Docker汇合Kafka HDFS接收器正在运行，但任务失败

我用融合的卡夫卡将卡夫卡设置在数字海洋液滴上。我能够使用Kafka Connect REST API成功运行Kafka并添加HDFS连接器。我用液滴的IP替换主机IP

 curl -X POST \
  -H "Content-Type: application/json" \
  --data '{
  "name": "hdfs-sink",
  "config": {
    "connector.class": "io.confluent.connect.hdfs.HdfsSinkConnector",
    "tasks.max": "1",
    "topics": "test_hdfs",
    "hdfs.url": "hdfs://HOST_IP:8020",
    "flush.size": "3",
    "name": "hdfs-sink"
  }}' \
  http://HOST_IP:8083/connectors

然后，当我将Kafka Connect设置为hdfs接收器状态时，我在任务下的JSON响应中收到以下错误（服务的状态为正在运行，但任务已失败）：

java.lang.RuntimeException:io.confluent.kafka.serializers.subject.TopicNameStrategy不是io.confluent.kafka.serializers.subject.Namestrategy的实例

更新 因此，我通过使用5.0.0来克服这个错误，而不是使用cricket007推荐的beta版（愚蠢的我）

然而，当我实际尝试将数据发布到我的HDFS实例时，我收到了一个不同的错误。我使用ksqldatagen来生成假数据

docker compose exec ksql datagen ksql datagen quickstart=users format=json topic=test\u hdfs maxInterval=1000\properties file=/etc/ksql/datagen.properties bootstrap server=broker:9092

{
    "name": "hdfs-sink",
    "connector": {
        "state": "RUNNING",
        "worker_id": "connect:8083"
    },
    "tasks": [{
        "state": "FAILED",
        "trace": "org.apache.kafka.connect.errors.ConnectException: Tolerance exceeded in error handler\n\tat org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:178)\n\tat org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execute(RetryWithToleranceOperator.java:104)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.convertAndTransformRecord(WorkerSinkTask.java:510)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:490)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:321)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:225)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:193)\n\tat org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:175)\n\tat org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:219)\n\tat java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)\n\tat java.util.concurrent.FutureTask.run(FutureTask.java:266)\n\tat java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)\n\tat java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)\n\tat java.lang.Thread.run(Thread.java:748)\nCaused by: org.apache.kafka.connect.errors.DataException: test_hdfs\n\tat io.confluent.connect.avro.AvroConverter.toConnectData(AvroConverter.java:97)\n\tat org.apache.kafka.connect.runtime.WorkerSinkTask.lambda$convertAndTransformRecord$0(WorkerSinkTask.java:510)\n\tat org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndRetry(RetryWithToleranceOperator.java:128)\n\tat org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:162)\n\t... 13 more\nCaused by: org.apache.kafka.common.errors.SerializationException: Error deserializing Avro message for id -1\nCaused by: org.apache.kafka.common.errors.SerializationException: Unknown magic byte!\n",
        "id": 0,
        "worker_id": "connect:8083"
    }],
    "type": "sink"
}

curl -X POST \
  -H "Content-Type: application/json" \
  --data '{
  "name": "hdfs-sink",
  "config": {
    "connector.class": "io.confluent.connect.hdfs.HdfsSinkConnector",
    "format.class": "io.confluent.connect.hdfs.avro.AvroFormat",
    "tasks.max": "1",
    "schema.compatibility": "FULL",
    "topics": "test_hdfs",
    "hdfs.url": "hdfs://cdh.nuvo.app:8020",
    "flush.size": "3",
    "name": "hdfs-sink"
  }}' \
  http://kafka.nuvo.app:8083/connectors

