] {
+
+ private var aggregateBuffer: Row = _
+ private var output: Row = _
+ private var collector: TimeWindowPropertyCollector = _
+ private var intermediateRowWindowStartPos = 0
+ private var intermediateRowWindowEndPos = 0
+
+ override def open(config: Configuration) {
+ Preconditions.checkNotNull(aggregates)
+ Preconditions.checkNotNull(groupKeysMapping)
+ aggregateBuffer = new Row(intermediateRowArity)
+ intermediateRowWindowStartPos = intermediateRowArity - 2
+ intermediateRowWindowEndPos = intermediateRowArity - 1
+ output = new Row(finalRowArity)
+ collector = new TimeWindowPropertyCollector(finalRowWindowStartPos,
finalRowWindowEndPos)
+ }
+
+ /**
+ * For grouped intermediate aggregate Rows, divide window according to
the window-start
+ * and window-end, merge data (within a unified window) into an
aggregate buffer, calculate
+ * aggregated values output from aggregate buffer, and then set them
into output
+ * Row based on the mapping relationship between intermediate aggregate
data and output data.
+ *
+ * @param records Grouped intermediate aggregate Rows iterator.
+ * @param out The collector to hand results to.
+ *
+ */
+ override def reduce(records: Iterable[Row], out: Collector[Row]): Unit =
{
+
+ var last: Row = null
+ var head: Row = null
+ var lastWindowEnd: java.lang.Long = null
+ var currentWindowStart:java.lang.Long = null
+
+ val iterator = records.iterator()
+
+ while (iterator.hasNext) {
+ val record = iterator.next()
+ currentWindowStart =
record.getField(intermediateRowWindowStartPos).asInstanceOf[Long]
+ // initial traversal or opening a new window
+ if (null == lastWindowEnd ||
+ (null != lastWindowEnd && currentWindowStart > lastWindowEnd)) {
+
+ // calculate the current window and open a new window
+ if (null != lastWindowEnd) {
+ // evaluate and emit the current window's result.
+ doEvaluateAndCollect(out, last, head)
+ }
+ // initiate intermediate aggregate value.
+ aggregates.foreach(_.initiate(aggregateBuffer))
+ head = record
+ }
+
+ aggregates.foreach(_.merge(record, aggregateBuffer))
+ last = record
--- End diff --
We cannot remember objects fetched from the iterator (see above).
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