Question

我正在寻找一种方法来打印Spark中Streaming应用程序的执行计划。我知道可以print the plan of a SQL Spark application。但是，我想显示流应用程序的逻辑和物理计划。这是我的应用程序：

package org.sense.spark.app

import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.{HashPartitioner, SparkConf}

object TestStreamCombineByKey {
  def main(args: Array[String]): Unit = {

    // Create a local StreamingContext with two working thread and batch interval of 1 second.
    // The master requires 2 cores to prevent from a starvation scenario.
    val conf = new SparkConf().setMaster("local[2]").setAppName("NetworkWordCount")
    val ssc = new StreamingContext(conf, Seconds(5))

    // Create a DStream that will connect to hostname:port, like localhost:9999
    val lines = ssc.socketTextStream("localhost", 9999)

    // Split each line into words
    val words = lines.flatMap(_.split(" "))

    // Count each word in each batch
    val pairs = words.map(word => (word, 1))
    // val wordCounts = pairs.reduceByKey(_ + _)
    val wordCounts = pairs.combineByKey(
      (v) => (v, 1), //createCombiner
      (acc: (Int, Int), v) => (acc._1 + v, acc._2 + 1), //mergeValue
      (acc1: (Int, Int), acc2: (Int, Int)) => (acc1._1 + acc2._1, acc1._2 + acc2._2), // mergeCombiners
      new HashPartitioner(3)
    )

    // Print the first ten elements of each RDD generated in this DStream to the console
    wordCounts.print()

    ssc.start() // Start the computation
    ssc.awaitTermination() // Wait for the computation to terminate
  }
}

Answer 1

使用UI（来自History Server）来获得稍微不同的视角。

无法在此处请求。为什么？您正在使用带有“ RDD”的dStream。逻辑计划和物理计划仅适用于数据框和数据集。

您将需要使用debugToString并使用spark-shell并将其插入正确的代码位置。就是说，dStream需要编译，并且就我所知不能仅在spark-shell中运行，因此我将与此相关的非dStream代码仅粘贴到spark-shell中。

此外，这一切都已弃用，我的建议是投资Spark结构化流媒体。

如何查看Spark Streaming应用程序的逻辑和物理计划？

1 个答案: