flink 使用sql实现kafka生产者和消费者

大家好，我是考100分的小小码，祝大家学习进步，加薪顺利呀。今天说一说flink 使用sql实现kafka生产者和消费者,希望您对编程的造诣更进一步.

1.maven依赖

<properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <flink.version>1.11.2</flink.version>
        <logback.version>1.1.7</logback.version>
        <slf4j.version>1.7.25</slf4j.version>
    </properties>

    <dependencies>
        <dependency>
            <!-- Used by maven-dependency-plugin -->
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-json</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-wikiedits_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-blink_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>${slf4j.version}</version>
        </dependency>
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-core</artifactId>
            <version>${logback.version}</version>
        </dependency>
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-classic</artifactId>
            <version>${logback.version}</version>
        </dependency>

        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <version>1.16.18</version>
        </dependency>
    </dependencies>

2.生产者

import com.g2.flink.models.CustomerStatusChangedEvent;

import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.tuple.Tuple;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

import java.util.concurrent.CompletableFuture;
import java.util.concurrent.TimeUnit;

import static org.apache.flink.table.api.Expressions.$;

/**
 * Hello world!
 */
//@Slf4j
public class KafkaTableStreamApiProducerTest {

    public static void main(String[] args) {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        EnvironmentSettings settings = EnvironmentSettings.newInstance()
                .inStreamingMode()
                //.useOldPlanner() // flink
                .useBlinkPlanner() // blink
                .build();
        StreamTableEnvironment tableEnvironment = StreamTableEnvironment.create(env, settings);

        Long baseTimestamp = 1600855709000L;
        DataStream<CustomerStatusChangedEvent> eventDataSet = env.fromElements(
                new CustomerStatusChangedEvent(1010L, 2, baseTimestamp),
                new CustomerStatusChangedEvent(1011L, 2, baseTimestamp + 100),
                new CustomerStatusChangedEvent(1011L, 1, baseTimestamp - 100),
                new CustomerStatusChangedEvent(1010L, 3, baseTimestamp + 150)
        );

        String ddl = "CREATE TABLE CustomerStatusChangedEvent(
" +
                "customerId int,
" +
                "oldStatus int,
" +
                "newStatus int,
" +
                "eventTime bigint
" +
                ") WITH(
" +
                "‘connector.type‘=‘kafka‘,
" +
                "‘connector.version‘=‘universal‘,
" +

                "‘connector.properties.bootstrap.servers‘=‘192.168.1.85:9092,192.168.1.86:9092,192.168.12.87:9092‘,
" +
                "‘connector.topic‘=‘customer_statusChangedEvent‘,
" +
               
                "‘format.type‘=‘json‘
" +
                ")
"
                ;
        tableEnvironment.executeSql(ddl);


        while (true) {
            try {
                TimeUnit.SECONDS.sleep(3);
                int status = (int) (System.currentTimeMillis() % 3);
                String insert = "insert into CustomerStatusChangedEvent(customerId,oldStatus,newStatus,eventTime)" +
                        "values(1001,1," + status + "," + System.currentTimeMillis() + ")";
                tableEnvironment.executeSql(insert);
            } catch (Exception ex) {

            }
        }

    }
}

3.消费者

import com.g2.flink.models.CustomerStatusChangedEvent;

import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * Hello world!
 */
//@Slf4j
public class KafkaTableStreamApiConsumerTest {

    public static void main(String[] args) {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        EnvironmentSettings settings = EnvironmentSettings.newInstance()
                .inStreamingMode()
                //.useOldPlanner() // flink
                .useBlinkPlanner() // blink
                .build();
        StreamTableEnvironment tableEnvironment = StreamTableEnvironment.create(env, settings);

        Long baseTimestamp = 1600855709000L;
        DataStream<CustomerStatusChangedEvent> eventDataSet = env.fromElements(
                new CustomerStatusChangedEvent(1010L, 2, baseTimestamp),
                new CustomerStatusChangedEvent(1011L, 2, baseTimestamp + 100),
                new CustomerStatusChangedEvent(1011L, 1, baseTimestamp - 100),
                new CustomerStatusChangedEvent(1010L, 3, baseTimestamp + 150)
        );

        String ddl = "CREATE TABLE CustomerStatusChangedEvent(
" +
                "customerId int,
" +
                "oldStatus int,
" +
                "newStatus int,
" +
                "eventTime bigint
" +
                ") WITH(
" +
                "‘connector.type‘=‘kafka‘,
" +
                "‘connector.version‘=‘universal‘,
" +
                "‘connector.properties.group.id‘=‘g2_group‘,
" +
                "‘connector.properties.bootstrap.servers‘=‘192.168.1.85:9092,192.168.1.86:9092,192.168.1.87:9092‘,
" +
                "‘connector.topic‘=‘customer_statusChangedEvent‘,
" +
                "‘connector.startup-mode‘ = ‘latest-offset‘,
" +
                "‘format.type‘=‘json‘
" +
                ")
";
        tableEnvironment.executeSql(ddl);

        Table resultTb = tableEnvironment.sqlQuery("select customerId,newStatus as status " +
                " from CustomerStatusChangedEvent" +
                " where newStatus in(1,2)"
        );


    /*
    DataStream<Tuple2<Boolean, Tuple2<Integer, Integer>>> result = tableEnvironment.toRetractStream(resultTb,
                Types.TUPLE(Types.INT, Types.INT));

  */
        DataStream<CustomerStatusLog> result = tableEnvironment.toAppendStream(resultTb, CustomerStatusLog.class);
        result.print();

        try {
            env.execute();
        } catch (Exception ex) {

        }
    }

    public static class CustomerStatusLog {
        private Long customerId;

        private Integer status;

        public Long getCustomerId() {
            return customerId;
        }

        public void setCustomerId(Long customerId) {
            this.customerId = customerId;
        }

        public Integer getStatus() {
            return status;
        }

        public void setStatus(Integer newStatus) {
            this.status = newStatus;
        }

        public CustomerStatusLog() {

        }

        @Override
        public String toString() {
            return "CustomerStatusLog{" +
                    "customerId=" + customerId +
                    ", status=" + status +
                    ‘}‘;
        }
    }
}

4.消费者打印

4> CustomerStatusLog{customerId=1001, status=2}
4> CustomerStatusLog{customerId=1001, status=1}
4> CustomerStatusLog{customerId=1001, status=2}
4> CustomerStatusLog{customerId=1001, status=2}

flink 使用sql实现kafka生产者和消费者

原文地址：https://www.cnblogs.com/zhshlimi/p/13725081.html

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flink 使用sql实现kafka生产者和消费者

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