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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.ui.jobs
import scala.collection.mutable
import scala.collection.mutable.HashMap
import org.apache.spark.JobExecutionStatus
import org.apache.spark.executor.TaskMetrics
import org.apache.spark.scheduler.{AccumulableInfo, TaskInfo}
import org.apache.spark.util.collection.OpenHashSet
private[spark] object UIData {
class ExecutorSummary {
var taskTime : Long = 0
var failedTasks : Int = 0
var succeededTasks : Int = 0
var inputBytes : Long = 0
var inputRecords : Long = 0
var outputBytes : Long = 0
var outputRecords : Long = 0
var shuffleRead : Long = 0
var shuffleReadRecords : Long = 0
var shuffleWrite : Long = 0
var shuffleWriteRecords : Long = 0
var memoryBytesSpilled : Long = 0
var diskBytesSpilled : Long = 0
}
class JobUIData(
var jobId: Int = -1,
var submissionTime: Option[Long] = None,
var completionTime: Option[Long] = None,
var stageIds: Seq[Int] = Seq.empty,
var jobGroup: Option[String] = None,
var status: JobExecutionStatus = JobExecutionStatus.UNKNOWN,
/* Tasks */
// `numTasks` is a potential underestimate of the true number of tasks that this job will run.
// This may be an underestimate because the job start event references all of the result
// stages' transitive stage dependencies, but some of these stages might be skipped if their
// output is available from earlier runs.
// See https://github.com/apache/spark/pull/3009 for a more extensive discussion.
var numTasks: Int = 0,
var numActiveTasks: Int = 0,
var numCompletedTasks: Int = 0,
var numSkippedTasks: Int = 0,
var numFailedTasks: Int = 0,
/* Stages */
var numActiveStages: Int = 0,
// This needs to be a set instead of a simple count to prevent double-counting of rerun stages:
var completedStageIndices: mutable.HashSet[Int] = new mutable.HashSet[Int](),
var numSkippedStages: Int = 0,
var numFailedStages: Int = 0
)
class StageUIData {
var numActiveTasks: Int = _
var numCompleteTasks: Int = _
var completedIndices = new OpenHashSet[Int]()
var numFailedTasks: Int = _
var executorRunTime: Long = _
var inputBytes: Long = _
var inputRecords: Long = _
var outputBytes: Long = _
var outputRecords: Long = _
var shuffleReadTotalBytes: Long = _
var shuffleReadRecords : Long = _
var shuffleWriteBytes: Long = _
var shuffleWriteRecords: Long = _
var memoryBytesSpilled: Long = _
var diskBytesSpilled: Long = _
var schedulingPool: String = ""
var description: Option[String] = None
var accumulables = new HashMap[Long, AccumulableInfo]
var taskData = new HashMap[Long, TaskUIData]
var executorSummary = new HashMap[String, ExecutorSummary]
def hasInput: Boolean = inputBytes > 0
def hasOutput: Boolean = outputBytes > 0
def hasShuffleRead: Boolean = shuffleReadTotalBytes > 0
def hasShuffleWrite: Boolean = shuffleWriteBytes > 0
def hasBytesSpilled: Boolean = memoryBytesSpilled > 0 && diskBytesSpilled > 0
}
/**
* These are kept mutable and reused throughout a task's lifetime to avoid excessive reallocation.
*/
case class TaskUIData(
var taskInfo: TaskInfo,
var taskMetrics: Option[TaskMetrics] = None,
var errorMessage: Option[String] = None)
case class ExecutorUIData(
val startTime: Long,
var finishTime: Option[Long] = None,
var finishReason: Option[String] = None)
}
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