org.apache.spark.sql.streaming.StreamingQueryManager.scala Maven / Gradle / Ivy
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* 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.streaming
import java.util.UUID
import java.util.concurrent.{TimeoutException, TimeUnit}
import javax.annotation.concurrent.GuardedBy
import scala.collection.mutable
import scala.jdk.CollectionConverters._
import org.apache.spark.annotation.Evolving
import org.apache.spark.internal.{Logging, MDC}
import org.apache.spark.internal.LogKeys.{CLASS_NAME, QUERY_ID, RUN_ID}
import org.apache.spark.sql.{DataFrame, SparkSession}
import org.apache.spark.sql.catalyst.catalog.CatalogTable
import org.apache.spark.sql.catalyst.streaming.{WriteToStream, WriteToStreamStatement}
import org.apache.spark.sql.connector.catalog.{Identifier, SupportsWrite, Table, TableCatalog}
import org.apache.spark.sql.errors.QueryExecutionErrors
import org.apache.spark.sql.execution.streaming._
import org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution
import org.apache.spark.sql.execution.streaming.state.StateStoreCoordinatorRef
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.internal.StaticSQLConf.STREAMING_QUERY_LISTENERS
import org.apache.spark.util.{Clock, SystemClock, Utils}
/**
* A class to manage all the [[StreamingQuery]] active in a `SparkSession`.
*
* @since 2.0.0
*/
@Evolving
class StreamingQueryManager private[sql] (
sparkSession: SparkSession,
sqlConf: SQLConf) extends Logging {
private[sql] val stateStoreCoordinator =
StateStoreCoordinatorRef.forDriver(sparkSession.sparkContext.env)
private val listenerBus =
new StreamingQueryListenerBus(Some(sparkSession.sparkContext.listenerBus))
@GuardedBy("activeQueriesSharedLock")
private val activeQueries = new mutable.HashMap[UUID, StreamingQuery]
// A global lock to keep track of active streaming queries across Spark sessions
private val activeQueriesSharedLock = sparkSession.sharedState.activeQueriesLock
private val awaitTerminationLock = new Object
/**
* Track the last terminated query and remember the last failure since the creation of the
* context, or since `resetTerminated()` was called. There are three possible values:
*
* - null: no query has been been terminated.
* - None: some queries have been terminated and no one has failed.
* - Some(StreamingQueryException): Some queries have been terminated and at least one query has
* failed. The exception is the exception of the last failed query.
*/
@GuardedBy("awaitTerminationLock")
private var lastTerminatedQueryException: Option[StreamingQueryException] = null
try {
sparkSession.sparkContext.conf.get(STREAMING_QUERY_LISTENERS).foreach { classNames =>
SQLConf.withExistingConf(sqlConf) {
Utils.loadExtensions(classOf[StreamingQueryListener], classNames,
sparkSession.sparkContext.conf).foreach { listener =>
addListener(listener)
logInfo(log"Registered listener ${MDC(CLASS_NAME, listener.getClass.getName)}")
}
}
}
sparkSession.sharedState.streamingQueryStatusListener.foreach { listener =>
addListener(listener)
}
} catch {
case e: Exception =>
throw QueryExecutionErrors.registeringStreamingQueryListenerError(e)
}
/**
* Returns a list of active queries associated with this SQLContext
*
* @since 2.0.0
*/
def active: Array[StreamingQuery] = activeQueriesSharedLock.synchronized {
activeQueries.values.toArray
}
/**
* Returns the query if there is an active query with the given id, or null.
*
* @since 2.1.0
*/
def get(id: UUID): StreamingQuery = activeQueriesSharedLock.synchronized {
activeQueries.get(id).orNull
}
/**
* Returns the query if there is an active query with the given id, or null.
*
* @since 2.1.0
*/
def get(id: String): StreamingQuery = get(UUID.fromString(id))
/**
* Wait until any of the queries on the associated SQLContext has terminated since the
* creation of the context, or since `resetTerminated()` was called. If any query was terminated
* with an exception, then the exception will be thrown.
*
* If a query has terminated, then subsequent calls to `awaitAnyTermination()` will either
* return immediately (if the query was terminated by `query.stop()`),
* or throw the exception immediately (if the query was terminated with exception). Use
* `resetTerminated()` to clear past terminations and wait for new terminations.
*
* In the case where multiple queries have terminated since `resetTermination()` was called,
* if any query has terminated with exception, then `awaitAnyTermination()` will
* throw any of the exception. For correctly documenting exceptions across multiple queries,
* users need to stop all of them after any of them terminates with exception, and then check the
* `query.exception()` for each query.
*
* @throws StreamingQueryException if any query has terminated with an exception
*
* @since 2.0.0
*/
@throws[StreamingQueryException]
def awaitAnyTermination(): Unit = {
awaitTerminationLock.synchronized {
while (lastTerminatedQueryException == null) {
awaitTerminationLock.wait(10)
}
if (lastTerminatedQueryException != null && lastTerminatedQueryException.nonEmpty) {
throw lastTerminatedQueryException.get
}
}
}
/**
* Wait until any of the queries on the associated SQLContext has terminated since the
* creation of the context, or since `resetTerminated()` was called. Returns whether any query
* has terminated or not (multiple may have terminated). If any query has terminated with an
* exception, then the exception will be thrown.
