Flink常用Sink(elasticsearch(es)Sink、RedisSink、KafkaSink、MysqlSink、FileSink）

深藏阁楼爱情的钟 2024-04-22 06:54 58阅读 0赞

**flink输出到es、redis、mysql、kafka、file**

#### 文章目录 ####

*   *  配置pom文件
     *  公共实体类
     *  KafkaSInk
     *  ElasticsearchSink(EsSink)
     *  RedisSink
     *  MysqlSink(JdbcSink)
     *  FileSink

自己先准备一下相关环境

### 配置pom文件 ###

<properties>
            <maven.compiler.source>8</maven.compiler.source>
            <maven.compiler.target>8</maven.compiler.target>
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
            <flink.version>1.13.0</flink.version>
            <java.version>1.8</java.version>
            <scala.binary.version>2.12</scala.binary.version>
            <slf4j.version>1.7.30</slf4j.version>
        </properties>
        <dependencies>
            
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-java</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-clients_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
            </dependency>
            
            <dependency>
                <groupId>org.slf4j</groupId>
                <artifactId>slf4j-api</artifactId>
                <version>${slf4j.version}</version>
            </dependency>
            <dependency>
                <groupId>org.slf4j</groupId>
                <artifactId>slf4j-log4j12</artifactId>
                <version>${slf4j.version}</version>
            </dependency>
            <dependency>
                <groupId>org.apache.logging.log4j</groupId>
                <artifactId>log4j-to-slf4j</artifactId>
                <version>2.14.0</version>
            </dependency>
    
            
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-connector-kafka_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
            </dependency>
            <dependency>
                <groupId>org.projectlombok</groupId>
                <artifactId>lombok</artifactId>
                <version>1.18.22</version>
                <scope>compile</scope>
            </dependency>
    
            <dependency>
                <groupId>com.alibaba</groupId>
                <artifactId>fastjson</artifactId>
                <version>1.2.58</version>
            </dependency>
    
        
        <dependency>
            <groupId>org.apache.bahir</groupId>
            <artifactId>flink-connector-redis_2.11</artifactId>
            <version>1.0</version>
        </dependency>
    
        
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-elasticsearch7_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
    
         
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.47</version>
        </dependency>
        </dependencies>
        <build>
            <plugins>
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-assembly-plugin</artifactId>
                    <version>3.0.0</version>
                    <configuration>
                        <descriptorRefs>
                            <descriptorRef>jar-with-dependencies</descriptorRef>
                        </descriptorRefs>
                    </configuration>
                    <executions>
                        <execution>
                            <id>make-assembly</id>
                            <phase>package</phase>
                            <goals>
                                <goal>single</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>3.2.2</version>
                    <executions>
                        <execution>
                            <id>scala-compile-first</id>
                            <phase>process-resources</phase>
                            <goals>
                                <goal>add-source</goal>
                                <goal>compile</goal>
                            </goals>
                        </execution>
                        <execution>
                            <id>scala-test-compile</id>
                            <phase>process-test-resources</phase>
                            <goals>
                                <goal>testCompile</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-compiler-plugin</artifactId>
                    <configuration>
                        <source>1.8</source>
                        <target>1.8</target>
                    </configuration>
                </plugin>
            </plugins>
        </build>

### 公共实体类 ###

import lombok.AllArgsConstructor;
    import lombok.Data;
    import lombok.NoArgsConstructor;
    import lombok.ToString;
    
    @Data
    @NoArgsConstructor
    @ToString
    @AllArgsConstructor
    public class UserEvent {
        private String userName;
        private String url;
        private Long timestemp;
    }

