Only Map objects supported in absence of schema for record conversion to BigQuery format - apache-kafka

Question

I'm streaming data from Postgres to Kakfa to Big Query. Most tables in PG have a primary key, as such most tables/topics have an Avro key and value schema, these all go to Big Query fine.
I do have a couple of tables that do not have a PK, and subsequently have no Avro key schema.
When I create a sink connector for those tables the connector errors with,
Caused by: com.wepay.kafka.connect.bigquery.exception.ConversionConnectException: Only Map objects supported in absence of schema for record conversion to BigQuery format.
If I remove the 'key.converter' config then I get 'Top-level Kafka Connect schema must be of type 'struct'' error.
How do I handle this?
Here's the connector config for reference,
{
"project": "staging",
"defaultDataset": "data_lake",
"keyfile": "<redacted>",
"keySource": "JSON",
"sanitizeTopics": "true",
"kafkaKeyFieldName": "_kid",
"autoCreateTables": "true",
"allowNewBigQueryFields": "true",
"upsertEnabled": "false",
"bigQueryRetry": "5",
"bigQueryRetryWait": "120000",
"bigQueryPartitionDecorator": "false",
"name": "hd-sink-bq",
"connector.class": "com.wepay.kafka.connect.bigquery.BigQuerySinkConnector",
"tasks.max": "1",
"key.converter": "io.confluent.connect.avro.AvroConverter",
"key.converter.schema.registry.url": "<redacted>",
"key.converter.basic.auth.credentials.source": "USER_INFO",
"key.converter.schema.registry.basic.auth.user.info": "<redacted>",
"value.converter": "io.confluent.connect.avro.AvroConverter",
"value.converter.schema.registry.url": "<redacted>",
"value.converter.basic.auth.credentials.source": "USER_INFO",
"value.converter.schema.registry.basic.auth.user.info": "<redacted>",
"topics": "public.event_issues",
"errors.tolerance": "all",
"errors.log.include.messages": "true",
"errors.deadletterqueue.topic.name": "connect.bq-sink.deadletter",
"errors.deadletterqueue.topic.replication.factor": "1",
"errors.deadletterqueue.context.headers.enable": "true",
"transforms": "tombstoneHandler",
"offset.flush.timeout.ms": "300000",
"transforms.dropNullRecords.predicate": "isNullRecord",
"transforms.dropNullRecords.type": "org.apache.kafka.connect.transforms.Filter",
"transforms.tombstoneHandler.behavior": "drop_warn",
"transforms.tombstoneHandler.type": "io.aiven.kafka.connect.transforms.TombstoneHandler"
}

Answer 1

For my case, I used to handle such case by using the predicate, as following
{
...
"predicates.isTombstone.type":
"org.apache.kafka.connect.transforms.predicates.RecordIsTombstone",
"predicates": "isTombstone",
"transforms.x.predicate":"isTombstone",
"transforms.x.negate":true
...
}
This as per the docs here, and the transforms.x.negate will skip such tompStone records.