spark UninterruptibleThreadRunner 源码
spark UninterruptibleThreadRunner 代码
文件路径：/core/src/main/scala/org/apache/spark/util/UninterruptibleThreadRunner.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.util
import java.util.concurrent.Executors
import scala.concurrent.{ExecutionContext, Future}
import scala.concurrent.duration.Duration
/**
* [[UninterruptibleThreadRunner]] ensures that all tasks are running in an
* [[UninterruptibleThread]]. A good example is Kafka consumer usage.
*/
private[spark] class UninterruptibleThreadRunner(threadName: String) {
private val thread = Executors.newSingleThreadExecutor((r: Runnable) => {
val t = new UninterruptibleThread(threadName) {
override def run(): Unit = {
r.run()
}
}
t.setDaemon(true)
t
})
private val execContext = ExecutionContext.fromExecutorService(thread)
def runUninterruptibly[T](body: => T): T = {
if (!Thread.currentThread.isInstanceOf[UninterruptibleThread]) {
val future = Future {
body
}(execContext)
ThreadUtils.awaitResult(future, Duration.Inf)
} else {
body
}
}
def shutdown(): Unit = {
thread.shutdown()
}
}
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