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Friday, June 4th, 2021 7:37 AM

JDBC Driver for Apache Kafka

Please post here your remarks, questions or feedback regarding the Marketplace listing JDBC Driver for Apache Kafka.

1.2K Messages

3 years ago

Hi Paulo - We are having some trouble scraping schemas, we have a successful connection, but unsure what is missing from our configuration to pull the schema details.

Is this page monitored? can we post our challenges here?

38 Messages

Hi Jamie,
Yes, this page is for seeking help from the community. However, this JDBC driver is Supported, to if your issue requires it, you can log in a support ticket.
Best regards,
Paulo

3 years ago

Hi Paulo- Is there any documentation that explains asset model and relations that will be created by this JDBC driver for Apache Kafka.

2 Messages

I am looking also the Kafka asset model with an explanatory example. Is it available somewhere?

36 Messages

Hi @peep.kungas ,
the Asset Model the Kafka JDBC Driver creates is quite easy:
Schema > Table (= Kafka Topic) > Column (=Field inside of a Kafka Topic)

So basically, the driver treats Kafka as a relational database with tables and columns. Furthermore, the driver will ingest only one schema version of the Kafka topic (the most recent) in Collibra.

2 Messages

@laurenz.hiller, could you provide also naming convention examples for these assets, e.g. names and full names?

36 Messages

Hi @peep.kungas,

AVRO Schemas in Kafka typically contain complex data structures (nested object arrays with fields etc.). The Collibra JDBC driver for Kafka is not able to ingest these complex data structures in a natural way.
Instead, ingesting a Kafka topic leads to a flattened table with columns per Kafka Topic. The column names ingested into Collibra are just qualified (Object.Object.Column).

Example:
You have a Kafka topic called “customer” with three fields “customerId”, “firstName” and “lastName”. In addition, the topic contains an “address” object that contains “street”, “city” and “country” fields.

The following assets are created in Collibra:
Table: “customer”
Column: “customerId” (name) , “customer > customerId” (full name)
Column: “firstName” (name) , “customer > firstName” (full name)
Column: “lastName” (name) , “customer > lastName” (full name)
Column: “address.street” (name) , “customer > address.street” (full name)
Column: “address.city” (name) , “customer > address.city”" (full name)
Column: “address.country”" (name) , “customer > address.country” (full name)

1.2K Messages

2 years ago

By the way, has anyone tried Hackolade for this?
Confluent Schema Registry | Hackolade

It’s a polyglot data modeling tool that can reverse engineer data models (e.g. read avro schemas and create the corresponding model) and forward engineer into Collibra!
I planned to a test drive, but it looks like a fantastic way to capture all the nuances of models such as avro, json schema, xml, openAPI, mongoDB collection, etc.

1 Message

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50 Points

5 months ago

We're using the CDATA Kafka driver to ingest metadata from our Kafka service.

All topics are being collected and if the schema is simple, the data elements are appearing as columns in the topic (displayed as tables)

However, if the schema is more complex and refers internally to other schemas (i.e. nested) then the topic is created as a table, but is empty, i.e. no columns.

Has anyone come across this and come up with a solution?

I have raised an ideation to get this lack addressed. https://productresources.collibra.com/ideation-platform/?id=DIP-I-40

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