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.streaming;
  
  import java.util.Arrays;
  import java.util.Iterator;
  import java.util.regex.Pattern;
  
  import org.apache.spark.SparkConf;
  import org.apache.spark.api.java.JavaRDD;
  import org.apache.spark.api.java.function.FlatMapFunction;
  import org.apache.spark.api.java.function.Function;
  import org.apache.spark.api.java.function.VoidFunction2;
  import org.apache.spark.sql.Dataset;
  import org.apache.spark.sql.Row;
  import org.apache.spark.sql.SparkSession;
  import org.apache.spark.api.java.StorageLevels;
  import org.apache.spark.streaming.Durations;
  import org.apache.spark.streaming.Time;
  import org.apache.spark.streaming.api.java.JavaDStream;
  import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
  import org.apache.spark.streaming.api.java.JavaStreamingContext;
  
  /**
   * Use DataFrames and SQL to count words in UTF8 encoded, '\n' delimited text received from the
   * network every second.
   *
   * Usage: JavaSqlNetworkWordCount <hostname> <port>
   * <hostname> and <port> describe the TCP server that Spark 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 org.apache.spark.examples.streaming.JavaSqlNetworkWordCount localhost 9999`
   */
  
  public final class JavaSqlNetworkWordCount {
    private static final Pattern SPACE = Pattern.compile(" ");
  
    public static void main(String[] args) throws Exception {
      if (args.length < 2) {
        System.err.println("Usage: JavaNetworkWordCount <hostname> <port>");
        System.exit(1);
      }
  
      StreamingExamples.setStreamingLogLevels();
  
      // Create the context with a 1 second batch size
      SparkConf sparkConf = new SparkConf().setAppName("JavaSqlNetworkWordCount");
      JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
  
      // Create a JavaReceiverInputDStream on target ip:port and count the
      // words in input stream of \n delimited text (eg. generated by 'nc')
      // Note that no duplication in storage level only for running locally.
      // Replication necessary in distributed scenario for fault tolerance.
      JavaReceiverInputDStream<String> lines = ssc.socketTextStream(
          args[0], Integer.parseInt(args[1]), StorageLevels.MEMORY_AND_DISK_SER);
      JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
        @Override
        public Iterator<String> call(String x) {
          return Arrays.asList(SPACE.split(x)).iterator();
        }
      });
  
      // Convert RDDs of the words DStream to DataFrame and run SQL query
      words.foreachRDD(new VoidFunction2<JavaRDD<String>, Time>() {
        @Override
        public void call(JavaRDD<String> rdd, Time time) {
          SparkSession spark = JavaSparkSessionSingleton.getInstance(rdd.context().getConf());
  
          // Convert JavaRDD[String] to JavaRDD[bean class] to DataFrame
          JavaRDD<JavaRecord> rowRDD = rdd.map(new Function<String, JavaRecord>() {
            @Override
            public JavaRecord call(String word) {
              JavaRecord record = new JavaRecord();
              record.setWord(word);
              return record;
            }
          });
          Dataset<Row> wordsDataFrame = spark.createDataFrame(rowRDD, JavaRecord.class);
  
          // Creates a temporary view using the DataFrame
          wordsDataFrame.createOrReplaceTempView("words");
  
          // Do word count on table using SQL and print it
          Dataset<Row> wordCountsDataFrame =
              spark.sql("select word, count(*) as total from words group by word");
          System.out.println("========= " + time + "=========");
          wordCountsDataFrame.show();
        }
      });
  
      ssc.start();
      ssc.awaitTermination();
    }
  }
  
  /** Lazily instantiated singleton instance of SparkSession */
  class JavaSparkSessionSingleton {
    private static transient SparkSession instance = null;
    public static SparkSession getInstance(SparkConf sparkConf) {
      if (instance == null) {
        instance = SparkSession
          .builder()
          .config(sparkConf)
          .getOrCreate();
      }
      return instance;
    }
  }
  