<ul><li>Message Passing Interface (MPI) and Apache Spark are two popular frameworks used for parallel and distributed computing.</li><li>MPI is a standardized and portable message-passing system designed for parallel computing, while Spark is an open-source analytics engine for processing large amounts of data.</li><li>Spark is more convenient but may compromise on performance, while MPI offers flexibility and maximum performance.</li><li>Spark is interpretive, offers less control over parallelism, and has JVM startup time implications, while MPI provides full control to the programmer and requires manual code implementation.</li></ul>

Data Processing With Python: Choosing Between MPI and Spark

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