sc parallelize
scala> val rdd = sc.parallelize(Array(1,2,3,4,5,6,7,8,9,10)) rdd: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[1] at parallelize at :24., ,However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... ,scala> val numbers=sc.parallelize(List("1,2,3,4,5,1,2,2,3,4,4,5,6")) numbers: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[7] at parallelize at ... ,However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... ,However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... , 举例:从普通数组创建RDD,里面包含了1到9这9个数字,它们分别在3个分区中。 scala> val a = sc.parallelize(1 to 9, 3) a: org.apache.spark.rdd., 并行集合是通过调用SparkContext的parallelize方法,在一个已经存在的Scala集合 ... val distData = sc.parallelize(data) ... scala> val distFile = sc., distData = sc.parallelize(data). 一旦分布式数据集(distData)被创建好,它们将可以被并行操作。例如,我们可以调用distData.reduce(lambda a, ..., val stringRDD = sc.parallelize(List("Apple", "Orange", "Banana","Grape","Apple")) stringRDD.collect() Step4 map運算 具名函數的寫法:
相關軟體 Spark 資訊 | |
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Spark 是針對企業和組織優化的 Windows PC 的開源,跨平台 IM 客戶端。它具有內置的群聊支持,電話集成和強大的安全性。它還提供了一個偉大的最終用戶體驗,如在線拼寫檢查,群聊室書籤和選項卡式對話功能。Spark 是一個功能齊全的即時消息(IM)和使用 XMPP 協議的群聊客戶端。 Spark 源代碼由 GNU 較寬鬆通用公共許可證(LGPL)管理,可在此發行版的 LICENSE.ht... Spark 軟體介紹
sc parallelize 相關參考資料
Create a Spark RDD using Parallelize — Spark by Examples}
scala> val rdd = sc.parallelize(Array(1,2,3,4,5,6,7,8,9,10)) rdd: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[1] at parallelize at :24. https://sparkbyexamples.com https:blog.csdn.netnanruoanhaoarticledetails...
https://blog.csdn.net RDD Programming Guide - Spark 2.4.4 Documentation
However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... https://spark.apache.org RDD基本操作 - iT 邦幫忙::一起幫忙解決難題,拯救IT 人的一天
scala> val numbers=sc.parallelize(List("1,2,3,4,5,1,2,2,3,4,4,5,6")) numbers: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[7] at parallelize at ... https://ithelp.ithome.com.tw Spark Programming Guide - Spark 2.1.0 Documentation
However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... https://spark.apache.org Spark Programming Guide - Spark 2.1.1 Documentation
However, you can also set it manually by passing it as a second parameter to parallelize (e.g. sc.parallelize(data, 10) ). Note: some places in the code use the ... https://spark.apache.org Spark RDD API详解(一) Map和Reduce - 作业部落Cmd ...
举例:从普通数组创建RDD,里面包含了1到9这9个数字,它们分别在3个分区中。 scala> val a = sc.parallelize(1 to 9, 3) a: org.apache.spark.rdd. https://www.zybuluo.com Spark 开发指南| 鸟窝
并行集合是通过调用SparkContext的parallelize方法,在一个已经存在的Scala集合 ... val distData = sc.parallelize(data) ... scala> val distFile = sc. https://colobu.com spark使用parallelize方法创建RDD - 简书
distData = sc.parallelize(data). 一旦分布式数据集(distData)被创建好,它们将可以被并行操作。例如,我们可以调用distData.reduce(lambda a, ... https://www.jianshu.com 第9章. Spark RDD介紹與範例指令| Hadoop+Spark大數據巨量 ...
val stringRDD = sc.parallelize(List("Apple", "Orange", "Banana","Grape","Apple")) stringRDD.collect() Step4 map運算 具名函數的寫法: http://hadoopspark.blogspot.co |