*
* If a query has terminated, then subsequent calls to `awaitAnyTermination()` will either
* return `true` immediately (if the query was terminated by `query.stop()`),
* or throw the exception immediately (if the query was terminated with exception). Use
* `resetTerminated()` to clear past terminations and wait for new terminations.
*
* In the case where multiple queries have terminated since `resetTermination()` was called,
* if any query has terminated with exception, then `awaitAnyTermination()` will
* throw any of the exception. For correctly documenting exceptions across multiple queries,
* users need to stop all of them after any of them terminates with exception, and then check the
* `query.exception()` for each query.
*
* @throws StreamingQueryException if any query has terminated with an exception
*
* @since 2.0.0
*/
@throws[StreamingQueryException]
def awaitAnyTermination(timeoutMs: Long): Boolean = {
val startTime = System.nanoTime()
def isTimedout = {
System.nanoTime() - startTime >= TimeUnit.MILLISECONDS.toNanos(timeoutMs)
}
awaitTerminationLock.synchronized {
while (!isTimedout && lastTerminatedQueryException == null) {
awaitTerminationLock.wait(10)
}
if (lastTerminatedQueryException != null && lastTerminatedQueryException.nonEmpty) {
throw lastTerminatedQueryException.get
}
lastTerminatedQueryException != null
}
}
/**
* Forget about past terminated queries so that `awaitAnyTermination()` can be used again to
* wait for new terminations.
*
* @since 2.0.0
*/
def resetTerminated(): Unit = {
awaitTerminationLock.synchronized {
lastTerminatedQueryException = null
}
}
/**
* Register a [[StreamingQueryListener]] to receive up-calls for life cycle events of
* [[StreamingQuery]].
*
* @since 2.0.0
*/
def addListener(listener: StreamingQueryListener): Unit = {
listenerBus.addListener(listener)
}
/**
* Deregister a [[StreamingQueryListener]].
*
* @since 2.0.0
*/
def removeListener(listener: StreamingQueryListener): Unit = {
listenerBus.removeListener(listener)
}
/**
* List all [[StreamingQueryListener]]s attached to this [[StreamingQueryManager]].
*
* @since 3.0.0
*/
def listListeners(): Array[StreamingQueryListener] = {
listenerBus.listeners.asScala.toArray
}
/** Post a listener event */
private[sql] def postListenerEvent(event: StreamingQueryListener.Event): Unit = {
listenerBus.post(event)
}
private def useAsyncProgressTracking(extraOptions: Map[String, String]): Boolean = {
extraOptions.getOrElse(
AsyncProgressTrackingMicroBatchExecution.ASYNC_PROGRESS_TRACKING_ENABLED, "false").toBoolean
}
// scalastyle:off argcount
private def createQuery(
userSpecifiedName: Option[String],
userSpecifiedCheckpointLocation: Option[String],
df: DataFrame,
extraOptions: Map[String, String],
sink: Table,
outputMode: OutputMode,
useTempCheckpointLocation: Boolean,
recoverFromCheckpointLocation: Boolean,
trigger: Trigger,
triggerClock: Clock,
catalogAndIdent: Option[(TableCatalog, Identifier)] = None,
catalogTable: Option[CatalogTable] = None): StreamingQueryWrapper = {
val analyzedPlan = df.queryExecution.analyzed
df.queryExecution.assertAnalyzed()
val dataStreamWritePlan = WriteToStreamStatement(
userSpecifiedName,
userSpecifiedCheckpointLocation,
useTempCheckpointLocation,
recoverFromCheckpointLocation,
sink,
outputMode,
df.sparkSession.sessionState.newHadoopConf(),
trigger.isInstanceOf[ContinuousTrigger],
analyzedPlan,
catalogAndIdent,
catalogTable)
val analyzedStreamWritePlan =
sparkSession.sessionState.executePlan(dataStreamWritePlan).analyzed
.asInstanceOf[WriteToStream]
(sink, trigger) match {
case (_: SupportsWrite, trigger: ContinuousTrigger) =>
new StreamingQueryWrapper(new ContinuousExecution(
sparkSession,
trigger,
triggerClock,
extraOptions,
analyzedStreamWritePlan))
case _ =>
val microBatchExecution = if (useAsyncProgressTracking(extraOptions)) {
new AsyncProgressTrackingMicroBatchExecution(
sparkSession,
trigger,
triggerClock,
extraOptions,
analyzedStreamWritePlan)
} else {
new MicroBatchExecution(
sparkSession,
trigger,
triggerClock,
extraOptions,
analyzedStreamWritePlan)
}
new StreamingQueryWrapper(microBatchExecution)
}
}
// scalastyle:on argcount
// scalastyle:off argcount
/**
* Start a [[StreamingQuery]].
*
* @param userSpecifiedName Query name optionally specified by the user.
* @param userSpecifiedCheckpointLocation Checkpoint location optionally specified by the user.
* @param df Streaming DataFrame.
