Created
August 13, 2016 15:18
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Java WordCount on Spark using Dataset
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| //tested on spark 2.0 | |
| import org.apache.spark.sql.*; | |
| import java.util.Arrays; | |
| public class WordCount { | |
| public static void main(String[] args) { | |
| if (args.length < 2) { | |
| System.err.println("Please provide the full path of input file and output dir as arguments"); | |
| System.exit(0); | |
| } | |
| SparkSession spark = SparkSession | |
| .builder() | |
| .master("local") | |
| .appName("WordCount") | |
| .getOrCreate(); | |
| Dataset<String> df = spark.read().text(args[0]).as(Encoders.STRING()); | |
| Dataset<String> words = df.flatMap(s -> { | |
| return Arrays.asList(s.toLowerCase().split(" ")).iterator(); | |
| }, Encoders.STRING()) | |
| .filter(s -> !s.isEmpty()) | |
| .coalesce(1); //one partition (parallelism level) | |
| //words.printSchema(); // { value: string (nullable = true) } | |
| Dataset<Row> t = words.groupBy("value") //<k, iter(V)> | |
| .count() | |
| .toDF("word","count"); | |
| t = t.sort(functions.desc("count")); | |
| t.toJavaRDD().saveAsTextFile(args[1]); | |
| } | |
| } |
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