Spark: get number of cluster cores programmaticall

问题:

I run my spark application in yarn cluster. In my code I use number available cores of queue for creating partitions on my dataset:

Dataset ds = ...
ds.coalesce(config.getNumberOfCores());

My question: how can I get number available cores of queue by programmatically way and not by configuration?

回答1:

There are ways to get both the number of executors and the number of cores in a cluster from Spark. Here is a bit of Scala utility code that I've used in the past. You should easily be able to adapt it to Java. There are two key ideas:

1. The number of workers is the number of executors minus one or sc.getExecutorStorageStatus.length - 1.

2. The number of cores per worker can be obtained by executing java.lang.Runtime.getRuntime.availableProcessors on a worker.

The rest of the code is boilerplate for adding convenience methods to SparkContext using Scala implicits. I wrote the code for 1.x years ago, which is why it is not using SparkSession.

One final point: it is often a good idea to coalesce to a multiple of your cores as this can improve performance in the case of skewed data. In practice, I use anywhere between 1.5x and 4x, depending on the size of data and whether the job is running on a shared cluster or not.

import org.apache.spark.SparkContext

import scala.language.implicitConversions


class RichSparkContext(val sc: SparkContext) {

  def executorCount: Int =
    sc.getExecutorStorageStatus.length - 1 // one is the driver

  def coresPerExecutor: Int =
    RichSparkContext.coresPerExecutor(sc)

  def coreCount: Int =
    executorCount * coresPerExecutor

  def coreCount(coresPerExecutor: Int): Int =
    executorCount * coresPerExecutor

}


object RichSparkContext {

  trait Enrichment {
    implicit def enrichMetadata(sc: SparkContext): RichSparkContext =
      new RichSparkContext(sc)
  }

  object implicits extends Enrichment

  private var _coresPerExecutor: Int = 0

  def coresPerExecutor(sc: SparkContext): Int =
    synchronized {
      if (_coresPerExecutor == 0)
        sc.range(0, 1).map(_ => java.lang.Runtime.getRuntime.availableProcessors).collect.head
      else _coresPerExecutor
    }

}