编辑2

Avro ksql datagen的堆栈跟踪失败

Outputting 1000000 to test_hdfs
Exception in thread "main" org.apache.kafka.common.errors.SerializationException: Error serializing row to topic test_hdfs using Converter API
Caused by: org.apache.kafka.connect.errors.DataException: test_hdfs
    at io.confluent.connect.avro.AvroConverter.fromConnectData(AvroConverter.java:77)
    at io.confluent.ksql.serde.connect.KsqlConnectSerializer.serialize(KsqlConnectSerializer.java:44)
    at io.confluent.ksql.serde.connect.KsqlConnectSerializer.serialize(KsqlConnectSerializer.java:27)
    at org.apache.kafka.common.serialization.ExtendedSerializer$Wrapper.serialize(ExtendedSerializer.java:65)
    at org.apache.kafka.common.serialization.ExtendedSerializer$Wrapper.serialize(ExtendedSerializer.java:55)
    at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:854)
    at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:816)
    at io.confluent.ksql.datagen.DataGenProducer.populateTopic(DataGenProducer.java:94)
    at io.confluent.ksql.datagen.DataGen.main(DataGen.java:100)
Caused by: org.apache.kafka.common.errors.SerializationException: Error serializing Avro message
Caused by: java.net.ConnectException: Connection refused (Connection refused)
    at java.net.PlainSocketImpl.socketConnect(Native Method)
    at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:350)
    at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
    at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
    at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
    at java.net.Socket.connect(Socket.java:589)
    at java.net.Socket.connect(Socket.java:538)
    at sun.net.NetworkClient.doConnect(NetworkClient.java:180)
    at sun.net.www.http.HttpClient.openServer(HttpClient.java:463)
    at sun.net.www.http.HttpClient.openServer(HttpClient.java:558)
    at sun.net.www.http.HttpClient.<init>(HttpClient.java:242)
    at sun.net.www.http.HttpClient.New(HttpClient.java:339)
    at sun.net.www.http.HttpClient.New(HttpClient.java:357)
    at sun.net.www.protocol.http.HttpURLConnection.getNewHttpClient(HttpURLConnection.java:1220)
    at sun.net.www.protocol.http.HttpURLConnection.plainConnect0(HttpURLConnection.java:1156)
    at sun.net.www.protocol.http.HttpURLConnection.plainConnect(HttpURLConnection.java:1050)
    at sun.net.www.protocol.http.HttpURLConnection.connect(HttpURLConnection.java:984)
    at sun.net.www.protocol.http.HttpURLConnection.getOutputStream0(HttpURLConnection.java:1334)
    at sun.net.www.protocol.http.HttpURLConnection.getOutputStream(HttpURLConnection.java:1309)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.sendHttpRequest(RestService.java:172)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.httpRequest(RestService.java:229)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:320)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:312)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.registerSchema(RestService.java:307)
    at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.registerAndGetId(CachedSchemaRegistryClient.java:114)
    at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.register(CachedSchemaRegistryClient.java:153)
    at io.confluent.kafka.serializers.AbstractKafkaAvroSerializer.serializeImpl(AbstractKafkaAvroSerializer.java:79)
    at io.confluent.connect.avro.AvroConverter$Serializer.serialize(AvroConverter.java:116)
    at io.confluent.connect.avro.AvroConverter.fromConnectData(AvroConverter.java:75)
    at io.confluent.ksql.serde.connect.KsqlConnectSerializer.serialize(KsqlConnectSerializer.java:44)
    at io.confluent.ksql.serde.connect.KsqlConnectSerializer.serialize(KsqlConnectSerializer.java:27)
    at org.apache.kafka.common.serialization.ExtendedSerializer$Wrapper.serialize(ExtendedSerializer.java:65)
    at org.apache.kafka.common.serialization.ExtendedSerializer$Wrapper.serialize(ExtendedSerializer.java:55)
    at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:854)
    at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:816)
    at io.confluent.ksql.datagen.DataGenProducer.populateTopic(DataGenProducer.java:94)
    at io.confluent.ksql.datagen.DataGen.main(DataGen.java:100)

架构注册表配置

# Bootstrap Kafka servers. If multiple servers are specified, they should be comma-separated.
bootstrap.servers=localhost:9092

# The converters specify the format of data in Kafka and how to translate it into Connect data.
# Every Connect user will need to configure these based on the format they want their data in
# when loaded from or stored into Kafka
key.converter=io.confluent.connect.avro.AvroConverter
key.converter.schema.registry.url=http://localhost:8081
value.converter=io.confluent.connect.avro.AvroConverter
value.converter.schema.registry.url=http://localhost:8081

# The internal converter used for offsets and config data is configurable and must be specified,
# but most users will always want to use the built-in default. Offset and config data is never
# visible outside of Connect in this format.
internal.key.converter=org.apache.kafka.connect.json.JsonConverter
internal.value.converter=org.apache.kafka.connect.json.JsonConverter
internal.key.converter.schemas.enable=false
internal.value.converter.schemas.enable=false

卡夫卡连接日志：

  org.apache.kafka.connect.errors.ConnectException: Tolerance exceeded in error handler
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:178)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execute(RetryWithToleranceOperator.java:104)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertAndTransformRecord(WorkerSinkTask.java:510)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:490)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:321)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:225)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:193)
    at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:175)
    at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:219)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.kafka.connect.errors.DataException: Converting byte[] to Kafka Connect data failed due to serialization error: 
    at org.apache.kafka.connect.json.JsonConverter.toConnectData(JsonConverter.java:334)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.lambda$convertAndTransformRecord$0(WorkerSinkTask.java:510)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndRetry(RetryWithToleranceOperator.java:128)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:162)
    ... 13 more
Caused by: org.apache.kafka.common.errors.SerializationException: com.fasterxml.jackson.core.JsonParseException: Unrecognized token 'impression_816': was expecting ('true', 'false' or 'null')
 at [Source: (byte[])"impression_816"; line: 1, column: 29]
Caused by: com.fasterxml.jackson.core.JsonParseException: Unrecognized token 'impression_816': was expecting ('true', 'false' or 'null')
 at [Source: (byte[])"impression_816"; line: 1, column: 29]