### KafkaSInk ###

将数据输出到kafka中,先启动kafka consumer，再运行程序

import com.event.UserEvent;
    import org.apache.flink.api.common.functions.MapFunction;
    import org.apache.flink.api.common.serialization.SimpleStringSchema;
    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.streaming.connectors.kafka.FlinkKafkaProducer;
    
    import java.lang.reflect.Array;
    import java.util.Arrays;
    import java.util.Properties;
    
    public class KafkaSinkTest {
        
        public static void main(String[] args) throws Exception {
        
            StreamExecutionEnvironment env =
                    StreamExecutionEnvironment.getExecutionEnvironment();
            env.setParallelism(1);
            Properties properties = new Properties();
            //kafka相关配置
            properties.setProperty("bootstrap.servers", "hadoop01:9092");
            properties.setProperty("group.id", "consumer-group");
            properties.setProperty("key.deserializer",
                    "org.apache.kafka.common.serialization.StringDeserializer");
            properties.setProperty("value.deserializer",
                    "org.apache.kafka.common.serialization.StringDeserializer");
            properties.setProperty("auto.offset.reset", "latest");
    
            DataStreamSource<String> stream = env.fromCollection(Arrays.asList(
                    "xiaoming,www.baidu.com,1287538716253",
                    "Mr Li,www.baidu.com,1287538710000",
                    "Mr Zhang,www.baidu.com,1287538710900"
            ));
    
            SingleOutputStreamOperator<String> result = stream.map(new MapFunction<String, String>() {
        
                @Override
                public String map(String value) throws Exception {
        
                	//输出规则
                    String[] split = value.split(",");
                    return new UserEvent(split[0].trim(), split[1].trim(), Long.valueOf(split[2].trim())).toString();
                }
            });
    		//启动kafkaconsumer指令
    		// ./bin/kafka-console-consumer.sh  --bootstrap-server  localhost:9092 --topic events
            result.addSink(new FlinkKafkaProducer<String>(
            		//kafka所在地址
                    "hadoop01:9092",
                    //指定输出的topic
                    "events",
                    new SimpleStringSchema()
            ));
    
            env.execute();
    
        }
    }

运行结果

![在这里插入图片描述][349ab846b3a94a559acc5cfb313a6476.png]

### ElasticsearchSink(EsSink) ###

将数据输出到elasticsearch中

**示例代码**

import com.event.UserEvent;
    import org.apache.flink.api.common.functions.RuntimeContext;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSinkFunction;
    import org.apache.flink.streaming.connectors.elasticsearch.RequestIndexer;
    import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink;
    import org.apache.flink.table.descriptors.Elasticsearch;
    import org.apache.http.HttpHost;
    import org.elasticsearch.action.index.IndexRequest;
    import org.elasticsearch.client.Requests;
    
    import java.util.Arrays;
    import java.util.HashMap;
    import java.util.List;
    
    public class EsSinkTest {
    
        public static void main(String[] args) throws Exception {
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
            DataStreamSource<UserEvent> userEventDataStreamSource =
                    env.fromCollection(
                            Arrays.asList(
                                    new UserEvent("zhangsan", "path?test123", System.currentTimeMillis() - 2000L),
                                    new UserEvent("zhangsan", "path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("lisi", "path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("bob", "path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("mary", "path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("lisi", "path?checkParam123", System.currentTimeMillis() - 2000L)
                            ));
    
    
            //定义host列表
            List<HttpHost> hosts = Arrays.asList(new HttpHost("hadoop01", 9200));
    
            //定义ElasticsearchSinkFunction
            ElasticsearchSinkFunction<UserEvent> elasticsearchSinkFunction = new ElasticsearchSinkFunction<UserEvent>() {
                @Override
                public void process(UserEvent userEvent, RuntimeContext runtimeContext, RequestIndexer requestIndexer) {
                    IndexRequest indexRequest = Requests.indexRequest()
                            .index("events")
                            .type("type")
                            .source(new HashMap<String, String>() {
       {
                                put(userEvent.getUserName(), userEvent.getUrl());
                            }});
                    requestIndexer.add(indexRequest);
                }
            };
    
