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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.
The Linux-HA (High-Availability Linux) project provides a high-availability solution for Linux, FreeBSD, OpenBSD, Solaris and Mac OS X which promotes reliability, availability, and serviceability (RAS). [1] The project's main software product is Heartbeat, a GPL-licensed portable cluster management program for high-availability clustering. Its ...
According to the Java BluePrints, the business logic of an application resides in Enterprise Beans—a modular server component providing many features, including declarative transaction management, and improving application scalability. Web container: the web modules include Jakarta Servlets and Jakarta Server Pages (JSP).
Aspen Systems Inc - Aspen Cluster Management Environment (ACME) Borg, used at Google; Bright Cluster Manager, from Bright Computing; ClusterVisor, [2] from Advanced Clustering Technologies [3] CycleCloud, from Cycle Computing acquired By Microsoft; Komodor, Enterprise Kubernetes Management Platform; Dell/EMC - Remote Cluster Manager (RCM)
Limited availability Heterogeneous Yes Yes Fully configurable Yes tested ~50,000 Millions Yes MPI, OpenMP Yes Yes: OpenLava: C/C++ OS authentication None NFS Heterogeneous Linux Yes Yes Configurable Yes Yes, supports preemption based on priority Yes Yes No Slurm: C: Munge, None, Kerberos Heterogeneous Yes Yes Multifactor Fair-share yes tested 120k
The most common size for an HA cluster is a two-node cluster, since that is the minimum required to provide redundancy, but many clusters consist of many more, sometimes dozens of nodes. The attached diagram is a good overview of a classic HA cluster, with the caveat that it does not make any mention of quorum/witness functionality (see above).
In computer science, data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data, financial transactions etc. Data stream clustering is usually studied as a streaming algorithm and the objective is, given a sequence of points, to construct a good clustering of the stream, using a small amount of memory and time.
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.