I have Debezium in a container, capturing all changes of PostgeSQL database records.
How to delete all kafka topics which are created already and initiate ad-hoc snapshot from the beginning for all tables configured?
You can use kafka-topics --delete, just like any other topic. The Debezium ones typically match your database schema/table name. You'll also need to find the internal offsets topic created by Kafka Connect framework.
For Docker, though, if you restart Kafka and Zookeeper and they don't have volumes attached, then they'll lose everything, which would be easier for ad-hoc development.
Also, you don't need Zookeeper anymore, as of Kafka 3.3.1
Related
my question is split to two. I've read Kafka Connect - Delete Connector with configs?. I'd like to completely remove a connector, with offsets and all, so I can recreate it with the same name later. Is this possible? To my understanding, a tombstone message will kill this connector indefinitely.
The second part is - is there a way to have the kafka-connect container automatically delete all connectors he created when bringing it down?
Thanks
There is no such command to completely cleanup connector state. For sink connectors, you can use kafka-consumer-groups to reset it's offsets. For source connectors, it's not as straightforward, as you'll need to manually produce data into the Connect-managed offsets topic.
The config and status topics also persist historical data, but shouldn't prevent you from recreating the connector with the same name/details.
The Connect containers published by Confluent and Debezium always uses Distributed mode. You'll need to override the entrypoint of the container to use standalone mode to not persist the connector metadata in Kafka topics (this won't be fault tolerant, but it'll be fine for testing)
I am running a Debezium connector to PostgreSQL. The snapshot.mode I use is initial, since I don't want to resnapshot just because the connector has been restarted. However, during development I want to restart the process, as the messages expire from Kafka before they have been read.
If I delete and recreate the connector via Kafka Connect REST API, this doesn't do anything, as the information in the offset/status/config topics is preserved. I have to delete and recreate them when restarting the whole connect cluster to trigger another snapshot.
Am I missing a more convenient way of doing this?
You will also need a new name for the connector as well as a new database.server.name name in the connector config, which stores all the offset information. It should almost be like deploying a connector for the first time again.
I want to ingest data from a datawarehouse into kafka and then I want to store the avro records into mySQL RDMS. I want to eliminate the zookeeper dependency. Is it possible to do this without using zookeeper?
It is not considered production ready, but you are looking for Kafka KRaft mode.
bin/test-kraft-server-start.sh script will start the broker in this mode...
Docs - https://github.com/apache/kafka/tree/trunk/raft
Reference - https://cwiki.apache.org/confluence/display/KAFKA/KIP-500%3A+Replace+ZooKeeper+with+a+Self-Managed+Metadata+Quorum
I have a table that is updated once / twice a day, but I want the data to be pushed to Kafka immediately after the table is updated. Is it possible to avoid running the connector every poll.interval.ms, but rather to run it only after the table is updated (sync on demand or trigger the sync in some other way after the table update)
I apologize if this question is stupid... Can sink connector be running on one Kafka cluster, but pull messages from another Kafka cluster and insert them into Postgres. I'm not talking about replicating messages from Cluster A to Cluster B and then inserting messages from Cluster B to Postgres. I'm talking about Connector running on Cluster B but pulling messages from Cluster A and writing them to Postgres.
Thanks!
If you use log-based change data capture (Debezium, etc) then you capture changes as soon as they are there, without needing to re-query the database. If you use query-based CDC then you do have to query the database on a polling interval. For query-based vs log-based CDC see this blog or talk.
One option would be to use the Kafka Connect REST API to control the connector - but you're kind of going against the streaming paradigm here and will start to find awkward edges in doing this. For example, when do you decide to pause the connector? How do you determine that it's ingested all the changes? etc.
Using log-based CDC is low-impact on the source system and commonly the route that people go.
Kafka Connect does not run on your Kafka cluster. Kafka Connect runs as its own cluster. Physically, it can be co-located for purposes of dev/sandbox environment (this ref arch is useful for production). See also this talk "Running Kafka Connect".
So in your example, "Cluster B" is actually a Kafka Connect cluster - and it would be configured to read from Kafka cluster "A", and that is fine.
We are migrating our application from Apache Kafka to Confluent Platform .
Apache Kafka version:1.1.0
Confluent :4.1.0
Tried these options:
Manually copying the zookeeper logs and Kafka Logs- Not an optimal way
because of volume and data correctness.
Mirror Maker - This will replicate newly created topics and ACL. It will not
migrate old details in Apache Kafka
Please suggest better approaches on this.
You can keep your existing Kafka and Zookeeper installation.
Confluent does not change any way these run or manage data.
You can configure the REST Proxy, Schema Registry, Control Center, KSQL, etc. to use your existing bootstrap servers or Zookeeper connection; nothing should need migrated, you're only adding extra consumer/producer services which just happen to be provided by Confluent.
If you later plan on upgrading your brokers, then you can start up new ones from the Confluent package, migrate the partitions, then shut down the old ones. Similarly for Zookeeper, but make sure that you have at least 2 up during this process, and always have an odd number of them available after your transition