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Sequential access is a term describing a group of elements (such as data in a memory array or a disk file or on magnetic-tape data storage) being accessed in a predetermined, ordered sequence. It is the opposite of random access , the ability to access an arbitrary element of a sequence as easily and efficiently as any other at any time.
In computing, sequential access memory (SAM) is a class of data storage devices that read stored data in a sequence. This is in contrast to random access memory (RAM) where data can be accessed in any order. Sequential access devices are usually a form of magnetic storage or optical storage. [1] [2]
The general class includes variations such as the B+ tree, the B * tree and the B *+ tree. In the B+ tree, the internal nodes do not store any pointers to records, thus all pointers to records are stored in the leaf nodes. In addition, a leaf node may include a pointer to the next leaf node to speed up sequential access. [2]
In computing, a memory access pattern or IO access pattern is the pattern with which a system or program reads and writes memory on secondary storage.These patterns differ in the level of locality of reference and drastically affect cache performance, [1] and also have implications for the approach to parallelism [2] [3] and distribution of workload in shared memory systems. [4]
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.
Memory ordering is the order of accesses to computer memory by a CPU. Memory ordering depends on both the order of the instructions generated by the compiler at compile time and the execution order of the CPU at runtime .
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
A queue is an example of a linear data structure, or more abstractly a sequential collection. Queues are common in computer programs, where they are implemented as data structures coupled with access routines, as an abstract data structure or in object-oriented languages as classes.