JDBC接收器连接器产生的错误:
org.apache.kafka.connect.errors.DataException: Invalid Java object for schema type INT64: class java.util.Date for field: "some_timestamp_field"
at org.apache.kafka.connect.data.ConnectSchema.validateValue(ConnectSchema.java:242)
at org.apache.kafka.connect.data.Struct.put(Struct.java:216)
at org.apache.kafka.connect.transforms.Cast.applyWithSchema(Cast.java:151)
at org.apache.kafka.connect.transforms.Cast.apply(Cast.java:107)
at org.apache.kafka.connect.runtime.TransformationChain.apply(TransformationChain.java:38)
at org.apache.kafka.connect.runtime.WorkerSinkTask.convertMessages(WorkerSinkTask.java:480)
at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:301)
at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:205)
at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:173)
at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:170)
at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:214)
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)
由源JDBC连接器(MySQL)注册的avro模式:
{
"type":"record",
"name":"ConnectDefault",
"namespace":"io.confluent.connect.avro",
"fields":[
...
{
"name":"some_timestamp_field",
"type":{
"type":"long",
"connect.version":1,
"connect.name":"org.apache.kafka.connect.data.Timestamp",
"logicalType":"timestamp-millis"
}
},
...
]
}
因此,在Avro架构中,时间戳字段以正确的(时间戳)逻辑类型注册为INT64。但是connect会将架构类型读取为INT64
,并将其与值类型java.util.Date
进行比较。
这是一个错误,还是可以解决的?可能是我缺少某种东西,因为它看起来像是标准的连接模型。
谢谢。
更新
接收器连接器配置:
{
"name": "sink",
"config": {
"connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",
"tasks.max": "1",
"topics": "topic",
"connection.url": "jdbc:postgresql://host:port/db",
"connection.user": "user",
"connection.password": "password",
"key.converter": "io.confluent.connect.avro.AvroConverter",
"key.converter.schema.registry.url": "http://host:port",
"value.converter": "io.confluent.connect.avro.AvroConverter",
"value.converter.schema.registry.url": "http://host:port",
"auto.create": "true",
"insert.mode": "upsert",
"pk.mode": "record_value",
"pk.fields": "id"
}
}
在Kafka中反序列化的数据:
{
"id":678148,
"some_timestamp_field":1543806057000,
...
}
答案 0 :(得分:1)
我们为此问题制定了work around
。我们的目标是将ID从BIGINT转换为STRING(TEXT / VARCHAR)并将记录保存在下游数据库中。
但是由于一个问题(可能是https://issues.apache.org/jira/browse/KAFKA-5891),强制转换id字段无效。 Kafka也在尝试在转换链中验证时间戳记字段,但是读取模式类型/名称错误并导致类型不匹配(请参见上面的记录主体和错误日志)。
因此,我们进行了以下工作:
extract only the id field as key
-> execute cast transform on the key
-> it works as key does not contain timestamp field
。
以下是解决方法:
{
"name": "sink",
"config": {
"connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",
"tasks.max": "1",
"topics": "topic",
"connection.url": "jdbc:postgresql://host:port/db",
"connection.user": "user",
"connection.password": "password",
"key.converter": "io.confluent.connect.avro.AvroConverter",
"key.converter.schema.registry.url": "http://host:port",
"value.converter": "io.confluent.connect.avro.AvroConverter",
"value.converter.schema.registry.url": "http://host:port",
"transforms": "createKey,castKeyToString",
"transforms.createKey.type": "org.apache.kafka.connect.transforms.ValueToKey",
"transforms.createKey.fields": "id",
"transforms.castKeyToString.type": "org.apache.kafka.connect.transforms.Cast$Key",
"transforms.castKeyToString.spec": "id:string",
"auto.create": "true",
"insert.mode": "upsert",
"pk.mode": "record_key",
"pk.fields": "id"
}
}
免责声明:这不是一个正确的解决方案,只是一种解决方法。强制转换转换中的错误应已修复。我认为,转换转换只应关注指定用于转换的字段,而不要关注消息中的其他字段。
祝你有美好的一天。