ClassNotFoundException火花-提交scala

Question

嗨，我正在尝试生成Salt示例的输出，但没有使用文档中提到的docker。我找到了帮助生成输出的scala代码，这是main.scala。我将main.scala修改为一个方便的main.scala,

package BinExTest
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.Row

import software.uncharted.salt.core.projection.numeric._
import software.uncharted.salt.core.generation.request._
import software.uncharted.salt.core.generation.Series
import software.uncharted.salt.core.generation.TileGenerator
import software.uncharted.salt.core.generation.output.SeriesData
import software.uncharted.salt.core.analytic.numeric._

import java.io._

import scala.util.parsing.json.JSONObject

object Main {

  // Defines the tile size in both x and y bin dimensions
  val tileSize = 256

  // Defines the output layer name
  val layerName = "pickups"

  // Creates and returns an Array of Double values encoded as 64bit Integers
  def createByteBuffer(tile: SeriesData[(Int, Int, Int), (Int, Int), Double, (Double, Double)]): Array[Byte] = {
    val byteArray = new Array[Byte](tileSize * tileSize * 8)
    var j = 0
    tile.bins.foreach(b => {
      val data = java.lang.Double.doubleToLongBits(b)
      for (i <- 0 to 7) {
        byteArray(j) = ((data >> (i * 8)) & 0xff).asInstanceOf[Byte]
        j += 1
      }
    })
    byteArray
  }

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

    val jarFile = "/home/kesava/Studies/BinExTest/BinExTest.jar"; 
    val inputPath = "/home/kesava/Downloads/taxi_micro.csv"
    val outputPath = "/home/kesava/SoftWares/salt/salt-examples/bin-example/Output"

    val conf = new SparkConf().setAppName("salt-bin-example").setJars(Array(jarFile))
    val sc = new SparkContext(conf)
    val sqlContext = new SQLContext(sc)

    sqlContext.read.format("com.databricks.spark.csv")
      .option("header", "true")
      .option("inferSchema", "true")
      .load(s"file://$inputPath")
      .registerTempTable("taxi_micro")

    // Construct an RDD of Rows containing only the fields we need. Cache the result
    val input = sqlContext.sql("select pickup_lon, pickup_lat from taxi_micro")
      .rdd.cache()

    // Given an input row, return pickup longitude, latitude as a tuple
    val pickupExtractor = (r: Row) => {
      if (r.isNullAt(0) || r.isNullAt(1)) {
        None
      } else {
        Some((r.getDouble(0), r.getDouble(1)))
      }
    }

    // Tile Generator object, which houses the generation logic
    val gen = TileGenerator(sc)

    // Break levels into batches. Process several higher levels at once because the
    // number of tile outputs is quite low. Lower levels done individually due to high tile counts.
    val levelBatches = List(List(0, 1, 2, 3, 4, 5, 6, 7, 8), List(9, 10, 11), List(12), List(13), List(14))

    // Iterate over sets of levels to generate.
    val levelMeta = levelBatches.map(level => {

      println("------------------------------")
      println(s"Generating level $level")
      println("------------------------------")

      // Construct the definition of the tiling jobs: pickups
      val pickups = new Series((tileSize - 1, tileSize - 1),
        pickupExtractor,
        new MercatorProjection(level),
        (r: Row) => Some(1),
        CountAggregator,
        Some(MinMaxAggregator))

      // Create a request for all tiles on these levels, generate
      val request = new TileLevelRequest(level, (coord: (Int, Int, Int)) => coord._1)
      val rdd = gen.generate(input, pickups, request)

      // Translate RDD of Tiles to RDD of (coordinate,byte array), collect to master for serialization
      val output = rdd
        .map(s => pickups(s).get)
        .map(tile => {
          // Return tuples of tile coordinate, byte array
          (tile.coords, createByteBuffer(tile))
        })
        .collect()

      // Save byte files to local filesystem
      output.foreach(tile => {
        val coord = tile._1
        val byteArray = tile._2
        val limit = (1 << coord._1) - 1
        // Use standard TMS path structure and file naming
        val file = new File(s"$outputPath/$layerName/${coord._1}/${coord._2}/${limit - coord._3}.bins")
        file.getParentFile.mkdirs()
        val output = new FileOutputStream(file)
        output.write(byteArray)
        output.close()
      })

      // Create map from each level to min / max values.
      rdd
        .map(s => pickups(s).get)
        .map(t => (t.coords._1.toString, t.tileMeta.get))
        .reduceByKey((l, r) => {
          (Math.min(l._1, r._1), Math.max(l._2, r._2))
        })
        .mapValues(minMax => {
          JSONObject(Map(
            "min" -> minMax._1,
            "max" -> minMax._2
          ))
        })
        .collect()
        .toMap
    })

    // Flatten array of maps into a single map
    val levelInfoJSON = JSONObject(levelMeta.reduce(_ ++ _)).toString()
    // Save level metadata to filesystem
    val pw = new PrintWriter(s"$outputPath/$layerName/meta.json")
    pw.write(levelInfoJSON)
    pw.close()

  }
}

我为这个scala创建了一个单独的文件夹,

calac-cp“lib/salt.jar：lib/spark.jar”main.scala

这已成功运行并在文件夹BinexTest下生成类。

现在,项目的build.gradle有以下几行代码,用于标识这是有助于生成输出数据集的命令,

task run(overwrite: true, type: Exec, dependsOn: [assemble]) {
  executable = 'spark-submit'
  args = ["--class","software.uncharted.salt.examples.bin.Main","/opt/salt/build/libs/salt-bin-example-${version}.jar", "/opt/data/taxi_one_day.csv", "/opt/output"]
}

spark-submit--类binextest.main lib/salt.jar

当我这样做时,我会得到以下错误,

java.lang.ClassNotFoundException：Main.BinexTest在java.net.URLClassLoader$1上运行(URLClassLoader.java:366)在java.net.URLClassLoader$1上运行(URLClassLoader.java:355)在java.security.AccessController.DOPrivileged（本机方法）在java.net.URLClassLoader.findClass（本机方法）在java.net.URLClassLoader.java:354)在java.lang.ClassLoader.java:354)

有人能帮我一下吗？我对此完全陌生，走到这一步完全是靠探索。

spark-submit--类binextest.main--jars“binextest.jar”“lib/salt.jar”

我让ClassNotFoundException生成新的错误,

知道怎么回事吗？

这是因为Scala2.11没有提到的类吗？

spark-submit--类“binextest.main”--jar“binextest.jar,lib/scala210.jar”“lib/salt.jar”

Answer 1

要运行Spark作业，它需要在组成Spark集群的不同节点上自我复制它的代码。它通过将jar文件复制到其他节点来做到这一点。

这意味着您需要确保您的类文件打包在一个.jar文件中。在我的典型解决方案中，我将构建一个Uber jar，将类文件和依赖的jar文件打包在一个.jar文件中。为此，我使用了Maven Shade插件。这不一定是您的解决方案，但至少您应该从生成的类中构建一个.jar文件。

要手动提供附加的jar文件，您需要使用--jars选项添加这些文件，该选项需要一个逗号分隔的列表。

你的问题的第二部分已经在另一个线程上得到了回答。