本文整理汇总了Scala中org.apache.spark.streaming.scheduler.StreamingListener类的典型用法代码示例。如果您正苦于以下问题：Scala StreamingListener类的具体用法？Scala StreamingListener怎么用？Scala StreamingListener使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了StreamingListener类的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Scala代码示例。
示例1: StreamingMetricsListener
//设置package包名称以及导入依赖的类
package com.groupon.dse.spark.listeners
import org.apache.spark.groupon.metrics.UserMetricsSystem
import org.apache.spark.streaming.scheduler.{StreamingListener, StreamingListenerBatchCompleted}
class StreamingMetricsListener extends StreamingListener {
private lazy val processingTimeHistogram = UserMetricsSystem.histogram("baryon.processingTime")
private lazy val schedulingDelayHistogram = UserMetricsSystem.histogram("baryon.schedulingDelay")
override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted): Unit = {
if (batchCompleted.batchInfo.processingDelay.isDefined) {
processingTimeHistogram.update(batchCompleted.batchInfo.processingDelay.get)
}
if (batchCompleted.batchInfo.schedulingDelay.isDefined) {
schedulingDelayHistogram.update(batchCompleted.batchInfo.schedulingDelay.get)
}
}
} 示例2: PrometheusSparkMetrics
//设置package包名称以及导入依赖的类
package com.godatadriven.twitter_classifier
import io.prometheus.client.exporter.PushGateway
import io.prometheus.client.{CollectorRegistry, Gauge}
import org.apache.spark.streaming.scheduler.{StreamingListener, StreamingListenerBatchCompleted}
class PrometheusSparkMetrics(sparkJob: String) extends StreamingListener {
override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted): Unit = {
val registry: CollectorRegistry = new CollectorRegistry()
val pushGateway: PushGateway = new PushGateway("127.0.0.1:9091")
addInputRate(batchCompleted, registry)
addSchedulingDelay(batchCompleted, registry)
addProcessingTime(batchCompleted, registry)
addTotalDelay(batchCompleted, registry)
pushGateway.push(registry, "spark_streaming_exporter")
}
def addInputRate(batchCompleted: StreamingListenerBatchCompleted, registry: CollectorRegistry): Unit = {
addMetric(registry, batchCompleted.batchInfo.numRecords, "spark_streaming_input_rate", "The input rate of our spark streaming job")
}
def addSchedulingDelay(batchCompleted: StreamingListenerBatchCompleted, registry: CollectorRegistry) = {
addMetric(registry, batchCompleted.batchInfo.schedulingDelay.get, "spark_streaming_scheduling_delay", "The scheduling delay of our spark streaming job")
}
def addProcessingTime(batchCompleted: StreamingListenerBatchCompleted, registry: CollectorRegistry) = {
addMetric(registry, batchCompleted.batchInfo.processingDelay.get, "spark_streaming_processing_time", "The processing delay of our spark streaming job")
}
def addTotalDelay(batchCompleted: StreamingListenerBatchCompleted, registry: CollectorRegistry) = {
addMetric(registry, batchCompleted.batchInfo.totalDelay.get, "spark_streaming_total_delay", "The total delay of our spark streaming job")
}
def addMetric(registry: CollectorRegistry, value: Double, name: String, helpText: String): Unit = {
val totalDelay: Gauge = Gauge.build()
.help(helpText)
.name(name)
.labelNames("spark_job")
.register(registry)
totalDelay.labels(sparkJob).set(value)
}
} 示例3: CompactorListener
//设置package包名称以及导入依赖的类
package com.groupon.dse.mezzanine.compactor
import com.groupon.dse.mezzanine.partitioner.Partitioner
import org.apache.hadoop.fs.FileSystem
import org.apache.hadoop.io.Writable
import org.apache.spark.SparkContext
import org.apache.spark.groupon.metrics.UserMetricsSystem
import org.apache.spark.streaming.scheduler.{StreamingListener, StreamingListenerBatchCompleted}
class CompactorListener[K <: Writable, V <: Writable](val sparkContext: SparkContext,
val fs: FileSystem,
val partitioner: Partitioner,
val compactor: Compactor[K, V]) extends StreamingListener {
override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted): Unit = {
// Get the leaf directories where staging files are written to for the topics we consume
val stagingLeafDirs = partitioner.stagingLeafDirectories(fs).filter(path => {
path.getName.startsWith(Partitioner.KeyPrefix)
})
stagingLeafDirs.par.foreach(stagingPath => {
val key = partitioner.keyForStagingDirectory(stagingPath)
val filesToCompact = compactor.getFilesToCompact(stagingPath, batchCompleted.batchInfo.processingEndTime.get)
if (filesToCompact.nonEmpty) {
val outputPath = partitioner.outputDirectory(key)
UserMetricsSystem.timer(s"mezzanine.write.time.output.$key").time({
compactor.saveToOutputDir(filesToCompact, outputPath)
})
filesToCompact.foreach(fs.delete(_, false))
}
})
}
}