Flink写入kafka的自定义Key值

第一步：序列化

package com.mz.iot.functions;
 
 
import com.mz.iot.bean.AlarmHistoryOrigin;
import com.mz.iot.utils.JsonUtil;
import org.apache.flink.streaming.util.serialization.KeyedSerializationSchema;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
 * liuyage
 */
public class UserDefinedSerializationSchema implements KeyedSerializationSchema {
    private final static Logger logger = LoggerFactory.getLogger(UserDefinedSerializationSchema.class);
    String topicName;     //取模确定的Topic名称
    public UserDefinedSerializationSchema(String topicName){
        this.topicName = topicName;
    }
 
 
    @Override
    public byte[] serializeKey(String element) {
        //element就是flink流中的真实数据，这里可以根据主键下标得到主键的值key，然后下面分区器就根据这个key去决定发送到kafka哪个分区中
        AlarmHistoryOrigin aho = JsonUtil.getObjFromJson(element, AlarmHistoryOrigin.class);
        StringBuffer sb=new StringBuffer();
        sb.append(aho.getProjectId()).append(":");
        sb.append(aho.getMeterCode()).append(":");
        sb.append(aho.getAlarmType()).append(":");
        sb.append(aho.getId()).append(":");
        sb.append(aho.getAlarmRuleId());
        String key = sb.toString();
        //取出key后要转成字节数组返回
        return key.getBytes();
    }
 
    @Override
    public byte[] serializeValue(String element) {
        //要序列化的value，这里一般就原封不动的转成字节数组就行了
        return element.toString().getBytes();
    }
 
    @Override
    public String getTargetTopic(String element) {
        //本次需求没啥用，可以用于根据字段分发不同topic的需求
        return topicName;
    }
}

第二步：自定义分区

package com.mz.iot.functions;
 
import org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
 
import java.util.Arrays;
/**
 * liuyage
 */
public class UserDefinedPartitioner extends FlinkKafkaPartitioner {
    private final static Logger logger = LoggerFactory.getLogger(UserDefinedPartitioner.class);
 
    /**
     *
     * @param record  正常记录Value                           {"id":"15959499868079104","alarmRuleId":"6789709006840532992","beginTime":"2022-09-01 04:42:29","endTime":"2022-09-01 04:42:40","ruleValue":0.60000,"firstValue":0.62000,"alarmType":1,"meterCode":"R19013-0003-0001-440300OII-10248","projectId":"440300OII","acquisitionTime":"2022-09-01 04:42:49","alarmValue":0.62000,"createUser":0,"createTime":"2022-09-01 04:42:49","updateUser":0,"updateTime":"2022-09-01 04:42:49","reasonTag":0,"makeUp":0}
     * @param key     KeyedSerializationSchema中配置的key     440300OII:R19013-0003-0001-440300OII-10248:1:15959499868079104:6789709006840532992
     * @param value   KeyedSerializationSchema中配置的value   {"id":"15959499868079104","alarmRuleId":"6789709006840532992","beginTime":"2022-09-01 04:42:29","endTime":"2022-09-01 04:42:40","ruleValue":0.60000,"firstValue":0.62000,"alarmType":1,"meterCode":"R19013-0003-0001-440300OII-10248","projectId":"440300OII","acquisitionTime":"2022-09-01 04:42:49","alarmValue":0.62000,"createUser":0,"createTime":"2022-09-01 04:42:49","updateUser":0,"updateTime":"2022-09-01 04:42:49","reasonTag":0,"makeUp":0}
     * @param targetTopic  iot-history-alarm-topic-test
     * @param partitions   partition列表[0, 1, 2, 3, 4, 5]
     * @return
     */
    @Override
    public int partition(Object record, byte[] key, byte[] value, String targetTopic, int[] partitions) {
        //这里接收到的key是上面MySchema()中序列化后的key，需要转成string，然后取key的hash值取模kafka分区数量
        int part = Math.abs(new String(key).hashCode() % partitions.length);
        logger.info("record:"+record.toString()+"key:"+new String(key)+"  value:"+new String(value) +"  targetTopic:"+targetTopic +"  partitions:"+ Arrays.toString(partitions) );
        /**
         *
         record:{"id":"15959499868079104","alarmRuleId":"6789709006840532992","beginTime":"2022-09-01 04:42:29","endTime":"2022-09-01 04:42:40","ruleValue":0.60000,"firstValue":0.62000,"alarmType":1,"meterCode":"R19013-0003-0001-440300OII-10248","projectId":"440300OII","acquisitionTime":"2022-09-01 04:42:49","alarmValue":0.62000,"createUser":0,"createTime":"2022-09-01 04:42:49","updateUser":0,"updateTime":"2022-09-01 04:42:49","reasonTag":0,"makeUp":0}
         key:440300OII:R19013-0003-0001-440300OII-10248:1:15959499868079104:6789709006840532992
         value:{"id":"15959499868079104","alarmRuleId":"6789709006840532992","beginTime":"2022-09-01 04:42:29","endTime":"2022-09-01 04:42:40","ruleValue":0.60000,"firstValue":0.62000,"alarmType":1,"meterCode":"R19013-0003-0001-440300OII-10248","projectId":"440300OII","acquisitionTime":"2022-09-01 04:42:49","alarmValue":0.62000,"createUser":0,"createTime":"2022-09-01 04:42:49","updateUser":0,"updateTime":"2022-09-01 04:42:49","reasonTag":0,"makeUp":0}
         targetTopic:iot-history-alarm-topic-test
         partitions:[0, 1, 2, 3, 4, 5]
         */
        return part;
    }
}

第三步：调用自定义序列化和自定义的分区

    public static FlinkKafkaProducer getKafkaSinkSimple(String topic,Boolean flag) {
        Properties props = new Properties();
        props.setProperty(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, ConfigUtils.SERVICE_KAFKA_HOST);
        if (ConfigUtils.SERVICE_KAFKA_SASL_PLAINTEXT) {
            props.put("security.protocol", "SASL_PLAINTEXT");
            props.put("sasl.mechanism", "PLAIN");
            props.put("sasl.jaas.config", "org.apache.kafka.common.security.plain.PlainLoginModule required username='" + ConfigUtils.SERVICE_KAFKA_USERNAME + "' password='" + ConfigUtils.SERVICE_KAFKA_PASSWORD + "';");
 
        }
        //设置生产数据的超时时间
        props.setProperty(ProducerConfig.TRANSACTION_TIMEOUT_CONFIG, 15 * 60 * 1000 + "");
 
        if(flag){
            return new FlinkKafkaProducer<>(
                    topic,
                    new UserDefinedSerializationSchema(topic),  //自定义序列化
                    props,
                    Optional.of(new UserDefinedPartitioner()), //自定义的分区
                    FlinkKafkaProducer.Semantic.EXACTLY_ONCE,
                    6
            );
        }else{
            KeyedSerializationSchema keyedSerializationSchema = new KeyedSerializationSchemaWrapper(new SimpleStringSchema());
            return new FlinkKafkaProducer<>(
                    topic,
                    keyedSerializationSchema,
                    props,
                    Optional.empty(),
                    FlinkKafkaProducer.Semantic.EXACTLY_ONCE,
                    6
            );
        }
 
    }