Spark算子:RDD行动Action操作(2)–take、top、takeOrdered
2016-12-26 15:51
591 查看
关键字:Spark算子、Spark RDD行动Action、take、top、takeOrdered
take用于获取RDD中从0到num-1下标的元素,不排序。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.take(1)
res0: Array[Int] = Array(10)
scala> rdd1.take(2)
res1: Array[Int] = Array(10, 4)
top函数用于从RDD中,按照默认(降序)或者指定的排序规则,返回前num个元素。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.top(1)
res2: Array[Int] = Array(12)
scala> rdd1.top(2)
res3: Array[Int] = Array(12, 10)
//指定排序规则
scala> implicit val myOrd = implicitly[Ordering[Int]].reverse
myOrd: scala.math.Ordering[Int] = scala.math.Ordering$$anon$4@767499ef
scala> rdd1.top(1)
res4: Array[Int] = Array(2)
scala> rdd1.top(2)
res5: Array[Int] = Array(2, 3)
takeOrdered和top类似,只不过以和top相反的顺序返回元素。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.top(1)
res4: Array[Int] = Array(2)
scala> rdd1.top(2)
res5: Array[Int] = Array(2, 3)
scala> rdd1.takeOrdered(1)
res6: Array[Int] = Array(12)
scala> rdd1.takeOrdered(2)
res7: Array[Int] = Array(12, 10)
更多关于Spark算子的介绍,可参考spark算子系列文章:
http://blog.csdn.net/ljp812184246/article/details/53895299
take
def take(num: Int): Array[T]take用于获取RDD中从0到num-1下标的元素,不排序。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.take(1)
res0: Array[Int] = Array(10)
scala> rdd1.take(2)
res1: Array[Int] = Array(10, 4)
top
def top(num: Int)(implicit ord: Ordering[T]): Array[T]top函数用于从RDD中,按照默认(降序)或者指定的排序规则,返回前num个元素。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.top(1)
res2: Array[Int] = Array(12)
scala> rdd1.top(2)
res3: Array[Int] = Array(12, 10)
//指定排序规则
scala> implicit val myOrd = implicitly[Ordering[Int]].reverse
myOrd: scala.math.Ordering[Int] = scala.math.Ordering$$anon$4@767499ef
scala> rdd1.top(1)
res4: Array[Int] = Array(2)
scala> rdd1.top(2)
res5: Array[Int] = Array(2, 3)
takeOrdered
def takeOrdered(num: Int)(implicit ord: Ordering[T]): Array[T]takeOrdered和top类似,只不过以和top相反的顺序返回元素。
scala> var rdd1 = sc.makeRDD(Seq(10, 4, 2, 12, 3))
rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[40] at makeRDD at :21
scala> rdd1.top(1)
res4: Array[Int] = Array(2)
scala> rdd1.top(2)
res5: Array[Int] = Array(2, 3)
scala> rdd1.takeOrdered(1)
res6: Array[Int] = Array(12)
scala> rdd1.takeOrdered(2)
res7: Array[Int] = Array(12, 10)
更多关于Spark算子的介绍,可参考spark算子系列文章:
http://blog.csdn.net/ljp812184246/article/details/53895299
相关文章推荐
- Spark算子:RDD行动Action操作(2)–take、top、takeOrdered
- Spark算子:RDD行动Action操作(2)–take、top、takeOrdered
- Spark算子:RDD行动Action操作(2)–take、top、takeOrdered
- Spark算子:RDD行动Action操作(2)–take、top、takeOrdered
- 3.4 Spark RDD Action操作2-take、top、takeOrdered
- Spark算子:RDD行动Action操作(1)–first、count、reduce、collect
- Spark算子:RDD行动Action操作(1)–first、count、reduce、collect
- Spark算子:RDD行动Action操作(7)–saveAsNewAPIHadoopFile、saveAsNewAPIHadoopDataset
- Spark算子:RDD行动Action操作(5)–saveAsTextFile、saveAsSequenceFile、saveAsObjectFile
- Spark算子:RDD行动Action操作(7)–saveAsNewAPIHadoopFile、saveAsNewAPIHadoopDataset
- Spark算子:RDD行动Action操作(7)–saveAsNewAPIHadoopFile、saveAsNewAPIHadoopDataset
- Spark算子:RDD行动Action操作(5)–saveAsTextFile、saveAsSequenceFile、saveAsObjectFile
- Spark算子:RDD行动Action操作(6)–saveAsHadoopFile、saveAsHadoopDataset
- Spark算子:RDD行动Action操作(3)–aggregate、fold、lookup
- Spark算子:RDD行动Action操作(3)–aggregate、fold、lookup
- Spark算子:RDD行动Action操作(3)–aggregate、fold、lookup
- Spark算子:RDD行动Action操作(1)–first、count、reduce、collect
- Spark算子:RDD行动Action操作(6)–saveAsHadoopFile、saveAsHadoopDataset
- Spark算子:RDD行动Action操作(4)–countByKey、foreach、foreachPartition、sortBy
- Spark算子:RDD行动Action操作(3)–aggregate、fold、lookup