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我正在尝试使用 kafka HDFS 连接器将 avro 格式的数据从我的 Java 代码写入 Kafka 到 HDFS，但我遇到了一些问题。当我使用 confluent 平台网站上提供的简单架构和数据时，我能够将数据写入 HDFS，但是当我尝试使用复杂的 avro 架构时，我在 HDFS 连接器日志中收到此错误：

ERROR Task hdfs-sink-0 threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask:142)
org.apache.kafka.connect.errors.DataException: Did not find matching union field for data: PROD
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:973)
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:981)
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:981)
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:981)
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:981)
    at io.confluent.connect.avro.AvroData.toConnectData(AvroData.java:782)
    at io.confluent.connect.avro.AvroConverter.toConnectData(AvroConverter.java:103)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:346)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:226)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:170)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:142)
    at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:140)
    at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:175)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

我正在使用融合平台 3.0.0

我的Java代码：

Properties props = new Properties();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokerUrl);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put("schema.registry.url", <url>);
// Set any other properties
KafkaProducer producer = new KafkaProducer(props);

Schema schema = new Schema.Parser().parse(new FileInputStream("avsc/schema.avsc"));
DatumReader<Object> reader = new GenericDatumReader<Object>(schema);

InputStream input = new FileInputStream("json/data.json");
DataInputStream din = new DataInputStream(input);
Decoder decoder = DecoderFactory.get().jsonDecoder(schema, din);

Object datum = null;
while (true) {
    try {
        datum = reader.read(null, decoder);
    } catch (EOFException e) {
        break;
    }
}

ProducerRecord<Object, Object> message = new ProducerRecord<Object, Object>(topic, datum);
producer.send(message);
producer.close();

架构（这是从 avdl 文件创建的）：

{
  "type" : "record",
  "name" : "RiskMeasureEvent",
  "namespace" : "risk",
  "fields" : [ {
    "name" : "info",
    "type" : {
      "type" : "record",
      "name" : "RiskMeasureInfo",
      "fields" : [ {
        "name" : "source",
        "type" : {
          "type" : "record",
          "name" : "Source",
          "fields" : [ {
            "name" : "app",
            "type" : {
              "type" : "record",
              "name" : "Application",
              "fields" : [ {
                "name" : "csi_id",
                "type" : "string"
              }, {
                "name" : "name",
                "type" : "string"
              } ]
            }
          }, {
            "name" : "env",
            "type" : {
              "type" : "record",
              "name" : "Environment",
              "fields" : [ {
                "name" : "value",
                "type" : [ {
                  "type" : "enum",
                  "name" : "EnvironmentConstants",
                  "symbols" : [ "DEV", "UAT", "PROD" ]
                }, "string" ]
              } ]
            }
          }, ...

json文件：

{
  "info": {
    "source": {
      "app": {
        "csi_id": "123",
        "name": "ABC"
      },
      "env": {
        "value": {
          "risk.EnvironmentConstants": "PROD"
        }
      }, ...

这似乎是架构的问题，但我无法确定问题所在。

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1 回答 1

1

我是 Confluent 的工程师。这是 Avro 转换器如何处理您对 env 的联合模式的一个错误。我创建了issue-393来解决这个问题。我还与修复一起提出了一个拉取请求。这应该很快合并。

Ĵ

于 2016-08-01T21:49:02.490 回答