anishshri-db commented on code in PR #43961: URL: https://github.com/apache/spark/pull/43961#discussion_r1430755921
########## sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TransformWithStateExec.scala: ########## @@ -0,0 +1,171 @@ +/* + * 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 java.util.concurrent.TimeUnit.NANOSECONDS + +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, Expression, SortOrder, UnsafeRow} +import org.apache.spark.sql.catalyst.plans.physical.Distribution +import org.apache.spark.sql.execution._ +import org.apache.spark.sql.execution.streaming.state._ +import org.apache.spark.sql.streaming.{OutputMode, StatefulProcessor} +import org.apache.spark.sql.types._ +import org.apache.spark.util.CompletionIterator + +/** + * Physical operator for executing `TransformWithState` + * + * @param statefulProcessor processor methods called on underlying data + * @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 Defines the output object + * @param batchTimestampMs processing timestamp of the current batch. + * @param eventTimeWatermarkForLateEvents event time watermark for filtering late events + * @param eventTimeWatermarkForEviction event time watermark for state eviction + * @param child the physical plan for the underlying data + */ +case class TransformWithStateExec( + keyDeserializer: Expression, + valueDeserializer: Expression, + groupingAttributes: Seq[Attribute], + dataAttributes: Seq[Attribute], + statefulProcessor: StatefulProcessor[Any, Any, Any], + outputMode: OutputMode, + outputObjAttr: Attribute, + stateInfo: Option[StatefulOperatorStateInfo], + batchTimestampMs: Option[Long], + eventTimeWatermarkForLateEvents: Option[Long], + eventTimeWatermarkForEviction: Option[Long], + child: SparkPlan) + extends UnaryExecNode + with StateStoreWriter + with WatermarkSupport + with ObjectProducerExec { + + override def shortName: String = "transformWithStateExec" + + override def shouldRunAnotherBatch(newInputWatermark: Long): Boolean = false + + override protected def withNewChildInternal( + newChild: SparkPlan): TransformWithStateExec = copy(child = newChild) + + override def keyExpressions: Seq[Attribute] = groupingAttributes + + protected val schemaForKeyRow: StructType = new StructType().add("key", BinaryType) + + protected val schemaForValueRow: StructType = new StructType().add("value", BinaryType) + + override def requiredChildDistribution: Seq[Distribution] = { + StatefulOperatorPartitioning.getCompatibleDistribution(groupingAttributes, + getStateInfo, conf) :: + Nil + } + + override def requiredChildOrdering: Seq[Seq[SortOrder]] = Seq( + groupingAttributes.map(SortOrder(_, Ascending))) + + private def handleInputRows(keyRow: UnsafeRow, valueRowIter: Iterator[InternalRow]): + Iterator[InternalRow] = { + val getKeyObj = + ObjectOperator.deserializeRowToObject(keyDeserializer, groupingAttributes) + + val getValueObj = + ObjectOperator.deserializeRowToObject(valueDeserializer, dataAttributes) + + val getOutputRow = ObjectOperator.wrapObjectToRow(outputObjectType) + + val keyObj = getKeyObj(keyRow) // convert key to objects + ImplicitKeyTracker.setImplicitKey(keyObj) + val valueObjIter = valueRowIter.map(getValueObj.apply) + val mappedIterator = statefulProcessor.handleInputRows(keyObj, valueObjIter, + new TimerValuesImpl(batchTimestampMs, eventTimeWatermarkForLateEvents)).map { obj => + getOutputRow(obj) + } + ImplicitKeyTracker.removeImplicitKey() + mappedIterator + } + + private def processNewData(dataIter: Iterator[InternalRow]): Iterator[InternalRow] = { + val groupedIter = GroupedIterator(dataIter, groupingAttributes, child.output) + groupedIter.flatMap { case (keyRow, valueRowIter) => + val keyUnsafeRow = keyRow.asInstanceOf[UnsafeRow] + handleInputRows(keyUnsafeRow, valueRowIter) + } + } + + private def processDataWithPartition( + iter: Iterator[InternalRow], + store: StateStore, + processorHandle: StatefulProcessorHandleImpl): + CompletionIterator[InternalRow, Iterator[InternalRow]] = { + val allUpdatesTimeMs = longMetric("allUpdatesTimeMs") + val commitTimeMs = longMetric("commitTimeMs") + + val currentTimeNs = System.nanoTime + val updatesStartTimeNs = currentTimeNs + + // If timeout is based on event time, then filter late data based on watermark + val filteredIter = watermarkPredicateForDataForLateEvents match { + case Some(predicate) => + applyRemovingRowsOlderThanWatermark(iter, predicate) + case _ => + iter + } + + val outputIterator = processNewData(filteredIter) + processorHandle.setHandleState(StatefulProcessorHandleState.DATA_PROCESSED) + // Return an iterator of all the rows generated by all the keys, such that when fully + // consumed, all the state updates will be committed by the state store + CompletionIterator[InternalRow, Iterator[InternalRow]](outputIterator, { + // Note: Due to the iterator lazy execution, this metric also captures the time taken + // by the upstream (consumer) operators in addition to the processing in this operator. + allUpdatesTimeMs += NANOSECONDS.toMillis(System.nanoTime - updatesStartTimeNs) + commitTimeMs += timeTakenMs { + store.commit() + } + setStoreMetrics(store) + setOperatorMetrics() + statefulProcessor.close() + processorHandle.setHandleState(StatefulProcessorHandleState.CLOSED) + }) + } + + override protected def doExecute(): RDD[InternalRow] = { + metrics Review Comment: 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