浪尖，我想要在driver端獲取executor執(zhí)行task返回的結果，比如task是個規(guī)則引擎，我想知道每條規(guī)則命中了幾條數(shù)據(jù)，請問這個怎么做呢？

  def count(): Long = sc.runJob(this, Utils.getIteratorSize _).sum

/**   * Counts the number of elements of an iterator using a while loop rather than calling   * [[scala.collection.Iterator#size]] because it uses a for loop, which is slightly slower   * in the current version of Scala.   */  def getIteratorSize[T](iterator: Iterator[T]): Long = {    var count = 0L    while (iterator.hasNext) {      count += 1L      iterator.next()    }    count  }

import org.apache.spark.{SparkConf, SparkContext, TaskContext}import org.elasticsearch.hadoop.cfg.ConfigurationOptions
object es2sparkRunJob {
  def main(args: Array[String]): Unit = {    val conf = new SparkConf().setMaster("local[*]").setAppName(this.getClass.getCanonicalName)
    conf.set(ConfigurationOptions.ES_NODES, "127.0.0.1")    conf.set(ConfigurationOptions.ES_PORT, "9200")    conf.set(ConfigurationOptions.ES_NODES_WAN_ONLY, "true")    conf.set(ConfigurationOptions.ES_INDEX_AUTO_CREATE, "true")    conf.set(ConfigurationOptions.ES_NODES_DISCOVERY, "false")    conf.set("es.write.rest.error.handlers", "ignoreConflict")    conf.set("es.write.rest.error.handler.ignoreConflict", "com.jointsky.bigdata.handler.IgnoreConflictsHandler")
    val sc = new SparkContext(conf)    import org.elasticsearch.spark._
    val rdd = sc.esJsonRDD("posts").repartition(10)
    rdd.count()    val func = (itr : Iterator[(String,String)]) => {      var count = 0      itr.foreach(each=>{        count += 1      })      (TaskContext.getPartitionId(),count)    }
    val res = sc.runJob(rdd,func)
    res.foreach(println)
    sc.stop()  }}