Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/17179#discussion_r106736186
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExec.scala
---
@@ -0,0 +1,270 @@
+/*
+ * 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.spark.sql.execution.streaming
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
+import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute,
AttributeReference, Expression, Literal, SortOrder, SpecificInternalRow,
UnsafeProjection, UnsafeRow}
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalKeyedState,
ProcessingTimeTimeout}
+import
org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution,
Distribution, Partitioning}
+import org.apache.spark.sql.execution._
+import org.apache.spark.sql.execution.streaming.state._
+import org.apache.spark.sql.streaming.{KeyedStateTimeout, OutputMode}
+import org.apache.spark.sql.types.{BooleanType, IntegerType}
+import org.apache.spark.util.CompletionIterator
+
+/**
+ * Physical operator for executing `FlatMapGroupsWithState.`
+ *
+ * @param func function called on each group
+ * @param keyDeserializer used to extract the key object for each group.
+ * @param valueDeserializer used to extract the items in the iterator from
an input row.
+ * @param groupingAttributes used to group the data
+ * @param dataAttributes used to read the data
+ * @param outputObjAttr used to define the output object
+ * @param stateEncoder used to serialize/deserialize state before calling
`func`
+ * @param outputMode the output mode of `func`
+ * @param timeout used to timeout groups that have not received data in a
while
+ * @param batchTimestampMs processing timestamp of the current batch.
+ */
+case class FlatMapGroupsWithStateExec(
+ func: (Any, Iterator[Any], LogicalKeyedState[Any]) => Iterator[Any],
+ keyDeserializer: Expression,
+ valueDeserializer: Expression,
+ groupingAttributes: Seq[Attribute],
+ dataAttributes: Seq[Attribute],
+ outputObjAttr: Attribute,
+ stateId: Option[OperatorStateId],
+ stateEncoder: ExpressionEncoder[Any],
+ outputMode: OutputMode,
+ timeout: KeyedStateTimeout,
+ batchTimestampMs: Long,
+ child: SparkPlan) extends UnaryExecNode with ObjectProducerExec with
StateStoreWriter {
+
+ private val isTimeoutEnabled = timeout == ProcessingTimeTimeout
+ private val timestampTimeoutAttribute =
+ AttributeReference("timeoutTimestamp", dataType = IntegerType,
nullable = false)()
+ private val stateExistsAttribute =
+ AttributeReference("stateExists", dataType = BooleanType, nullable =
false)()
+ private val stateAttributes: Seq[Attribute] = {
+ val encoderSchemaAttributes = stateEncoder.schema.toAttributes
+ if (isTimeoutEnabled) {
+ encoderSchemaAttributes :+ stateExistsAttribute :+
timestampTimeoutAttribute
+ } else encoderSchemaAttributes
+ }
+
+ import KeyedStateImpl._
+ override def outputPartitioning: Partitioning = child.outputPartitioning
+
+ /** Distribute by grouping attributes */
+ override def requiredChildDistribution: Seq[Distribution] =
+ ClusteredDistribution(groupingAttributes) :: Nil
+
+ /** Ordering needed for using GroupingIterator */
+ override def requiredChildOrdering: Seq[Seq[SortOrder]] =
+ Seq(groupingAttributes.map(SortOrder(_, Ascending)))
+
+ override protected def doExecute(): RDD[InternalRow] = {
+ metrics // force lazy init at driver
+
+ child.execute().mapPartitionsWithStateStore[InternalRow](
+ getStateId.checkpointLocation,
+ getStateId.operatorId,
+ getStateId.batchId,
+ groupingAttributes.toStructType,
+ stateAttributes.toStructType,
+ sqlContext.sessionState,
+ Some(sqlContext.streams.stateStoreCoordinator)) { case (store,
iterator) =>
+ val updater = new StateStoreUpdater(store)
+
+ // Generate a iterator that returns the rows grouped by the
grouping function
+ // Note that this code ensures that the filtering for timeout
occurs only after
+ // all the data has been processed. This is to ensure that the
timeout information of all
+ // the keys with data is updated before they are processed for
timeouts.
+ val outputIterator =
+ Seq(
--- End diff --
The parameter in `Iterator.++` is call-by-name: `def ++[B >: A](that: =>
GenTraversableOnce[B]): Iterator[B]`
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