如何使流从卡夫卡主题到elasticsearch与汇合？

Question

我从机器中读取数据，并将其作为JSON流到kafka主题。我想阅读这个主题，并将流数据存储到elasticsearch中。

我的步骤: 1.创建从JSON到AVRO的KSQL流

json流：

 CREATE STREAM source_json_pressure 
 (
  timestamp BIGINT, 
  opcuaObject VARCHAR, 
  value DOUBLE
  ) 
 WITH (KAFKA_TOPIC='7d12h100mbpressure',
   VALUE_FORMAT='JSON');

阿夫罗溪流：

 CREATE STREAM target_avro_pressure 
  WITH (
     KAFKA_TOPIC='7d12h100mbpressure_avro', 
     VALUE_FORMAT='AVRO'
  ) AS 
  SELECT * FROM source_json_pressure;

在这之后我得到了阿夫罗流：

 ksql> print "7d12h100mbpressure_avro";

 Format:AVRO
 23.04.19 19:29:58 MESZ,   jK?C, {"TIMESTAMP": 1556040449728, "OPCUAOBJECT": "DatLuDrUeb.EinDru", "VALUE": 7.42}

我的elasticsearch.properties：

15 name=elasticsearch-sink
16 connector.class=io.confluent.connect.elasticsearch.ElasticsearchSinkConnector
17 tasks.max=1
18 topics=7d12h100mbpressure_avro
19 key.ignore=true
20 connection.url=http://localhost:9200
21 type.name=kafka-connect

在此之后，我期待ES中的流，但是我得到没有流数据的索引。

我在哪里搞错了？

来自汇合日志连接的错误：

 [2019-04-24 11:01:29,316] INFO [Consumer clientId=consumer-4, groupId=connect-elasticsearch-sink] Setting newly assigned partitions: 7d12h100mbpressure_avro-3, 7d12h100mbpressure_avro-2, 7d12h100mbpressure_avro-1, 7d12h100mbpressure_avro-0 (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:290)
 [2019-04-24 11:01:29,327] INFO [Consumer clientId=consumer-4, groupId=connect-elasticsearch-sink] Resetting offset for partition 7d12h100mbpressure_avro-3 to offset 0. (org.apache.kafka.clients.consumer.internals.Fetcher:584)
 [2019-04-24 11:01:29,327] INFO [Consumer clientId=consumer-4, groupId=connect-elasticsearch-sink] Resetting offset for partition 7d12h100mbpressure_avro-2 to offset 0. (org.apache.kafka.clients.consumer.internals.Fetcher:584)
 [2019-04-24 11:01:29,327] INFO [Consumer clientId=consumer-4, groupId=connect-elasticsearch-sink] Resetting offset for partition 7d12h100mbpressure_avro-1 to offset 0. (org.apache.kafka.clients.consumer.internals.Fetcher:584)
 [2019-04-24 11:01:29,328] INFO [Consumer clientId=consumer-4, groupId=connect-elasticsearch-sink] Resetting offset for partition 7d12h100mbpressure_avro-0 to offset 0. (org.apache.kafka.clients.consumer.internals.Fetcher:584)
 [2019-04-24 11:01:29,667] ERROR WorkerSinkTask{id=elasticsearch-sink-0} Task threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask:177)
 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:484)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:464)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:320)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:224)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:192)
    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: Failed to deserialize data for topic 7d12h100mbpressure_avro to Avro:
    at io.confluent.connect.avro.AvroConverter.toConnectData(AvroConverter.java:107)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.lambda$convertAndTransformRecord$0(WorkerSinkTask.java:484)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndRetry(RetryWithToleranceOperator.java:128)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:162)
    ... 13 more 
 Caused by: org.apache.kafka.common.errors.SerializationException: Error retrieving Avro schema for id 92747
 Caused by: io.confluent.kafka.schemaregistry.client.rest.exceptions.RestClientException: Schema not found; error code: 40403
    at io.confluent.kafka.schemaregistry.client.rest.RestService.sendHttpRequest(RestService.java:226)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.httpRequest(RestService.java:252)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.getId(RestService.java:482)
    at io.confluent.kafka.schemaregistry.client.rest.RestService.getId(RestService.java:475)
    at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.getSchemaByIdFromRegistry(CachedSchemaRegistryClient.java:151)
    at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.getBySubjectAndId(CachedSchemaRegistryClient.java:230)
    at io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient.getById(CachedSchemaRegistryClient.java:209)
    at io.confluent.kafka.serializers.AbstractKafkaAvroDeserializer.deserialize(AbstractKafkaAvroDeserializer.java:116)
    at io.confluent.kafka.serializers.AbstractKafkaAvroDeserializer.deserializeWithSchemaAndVersion(AbstractKafkaAvroDeserializer.java:215)
    at io.confluent.connect.avro.AvroConverter$Deserializer.deserialize(AvroConverter.java:145)
    at io.confluent.connect.avro.AvroConverter.toConnectData(AvroConverter.java:90)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.lambda$convertAndTransformRecord$0(WorkerSinkTask.java:484)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndRetry(RetryWithToleranceOperator.java:128)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execAndHandleError(RetryWithToleranceOperator.java:162)
    at org.apache.kafka.connect.runtime.errors.RetryWithToleranceOperator.execute(RetryWithToleranceOperator.java:104)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertAndTransformRecord(WorkerSinkTask.java:484)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:464)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:320)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:224)
    at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:192)
    at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:175)
    at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:219)
    at java.util.concurrent.Executors$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)
 [2019-04-24 11:01:29,668] ERROR WorkerSinkTask{id=elasticsearch-sink-0} Task is being killed and will not recover until manually restarted (org.apache.kafka.connect.runtime.WorkerTask:178)

我的连接-avro-分发.属性：

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

  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

  config.storage.topic=connect-configs
  offset.storage.topic=connect-offsets
  status.storage.topic=connect-statuses

  config.storage.replication.factor=1
  offset.storage.replication.factor=1
  status.storage.replication.factor=1

 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

Answer 1

但是，您可以从Elastic接收器设置key.ignore=true，但这并不能阻止Connect尝试反序列化记录。

当您只执行confluent start时，它将始终使用AvroConverter作为键和值转换器。

值得一提的是，我认为，KSQL中的VALUE_FORMAT='AVRO'只将值作为Avro，而不是关键。

其中一个原因也许可以解释为什么你会看到

• 主体未找到
• 模式未找到
• 检索id的Avro模式时出错

为了解决这个问题，在您的elasticsearch.properties中，您可以重写key.converter，使其成为类似于org.apache.kafka.connect.storage.StringConverter的其他东西。

另外，与使用Connect+KSQL进行调试不同，我建议使用kafka-avro-console-consumer并包括--property print.key=true选项，以查看是否有类似的错误。