вывод flink в базу данных

Храните данные в kafka в clickhouse через flink.

Шаги тестирования Clickhouse для записи данных следующие.

(1) Добавить зависимости

Не забудьте добавить основные зависимости flink

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_2.11</artifactId>
            <version>1.12.7</version>
        </dependency>

        <dependency>
            <groupId>ru.yandex.clickhouse</groupId>
            <artifactId>clickhouse-jdbc</artifactId>
            <version>0.3.2</version>
        </dependency>

(2) Запустите clickhouse и создайте таблицу source_log в библиотеке test1.

CREATE TABLE test1.source_log
(

    `id` String,

    `src_ip` String,

    `src_port` Int32,

    `dst_ip` String,

    `dst_port` Int32,

    `protocol` String,

    `type` String,

    `device_num` String,

    `create_date` DateTime
)
ENGINE = MergeTree
ORDER BY id

(3) Напишите пример вывода кода в Clickhouse

import com.clickhouse.jdbc.ClickHouseDriver;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.flink.WuYuan;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.connector.jdbc.JdbcConnectionOptions;
import org.apache.flink.connector.jdbc.JdbcSink;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.types.Row;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;

import java.util.Properties;
import java.util.UUID;

public class FlinkReadKafka {

    public static void main(String[] args) throws Exception {
        ObjectMapper objectMapper = new ObjectMapper();

        StreamExecutionEnvironment executionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment();

        //1. source 数据源
        //参数1: topic  参数2: 相当于之前的stringserilize  参数3: kafka的基本配置
        Properties properties = new Properties();
        properties.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "81.70.199.213:9092");
        properties.setProperty(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        properties.setProperty(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());

        DataStreamSource<String> sourceStream = executionEnvironment.addSource(new FlinkKafkaConsumer<>("wangluo", new SimpleStringSchema(), properties));

        //简单的打印每条来自kafka的数据
        //sourceStream.print();

        //2. transform 数据处理  将json字符串转成java对象
        SingleOutputStreamOperator<Row> singleOutputStreamOperator = sourceStream.map(jsonStr -> {
            WuYuan wuYuan = objectMapper.readValue(jsonStr, WuYuan.class);

            Row row = new Row(6);
            row.setField(0, UUID.randomUUID().toString());
            row.setField(1, wuYuan.getSrcIp());
            row.setField(2, wuYuan.getSrcPort());
            row.setField(3, wuYuan.getDstIp());
            row.setField(4, wuYuan.getDstPort());
            row.setField(5, wuYuan.getProtocol());

            return row;
        });

        singleOutputStreamOperator.addSink(JdbcSink.sink(
                "insert into source_log values(?,?,?,?,?,?)",
                (preparedStatement, row) -> {
                    preparedStatement.setObject(1, row.getField(0));
                    preparedStatement.setObject(2, row.getField(1));
                    preparedStatement.setObject(3, row.getField(2));
                    preparedStatement.setObject(4, row.getField(3));
                    preparedStatement.setObject(5, row.getField(4));
                    preparedStatement.setObject(6, row.getField(5));
                },
                new JdbcConnectionOptions.JdbcConnectionOptionsBuilder()
                        .withDriverName(ClickHouseDriver.class.getName())
                        .withUrl("jdbc:clickhouse://81.70.199.213:8123/test1?socket_timeout=600000")
                        .withUsername("root")
                        .withPassword("hexin")
                        .build()
        ));


        //启动flink
        executionEnvironment.execute();
    }
}