Apache kafka 如何从卡夫卡主题流到elasticsearch和confluent？

我从机器中读取数据，并将其作为JSON流式传输到卡夫卡主题。我想阅读本主题并使用confluent将streamdata存储到elasticsearch中

我的步骤： 1.创建要从JSON转换为AVRO的KSQL流

json流：

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

avro流：

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

 ksql> print "7d12h100mbpressure_avro";

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

在此之后，我得到这个avro流：

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

 ksql> print "7d12h100mbpressure_avro";

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

My 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

 # 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

在此之后，我希望流是ES，但我得到的索引没有流数据

我哪里出错了

合流日志连接中的错误：

 [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connect-avro-distributed.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

 # 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

---

您可以从Elasticsink设置

key.ignore=true

，但是，这不会阻止Connect尝试反序列化记录

当您只需执行

汇合启动

时，它将始终对键和值转换器使用

AvroConverter

值得一提的是，KSQL中的

VALUE\u FORMAT='AVRO'

只将值作为AVRO，我相信，不是键

其中一个原因可以解释为什么你会看到

• 找不到主题
• 找不到架构
• 检索id的Avro架构时出错

为了解决这个问题，在

elasticsearch.properties

中，您可以覆盖

key.converter

，使其成为类似于

org.apache.kafka.connect.storage.StringConverter

---

---

此外，我建议使用

kafka avro console consumer

并包括

--property print.key=true

选项，而不是使用Connect+KSQL进行调试，以查看是否出现类似错误

不清楚您运行了什么命令来启动Kafka connect如果执行融合日志连接，您是否看到任何错误？@ofitz能否共享您的Kafka connect worker配置？很可能您的转换器设置不正确。最好是你可以编辑你的问题，以包括卡夫卡连接工作日志中的任何错误（

confluent log Connect

），如@cricket_007所说。这是一个重要的例外，但我如何解决它：

原因：org.apache.kafka.connect.errors.DataException:未能将主题7D12H100MB压力的数据反序列化为avro:

检索id 92747的avro架构时出错

<代码>RestClientException:未找到架构。。。我认为您需要删除作为AvroConverter的

key.converter

，因为KSQL不使用

/kafka Avro控制台使用者创建Avro密钥——主题7d12h100mbpressure_avro1——引导服务器localhost:9092

是我的输出：

{“TIMESTAMP”：{“long”：1556171473227}，“opcuaoobject”：{“string”：“DatLuDrUeb.EinDru”}，“VALUE”：{“double”：8.06}

如果我设置

--property print.key=true

我会得到与启动confluent时哪个配置文件使用confluent相同的错误

/confluent start

？我在

confluent-5.2.1/etc/schema registry/connect avro distributed.properties

和

confluent-5.2.1/etc/kafka/connect distributed.properties

中有配置，它使用

connect avro distributed.properties

。但就像我说的，你可以覆盖Elasticsearch水槽属性中的转换器非常感谢你。在我覆盖

键后，转换器就可以工作了！我怎样才能用elastic编写多个主题？我可以为多个主题配置
elasticsearch.properties
，如下所示：
topics=topic1，topic2
FYI:KSQL即将支持Avro格式的密钥（通常是“结构化密钥”）。