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Divide-and-conquer approach to sort the list (38, 27, 43, 3, 9, 82, 10) in increasing order. Upper half: splitting into sublists; mid: a one-element list is trivially sorted; lower half: composing sorted sublists. The divide-and-conquer paradigm is often used to find an optimal solution of a problem.
Free lists make the allocation and deallocation operations very simple. To free a region, one would just link it to the free list. To allocate a region, one would simply remove a single region from the end of the free list and use it. If the regions are variable-sized, one may have to search for a region of large enough size, which can be ...
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Ability to break volume into chunks then rejoin for batch of parallel processing. Automatic iso-surfacing using a threshold system. Converting images to contours (vector form) and vice versa. Segmentation: Allows manual tracing of regions of interest using closed contours, open contours (for tubes) and scattered pints (for spheres).
In data deduplication, data synchronization and remote data compression, Chunking is a process to split a file into smaller pieces called chunks by the chunking algorithm. It can help to eliminate duplicate copies of repeating data on storage, or reduces the amount of data sent over the network by only selecting changed chunks.
A job scheduler is a computer application for controlling unattended background program execution of jobs. [1] This is commonly called batch scheduling, as execution of non-interactive jobs is often called batch processing, though traditional job and batch are distinguished and contrasted; see that page for details.
Flow-based programming defines applications using the metaphor of a "data factory". It views an application not as a single, sequential process, which starts at a point in time, and then does one thing at a time until it is finished, but as a network of asynchronous processes communicating by means of streams of structured data chunks, called "information packets" (IPs).
The master maintains all of the files's metadata, including file names, directories, and the mapping of files to the list of chunks that contain each file's data. The metadata is kept in the master server's main memory, along with the mapping of files to chunks. Updates to this data are logged to an operation log on disk.