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Because this method is asynchronous, it will not download the entire batch of data before returning. Instead, it will begin the download process using a non-blocking mechanism (such as a background thread ), and immediately return an unresolved, unrejected Task<byte[]> to this function.
In computer science, asynchronous I/O (also non-sequential I/O) is a form of input/output processing that permits other processing to continue before the I/O operation has finished.
A Runnable, however, does not return a result and cannot throw a checked exception. [4] Each thread can be scheduled [5] on a different CPU core [6] or use time-slicing on a single hardware processor, or time-slicing on many hardware processors. There is no general solution to how Java threads are mapped to native OS threads.
Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model. A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
In concurrent programming, a monitor is a synchronization construct that prevents threads from concurrently accessing a shared object's state and allows them to wait for the state to change. They provide a mechanism for threads to temporarily give up exclusive access in order to wait for some condition to be met, before regaining exclusive ...
The lost update problem: A second transaction writes a second value of a data-item (datum) on top of a first value written by a first concurrent transaction, and the first value is lost to other transactions running concurrently which need, by their precedence, to read the first value. The transactions that have read the wrong value end with ...
Gather/scatter is a type of memory addressing that at once collects (gathers) from, or stores (scatters) data to, multiple, arbitrary indices. Examples of its use include sparse linear algebra operations, [ 1 ] sorting algorithms, fast Fourier transforms , [ 2 ] and some computational graph theory problems. [ 3 ]
In computer science, the readers–writers problems are examples of a common computing problem in concurrency. [1] There are at least three variations of the problems, which deal with situations in which many concurrent threads of execution try to access the same shared resource at one time.