Concurrency is a computing approach in which the progress of multiple tasks is managed within the same period. These tasks do not necessarily have to run physically at the exact same moment. A single-processor system can switch rapidly between tasks and allow them to make overlapping progress. When multiple tasks are executed simultaneously on separate processor cores, the process is more accurately described as parallel computing.
Concurrent systems aim to use computing resources more efficiently and improve application responsiveness. For example, an application can continue operating while it waits for data from a network request. This approach can be used on personal computers, servers, mobile applications and distributed systems. It is particularly valuable in systems that must manage many independent tasks or user requests.
Processes or threads within a concurrent program may progress independently. However, coordination is required when they access the same memory, file or system resource. Synchronisation mechanisms ensure that shared resources are accessed in a controlled manner. Without appropriate controls, problems such as race conditions, inconsistent data and deadlocks may occur.
Concurrency is not limited to big data environments. Web servers, operating systems, messaging applications, games and user interfaces can all use concurrent processing. In big data systems, separate portions of a dataset may be processed within the same period and distributed across multiple machines. Memory allocation, network communication and processing order must be managed carefully in these environments.
Multithreading allows multiple threads to operate within the same program process. Threads may share the same memory, making communication between them relatively fast. However, uncontrolled access to shared resources can produce incorrect or inconsistent results. Locks, semaphores and other synchronisation tools may therefore be required.
Asynchronous programming allows a program to continue with other work while it waits for an operation to finish. For example, an application may accept another user command while waiting for a server response. This approach is particularly useful for network, file and database operations that involve considerable waiting time. However, asynchronous programming does not automatically mean that tasks are running simultaneously or in parallel.
Pre-emptive multitasking allows the operating system to control how running tasks use the processor. The system can interrupt one task and assign processing time to another. This prevents a single program from continuously occupying the processor and helps maintain responsiveness. Task switching and priority management are handled by the operating system scheduler.
Concurrent programming can improve performance and resource utilisation, but it can also make software development more complex. The order in which tasks finish may not always be predictable, and the same program may behave differently across separate executions. Shared data, error handling and dependencies between tasks must therefore be designed carefully. When implemented correctly, concurrency can make systems more scalable, efficient and responsive.
