What is backpressure handling in data streams?
An example of an AI chatbot conversation about backpressure handling in data streams.
What is backpressure handling in data streams?
Backpressure handling is a technique used in data streaming to manage the flow of data between producers and consumers, preventing data loss.
Why is backpressure important in streaming applications?
It's crucial because it helps maintain system stability and performance by ensuring that consumers can process data at their own pace.
Can you give an example of how backpressure is implemented?
Sure! In a system like Apache Kafka, backpressure can be managed by controlling the rate at which messages are produced based on the consumer's processing speed.
What happens if backpressure is not handled properly?
If not handled, it can lead to data loss, increased latency, and even system crashes due to overwhelming the consumers.
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