org.apache.spark.streaming.scheduler.StreamInputInfo Scala Examples

The following examples show how to use org.apache.spark.streaming.scheduler.StreamInputInfo. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
Example 1
Source File: BatchUIData.scala    From drizzle-spark   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import scala.collection.mutable

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, OutputOperationInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val outputOperations: mutable.HashMap[OutputOpId, OutputOperationUIData] = mutable.HashMap(),
    var outputOpIdSparkJobIdPairs: Iterable[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def isFailed: Boolean = numFailedOutputOp != 0
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    val outputOperations = mutable.HashMap[OutputOpId, OutputOperationUIData]()
    outputOperations ++= batchInfo.outputOperationInfos.mapValues(OutputOperationUIData.apply)
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      outputOperations
    )
  }
}

private[ui] case class OutputOperationUIData(
    id: OutputOpId,
    name: String,
    description: String,
    startTime: Option[Long],
    endTime: Option[Long],
    failureReason: Option[String]) {

  def duration: Option[Long] = for (s <- startTime; e <- endTime) yield e - s
}

private[ui] object OutputOperationUIData {

  def apply(outputOperationInfo: OutputOperationInfo): OutputOperationUIData = {
    OutputOperationUIData(
      outputOperationInfo.id,
      outputOperationInfo.name,
      outputOperationInfo.description,
      outputOperationInfo.startTime,
      outputOperationInfo.endTime,
      outputOperationInfo.failureReason
    )
  }
}
Example 2
Source File: BatchUIData.scala    From sparkoscope   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import scala.collection.mutable

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, OutputOperationInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val outputOperations: mutable.HashMap[OutputOpId, OutputOperationUIData] = mutable.HashMap(),
    var outputOpIdSparkJobIdPairs: Iterable[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def isFailed: Boolean = numFailedOutputOp != 0
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    val outputOperations = mutable.HashMap[OutputOpId, OutputOperationUIData]()
    outputOperations ++= batchInfo.outputOperationInfos.mapValues(OutputOperationUIData.apply)
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      outputOperations
    )
  }
}

private[ui] case class OutputOperationUIData(
    id: OutputOpId,
    name: String,
    description: String,
    startTime: Option[Long],
    endTime: Option[Long],
    failureReason: Option[String]) {

  def duration: Option[Long] = for (s <- startTime; e <- endTime) yield e - s
}

private[ui] object OutputOperationUIData {

  def apply(outputOperationInfo: OutputOperationInfo): OutputOperationUIData = {
    OutputOperationUIData(
      outputOperationInfo.id,
      outputOperationInfo.name,
      outputOperationInfo.description,
      outputOperationInfo.startTime,
      outputOperationInfo.endTime,
      outputOperationInfo.failureReason
    )
  }
}
Example 3
Source File: BatchUIData.scala    From multi-tenancy-spark   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import scala.collection.mutable

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, OutputOperationInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val outputOperations: mutable.HashMap[OutputOpId, OutputOperationUIData] = mutable.HashMap(),
    var outputOpIdSparkJobIdPairs: Iterable[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def isFailed: Boolean = numFailedOutputOp != 0
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    val outputOperations = mutable.HashMap[OutputOpId, OutputOperationUIData]()
    outputOperations ++= batchInfo.outputOperationInfos.mapValues(OutputOperationUIData.apply)
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      outputOperations
    )
  }
}

private[ui] case class OutputOperationUIData(
    id: OutputOpId,
    name: String,
    description: String,
    startTime: Option[Long],
    endTime: Option[Long],
    failureReason: Option[String]) {

  def duration: Option[Long] = for (s <- startTime; e <- endTime) yield e - s
}

private[ui] object OutputOperationUIData {

  def apply(outputOperationInfo: OutputOperationInfo): OutputOperationUIData = {
    OutputOperationUIData(
      outputOperationInfo.id,
      outputOperationInfo.name,
      outputOperationInfo.description,
      outputOperationInfo.startTime,
      outputOperationInfo.endTime,
      outputOperationInfo.failureReason
    )
  }
}
Example 4
Source File: BatchUIData.scala    From spark1.52   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val numOutputOp: Int,
    val failureReason: Map[Int, String],
    var outputOpIdSparkJobIdPairs: Seq[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def numRecords: Long = streamIdToInputInfo.values.map(_.numRecords).sum
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      batchInfo.numOutputOp,
      batchInfo.failureReasons
    )
  }
}
Example 5
Source File: BatchUIData.scala    From Spark-2.3.1   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import scala.collection.mutable

