Confluent CCDAK Dumps

Schema registry is a separate application that provides RESTful interface for storing and retrieving Avro schemas.

Kafka transfers data with zero copy and no transformation. Any transformation (including compression) is the responsibility of clients.

Data is stored on brokers.

Kafka Connect Sink is used to export data from Kafka to external databases and Kafka Connect Source is used to import from external databases into Kafka.

Here, you shouldn't commit offsets 11 or 10 as it would indicate that the message #10 has been processed successfully.

retention.ms can be configured at topic level while creating topic or by altering topic. It shouldn't be set at the broker level (log.retention.ms) as this would impact all the topics in the cluster, not just the one we are interested in

Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.idempotence=true which takes care of the out of ordering case on its own.

clients can interact with the schema registry using the HTTP or HTTPS interface

Latest means that data retrievals will start from where the offsets currently end

This metric shows the current lag (number of messages behind the broker)

Increasing the number of partition causes new messages keys to get hashed differently, and breaks the guarantee "same keys goes to the same partition". Kafka logs are immutable and the previous messages are not re-shuffled.

we have two tables, so the max number of tasks is 2

One consumer per partition assignment will keep 5 consumers idle.

Producer idempotence helps prevent the network introduced duplicates. More details

Keys are necessary if you require strong ordering or grouping for messages that share the same key. If you require that messages with the same key are always seen in the correct order, attaching a key to messages will ensure messages with the same key always go to the same partition in a topic. Kafka guarantees order within a partition, but not across partitions in a topic, so alternatively not providing a key - which will result in round-robin distribution across partitions - will not maintain such order.

Log compaction retains at least the last known value for each record key for a single topic partition. All compacted log offsets remain valid, even if record at offset has been compacted away as a consumer will get the next highest offset.

A Custom Partitioner allows you to easily customise how the partition number gets computed from a source message.

A kafka broker automatically creates a topic under the following circumstances- When a producer starts writing messages to the topic - When a consumer starts reading messages from the topic - When any client requests metadata for the topic

With this configuration, a single in-sync replica is still readable, but not writeable if the producer using acks=all

min.insync.replicas does not impact producers when acks=1 (only when acks=all)

Calling close() on consumer immediately triggers a partition rebalance as the consumer will not be available anymore.

This is active-passing as the replicated topic is used for read-only purposes only