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更新时间：2024-12-17 GMT+08:00
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Flink Stream SQL Join Java样例代码

功能简介

在Flink应用中，调用flink-connector-kafka模块的接口，生产并消费数据。

用户在开发前需要使用对接安全模式的Kafka，则需要引入MRS的kafka-client-xx.x.x.jar，该jar包可在MRS client目录下获取。

代码样例

下面列出producer和consumer，以及Flink Stream SQL Join使用主要逻辑代码作为演示。

完整代码参见com.huawei.bigdata.flink.examples.WriteIntoKafka和com.huawei.bigdata.flink.examples.SqlJoinWithSocket。

  • 每秒钟往Kafka中生产一条用户信息，用户信息由姓名、年龄、性别组成。 
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    //producer代码
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;

import java.util.Random;

public class WriteIntoKafka4SQLJoin {

    public static void main(String[] args) throws Exception {
        // 打印出执行flink run的参考命令
        System.out.println("use command as: ");
        System.out.println("./bin/flink run --class com.huawei.flink.example.sqljoin.WriteIntoKafka4SQLJoin" +
                " /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21005");
        System.out.println("./bin/flink run --class com.huawei.flink.example.sqljoin.WriteIntoKafka4SQLJoin" +
                " /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("******************************************************************************************");

        // 构造执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        // 设置并发度
        env.setParallelism(1);
        // 解析运行参数
        ParameterTool paraTool = ParameterTool.fromArgs(args);
        // 构造流图，将自定义Source生成的数据写入Kafka
        DataStream<String> messageStream = env.addSource(new SimpleStringGenerator());
        FlinkKafkaProducer producer = new FlinkKafkaProducer<>(paraTool.get("topic"), new SimpleStringSchema(), paraTool.getProperties());
        messageStream.addSink(producer);
        // 调用execute触发执行
        env.execute();
    }

    // 自定义Source，每隔1s持续产生消息
    public static class SimpleStringGenerator implements SourceFunction<String> {
        static final String[] NAME = {"Carry", "Alen", "Mike", "Ian", "John", "Kobe", "James"};
        static final String[] Gender = {"MALE", "FEMALE"};
        static final int COUNT = NAME.length;
        boolean running = true;
        Random rand = new Random(47);

        @Override
        //rand随机产生名字，性别，年龄的组合信息
        public void run(SourceContext<String> ctx) throws Exception {
            while (running) {
                int i = rand.nextInt(COUNT);
                int age = rand.nextInt(70);
                String Gender = Gender[rand.nextInt(2)];
                ctx.collect(NAME[i] + "," + age + "," + Gender);
                Thread.sleep(1000);
            }
        }

        @Override
        public void cancel() {
            running = false;
        }
    }
}
  • 生成Table1和Table2，并使用Join对Table1和Table2进行联合查询，打印输出结果。 
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    import org.apache.calcite.interpreter.Row;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.tuple.Tuple3;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.java.StreamTableEnvironment;

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.flink.example.sqljoin.SqlJoinWithSocket" +
                " /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:9092 --hostname xxx.xxx.xxx.xxx --port xxx");

        System.out.println("flink run --class com.huawei.flink.example.sqljoin.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;
        }

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);

        //基于EventTime进行处理
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);

        env.setParallelism(1);

        ParameterTool paraTool = ParameterTool.fromArgs(args);

        //Stream1，从Kafka中读取数据
        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]);
                    }
                });

        //将Stream1注册为Table1
        tableEnv.registerDataStream("Table1", kafkaStream, "name, age, Gender, proctime.proctime");

        //Stream2，从Socket中读取数据
        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]);
                    }
                });

        //将Stream2注册为Table2
        tableEnv.registerDataStream("Table2", socketStream, "name, job, proctime.proctime");

        //执行SQL Join进行联合查询
        Table result = tableEnv.sqlQuery("SELECT t1.name, t1.age, t1.Gender, 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");

        //将查询结果转换为Stream，并打印输出
        tableEnv.toAppendStream(result, Row.class).print();

        env.execute();
    }
}
父主题： Stream SQL Join程序

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