SparkStreaming和KafKa结合报错!报错之前代码如下: object KafkaWordCount{ val updateFunc = (iter:Iterator[(String,Seq[Int],Option[Int])])=>{ iter.flatMap{case(x,y,z) => Some(y.sum+z.getOrElse(0)).map(i => (x,i))} } def main(args: Array[String]): Unit = { val Arr…

Spark 1.5.2 Spark Streaming 学习笔记和编程练习 Overview 概述 Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources like Kafka,…

Overview A Quick Example Basic Concepts Linking Initializing StreamingContext Discretized Streams (DStreams) Input DStreams and Receivers Transformations on DStreams Output Operations on DStreams DataFrame and SQL Operations MLlib Operations Caching…

转载自:http://blog.csdn.net/erfucun/article/details/52312682 本博文主要内容包括: 技术实现foreachRDD与foreachPartition解析 foreachRDD与foreachPartition实现实战 一:技术实现foreach解析: 1.首先我们看一下Output Operations on DStreams提供的API:   SparkStreaming的DStream提供了一个dstream.foreachRDD方法,该方…

1.Spark Streaming是什么? a.Spark Streaming是什么? Spark Streaming类似于Apache Storm,用于流式数据的处理.根据其官方文档介绍,Spark Streaming有高吞吐量和容错能力强等特点.Spark Streaming支持的数据输入源很多,例如:Kafka.Flume.Twitter.ZeroMQ和简单的TCP套接字等等.数据输入后可以用Spark的高度抽象原语如:map.reduce.join.window等进行运算.而结果也能保存…

Spark Streaming学习笔记 liunx系统的习惯创建hadoop用户在hadoop根目录(/home/hadoop)上创建如下目录app 存放所有软件的安装目录 app/tmp 存放临时文件 data 存放测试数据lib 存放开发用的jar包software 存放软件安装包的目录source 存放框架源码 hadoop生态系统 CDH5.7.x地址:http://archive.cloudera.com/cdh5/cdh/5/ 需求:统计主站每个课程访问的客户端,地域信息分布地域:i…

Spark Streaming核心概念与编程 1. 核心概念 StreamingContext Create StreamingContext import org.apache.spark._ import org.apache.spark.streaming._ val conf = new SparkConf().setAppName(appName).setMaster(master) //Second(1) #表示处理的批次, 当前1秒处理一次 val ssc = new Stream…

SparkStreaming Spark Streaming类似于Apache Storm,用于流式数据的处理.Spark Streaming有高吞吐量和容错能力强等特点.Spark Streaming支持的数据源有很多,例如:Kafka.Flume.Twitter.ZeroMQ和简单的TCP套接字等等.数据输入后可以用Spark的高度抽象操作如:map.reduce.join.window等进行运算.而结果也能保存在很多地方,如HDFS,数据库等. 特性 1.易用性 可以像编写离线批处理一样去…

1 Overview Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources like Kafka, Flume, Twitter, ZeroMQ, Kinesis, or TCP…

Spark Streaming 编程指南 Overview A Quick Example Basic Concepts Linking Initializing StreamingContext Discretized Streams (DStreams) Input DStreams and Receivers Transformations on DStreams Output Operations on DStreams DataFrame and SQL Operations MLli…