大数据面试·Spark篇(一)

    技术2022-07-11  130

    Spark的shuffle算子

    一、去重二、聚合三、排序四、重分区五、集合或者表操作

    一、去重

    def distinct() def distinct(numPartitions: Int)

    二、聚合

    def reduceByKey(func: (V, V) => V, numPartitions: Int): RDD[(K, V)] def reduceByKey(partitioner: Partitioner, func: (V, V) => V): RDD[(K, V)] def groupBy[K](f: T => K, p: Partitioner):RDD[(K, Iterable[V])] def groupByKey(partitioner: Partitioner):RDD[(K, Iterable[V])] def aggregateByKey[U: ClassTag](zeroValue: U, partitioner: Partitioner): RDD[(K, U)] def aggregateByKey[U: ClassTag](zeroValue: U, numPartitions: Int): RDD[(K, U)] def combineByKey[C](createCombiner: V => C, mergeValue: (C, V) => C, mergeCombiners: (C, C) => C): RDD[(K, C)] def combineByKey[C](createCombiner: V => C, mergeValue: (C, V) => C, mergeCombiners: (C, C) => C, numPartitions: Int): RDD[(K, C)] def combineByKey[C](createCombiner: V => C, mergeValue: (C, V) => C, mergeCombiners: (C, C) =>

    三、排序

    def sortByKey(ascending: Boolean = true, numPartitions: Int = self.partitions.length): RDD[(K, V)] def sortBy[K](f: (T) => K, ascending: Boolean = true, numPartitions: Int = this.partitions.length

    四、重分区

    def coalesce(numPartitions: Int, shuffle: Boolean = false, partitionCoalescer: Option[PartitionCoalescer] = Option.empty) def repartition(numPartitions: Int)(implicit ord: Ordering[T] = null)

    五、集合或者表操作

    def intersection(other: RDD[T]): RDD[T] def intersection(other: RDD[T], partitioner: Partitioner)(implicit ord: Ordering[T] = null): RDD[T] def intersection(other: RDD[T], numPartitions: Int): RDD[T] def subtract(other: RDD[T], numPartitions: Int): RDD[T] def subtract(other: RDD[T], p: Partitioner)(implicit ord: Ordering[T] = null): RDD[T] def subtractByKey[W: ClassTag](other: RDD[(K, W)]): RDD[(K, V)] def subtractByKey[W: ClassTag](other: RDD[(K, W)], numPartitions: Int): RDD[(K, V)] def subtractByKey[W: ClassTag](other: RDD[(K, W)], p: Partitioner): RDD[(K, V)] def join[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (V, W))] def join[W](other: RDD[(K, W)]): RDD[(K, (V, W))] def join[W](other: RDD[(K, W)], numPartitions: Int): RDD[(K, (V, W))] def leftOuterJoin[W](other: RDD[(K, W)]): RDD[(K, (V, Option[W]))]
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