Flink解析kafka canal未压平数据为message报错

canal使用非flatmessage方式获取mysql bin log日志发至kafka比直接发送json效率要高很多，数据发到kafka后需要实时解析为json,这里可以使用strom或者flink,公司本来就是使用strom解析，但是在吞吐量上有瓶颈，优化空间不大。所以试一试通过flink来做。

非flatmessage需要使用特定的反序列化方式来处理为Message对象，所以这里需要自定义一个类

 /**
  * 反序列化canal binlog
  *
  * @author   @ 2019-02-20
  * @version 1.0.0
  */
 @PublicEvolving
 public class MessageDeserializationSchema implements KeyedDeserializationSchema<Message> {

     private static final long serialVersionUID = -678988040385271953L;
     private MessageDeserializer mesDesc;

     @Override
     public Message deserialize(byte[] messageKey, byte[] message, String topic, int partition, long offset) throws IOException {
         try {
             if (mesDesc == null) {
                 mesDesc = new MessageDeserializer();
             }
             Message result = mesDesc.deserialize(topic, message);
             //result.setMetaData(topic, partition, offset);
             return result;
         } catch (Exception e) {
             System.out.println(e);
         }
         return null;
     }

     @Override
     public boolean isEndOfStream(Message nextElement) {
         return false;
     }

     @Override
     public TypeInformation<Message> getProducedType() {
         return getForClass(Message.class);
     }
 }

然后就可以获取到DataStream[Message]，但是在做算子操作的时候就报错了,意思是不支持kryo序列化

com.esotericsoftware.kryo.KryoException: java.lang.UnsupportedOperationException
Serialization trace:
props_ (com.alibaba.otter.canal.protocol.CanalEntry$Header)
header_ (com.alibaba.otter.canal.protocol.CanalEntry$Entry)
entries (com.alibaba.otter.canal.protocol.Message)
	at com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
	at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:528)
	at com.esotericsoftware.kryo.Kryo.readObjectOrNull(Kryo.java:730)
	at com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:113)
	at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:528)
	at com.esotericsoftware.kryo.Kryo.readObjectOrNull(Kryo.java:730)
	at com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:109)
	at com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:22)
	at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:679)
	at com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:106)
	at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:528)
	at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:657)
	at org.apache.flink.api.java.typeutils.runtime.kryo.KryoSerializer.copy(KryoSerializer.java:231)
	at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:577)
	at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:554)
	at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:534)
	at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718)
	at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696)
	at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104)
	at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111)
	at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398)
	at org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:89)
	at org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:154)
	at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:665)
	at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:94)
	at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:58)
	at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:99)
	at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:300)
	at org.apache.flink.runtime.taskmanager.Task.run(Task.java:704)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.UnsupportedOperationException
	at java.util.Collections$UnmodifiableCollection.add(Collections.java:1055)
	at com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:109)
	at com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:22)
	at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:679)
	at com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:106)
	... 29 more

参考官方文档，需要注册类的序列化方式：https://ci.apache.org/projects/flink/flink-docs-release-1.7/dev/custom_serializers.html

　　//message 不支持kryo序列化 不然在map flatmap的时候报错

　　env.getConfig.addDefaultKryoSerializer(classOf[Message], classOf[StringSerializer])

如果在算子之间会有其他对象传输的话，也同样需要注册。最后通过测试，flink解析的量大概在单个solt 1W+/s 左右。