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The Java programming language and the Java virtual machine (JVM) is designed to support concurrent programming. All execution takes place in the context of threads. Objects and resources can be accessed by many separate threads. Each thread has its own path of execution, but can potentially access any object in the program.
Free availability under the GNU General Public License. Portability, since it is fully implemented in the Java programming language and thus runs on almost any modern computing platform. A comprehensive collection of data preprocessing and modeling techniques. Ease of use due to its graphical user interfaces.
Raft offers a generic way to distribute a state machine across a cluster of computing systems, ensuring that each node in the cluster agrees upon the same series of state transitions. It has a number of open-source reference implementations, with full-specification implementations in Go, C++, Java, and Scala. [2]
In statistics and data mining, affinity propagation (AP) is a clustering algorithm based on the concept of "message passing" between data points. [1] Unlike clustering algorithms such as k-means or k-medoids, affinity propagation does not require the number of clusters to be determined or estimated before running the algorithm.
With the release of Oracle Database 10g Release 2 (10.2), Cluster Ready Services was renamed to Oracle Clusterware. When using Oracle 10g or higher, Oracle Clusterware is the only clusterware that you need for most platforms on which Oracle RAC operates (except for Tru cluster, in which case you need vendor clusterware).
Free Grid MP: Univa (formerly United Devices) Job Scheduler no active development Distributed master/worker HTC/HPC Proprietary: Windows, Linux, Mac OS X, Solaris Cost Apache Mesos: Apache actively developed Apache license v2.0 Linux Free Yes Moab Cluster Suite: Adaptive Computing Job Scheduler actively developed HPC Proprietary
BIRCH (balanced iterative reducing and clustering using hierarchies) is an algorithm used to perform connectivity-based clustering for large data-sets. [7] It is regarded as one of the fastest clustering algorithms, but it is limited because it requires the number of clusters as an input.
Fuzzy clustering (also referred to as soft clustering or soft k-means) is a form of clustering in which each data point can belong to more than one cluster.. Clustering or cluster analysis involves assigning data points to clusters such that items in the same cluster are as similar as possible, while items belonging to different clusters are as dissimilar as possible.