* @param sink Sink to write the streaming outputs.
* @param outputMode Output mode for the sink.
* @param useTempCheckpointLocation Whether to use a temporary checkpoint location when the user
* has not specified one. If false, then error will be thrown.
* @param recoverFromCheckpointLocation Whether to recover query from the checkpoint location.
* If false and the checkpoint location exists, then error
* will be thrown.
* @param trigger [[Trigger]] for the query.
* @param triggerClock [[Clock]] to use for the triggering.
* @param catalogAndIdent Catalog and identifier for the sink, set when it is a V2 catalog table
*/
@throws[TimeoutException]
private[sql] def startQuery(
userSpecifiedName: Option[String],
userSpecifiedCheckpointLocation: Option[String],
df: DataFrame,
extraOptions: Map[String, String],
sink: Table,
outputMode: OutputMode,
useTempCheckpointLocation: Boolean = false,
recoverFromCheckpointLocation: Boolean = true,
trigger: Trigger = Trigger.ProcessingTime(0),
triggerClock: Clock = new SystemClock(),
catalogAndIdent: Option[(TableCatalog, Identifier)] = None,
catalogTable: Option[CatalogTable] = None): StreamingQuery = {
val query = createQuery(
userSpecifiedName,
userSpecifiedCheckpointLocation,
df,
extraOptions,
sink,
outputMode,
useTempCheckpointLocation,
recoverFromCheckpointLocation,
trigger,
triggerClock,
catalogAndIdent,
catalogTable)
// scalastyle:on argcount
// The following code block checks if a stream with the same name or id is running. Then it
// returns an Option of an already active stream to stop outside of the lock
// to avoid a deadlock.
val activeRunOpt = activeQueriesSharedLock.synchronized {
// Make sure no other query with same name is active
userSpecifiedName.foreach { name =>
if (activeQueries.values.exists(_.name == name)) {
throw new IllegalArgumentException(s"Cannot start query with name $name as a query " +
s"with that name is already active in this SparkSession")
}
}
// Make sure no other query with same id is active across all sessions
val activeOption = Option(sparkSession.sharedState.activeStreamingQueries.get(query.id))
.orElse(activeQueries.get(query.id)) // shouldn't be needed but paranoia ...
val shouldStopActiveRun =
sparkSession.conf.get(SQLConf.STREAMING_STOP_ACTIVE_RUN_ON_RESTART)
if (activeOption.isDefined) {
if (shouldStopActiveRun) {
val oldQuery = activeOption.get
logWarning(log"Stopping existing streaming query [id=${MDC(QUERY_ID, query.id)}, " +
log"runId=${MDC(RUN_ID, oldQuery.runId)}], as a new run is being started.")
Some(oldQuery)
} else {
throw new IllegalStateException(
s"Cannot start query with id ${query.id} as another query with same id is " +
s"already active. Perhaps you are attempting to restart a query from checkpoint " +
s"that is already active. You may stop the old query by setting the SQL " +
"configuration: " +
s"""spark.conf.set("${SQLConf.STREAMING_STOP_ACTIVE_RUN_ON_RESTART.key}", true) """ +
"and retry.")
}
} else {
// nothing to stop so, no-op
None
}
}
// stop() will clear the queryId from activeStreamingQueries as well as activeQueries
activeRunOpt.foreach(_.stop())
activeQueriesSharedLock.synchronized {
// We still can have a race condition when two concurrent instances try to start the same
// stream, while a third one was already active and stopped above. In this case, we throw a
// ConcurrentModificationException.
val oldActiveQuery = sparkSession.sharedState.activeStreamingQueries.put(
query.id, query.streamingQuery) // we need to put the StreamExecution, not the wrapper
if (oldActiveQuery != null) {
throw QueryExecutionErrors.concurrentQueryInstanceError()
}
activeQueries.put(query.id, query)
}
try {
// When starting a query, it will call `StreamingQueryListener.onQueryStarted` synchronously.
// As it's provided by the user and can run arbitrary codes, we must not hold any lock here.
// Otherwise, it's easy to cause dead-lock, or block too long if the user codes take a long
// time to finish.
query.streamingQuery.start()
} catch {
case e: Throwable =>
unregisterTerminatedStream(query)
throw e
}
query
}
/** Notify (by the StreamingQuery) that the query has been terminated */
private[sql] def notifyQueryTermination(terminatedQuery: StreamingQuery): Unit = {
unregisterTerminatedStream(terminatedQuery)
awaitTerminationLock.synchronized {
if (lastTerminatedQueryException == null || terminatedQuery.exception.nonEmpty) {
lastTerminatedQueryException = terminatedQuery.exception
}
awaitTerminationLock.notifyAll()
}
stateStoreCoordinator.deactivateInstances(terminatedQuery.runId)
}
private def unregisterTerminatedStream(terminatedQuery: StreamingQuery): Unit = {
activeQueriesSharedLock.synchronized {
// remove from shared state only if the streaming execution also matches
sparkSession.sharedState.activeStreamingQueries.remove(
terminatedQuery.id, terminatedQuery)
activeQueries -= terminatedQuery.id
}
}
}