Spark学习六：spark streaming

Spark学习六：spark streaming

标签（空格分隔）： Spark

一，概述

一个简单的实例
1，安装nc

nc -lk 9999

2,启动应用

./bin/run-example streaming.NeworkWordCount localhost 9999

二，企业案例分析

需求：
实时统计最近两个小时的网站访问状况，
pv，uv，地区

5分钟执行一次

10:00
8:00 - 10:00 window 24
10:05
8:05 - 10:05 window 24

StreamingContext(sc, Mintuns(5))
DStream.window(Mintuns(24 * 5), Mintuns(2 * 5))

代码实现

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-streaming_2.10</artifactId>
    <version>1.3.0</version>
</dependency>

如何在spark-shell中执行某个scala代码

scala > :load /opt/cdh5.3.6/spark-1.3.0-bin-2.5.0-cdh5.3.6/HdfsWordCount.scala

三，Spark streaming的工作原理

四，textFileStreaming的应用

1，准备数据

bin/hdfs dfs -put wordcount.txt /spark/streaming

2,启动spark应用

bin/spark-shell --master local[2]

3,编写代码

import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.StreamingContext._

val ssc = new StreamingContext(sc, Seconds(30))

val lines = ssc.textFileStream("hdfs://study.com.cn:8020/myspark")

val words = lines.flatMap(_.split(","))
val pairs = words.map(word => (word, 1))
val wordCounts = pairs.reduceByKey(_ + _)

wordCounts.print()
ssc.start()
ssc.awaitTermination()

4,测试结果

四，企业中的开发方式：

1，idea编码，打成jar包执行
2，放到脚本里面执行

touch test.scala

import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.StreamingContext._

val ssc = new StreamingContext(sc, Seconds(30))

val lines = ssc.textFileStream("hdfs://study.com.cn:8020/myspark")

val words = lines.flatMap(_.split(","))
val pairs = words.map(word => (word, 1))
val wordCounts = pairs.reduceByKey(_ + _)

wordCounts.print()
ssc.start()
ssc.awaitTermination()

scala > :load /opt/app/spark-1.3.0-bin-2.5.0/test/test.scala

五，总结