Flink示例——Sink

其他 2020-03-04 10:51:24 阅读次数: 0

文章目录

Flink示例——Sink

版本信息

产品 版本
Flink 1.7.2
Java 1.8.0_231
Scala 2.11.12

Mavan依赖

  • pom.xml 依赖部分
    <dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-java</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-java_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-clients_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>

自定义SourceFunction

  • 提供一个SourceFunction，方便后面测试
    public class CustomSourceFunction extends RichSourceFunction<Tuple2<String, Long>> {

    private boolean flag = true;

    @Override
    public void run(SourceContext<Tuple2<String, Long>> ctx) throws Exception {
        List<String> data = Arrays.asList("a", "b", "c", "d", "e", "f", "g");
        Random random = new Random();
        while (flag) {
            Thread.sleep(100);
            // 随机取一个值
            String key = data.get(random.nextInt(data.size()));
            long value = System.currentTimeMillis();
            ctx.collect(Tuple2.of(key, value));
        }
    }

    @Override
    public void cancel() {
        flag = false;
    }

}

Print Sink 示例

  • 代码 PrintSinkDemo
    public class PrintSinkDemo {

    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        
        // 自定义SourceFunction
        CustomSourceFunction sourceFunction = new CustomSourceFunction();
        DataStreamSource<Tuple2<String, Long>> customDS = env.addSource(sourceFunction);
        
//        dataDS.print("stream");

        // 查看源码可知，print内调用了 PrintSinkFunction
        PrintSinkFunction<Tuple2<String, Long>> sinkFunction = new PrintSinkFunction<>("stream", false);
        customDS.addSink(sinkFunction);

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

}

Kafka Sink 示例

  • Maven导包 pom.xml
    <dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-kafka-0.11_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>
  • 代码 KafkaSinkDemo
    public class KafkaSinkDemo {

    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 自定义SourceFunction
        CustomSourceFunction sourceFunction = new CustomSourceFunction();
        // 添加数据源
        DataStreamSource<Tuple2<String, Long>> customDS = env.addSource(sourceFunction);
        // 处理，转为String
        DataStream<String> resultDS = customDS.map(new MapFunction<Tuple2<String, Long>, String>() {
            @Override
            public String map(Tuple2<String, Long> value) throws Exception {
                return value.f0 + "|" + value.f1;
            }
        });

        // 创建FlinkKafkaProduce
        FlinkKafkaProducer011<String> kafkaProducer011 = generateKafkaProducer();

        // 发入Kafka
        resultDS.addSink(kafkaProducer011);

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /**
     * 生成 FlinkKafkaProducer
     */
    private static FlinkKafkaProducer011<String> generateKafkaProducer() {
        // 创建FlinkKafkaProducer
        FlinkKafkaProducer011<String> kafkaProducer011 = new FlinkKafkaProducer011<>(
                "192.168.0.101:9092", "topic_01", new SimpleStringSchema()
        );
        // 自定义序列化 - 示例
        /*
        new KeyedSerializationSchema<String>() {
            @Override
            public byte[] serializeKey(String element) {
                // 可以直接为null，也可以为String编码
                return null;
            }

            @Override
            public byte[] serializeValue(String element) {
                // 编码String为byte[]
                return element.getBytes(StandardCharsets.UTF_8);
            }

            @Override
            public String getTargetTopic(String element) {
                // 由源码可知，此处优先级最高，FlinkKafkaProducer011中传的topicid是默认值
                // 可以在此决定不同的数据发往到不同的topic
                return null;
            }
        };
        */

        return kafkaProducer011;
    }

}
  • 两阶段提交，保证exactly-once
    // 关于事务超时问题
// Kafka默认事务最大超时15min，transaction.max.timeout.ms = 900000
// Flink默认事务超时1h， transaction.timeout.ms = 3600000
// 如果时间间隔过长，会导致Kafka已关闭事务，Flink却以为未关闭
// 因此可以将Flink设置小于等于Kafka事务超时时间
Properties props = new Properties();
props.setProperty("bootstrap.servers", "192.168.0.101:9092");
props.setProperty("transaction.timeout.ms", "900000");
FlinkKafkaProducer011<String> kafkaProducer011 = new FlinkKafkaProducer011<>(
        "topic_01",
        new SimpleStringSchema(),
        props,
        // 两阶段提交，保证exactly-once，默认AT_LEAST_ONCE
        FlinkKafkaProducer011.Semantic.EXACTLY_ONCE 
);

ElasticSearch Sink 示例

  • Maven导包 pom.xml
    <dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-elasticsearch6_2.11</artifactId>
    <version>${flink.version}</version>
</dependency>
  • 代码 ESSinkDemo
    public class ESSinkDemo {

    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 自定义SourceFunction
        CustomSourceFunction sourceFunction = new CustomSourceFunction();
        // 添加数据源
        DataStreamSource<Tuple2<String, Long>> customDS = env.addSource(sourceFunction);
        
        // 创建ElasticsearchSink
        ElasticsearchSink<Tuple2<String, Long>> esSink = generateESSink();

        // 发入Elasticsearch
        customDS.addSink(esSink);

