Flink Join Sample Program (Java)

Function

In the Flink application, this code invokes the flink-connector-kafka module's API to generate and consume data.

Sample Code

If the user needs to use FusionInsight Kafka interconnected with the security mode before the development, obtain the kafka-clients-*.jar JAR file from the Kafka client directory.

The following lists Producer, Consumer, and the main logic code used by Flink Stream SQL Join.

For the complete code, see com.huawei.bigdata.flink.examples.WriteIntoKafkaand com.huawei.bigdata.flink.examples.SqlJoinWithSocket.

1. A piece of user information is generated in Kafka every second. The user information includes the name, age, and gender.

   //Producer code
   public class WriteIntoKafka {
         public static void main(String[] args) throws Exception {
         //Print the command reference for flink run. 
           System.out.println("use command as: ");
           System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
              " /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21005");
           System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
              " /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21007 --security.protocol SASL_PLAINTEXT --sasl.kerberos.service.name kafka");
           System.out.println("******************************************************************************************");
           System.out.println("<topic> is the kafka topic name");
           System.out.println("<bootstrap.servers> is the ip:port list of brokers");
           System.out.println("******************************************************************************************");
          
           //Construct the execution environment.
           StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
           //Set the concurrency. 
           env.setParallelism(1);
           //Parse the running parameters.
           ParameterTool paraTool = ParameterTool.fromArgs(args);
           //Construct a flow diagram and write the data generated from self-defined sources to Kafka.
           DataStream<String> messageStream = env.addSource(new SimpleStringGenerator());
           FlinkKafkaProducer<String> producer = new FlinkKafkaProducer<>(paraTool.get("topic"),
              new SimpleStringSchema(),
              paraTool.getProperties());
           producer.setWriteTimestampToKafka(true);
           messageStream.addSink(producer);
           //Invoke execute to trigger the execution. 
           env.execute();
        }
   //Customize the sources and generate a message every second.
   public static class SimpleStringGenerator implements SourceFunction<String> {
           static final String[] NAME = {"Carry", "Alen", "Mike", "Ian", "John", "Kobe", "James"};
           static final String[] SEX = {"MALE", "FEMALE"};
           static final int COUNT = NAME.length;   
           boolean running = true;
           Random rand = new Random(47);
          @Override
           //Use rand to randomly generate a combination of the name, gender, and age.
            public void run(SourceContext<String> ctx) throws Exception {
               while (running) {
                   int i = rand.nextInt(COUNT);
                   int age = rand.nextInt(70);
                   String sexy = SEX[rand.nextInt(2)];
                   ctx.collect(NAME[i] + "," + age + "," + sexy);
                   thread.sleep(1000);
               }
       }
          @Override
          public void cancel() {
            running = false;
          }
        }
      }

2. Generate Table1 and Table2, use Join to jointly query Table1 and Table2, and print the output result.

   public class SqlJoinWithSocket {
       public static void main(String[] args) throws Exception{
           final String hostname;
           final int port;
           System.out.println("use command as: ");
           System.out.println("flink run --class com.huawei.bigdata.flink.examples.SqlJoinWithSocket" +
                   " /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:21005 --hostname xxx.xxx.xxx.xxx --port xxx");
           System.out.println("flink run --class com.huawei.bigdata.flink.examples.SqlJoinWithSocket" +
                   " /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:21007 --security.protocol SASL_PLAINTEXT --sasl.kerberos.service.name kafka"
                   + "--hostname xxx.xxx.xxx.xxx --port xxx");
           System.out.println("******************************************************************************************");
           System.out.println("<topic> is the kafka topic name");
           System.out.println("<bootstrap.servers> is the ip:port list of brokers");
           System.out.println("******************************************************************************************");
           try {
               final ParameterTool params = ParameterTool.fromArgs(args);
               hostname = params.has("hostname") ? params.get("hostname") : "localhost";
               port = params.getInt("port");
           } catch (Exception e) {
               System.err.println("No port specified. Please run 'FlinkStreamSqlJoinExample " +
                       "--hostname <hostname> --port <port>', where hostname (localhost by default) " +
                       "and port is the address of the text server");
               System.err.println("To start a simple text server, run 'netcat -l -p <port>' and " +
                       "type the input text into the command line");
               return;
           }
           
           EnvironmentSettings fsSettings = EnvironmentSettings.newInstance().useOldPlanner().inStreamingMode().build();
           StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
           StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env, fsSettings);
           //Perform processing based on EventTime. 
           env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
           env.setParallelism(1);
           ParameterTool paraTool = ParameterTool.fromArgs(args);
           //Use Stream1 to read data from Kafka. 
           DataStream<Tuple3<String, String, String>> kafkaStream = env.addSource(new FlinkKafkaConsumer<>(paraTool.get("topic"),
                   new SimpleStringSchema(),
                   paraTool.getProperties())).map(new MapFunction<String, Tuple3<String, String, String>>() {
               @Override
               public Tuple3<String, String, String> map(String s) throws Exception {
                   String[] word = s.split(",");
                   return new Tuple3<>(word[0], word[1], word[2]);
               }
           });
           //Register Stream1 as Table1. 
           tableEnv.registerDataStream("Table1", kafkaStream, "name, age, sexy, proctime.proctime");
           //Use Stream2 to read data from the socket. 
           DataStream<Tuple2<String, String>> socketStream = env.socketTextStream(hostname, port, "\n").
                   map(new MapFunction<String, Tuple2<String, String>>() {
                       @Override
                       public Tuple2<String, String> map(String s) throws Exception {
                           String[] words = s.split("\\s");
                           if (words.length < 2) {
                               return new Tuple2<>();
                           }
                           return new Tuple2<>(words[0], words[1]);
                       }
                   });
           //Register Stream2 as Table2. 
           tableEnv.registerDataStream("Table2", socketStream, "name, job, proctime.proctime");
           //Run SQL Join to perform a combined query.
           Table result = tableEnv.sqlQuery("SELECT t1.name, t1.age, t1.sexy, t2.job, t2.proctime as shiptime\n" +
                   "FROM Table1 AS t1\n" +
                   "JOIN Table2 AS t2\n" +
                   "ON t1.name = t2.name\n" +
                   "AND t1.proctime BETWEEN t2.proctime - INTERVAL '1' SECOND AND t2.proctime + INTERVAL '1' SECOND");
           //Convert the query result into the stream and print the output.
           tableEnv.toAppendStream(result, Row.class).print();
           env.execute();
       }
   }