            //写入es
            userEventDataStreamSource.addSink(new ElasticsearchSink.Builder<>(hosts, elasticsearchSinkFunction).build());
    
            env.execute();
        }
    }

指令

GET _cat/indices
    
    GET _cat/indices/events
    
    GET events/_search

**运行结果**  
![在这里插入图片描述][8e93ac66b7d743f58ad9af924c083401.png]

### RedisSink ###

将数据输出到Redis

**示例代码**

import com.event.UserEvent;
    import my.test.source.CustomSouce;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.streaming.connectors.redis.RedisSink;
    import org.apache.flink.streaming.connectors.redis.common.config.FlinkJedisClusterConfig;
    import org.apache.flink.streaming.connectors.redis.common.config.FlinkJedisConfigBase;
    import org.apache.flink.streaming.connectors.redis.common.config.FlinkJedisPoolConfig;
    import org.apache.flink.streaming.connectors.redis.common.mapper.RedisCommand;
    import org.apache.flink.streaming.connectors.redis.common.mapper.RedisCommandDescription;
    import org.apache.flink.streaming.connectors.redis.common.mapper.RedisMapper;
    
    public class RedisSinkTest {
        
        public static void main(String[] args) throws Exception {
        
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
            env.setParallelism(1);
    
            DataStreamSource<UserEvent> streamSource = env.addSource(new CustomSouce());
    
            //创建jedis连接配置
            FlinkJedisPoolConfig config = new FlinkJedisPoolConfig.Builder()
                    .setHost("master")
                    .setTimeout(10000)
                    .setPort(6379)
                    .build();
            
    
            //写到redis
            streamSource.addSink(new RedisSink<>(config, new MyRedisMapper()));
    
    
            env.execute();
        }
    
        public static class MyRedisMapper implements RedisMapper<UserEvent>{
        
            @Override
            public RedisCommandDescription getCommandDescription() {
        
                //写入方式为hset
                return new RedisCommandDescription(RedisCommand.HSET, "events"); //additionalKey参数标识存储再哪里
            }
    
            @Override
            public String getKeyFromData(UserEvent userEvent) {
        
                return userEvent.getUserName();
            }
    
            @Override
            public String getValueFromData(UserEvent userEvent) {
        
                return userEvent.getUrl();
            }
        }
    
    
    
    }

自定义source

import com.event.UserEvent;
    import org.apache.flink.streaming.api.functions.source.SourceFunction;
    
    import java.util.Calendar;
    import java.util.Random;
    
    public class CustomSouce implements SourceFunction<UserEvent> {
        // 声明一个布尔变量，作为控制数据生成的标识位
        private Boolean running = true;
    
        @Override
        public void run(SourceContext<UserEvent> ctx) throws Exception {
            Random random = new Random(); // 在指定的数据集中随机选取数据
            String[] users = {"Mary", "Alice", "Bob", "Cary"};
            String[] urls = {"./home", "./cart", "./fav", "./prod?id=1",
                    "./prod?id=2"};
            while (running) {
                ctx.collect(new UserEvent(
                        users[random.nextInt(users.length)],
                        urls[random.nextInt(urls.length)],
                        Calendar .getInstance().getTimeInMillis()
                ));
                // 隔 1 秒生成一个点击事件，方便观测
                Thread.sleep(1000);
            }
        }
        @Override
        public void cancel() {
            running = false;
        }
    }

**运行结果**  
因为上述source是一个无界流，所以数据一直会变化  
![在这里插入图片描述][0e488e15025141c0a14ed7fbfb4909bd.png]

### MysqlSink(JdbcSink) ###

将数据输出到mysql

**表结构**

create table events(
        user_name varchar(20) not null,
        url varchar(100) not null
    );

示例代码

import com.event.UserEvent;
    import org.apache.flink.api.common.functions.RuntimeContext;
    import org.apache.flink.connector.jdbc.JdbcConnectionOptions;
    import org.apache.flink.connector.jdbc.JdbcSink;
    import org.apache.flink.connector.jdbc.JdbcStatementBuilder;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSinkFunction;
    import org.apache.flink.streaming.connectors.elasticsearch.RequestIndexer;
    import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink;
    import org.apache.http.HttpHost;
    import org.elasticsearch.action.index.IndexRequest;
    import org.elasticsearch.client.Requests;
    
    import java.sql.PreparedStatement;
    import java.sql.SQLException;
    import java.util.Arrays;
    import java.util.HashMap;
    import java.util.List;
    
    public class MysqlSinkTest {
        
    
        public static void main(String[] args) throws Exception {
        
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
            //一组数据
            DataStreamSource<UserEvent> userEventDataStreamSource =
                    env.fromCollection(
                            Arrays.asList(
                                    new UserEvent("zhangsan", "/path?test123", System.currentTimeMillis() - 2000L),
                                    new UserEvent("zhangsan", "/path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("lisi", "/path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("bob", "/path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("mary", "/path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("lisi", "/path?checkParam123", System.currentTimeMillis() - 2000L)
                            ));
    
    
           userEventDataStreamSource.addSink(JdbcSink.sink(
           			//要执行的sql语句
                   "INSERT INTO events (user_name, url) VALUES(?, ?)",
                   new JdbcStatementBuilder<UserEvent>() {
        
