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我正在尝试使用Flink来从Kafka主题读取AVRO数据1.0.3。如何使用Avro和Flink解码Kafka邮件
我只知道，这个特定的卡夫卡主题是有AVRO编码的消息，我有AVRO架构文件。
My Flink code:
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "dojo3xxxxx:9092,dojoxxxxx:9092,dojoxxxxx:9092");
properties.setProperty("zookeeper.connect", "dojo3xxxxx:2181,dojoxxxxx:2181,dojoxxxxx:2181");
properties.setProperty("group.id", "Zeeshantest");
AvroDeserializationSchema<Event> avroSchema = new AvroDeserializationSchema<>(Event.class);
FlinkKafkaConsumer08<Event> kafkaConsumer = new FlinkKafkaConsumer08<>("myavrotopic", avroSchema, properties);
DataStream<Event> messageStream = env.addSource(kafkaConsumer);
messageStream.rebalance().print();
env.execute("Flink AVRO KAFKA Test");
}
我已经使用的Avro工具和架构 “rocana.avsc”
这里是rocana.avsc文件在github上上传创建我的Event.java文件。
AvroDeserializationSchema.java
import org.apache.avro.io.BinaryDecoder;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.DecoderFactory;
import org.apache.avro.reflect.ReflectDatumReader;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.typeutils.TypeExtractor;
import org.apache.flink.streaming.util.serialization.DeserializationSchema;
public class AvroDeserializationSchema<T> implements DeserializationSchema<T> {
private static final long serialVersionUID = 4330538776656642778L;
private final Class<T> avroType;
private transient DatumReader<T> reader;
private transient BinaryDecoder decoder;
public AvroDeserializationSchema(Class<T> avroType) {
this.avroType = avroType;
}
@Override
public T deserialize(byte[] message) {
ensureInitialized();
try {
decoder = DecoderFactory.get().binaryDecoder(message, decoder);
return reader.read(null, decoder);
} catch (Exception e) {
throw new RuntimeException(e);
}
}
@Override
public boolean isEndOfStream(T nextElement) {
return false;
}
@Override
public TypeInformation<T> getProducedType() {
return TypeExtractor.getForClass(avroType);
}
private void ensureInitialized() {
if (reader == null) {
if (org.apache.avro.specific.SpecificRecordBase.class.isAssignableFrom(avroType)) {
reader = new SpecificDatumReader<T>(avroType);
} else {
reader = new ReflectDatumReader<T>(avroType);
}
}
}
}
在运行我的程序，我收到以下错误：
17:25:30,759 INFO org.apache.zookeeper.ZooKeeper - Session: 0x356350cb9001857 closed
17:25:30,759 INFO org.apache.zookeeper.ClientCnxn - EventThread shut down
17:25:30,761 INFO org.apache.flink.runtime.taskmanager.Task - Source: Custom Source (3/4) switched to FAILED with exception.
java.lang.Exception: 2
at org.apache.flink.streaming.connectors.kafka.internals.LegacyFetcher.run(LegacyFetcher.java:222)
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer08.run(FlinkKafkaConsumer08.java:316)
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:78)
at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:56)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:225)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:559)
at java.lang.Thread.run(Unknown Source)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 2
at org.apache.avro.io.parsing.Symbol$Alternative.getSymbol(Symbol.java:402)
at org.apache.avro.io.ResolvingDecoder.doAction(ResolvingDecoder.java:290)
at org.apache.avro.io.parsing.Parser.advance(Parser.java:88)
at org.apache.avro.io.ResolvingDecoder.readIndex(ResolvingDecoder.java:267)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:155)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:193)
at org.apache.avro.reflect.ReflectDatumReader.readField(ReflectDatumReader.java:230)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:183)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:151)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:142)
at com.google.cloud.dataflow.sdk.coders.AvroCoder.decode(AvroCoder.java:274)
at org.fmr.flink.AvroDeserializationSchema.deserialize(AvroDeserializationSchema.java:52)
at org.apache.flink.streaming.util.serialization.KeyedDeserializationSchemaWrapper.deserialize(KeyedDeserializationSchemaWrapper.java:39)
at org.apache.flink.streaming.connectors.kafka.internals.LegacyFetcher$SimpleConsumerThread.run(LegacyFetcher.java:657)
17:25:30,769 INFO org.apache.flink.runtime.taskmanager.Task - Freeing task resources for Source: Custom Source (3/4)
17:25:30,776 INFO org.apache.flink.runtime.taskmanager.Task - Sink: Unnamed (1/4) switched
我认为我的反序列化的代码是不正确的。有谁知道我做错了什么？这是使用Flink从Kafka读取AVRO数据的方式，还是有更好的办法？
您确定Kafka中的数据是使用完全相同的模式版本编码的吗？通过创建一个'新的SpecificDatumReader（avroType）'，你告诉数据读取器'avroType'模式既是读写器模式，我相信你可能会得到这些类型的异常，如果事实上有不同版本的架构最初用于编码消息。 –
Josh
是的，模式文件是正确的，我在'logstash'中使用了相同的'schema file'和'kafka topic'，它的工作完美无瑕。 – Zeeshan