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /**
     * 生成ElasticsearchSink
     */
    private static ElasticsearchSink<Tuple2<String, Long>> generateESSink() {
        // 配置HttpHost
        List<HttpHost> httpHosts = Collections.singletonList(
                new HttpHost("192.168.0.120", 9200)
        );
        ElasticsearchSinkFunction<Tuple2<String, Long>> sinkFunction = new ElasticsearchSinkFunction<Tuple2<String, Long>>() {
            @Override
            public void process(Tuple2<String, Long> tuple2, RuntimeContext runtimeContext, RequestIndexer requestIndexer) {
                // 封装数据
                HashMap<String, String> map = new HashMap<>();
                map.put("content", tuple2.f0);
                map.put("eventTime", tuple2.f1.toString());
                map.put("processTime", String.valueOf(System.currentTimeMillis()));
                // 封装Request
                IndexRequest request = Requests.indexRequest()
                        .index("my_index")
                        .type("my_data")
                        .source(map);
                
                // 发送request
                requestIndexer.add(request);
            }
        };

        ElasticsearchSink<Tuple2<String, Long>> esSink = new ElasticsearchSink.Builder<>(
                httpHosts, sinkFunction
        ).build();

        return esSink;
    }

}

Redis Sink 示例

  • Maven导包 pom.xml
    <dependency>
    <groupId>org.apache.bahir</groupId>
    <artifactId>flink-connector-redis_2.11</artifactId>
    <version>1.0</version>
</dependency>
  • 代码 RedisSinkDemo
    public class RedisSinkDemo {

    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 自定义SourceFunction
        CustomSourceFunction sourceFunction = new CustomSourceFunction();
        // 添加数据源
        DataStreamSource<Tuple2<String, Long>> customDS = env.addSource(sourceFunction);

        // 创建RedisSink
        RedisSink<Tuple2<String, Long>> redisSink = generateRedisSink();

        // 发入Redis
        customDS.addSink(redisSink);

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /**
     * 生成RedisSink
     */
    private static RedisSink<Tuple2<String, Long>> generateRedisSink() {
        // Redis配置
        FlinkJedisPoolConfig config = new FlinkJedisPoolConfig.Builder()
                .setMaxTotal(8) // 最大实例总数
                .setMaxIdle(4) // 实例最多空闲数
                .setMinIdle(2)
                .setHost("192.168.0.110")
                .setPort(6379)
                .build();
        // Mapper
        RedisMapper<Tuple2<String, Long>> redisMapper = new RedisMapper<Tuple2<String, Long>>() {
            @Override
            public RedisCommandDescription getCommandDescription() {
                // 定义保存数据到Redis的命令
                return new RedisCommandDescription(
                        RedisCommand.HSET, // 使用hset命令
                        "my_hash" // 表名
                );
            }

            @Override
            public String getKeyFromData(Tuple2<String, Long> tuple2) {
                return tuple2.f0;
            }

            @Override
            public String getValueFromData(Tuple2<String, Long> tuple2) {
                return tuple2.f1.toString();
            }
        };

        return new RedisSink<>(config, redisMapper);
    }

}

自定义 Sink 示例 （JDBC）

  • Maven导包 pom.xml
    <dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.38</version>
</dependency>
  • 代码 JDBCUtils
    public class JDBCUtils {

    static {
        try {
            Class.forName("com.mysql.jdbc.Driver");
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        }
    }

    public static Connection getConnection() {
        String url = "jdbc:mysql://192.168.0.130:3306/test_db";
        String user = "user_name";
        String password = "123456";

        Connection conn = null;
        try {
            conn = DriverManager.getConnection(url, user, password);
        } catch (SQLException e) {
            e.printStackTrace();
        }

        if (conn == null) {
            throw new RuntimeException("JDBC创建连接失败！");
        }

        return conn;
    }

}
  • 代码 JDBCSinkFunction
    public class JDBCSinkFunction extends RichSinkFunction<Tuple2<String, Long>> {

    private Connection conn = null;
    private PreparedStatement pst;

    @Override
    public void open(Configuration parameters) throws Exception {
        conn = JDBCUtils.getConnection();
        pst = conn.prepareStatement(
                "INSERT INTO tb_name (content, event_time, update_time) VALUES (?, ?, ?)"
        );
    }

    @Override
    public void close() throws Exception {
        conn.close();
    }

    @Override
    public void invoke(Tuple2<String, Long> value, Context context) throws Exception {
        // 执行插入
        pst.setString(1, value.f0);
        pst.setLong(2, value.f1);
        pst.setLong(3, System.currentTimeMillis());
        pst.execute();
    }

    // 批量插入-示例
    /*
    private int count = 0;

    @Override
    public void invoke(Tuple2<String, Long> value, Context context) throws Exception {
        // 执行插入
        pst.setString(1, value.f0);
        pst.setLong(2, value.f1);
        pst.setLong(3, System.currentTimeMillis());
        pst.addBatch();

        count++;

        // 每1000条记录插入一次
        if (count == 1000){
            pst.executeBatch();
            conn.commit(); // 进行手动提交
            pst.clearBatch();
            count = 0;
        }
        // 记得在open处关闭自动提交[conn.setAutoCommit(false);]
    }
    */

}
  • 代码 CustomSinkDemo
    public class CustomSinkDemo {

    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 自定义SourceFunction
        CustomSourceFunction sourceFunction = new CustomSourceFunction();
        // 添加数据源
        DataStreamSource<Tuple2<String, Long>> dataDS = env.addSource(sourceFunction);

        // 创建JDBCSinkFunction
        JDBCSinkFunction jdbcSink = new JDBCSinkFunction();

        // 自定义发入MySQL
        dataDS.addSink(jdbcSink);

        try {
            env.execute();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

}
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