The book is dedicated to the paradigm of DOP (data-oriented programming), which is an extension of the philosophy of object-oriented programming. It offers a new perspective on the formation of data structures and operations on them in high-load applications. The...
material presented provides solutions to complex problems that arise in state management, shared and distributed data, allows for safe organization of parallelism and concurrency, and adapts key principles of object-oriented programming (polymorphism, composition, inheritance) to new tasks related to big data processing.
For data analysts, programmers, team leaders, and educators
The book is dedicated to the paradigm of DOP (data-oriented programming), which is an extension of the philosophy of object-oriented programming. It offers a new perspective on the formation of data structures and operations on them in high-load applications. The material presented provides solutions to complex problems that arise in state management, shared and distributed data, allows for safe organization of parallelism and concurrency, and adapts key principles of object-oriented programming (polymorphism, composition, inheritance) to new tasks related to big data processing.
For data analysts, programmers, team leaders, and educators
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