spark package 源码
spark package 代码
文件路径:/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/package.scala
/*
* 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 scala.reflect.ClassTag
import org.apache.spark.TaskContext
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.internal.SessionState
import org.apache.spark.sql.types.StructType
package object state {
implicit class StateStoreOps[T: ClassTag](dataRDD: RDD[T]) {
/** Map each partition of an RDD along with data in a [[StateStore]]. */
def mapPartitionsWithStateStore[U: ClassTag](
sqlContext: SQLContext,
stateInfo: StatefulOperatorStateInfo,
keySchema: StructType,
valueSchema: StructType,
numColsPrefixKey: Int)(
storeUpdateFunction: (StateStore, Iterator[T]) => Iterator[U]): StateStoreRDD[T, U] = {
mapPartitionsWithStateStore(
stateInfo,
keySchema,
valueSchema,
numColsPrefixKey,
sqlContext.sessionState,
Some(sqlContext.streams.stateStoreCoordinator))(
storeUpdateFunction)
}
/** Map each partition of an RDD along with data in a [[StateStore]]. */
def mapPartitionsWithStateStore[U: ClassTag](
stateInfo: StatefulOperatorStateInfo,
keySchema: StructType,
valueSchema: StructType,
numColsPrefixKey: Int,
sessionState: SessionState,
storeCoordinator: Option[StateStoreCoordinatorRef],
extraOptions: Map[String, String] = Map.empty)(
storeUpdateFunction: (StateStore, Iterator[T]) => Iterator[U]): StateStoreRDD[T, U] = {
val cleanedF = dataRDD.sparkContext.clean(storeUpdateFunction)
val wrappedF = (store: StateStore, iter: Iterator[T]) => {
// Abort the state store in case of error
TaskContext.get().addTaskCompletionListener[Unit](_ => {
if (!store.hasCommitted) store.abort()
})
cleanedF(store, iter)
}
new StateStoreRDD(
dataRDD,
wrappedF,
stateInfo.checkpointLocation,
stateInfo.queryRunId,
stateInfo.operatorId,
stateInfo.storeVersion,
keySchema,
valueSchema,
numColsPrefixKey,
sessionState,
storeCoordinator,
extraOptions)
}
/** Map each partition of an RDD along with data in a [[ReadStateStore]]. */
private[streaming] def mapPartitionsWithReadStateStore[U: ClassTag](
stateInfo: StatefulOperatorStateInfo,
keySchema: StructType,
valueSchema: StructType,
numColsPrefixKey: Int,
sessionState: SessionState,
storeCoordinator: Option[StateStoreCoordinatorRef],
extraOptions: Map[String, String] = Map.empty)(
storeReadFn: (ReadStateStore, Iterator[T]) => Iterator[U])
: ReadStateStoreRDD[T, U] = {
val cleanedF = dataRDD.sparkContext.clean(storeReadFn)
val wrappedF = (store: ReadStateStore, iter: Iterator[T]) => {
// Clean up the state store.
TaskContext.get().addTaskCompletionListener[Unit](_ => {
store.abort()
})
cleanedF(store, iter)
}
new ReadStateStoreRDD(
dataRDD,
wrappedF,
stateInfo.checkpointLocation,
stateInfo.queryRunId,
stateInfo.operatorId,
stateInfo.storeVersion,
keySchema,
valueSchema,
numColsPrefixKey,
sessionState,
storeCoordinator,
extraOptions)
}
}
}
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