编辑4

[2018-08-22 02:05:51,140] ERROR WorkerSinkTask{id=hdfs-sink-0} Task threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask)
org.apache.kafka.connect.errors.ConnectException: Tolerance exceeded in error handler
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:178)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execute(RetryWithToleranceOperator.java:104)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertAndTransformRecord(WorkerSinkTask.java:510)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:490)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:321)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:225)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:193)
    at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:175)
    at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:219)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.kafka.connect.errors.DataException: test_hdfs1
    at io.confluent.connect.avro.AvroConverter.toConnectData(AvroConverter.java:97)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.lambda$convertAndTransformRecord$0(WorkerSinkTask.java:510)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndRetry(RetryWithToleranceOperator.java:128)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:162)
    ... 13 more
Caused by: org.apache.kafka.common.errors.SerializationException: Error deserializing Avro message for id -1
Caused by: org.apache.kafka.common.errors.SerializationException: Unknown magic byte!
[2018-08-22 02:05:51,141] ERROR WorkerSinkTask{id=hdfs-sink-0} Task is being killed and will not recover until manually restarted (org.apache.kafka.connect.runtime.WorkerTask)
[2018-08-22 02:05:51,243] INFO Publish thread interrupted for client_id=consumer-8 client_type=CONSUMER session= cluster=lUWD_PR0RsiTkaunoUrUfA group=connect-hdfs-sink (io.confluent.monitoring.clients.interceptor.MonitoringInterceptor)

---

您设置了

ksqldatagen。。。format=json

但该错误表示您已在Kafka Connect中设置了AvroConverter

Caused by: org.apache.kafka.common.errors.SerializationException: Error deserializing Avro message for id -1
Caused by: org.apache.kafka.common.errors.SerializationException: Unknown magic byte!

查看您的撰写文件

  CONNECT_KEY_CONVERTER: io.confluent.connect.avro.AvroConverter
  CONNECT_KEY_CONVERTER_SCHEMA_REGISTRY_URL: 'http://schema-registry:8081'
  CONNECT_VALUE_CONVERTER: io.confluent.connect.avro.AvroConverter
  CONNECT_VALUE_CONVERTER_SCHEMA_REGISTRY_URL: 'http://schema-registry:8081'

如果您想生成Avro数据，请改为

尽管您正在生成JSON，但目前，这并不是您配置的HDFS上的内容。
Avro是HDFS Connect的默认输出格式；如果你提到了

format.class

将数据写入时要使用的format类 商店。格式类实现

io.confluent.connect.storage.format.format

接口

类型：类别
默认值：

io.confluent.connect.hdfs.avro.AvroFormat

重要性：高

默认情况下，这些类可用：

• io.confluent.connect.hdfs.avro.AvroFormat

• io.confluent.connect.hdfs.json.JsonFormat

• io.confluent.connect.hdfs.parquet.ParquetFormat

• io.confluent.connect.hdfs.string.StringFormat

如果您不使用JsonFormat，我相信为了从JSON输出Avro

否则，无法从JSON记录推断Avro模式

---

通过您的一系列编辑，我认为您转向了生成Avro，但基于我上面提到的内容使用JsonConverter，这不是我的建议。基本上，转换器类类型必须与生产者数据匹配，并定义使用者反序列化器

对于id为-1的序列化错误，基本上是说键或值中的数据不是Avro。现在，KSQL不能与Avro密钥一起工作，所以我敢打赌是密钥反序列化器失败了。要解决这个问题，请设置

key.converter=org.apache.kafka.connect.converters.ByteArrayConverter

---

你能发布完整的堆栈跟踪吗？这可能是因为您必须从连接日志中获取，而不是从其他日志中获取。听起来您的此类版本有冲突。这些链接的撰写文件尚未更新到5.0.0版本，仍然是beta版。请使用释放version@dawsaw明天将发布完整的堆栈跟踪。@cricket_007明天将尝试使用受支持的发布版本。@cricket007我通过使用带有Avro格式消息的ksql datagen在这方面取得了进展，但我遇到了一个问题`docker compose exec ksql datagen ksql datagen schema=/impressions.Avro format=Avrokey=impressionid topic=test\u hdfs maxInterval=1000\properties文件=/etc/ksql/datagen.properties引导服务器=broker:9092`

输出1000000以测试线程“main”中的hdfs异常org.apache.kafka.common.errors.SerializationException:使用转换器API将行序列化为主题测试\u hdfs时出错

请参见编辑2

java.net.ConnectException:连接被拒绝

。。。您的架构注册表不起作用，或者您从未运行过。哦，在

ksql datagen

上，如果您通过

format=avro

，那么您需要通过

schemaRegistryUrl=http://schema-registry:8081

@cricket007我仍然收到一个JSON解析错误，尽管我到处都指定了Avro。我唯一想做的是与内部有关的事情#用于偏移和配置数据的内部转换器是可配置的，必须指定，请参见上面的编辑3井1）我在日志中看到了

JsonConverter

，但这不应该是撰写文件的一部分。2）

byte[]

数据不是JSON类型。最终，我不知道您的主题中最初包含哪些数据，但Connect正在尝试从Kafka主题中读取字节，然后最终以某种方式解析它。如果生成了Avro数据，则必须使用AvroConverter。您可以更改的是HDFS Connect配置中的

格式.class

key.converter=org.apache.kafka.connect.converters.ByteArrayConverter