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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
import java.util.Arrays
import org.apache.spark.status.AppStatusStore
import org.apache.spark.status.api.v1.StageStatus
/**
* Low-level status reporting APIs for monitoring job and stage progress.
*
* These APIs intentionally provide very weak consistency semantics; consumers of these APIs should
* be prepared to handle empty / missing information. For example, a job's stage ids may be known
* but the status API may not have any information about the details of those stages, so
* `getStageInfo` could potentially return `None` for a valid stage id.
*
* To limit memory usage, these APIs only provide information on recent jobs / stages. These APIs
* will provide information for the last `spark.ui.retainedStages` stages and
* `spark.ui.retainedJobs` jobs.
*
* NOTE: this class's constructor should be considered private and may be subject to change.
*/
class SparkStatusTracker private[spark] (sc: SparkContext, store: AppStatusStore) {
/**
* Return a list of all known jobs in a particular job group. If `jobGroup` is `null`, then
* returns all known jobs that are not associated with a job group.
*
* The returned list may contain running, failed, and completed jobs, and may vary across
* invocations of this method. This method does not guarantee the order of the elements in
* its result.
*/
def getJobIdsForGroup(jobGroup: String): Array[Int] = {
val expected = Option(jobGroup)
store.jobsList(null).filter(_.jobGroup == expected).map(_.jobId).toArray
}
/**
* Returns an array containing the ids of all active stages.
*
* This method does not guarantee the order of the elements in its result.
*/
def getActiveStageIds(): Array[Int] = {
store.stageList(Arrays.asList(StageStatus.ACTIVE)).map(_.stageId).toArray
}
/**
* Returns an array containing the ids of all active jobs.
*
* This method does not guarantee the order of the elements in its result.
*/
def getActiveJobIds(): Array[Int] = {
store.jobsList(Arrays.asList(JobExecutionStatus.RUNNING)).map(_.jobId).toArray
}
/**
* Returns job information, or `None` if the job info could not be found or was garbage collected.
*/
def getJobInfo(jobId: Int): Option[SparkJobInfo] = {
store.asOption(store.job(jobId)).map { job =>
new SparkJobInfoImpl(jobId, job.stageIds.toArray, job.status)
}
}
/**
* Returns stage information, or `None` if the stage info could not be found or was
* garbage collected.
*/
def getStageInfo(stageId: Int): Option[SparkStageInfo] = {
store.asOption(store.lastStageAttempt(stageId)).map { stage =>
new SparkStageInfoImpl(
stageId,
stage.attemptId,
stage.submissionTime.map(_.getTime()).getOrElse(0L),
stage.name,
stage.numTasks,
stage.numActiveTasks,
stage.numCompleteTasks,
stage.numFailedTasks)
}
}
/**
* Returns information of all known executors, including host, port, cacheSize, numRunningTasks
* and memory metrics.
*/
def getExecutorInfos: Array[SparkExecutorInfo] = {
store.executorList(true).map { exec =>
val (host, port) = exec.hostPort.split(":", 2) match {
case Array(h, p) => (h, p.toInt)
case Array(h) => (h, -1)
}
val cachedMem = exec.memoryMetrics.map { mem =>
mem.usedOnHeapStorageMemory + mem.usedOffHeapStorageMemory
}.getOrElse(0L)
new SparkExecutorInfoImpl(
host,
port,
cachedMem,
exec.activeTasks,
exec.memoryMetrics.map(_.usedOffHeapStorageMemory).getOrElse(0L),
exec.memoryMetrics.map(_.usedOnHeapStorageMemory).getOrElse(0L),
exec.memoryMetrics.map(_.totalOffHeapStorageMemory).getOrElse(0L),
exec.memoryMetrics.map(_.totalOnHeapStorageMemory).getOrElse(0L))
}.toArray
}
}
