content: /*
   * Licensed to the Apache Software Foundation (ASF) under one or more
   * contributor license agreements.  See the NOTICE file distributed with
   * this work for additional information regarding copyright ownership.
   * The ASF licenses this file to You under the Apache License, Version 2.0
   * (the "License"); you may not use this file except in compliance with
   * the License.  You may obtain a copy of the License at
   *
   *    http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  package org.apache.spark.examples.sql.streaming;
  
  import org.apache.spark.api.java.function.FlatMapFunction;
  import org.apache.spark.sql.*;
  import org.apache.spark.sql.streaming.StreamingQuery;
  
  import java.util.Arrays;
  import java.util.Iterator;
  
  /**
   * Counts words in UTF8 encoded, '\n' delimited text received from the network.
   *
   * Usage: JavaStructuredNetworkWordCount <hostname> <port>
   * <hostname> and <port> describe the TCP server that Structured Streaming
   * would connect to receive data.
   *
   * To run this on your local machine, you need to first run a Netcat server
   *    `$ nc -lk 9999`
   * and then run the example
   *    `$ bin/run-example sql.streaming.JavaStructuredNetworkWordCount
   *    localhost 9999`
   */
  public final class JavaStructuredNetworkWordCount {
  
    public static void main(String[] args) throws Exception {
      if (args.length < 2) {
        System.err.println("Usage: JavaStructuredNetworkWordCount <hostname> <port>");
        System.exit(1);
      }
  
      String host = args[0];
      int port = Integer.parseInt(args[1]);
  
      SparkSession spark = SparkSession
        .builder()
        .appName("JavaStructuredNetworkWordCount")
        .getOrCreate();
  
      // Create DataFrame representing the stream of input lines from connection to host:port
      Dataset<Row> lines = spark
        .readStream()
        .format("socket")
        .option("host", host)
        .option("port", port)
        .load();
  
      // Split the lines into words
      Dataset<String> words = lines.as(Encoders.STRING())
        .flatMap(new FlatMapFunction<String, String>() {
          @Override
          public Iterator<String> call(String x) {
            return Arrays.asList(x.split(" ")).iterator();
          }
      }, Encoders.STRING());
  
      // Generate running word count
      Dataset<Row> wordCounts = words.groupBy("value").count();
  
      // Start running the query that prints the running counts to the console
      StreamingQuery query = wordCounts.writeStream()
        .outputMode("complete")
        .format("console")
        .start();
  
      query.awaitTermination();
    }
  }
  