问题描述
限时送ChatGPT账号..我正在使用 kafka 和 apache flink.我正在尝试从 apache flink 中的 kafka 主题使用记录(采用 avro 格式).下面是我正在尝试使用的一段代码.
I am working with kafka and apache flink. I am trying to consume records (which are in avro format) from a kafka topic in apache flink. Below is the piece of code I am trying with.
使用自定义反序列化器反序列化主题中的 avro 记录.
Using a custom deserialiser to deserialise avro records from the topic.
我发送到主题test-topic"的数据的 Avro 模式;如下.
the Avro schema for the data I am sending to topic "test-topic" is as below.
{
"namespace": "com.example.flink.avro",
"type": "record",
"name": "UserInfo",
"fields": [
{"name": "name", "type": "string"}
]
}
我使用的自定义解串器如下.
The custom deserialiser I am using is as below.
public class AvroDeserializationSchema<T> implements DeserializationSchema<T> {
private static final long serialVersionUID = 1L;
private final Class<T> avroType;
private transient DatumReader<T> reader;
private transient BinaryDecoder decoder;
public AvroDeserializationSchema(Class<T> avroType) {
this.avroType = avroType;
}
public T deserialize(byte[] message) {
ensureInitialized();
try {
decoder = DecoderFactory.get().binaryDecoder(message, decoder);
T t = reader.read(null, decoder);
return t;
} catch (Exception ex) {
throw new RuntimeException(ex);
}
}
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);
}
}
}
public boolean isEndOfStream(T nextElement) {
return false;
}
public TypeInformation<T> getProducedType() {
return TypeExtractor.getForClass(avroType);
}
}
这就是我的 flink 应用程序的编写方式.
And this is how my flink app is written.
public class FlinkKafkaApp {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
Properties kafkaProperties = new Properties();
kafkaProperties.put("bootstrap.servers", "localhost:9092");
kafkaProperties.put("group.id", "test");
AvroDeserializationSchema<UserInfo> schema = new AvroDeserializationSchema<UserInfo>(UserInfo.class);
FlinkKafkaConsumer011<UserInfo> consumer = new FlinkKafkaConsumer011<UserInfo>("test-topic", schema, kafkaProperties);
DataStreamSource<UserInfo> userStream = env.addSource(consumer);
userStream.map(new MapFunction<UserInfo, UserInfo>() {
@Override
public UserInfo map(UserInfo userInfo) {
return userInfo;
}
}).print();
env.execute("Test Kafka");
}
我正在尝试打印发送到主题的记录,如下所示.<代码>{名称":"sumit"}
I am trying to print the record sent to the the topic which is as below.
{"name" :"sumit"}
输出:
我得到的输出是{"name":""}
任何人都可以帮助弄清楚这里的问题是什么以及为什么我没有收到 {name";:sumit"}
作为输出.
Can anyone help to figure out what is the issue here and why I am not getting {"name" : "sumit"}
as output.
推荐答案
Flink 文档说:Flink 的 Kafka 消费者称为 FlinkKafkaConsumer08(或 09 代表 Kafka 0.9.0.x 版本等,或者 FlinkKafkaConsumer 代表 Kafka >= 1.0.0 版本).它提供对一个或多个 Kafka 主题的访问.
Flink documentation says : Flink’s Kafka consumer is called FlinkKafkaConsumer08 (or 09 for Kafka 0.9.0.x versions, etc. or just FlinkKafkaConsumer for Kafka >= 1.0.0 versions). It provides access to one or more Kafka topics.
我们不必编写自定义反序列化器来使用来自 Kafka 的 Avro 消息.
We do not have to write the custom de-serializer to consume Avro messages from Kafka.
-读取特定记录:
DataStreamSource<UserInfo> stream = streamExecutionEnvironment.addSource(new FlinkKafkaConsumer<>("test_topic", AvroDeserializationSchema.forSpecific(UserInfo.class), properties).setStartFromEarliest());
读取通用记录:
Schema schema = Schema.parse("{"namespace": "com.example.flink.avro","type": "record","name": "UserInfo","fields": [{"name": "name", "type": "string"}]}");
DataStreamSource<GenericRecord> stream = streamExecutionEnvironment.addSource(new FlinkKafkaConsumer<>("test_topic", AvroDeserializationSchema.forGeneric(schema), properties).setStartFromEarliest());
更多详情:https://ci.apache/projects/flink/flink-docs-stable/dev/connectors/kafka.html#kafka-consumer
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