接收器连接器不起作用

接收器连接器不起作用

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Kafka Connect JDBC 接收器连接器不起作用

本文介绍了Kafka Connect JDBC 接收器连接器不起作用的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我正在尝试使用 Kafka Connect JDBC sink 连接器将数据插入 Oracle，但它抛出了错误.我已经尝试了所有可能的架构配置.下面是例子.

I am trying to use Kafka Connect JDBC sink connector to insert data into Oracle but it is throwing an error . I have tried with all the possible configurations of the schema. Below is the examples .

如果我遗漏了以下内容，请指出我的配置文件和错误.

Please suggest if I am missing anything below are my configurations files and errors.

internal.value.converter.schemas.enable=false .

所以我得到了

[2017-08-28 16:16:26,119] INFO Sink task WorkerSinkTask{id=oracle_sink-0} finished initialization and start (org.apache.kafka.connect.runtime.WorkerSinkTask:233)

[2017-08-28 16:16:26,606] INFO Discovered coordinator dfw-appblx097-01.prod.walmart.com:9092 (id: 2147483647 rack: null) for group connect-oracle_sink. (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:597)

[2017-08-28 16:16:26,608] INFO Revoking previously assigned partitions [] for group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:419)

[2017-08-28 16:16:26,609] INFO (Re-)joining group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:432)

[2017-08-28 16:16:27,174] INFO Successfully joined group connect-oracle_sink with generation 26 (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:399)

[2017-08-28 16:16:27,176] INFO Setting newly assigned partitions [DJ-7, DJ-6, DJ-5, DJ-4, DJ-3, DJ-2, DJ-1, DJ-0, DJ-9, DJ-8] for group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:262)

[2017-08-28 16:16:28,580] ERROR Task oracle_sink-0 threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerSinkTask:455)

org.apache.kafka.connect.errors.ConnectException: No fields found using key and value schemas for table: DJ

   at io.confluent.connect.jdbc.sink.metadata.FieldsMetadata.extract(FieldsMetadata.java:190)

   at io.confluent.connect.jdbc.sink.metadata.FieldsMetadata.extract(FieldsMetadata.java:58)

   at io.confluent.connect.jdbc.sink.BufferedRecords.add(BufferedRecords.java:65)

   at io.confluent.connect.jdbc.sink.JdbcDbWriter.write(JdbcDbWriter.java:62)

   at io.confluent.connect.jdbc.sink.JdbcSinkTask.put(JdbcSinkTask.java:66)

   at org.apache.kafka.connect.runtime.WorkerSinkTask.deliverMessages(WorkerSinkTask.java:435)

   at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:251)

   at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:180)

   at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:148)

   at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:146)

   at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:190)

   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)

第二个配置 -

internal.key.converter.schemas.enable=true

internal.value.converter.schemas.enable=true

日志:

[2017-08-28 16:23:50,993] INFO Revoking previously assigned partitions [] for group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:419)

[2017-08-28 16:23:50,993] INFO (Re-)joining group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:432)

[2017-08-28 16:23:51,260] INFO (Re-)joining group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:432)

[2017-08-28 16:23:51,381] INFO Successfully joined group connect-oracle_sink with generation 29 (org.apache.kafka.clients.consumer.internals.AbstractCoordinator:399)

[2017-08-28 16:23:51,384] INFO Setting newly assigned partitions [DJ-7, DJ-6, DJ-5, DJ-4, DJ-3, DJ-2, DJ-1, DJ-0, DJ-9, DJ-8] for group connect-oracle_sink (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:262)

[2017-08-28 16:23:51,727] ERROR Task oracle_sink-0 threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask:148)

org.apache.kafka.connect.errors.DataException: JsonConverter with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. If you are trying to deserialize plain JSON data, set schemas.enable=false in your converter configuration.

   at org.apache.kafka.connect.json.JsonConverter.toConnectData(JsonConverter.java:308)

Oracle connector.properties 看起来像

Oracle connector.properties looks like

name=oracle_sink

connector.class=io.confluent.connect.jdbc.JdbcSinkConnector

tasks.max=1

topics=DJ

connection.url=jdbc:oracle:thin:@hostname:port:sid

connection.user=username

connection.password=password

#key.converter=org.apache.kafka.connect.json.JsonConverter

#value.converter=org.apache.kafka.connect.json.JsonConverter

auto.create=true

auto.evolve=true

Connect-Standalone.properties

Connect-Standalone.properties

我的 JSON 看起来像 - 

{"Item":"12","Sourcing Reason":"corr","Postal Code":"l45","OrderNum":"10023","Intended Node Distance":1125.8,"Chosen Node":"34556","Quantity":1,"Order Date":1503808765201,"Intended Node":"001","Chosen Node Distance":315.8,"Sourcing Logic":"reducesplits"}

推荐答案

Per 文档

接收器连接器需要架构知识，因此您应该使用合适的转换器，例如架构注册表附带的 Avro 转换器，或启用架构的 JSON 转换器.

因此，如果您的数据是 JSON，您将具有以下配置:

So if your data is JSON you would have the following configuration: 

[...]
"value.converter": "org.apache.kafka.connect.json.JsonConverter",
"value.converter.schemas.enable": "true",
[...]

您在第二个实例中看到的错误是相关的——JsonConverter with schemas.enable 需要schema"和payload"字段——您共享的 JSON 不符合此要求的格式.

The error you see in the second instance is pertinent -- JsonConverter with schemas.enable requires "schema" and "payload" fields - the JSON you share does not meet this required format.

下面是一个带有 schema 和 payload 的有效 JSON 消息的简单示例:

Here's a simple example of a valid JSON message with schema and payload : 

{
    "schema": {
        "type": "struct",
        "fields": [{
            "type": "int32",
            "optional": true,
            "field": "c1"
        }, {
            "type": "string",
            "optional": true,
            "field": "c2"
        }, {
            "type": "int64",
            "optional": false,
            "name": "org.apache.kafka.connect.data.Timestamp",
            "version": 1,
            "field": "create_ts"
        }, {
            "type": "int64",
            "optional": false,
            "name": "org.apache.kafka.connect.data.Timestamp",
            "version": 1,
            "field": "update_ts"
        }],
        "optional": false,
        "name": "foobar"
    },
    "payload": {
        "c1": 10000,
        "c2": "bar",
        "create_ts": 1501834166000,
        "update_ts": 1501834166000
    }
}

您尝试登陆 Oracle 的数据的来源是什么?如果是 Kafka Connect 入站，那么您只需使用相同的 converter 配置(Avro + Confluent Schema Registry)会更容易、更高效.如果它是自定义应用程序，则需要使其 (a) 使用 Confluent Avro 序列化器或 (b) 以上述所需格式编写 JSON，提供与消息内联的有效负载架构.

What's your source for the data that you're trying to land to Oracle? If it's Kafka Connect inbound then you simply use the same converter configuration (Avro + Confluent Schema Registry) would be easier and more efficient. If it's a custom application, you'll need to get it to either (a) use the Confluent Avro serialiser or (b) write the JSON in the required format above, providing the schema of the payload inline with the message.

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07-28 02:44
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