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Kafka Connect (or Connect API) is a framework to import/export data from/to other systems. It was added in the Kafka 0.9.0.0 release and uses the Producer and Consumer API internally. The Connect framework itself executes so-called "connectors" that implement the actual logic to read/write data from other systems.
In some situations, overwriting circular buffer can be used, e.g. in multimedia. If the buffer is used as the bounded buffer in the producer–consumer problem then it is probably desired for the producer (e.g., an audio generator) to overwrite old data if the consumer (e.g., the sound card) is unable to momentarily
In computing, the producer-consumer problem (also known as the bounded-buffer problem) is a family of problems described by Edsger W. Dijkstra since 1965.. Dijkstra found the solution for the producer-consumer problem as he worked as a consultant for the Electrologica X1 and X8 computers: "The first use of producer-consumer was partly software, partly hardware: The component taking care of the ...
Zero-copy programming techniques can be used when exchanging data within a user space process (i.e. between two or more threads, etc.) and/or between two or more processes (see also producer–consumer problem) and/or when data has to be accessed / copied / moved inside kernel space or between a user space process and kernel space portions of operating systems (OS).
Further, (4) a common variant of the producer-consumer problem is to allow *multiple* producers and consumers, in which case an additional mutex is necessary in order to get mutual exclusion, but (5) the order in which producers / consumers wait and signal the mutex and semaphores may lead to deadlock if implemented incorrectly.
The pub/sub pattern scales well for small networks with a small number of publisher and subscriber nodes and low message volume. However, as the number of nodes and messages grows, the likelihood of instabilities increases, limiting the maximum scalability of a pub/sub network. Example throughput instabilities at large scales include:
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In distributed systems, events represent a fact or state change (e.g., OrderPlaced) and are typically broadcast asynchronously to multiple consumers, promoting loose coupling and scalability. While events generally don’t expect an immediate response, acknowledgment mechanisms are often implemented at the infrastructure level (e.g., Kafka ...