Spark Partition is a trait. /** * An identifier for a partition in an RDD. */ trait Partition extends Serializable { /** * Get the partition's index within its parent RDD */ def index: Int

先输入:paste,然后粘贴代码块,之后按ctrl+D结束输入。注意必须输入大小的D,如果当前不是大写模式,则需要多按一个shift键,把d转成大写。 示例如下: scala> :paste // Entering paste mode (ctrl-D to finish) val lr = new LogisticRegression() .setMaxIter(10) .setReg

 Apache Spark 2.0引入了SparkSession,其为用户提供了一个统一的切入点来使用Spark的各项功能,并且允许用户通过它调用DataFrame和Dataset相关API来编写Spark程序。最重要的是,它减少了用户需要了解的一些概念,使得我们可以很容易地与Spark交互。   本文我们将介绍在Spark 2.0中如何使用SparkSession。更多关于SparkSessio

Zhen He Associate Professor Department of Computer Science and Computer Engineering La Trobe University Bundoora, Victoria 3086 Australia Tel : + 61 3 9479 3036 Email: z.he@latrobe.edu.au Building: Be

Fold is a very powerful operation in spark which allows you to calculate many important values in O(n) time. If you are familiar with Scala collection it will be like using fold operation on collectio

There is a fundamental difference between the two-reduceByKey is only available on key-value pair RDDs, while treeReduce is a generalization of reduce operation on any RDD. reduceByKey is used for imp

关键字:Spark算子、Spark RDD基本转换、mapPartitions、mapPartitionsWithIndex mapPartitions def mapPartitions[U](f: (Iterator[T]) => Iterator[U], preservesPartitioning: Boolean = false)(implicit arg0: ClassTag[U]):

trait PartitionCoalescer { /** * Coalesce the partitions of the given RDD. * * @param maxPartitions the maximum number of partitions to have after coalescing * @param parent the parent

BlockId identified a particular Block of data, usually associated with a single file. A Block can be uniquely identified by its filenme, but eatch type of Block has a dirrent set of keys which produce

/** * An identifier for a partition in an RDD. */ trait Partition extends Serializable { /** * Get the partition's index within its parent RDD */ def index: Int // A better default impl

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