What is the role of backpressure in Reactive Streams, and how is it managed in Spring Boot?
- Backpressure controls the flow of data from the publisher to the subscriber.
- Backpressure is used to prevent data loss in case of slow consumers.
- Spring Boot doesn't support backpressure in Reactive Streams.
- Spring Boot uses thread blocking to handle backpressure.
Backpressure in Reactive Streams is a mechanism to deal with situations where a subscriber can't keep up with the rate of data emitted by the publisher. It allows the subscriber to signal the publisher to slow down or stop emitting data temporarily. Spring Boot handles backpressure by allowing subscribers to request a specific number of items they can handle, and the publisher will respect this request, preventing data loss or overwhelming the subscriber.
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