TheKafka Streams DSLprovides three primary abstractions:
* KStream: Represents an unbounded stream of records (append-only).
* KTable: Represents a changelog stream where each key has the latest value (like a materialized view).
* GlobalKTable: A fully replicated version of KTable across all stream instances, enabling global joins.
FromKafka Streams Developer Guide:
"Kafka Streams provides three core abstractions: KStream, KTable, and GlobalKTable, each serving different purposes in stream processing and joins."
* GlobalKStream and StreamTable donot existin Kafka's API.
Reference:Kafka Streams Concepts > KStream, KTable, GlobalKTable

Kafka Streams is a library for building streaming applications, specifically applications that transform input Kafka topics into output Kafka topics

batch.size controls how many bytes of data to collect before sending messages to the Kafka broker. Set this as high as possible, without exceeding available memory. Enabling compression can also help make more compact batches and increase the throughput of your producer. Linger.ms will have no effect as the batches are already full

For proper delivery handling with acks=all:
* Usecallbackto log or act on success/failure.
* Usetry/catchto handle synchronous exceptions like serialization errors or network failures.
FromKafka Producer Documentation:
"Errors can be caught either via the returned Future<RecordMetadata> or via the callback interface. For fatal errors, use a try/catch block around the send call." Option B is incorrect because send() returns a Future, not RecordMetadata directly.
Option D is invalid - ProducerRecord has no method called status().
Reference:Kafka Producer Error Handling and Callback APIs