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, OutputOperationInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val outputOperations: mutable.HashMap[OutputOpId, OutputOperationUIData] = mutable.HashMap(),
    var outputOpIdSparkJobIdPairs: Iterable[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def isFailed: Boolean = numFailedOutputOp != 0
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    val outputOperations = mutable.HashMap[OutputOpId, OutputOperationUIData]()
    outputOperations ++= batchInfo.outputOperationInfos.mapValues(OutputOperationUIData.apply)
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      outputOperations
    )
  }
}

private[ui] case class OutputOperationUIData(
    id: OutputOpId,
    name: String,
    description: String,
    startTime: Option[Long],
    endTime: Option[Long],
    failureReason: Option[String]) {

  def duration: Option[Long] = for (s <- startTime; e <- endTime) yield e - s
}

private[ui] object OutputOperationUIData {

  def apply(outputOperationInfo: OutputOperationInfo): OutputOperationUIData = {
    OutputOperationUIData(
      outputOperationInfo.id,
      outputOperationInfo.name,
      outputOperationInfo.description,
      outputOperationInfo.startTime,
      outputOperationInfo.endTime,
      outputOperationInfo.failureReason
    )
  }
}
Example 6
Source File: BatchUIData.scala    From BigDatalog   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.streaming.ui

import scala.collection.mutable

import org.apache.spark.streaming.Time
import org.apache.spark.streaming.scheduler.{BatchInfo, OutputOperationInfo, StreamInputInfo}
import org.apache.spark.streaming.ui.StreamingJobProgressListener._

private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId)

private[ui] case class BatchUIData(
    val batchTime: Time,
    val streamIdToInputInfo: Map[Int, StreamInputInfo],
    val submissionTime: Long,
    val processingStartTime: Option[Long],
    val processingEndTime: Option[Long],
    val outputOperations: mutable.HashMap[OutputOpId, OutputOperationUIData] = mutable.HashMap(),
    var outputOpIdSparkJobIdPairs: Seq[OutputOpIdAndSparkJobId] = Seq.empty) {

  
  def isFailed: Boolean = numFailedOutputOp != 0
}

private[ui] object BatchUIData {

  def apply(batchInfo: BatchInfo): BatchUIData = {
    val outputOperations = mutable.HashMap[OutputOpId, OutputOperationUIData]()
    outputOperations ++= batchInfo.outputOperationInfos.mapValues(OutputOperationUIData.apply)
    new BatchUIData(
      batchInfo.batchTime,
      batchInfo.streamIdToInputInfo,
      batchInfo.submissionTime,
      batchInfo.processingStartTime,
      batchInfo.processingEndTime,
      outputOperations
    )
  }
}

private[ui] case class OutputOperationUIData(
    id: OutputOpId,
    name: String,
    description: String,
    startTime: Option[Long],
    endTime: Option[Long],
    failureReason: Option[String]) {

  def duration: Option[Long] = for (s <- startTime; e <- endTime) yield e - s
}

private[ui] object OutputOperationUIData {

  def apply(outputOperationInfo: OutputOperationInfo): OutputOperationUIData = {
    OutputOperationUIData(
      outputOperationInfo.id,
      outputOperationInfo.name,
      outputOperationInfo.description,
      outputOperationInfo.startTime,
      outputOperationInfo.endTime,
      outputOperationInfo.failureReason
    )
  }
}