spark讀hdfs檔案實現wordcount並將結果存回hdfs
阿新 • • 發佈:2019-02-08
package iie.udps.example.operator.spark; import scala.Tuple2; import org.apache.spark.SparkConf; import org.apache.spark.api.java.JavaPairRDD; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; import org.apache.spark.api.java.function.FlatMapFunction; import org.apache.spark.api.java.function.Function; import org.apache.spark.api.java.function.Function2; import org.apache.spark.api.java.function.PairFunction; import java.util.Arrays; import java.util.regex.Pattern; /** * 利用Spark框架讀取HDFS檔案,實現WordCount示例 * * 執行命令:spark-submit --class iie.hadoop.hcatalog.TextFileSparkTest --master * yarn-cluster /tmp/sparkTest.jar hdfs://192.168.8.101/test/words * hdfs://192.168.8.101/test/spark/out * * @author xiaodongfang * */ public final class TextFileSparkTest { private static final Pattern SPACE = Pattern.compile(" "); @SuppressWarnings("serial") public static void main(String[] args) throws Exception { if (args.length < 2) { System.err.println("Usage: JavaWordCount <file>"); System.exit(1); } String inputSparkFile = args[0]; String outputSparkFile = args[1]; SparkConf sparkConf = new SparkConf().setAppName("SparkWordCount"); JavaSparkContext ctx = new JavaSparkContext(sparkConf); JavaRDD<String> lines = ctx.textFile(inputSparkFile, 1); JavaRDD<String> words = lines .flatMap(new FlatMapFunction<String, String>() { @Override public Iterable<String> call(String s) { return Arrays.asList(SPACE.split(s)); } }); JavaPairRDD<String, Integer> ones = words .mapToPair(new PairFunction<String, String, Integer>() { @Override public Tuple2<String, Integer> call(String s) { return new Tuple2<String, Integer>(s, 1); } }); JavaPairRDD<String, Integer> counts = ones .reduceByKey(new Function2<Integer, Integer, Integer>() { @Override public Integer call(Integer i1, Integer i2) { return i1 + i2; } }); counts.map(new Function<Tuple2<String, Integer>, String>() { @Override public String call(Tuple2<String, Integer> arg0) throws Exception { return arg0._1.toUpperCase() + ": " + arg0._2; } }).saveAsTextFile(outputSparkFile); ctx.stop(); } }