Flink WordCount入门 _生活百科

下面通过一个单词统计的案例，快速上手应用 Flink ，进行流处理（Streaming）和批处理（Batch）
单词统计（批处理）

引入依赖

<!--flink核心包--><dependency><groupId>org.apache.flink</groupId><artifactId>flink-java</artifactId><version>1.7.2</version></dependency><!--flink流处理包--><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-java_2.12</artifactId><version>1.7.2</version></dependency>

代码实现

public class WordCountBatch {public static void main(String[] args) throws Exception {String inputFile= "E:\\data\\word.txt";String outPutFile= "E:\\data\\wordResult.txt";ExecutionEnvironment executionEnvironment = ExecutionEnvironment.getExecutionEnvironment();//1. 读取数据DataSource<String> dataSource = executionEnvironment.readTextFile(inputFile);//2. 对数据进行处理 ， 转成word,1的格式FlatMapOperator<String, Tuple2<String, Integer>> flatMapOperator = dataSource.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {@Overridepublic void flatMap(String s, Collector<Tuple2<String, Integer>> collector) throws Exception {String[] words = s.split(" ");for (String word : words) {collector.collect(new Tuple2<>(word, 1));}}});//3. 对数据分组 ， 相同word的一个组UnsortedGrouping<Tuple2<String, Integer>> tuple2UnsortedGrouping = flatMapOperator.groupBy(0);//4. 对分组后的数据求和AggregateOperator<Tuple2<String, Integer>> sum = tuple2UnsortedGrouping.sum(1);//5. 写出数据sum.writeAsCsv(outPutFile).setParallelism(1);//执行executionEnvironment.execute("wordcount batch process");}}

执行 main 方法，得出结果。我测试的 word.txt 内容如下：
ni hao hiwang mei meiliu meini haowo hen haothis is a good ideaApache Flink输出的文件结果：
a,1mei,3Apache,1Flink,1good,1hen,1hi,1idea,1ni,2is,1liu,1this,1wo,1hao,3wang,1单词统计（流数据）需求：Socket 模拟实时发送单词，使用 Flink 实时接收数据，对指定时间窗口内（如 5s）的数据进行聚合统计，每隔 1s 汇总计算一次，并且把时间窗口内计算结果打印出来

public class WordCountStream {public static void main(String[] args) throws Exception {int port = 7000;StreamExecutionEnvironment executionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment();DataStreamSource<String> textStream = executionEnvironment.socketTextStream("192.168.56.103", port, "\n");SingleOutputStreamOperator<Tuple2<String, Integer>> tuple2SingleOutputStreamOperator = textStream.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {@Overridepublic void flatMap(String s, Collector<Tuple2<String, Integer>> collector) throws Exception {String[] split = s.split("\\s");for (String word : split) {collector.collect(Tuple2.of(word, 1));}}});SingleOutputStreamOperator<Tuple2<String, Integer>> word = tuple2SingleOutputStreamOperator.keyBy(0).timeWindow(Time.seconds(5),Time.seconds(1)).sum(1);word.print();executionEnvironment.execute("wordcount stream process");}}

运行起来之后，我们就可以开始发送 socket 请求过去。我们测试可以使用 netcat 工具。在 linux 上安装好后，使用下面的命令：
nc -lk 7000然后发送数据即可。