flink对文件top打包执行代码
时间: 2024-03-16 19:45:48 浏览: 65
打包的代码
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以下是使用Flink对文件top打包执行的代码:
```java
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.common.functions.RuntimeContext;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.DataSource;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.core.fs.FileSystem;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;
public class FileTop {
public static void main(String[] args) throws Exception {
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
// 读取文件
DataSource<String> input = env.readTextFile("path/to/file");
// 进行单词计数
input.flatMap(new LineSplitter())
.groupBy(0)
.reduce(new WordCountReducer())
.writeAsCsv("path/to/output", FileSystem.WriteMode.OVERWRITE);
env.execute("File Top");
}
private static class LineSplitter implements FlatMapFunction<String, Tuple2<String, Integer>> {
@Override
public void flatMap(String line, Collector<Tuple2<String, Integer>> out) {
// 按空格拆分单词
for (String word : line.split(" ")) {
out.collect(new Tuple2<>(word, 1));
}
}
}
private static class WordCountReducer implements ReduceFunction<Tuple2<String, Integer>> {
@Override
public Tuple2<String, Integer> reduce(Tuple2<String, Integer> t1, Tuple2<String, Integer> t2) {
// 对相同单词进行计数
return new Tuple2<>(t1.f0, t1.f1 + t2.f1);
}
}
}
```
这个程序首先读取一个文件,然后对文件中的每一行进行单词计数。最后将计数结果写出到文件中。你可以将这个程序打包成一个可执行的 jar 文件,在命令行中执行:
```bash
$ flink run -c FileTop path/to/jar
```
其中 `FileTop` 是程序的入口类,`path/to/jar` 是打包后的 jar 文件路径。
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