Spark2.x学习笔记：17、Spark Streaming之HdfsWordCount 学习

Spark2.x学习笔记：17、Spark Streaming之HdfsWordCount 学习

17.1 HdfsWordCount 源码解析

// scalastyle:off printlnpackage org.apache.spark.examples.streamingimport org.apache.spark.SparkConfimport org.apache.spark.streaming.{Seconds, StreamingContext}/** * Counts words in new text files created in the given directory * Usage: HdfsWordCount <directory> *   <directory> is the directory that Spark Streaming will use to find and read new text files. * * To run this on your local machine on directory `localdir`, run this example *    $ bin/run-example \ *       org.apache.spark.examples.streaming.HdfsWordCount localdir * * Then create a text file in `localdir` and the words in the file will get counted. */object HdfsWordCount {  def main(args: Array[String]) {    if (args.length < 1) {      System.err.println("Usage: HdfsWordCount <directory>")      System.exit(1)    }    StreamingExamples.setStreamingLogLevels()    val sparkConf = new SparkConf().setAppName("HdfsWordCount")    // Create the context    val ssc = new StreamingContext(sparkConf, Seconds(2))    // Create the FileInputDStream on the directory and use the    // stream to count words in new files created    val lines = ssc.textFileStream(args(0))    val words = lines.flatMap(_.split(" "))    val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)    wordCounts.print()    ssc.start()    ssc.awaitTermination()  }}// scalastyle:on println

通过注释可以知道，

• HdfsWordCount 是统计在给定目录中新文本文件中的单词
• 运行方式run-example org.apache.spark.examples.streaming.HdfsWordCount localdir,其中localdir是Spark Streaming将用来查找和读取新文本文件的目录

17.2 测试运行

（1）创建目录

[root@node1 ~]# hdfs dfs -mkdir /streaming[root@node1 ~]# hdfs dfs -ls /streaming[root@node1 ~]#

（2）先上传一个文件

[root@node1 ~]# hdfs dfs -put data/word1.txt /streaming[root@node1 ~]# hdfs dfs -ls /streamingFound 1 items-rw-r--r--   3 root supergroup         30 2017-11-04 09:21 /streaming/word1.txt[root@node1 ~]#

这里需要先在Spark Streaming需要读取的目录中上传一个文件，不然HdfsWordCount 运行后再上传会报错

java.io.FileNotFoundException: File does not exist: /streaming/books.txt._COPYING_

（3）开始运行

[root@node1 ~]# run-example org.apache.spark.examples.streaming.HdfsWordCount /streaming17/11/04 09:22:09 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable-------------------------------------------Time: 1509801734000 ms--------------------------------------------------------------------------------------Time: 1509801736000 ms--------------------------------------------------------------------------------------Time: 1509801738000 ms--------------------------------------------------------------------------------------Time: 1509801740000 ms--------------------------------------------------------------------------------------Time: 1509801742000 ms--------------------------------------------------------------------------------------Time: 1509801744000 ms-------------------------------------------

（4）上传需要处理的文件
另外开一个终端，上传文件。

[root@node1 ~]# hdfs dfs -put data/books.txt /streaming

这是可以看到HdfsWordCount 程序的输出

-------------------------------------------Time: 1509801746000 ms--------------------------------------------------------------------------------------Time: 1509801748000 ms-------------------------------------------(2001   49.0    S2  Java,1)(3003   49.0    S3  Hive教程,1)(3002   98.0    S3  Spark基础,1)(3004   56.0    S3  HBase教程,1)(3005   49.5    S3  大数据概论,1)(1002   39.0    S1  C语言,1)(2071   99.0    S2  Oracle,1)(1021   45.0    S1  数据结构,1)(1001   39.0    S1  计算机基础,1)(2091   69.0    S2  Linux,1)...-------------------------------------------Time: 1509801750000 ms--------------------------------------------------------------------------------------Time: 1509801752000 ms--------------------------------------------------------------------------------------Time: 1509801754000 ms--------------------------------------------------------------------------------------Time: 1509801756000 ms-------------------------------------------

再上传一个文件

[root@node1 ~]# hdfs dfs -put data/Hamlet.txt /streaming

同样，这时可以可以看到HdfsWordCount 程序的输出

-------------------------------------------Time: 1509801758000 ms--------------------------------------------------------------------------------------Time: 1509801760000 ms--------------------------------------------------------------------------------------Time: 1509801762000 ms--------------------------------------------------------------------------------------Time: 1509801764000 ms-------------------------------------------(weary,,1)(pate,4)(whereof,,1)(joy.,1)(rises.,1)(lug,1)(stuck,,1)(shot,7)(line:,1)(order,2)...-------------------------------------------Time: 1509801766000 ms--------------------------------------------------------------------------------------Time: 1509801768000 ms-------------------------------------------