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From zsxwing <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-7150] add range() api
Date Thu, 14 May 2015 06:53:41 GMT
Github user zsxwing commented on a diff in the pull request:

    https://github.com/apache/spark/pull/6081#discussion_r30301336
  
    --- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
    @@ -689,6 +689,64 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
         new ParallelCollectionRDD[T](this, seq, numSlices, Map[Int, Seq[String]]())
       }
     
    +  /**
    +   * Creates a new RDD[Long] containing elements from `start` to `end`(exclusive), increased
by
    +   * `step` every element.
    +   *
    +   * @note if we need to cache this RDD, we should make sure each partition contains
no more than
    +   *       2 billion element.
    +   *
    +   * @param start the start value.
    +   * @param end the end value.
    +   * @param step the incremental step
    +   * @param numSlices the partition number of the new RDD.
    +   * @return
    +   */
    +  def range(
    +      start: Long,
    +      end: Long,
    +      step: Long = 1,
    +      numSlices: Int = defaultParallelism): RDD[Long] = withScope {
    +    assertNotStopped()
    +    if (step == 0) {
    +      // when step is 0, range will run infinite
    +      throw new IllegalArgumentException("`step` cannot be 0")
    +    }
    +    val length =
    +      if ((end - start) % step == 0) {
    +        (end - start) / step
    +      } else {
    +        (end - start) / step + 1
    +      }
    +    parallelize(0 to numSlices).mapPartitions(iter => {
    +      val i = iter.next()
    +      val partitionStart = (i * length) / numSlices * step + start
    +      val partitionEnd = ((i + 1) * length) / numSlices * step + start
    --- End diff --
    
    I think that's fine if you just use to get the `long` length.


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