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废话不说,先来个示例,有个感性认识再介绍。
这个示例来自spark自带的example,基本步骤如下:
(1)使用以下命令输入流消息:
$ nc -lk 9999
(2)在一个新的终端中运行NetworkWordCount,统计上面的词语数量并输出:
$ bin/run-example streaming.NetworkWordCount localhost 9999
(3)在第一步创建的输入流程中敲入一些内容,在第二步创建的终端中会看到统计结果,如:
第一个终端输入的内容:
hello world again
第二个端口的输出
-------------------------------------------
Time: 1436758706000 ms
-------------------------------------------
(again,1)
(hello,1)
(world,1)
简单解释一下,上面的示例通过手工敲入内容,并传给spark streaming统计单词数量,然后将结果打印出来。
附上代码:
package org.apache.spark.examples.streaming
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.storage.StorageLevel
/**
* Counts words in UTF8 encoded, ‘\n‘ delimited text received from the network every second.
*
* Usage: NetworkWordCount <hostname> <port>
* <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive data.
*
* To run this on your local machine, you need to first run a Netcat server
* `$ nc -lk 9999`
* and then run the example
* `$ bin/run-example org.apache.spark.examples.streaming.NetworkWordCount localhost 9999`
*/
object NetworkWordCount {
def main(args: Array[String]) {
if (args.length < 2) {
System.err.println("Usage: NetworkWordCount <hostname> <port>")
System.exit(1)
}
StreamingExamples.setStreamingLogLevels()
// Create the context with a 1 second batch size
val sparkConf = new SparkConf().setAppName("NetworkWordCount")
val ssc = new StreamingContext(sparkConf, Seconds(1))
// Create a socket stream on target ip:port and count the
// words in input stream of \n delimited text (eg. generated by ‘nc‘)
// Note that no duplication in storage level only for running locally.
// Replication necessary in distributed scenario for fault tolerance.
val lines = ssc.socketTextStream(args(0), args(1).toInt, StorageLevel.MEMORY_AND_DISK_SER)
val words = lines.flatMap(_.split(" "))
val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
wordCounts.print()
ssc.start()
ssc.awaitTermination()
}
}
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原文地址:http://www.cnblogs.com/lujinhong2/p/4642498.html