                       @Override
                       public void accept(PreparedStatement preparedStatement, UserEvent userEvent) throws SQLException {
        
                       		//sql占位符赋值
                            preparedStatement.setString(1, userEvent.getUserName());
                            preparedStatement.setString(2, userEvent.getUrl());
                       }
                   },
                   //jdbc相关参数配置
                   new JdbcConnectionOptions.JdbcConnectionOptionsBuilder()
                           .withUrl("jdbc:mysql://hadoop01:3306/mysql")
                           .withUsername("root")
                           .withPassword("123456")
                           .withDriverName("com.mysql.jdbc.Driver")
                           .build()
           ));
    
            env.execute();
        }
    }

当程序运行结束之后可以看到mysql的events表里面多了数据  
![在这里插入图片描述][4e7b0df55cd34fbaa5f63f77d941498b.png]

### FileSink ###

将数据输出到文件中(可以输出分区文件)

import com.event.UserEvent;
    import org.apache.flink.api.common.serialization.SimpleStringEncoder;
    import org.apache.flink.core.fs.Path;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink;
    import org.apache.flink.streaming.api.functions.sink.filesystem.rollingpolicies.DefaultRollingPolicy;
    import org.apache.flink.util.TimeUtils;
    
    import java.util.Arrays;
    import java.util.concurrent.TimeUnit;
    
    public class FileSinkTest {
        
    
        public static void main(String[] args) throws Exception {
        
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
            DataStreamSource<UserEvent> userEventDataStreamSource =
                    env.fromCollection(
                            Arrays.asList(
                                    new UserEvent("zhangsan", "path?test123", System.currentTimeMillis() - 2000L),
                                    new UserEvent("zhangsan", "path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("lisi", "path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("bob", "path?test", System.currentTimeMillis() + 2000L),
                                    new UserEvent("mary", "path?checkParam", System.currentTimeMillis()),
                                    new UserEvent("lisi", "path?checkParam123", System.currentTimeMillis() - 2000L)
                            ));
    
    
            StreamingFileSink<String> streamingFileSink = StreamingFileSink.
                    <String>forRowFormat(new Path("./output/"), new SimpleStringEncoder<>("UTF-8"))
                    .withRollingPolicy(
                            DefaultRollingPolicy.builder()
                                    .withMaxPartSize(1024 * 1024 * 1024)
                                    .withRolloverInterval(TimeUnit.MINUTES.toMillis(15))
                                    //不活跃的间隔时间，用于归档保存使用
                                    .withInactivityInterval(TimeUnit.MINUTES.toMillis(5))
                                    .build()
                    ).build();
    
            userEventDataStreamSource.map(data -> data.getUserName()).addSink(streamingFileSink);
    
    
            env.execute();
    
        }
    }

运行结束后会多出来一些文件  
![在这里插入图片描述][e029cf1d1b344c40a7c84f3297b353d3.png]

[349ab846b3a94a559acc5cfb313a6476.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/22/ce77bebb1fb049eea051946fde8eb652.png
[8e93ac66b7d743f58ad9af924c083401.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/22/f1aac8ce6191477d8b94e1b2a5bc393d.png
[0e488e15025141c0a14ed7fbfb4909bd.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/22/968e6ce9419f4741a4deac8b8f210d0e.png
[4e7b0df55cd34fbaa5f63f77d941498b.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/22/9b644dd5c5ad4fb5bcb692a50054bbcc.png
[e029cf1d1b344c40a7c84f3297b353d3.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/22/948ed60cfa7049ef8439b98a0df7fe93.png