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Availability Every request received by a non-failing node in the system must result in a response. This is the definition of availability in CAP theorem as defined by Gilbert and Lynch. [1] Note that availability as defined in CAP theorem is different from high availability in software architecture. [5] Partition tolerance
Document Clustering Workbench added for easy experimenting with Carrot² clustering, radically simplified Java API, search results clustering web application re-implemented, user manual [5] available 2.1.0 August 2007 Document Clustering Server added for exposing clustering as a REST service 2.0.0 September 2006
The following tables compare general and technical information for notable computer cluster software. This software can be grossly separated in four categories: Job scheduler , nodes management, nodes installation and integrated stack (all the above).
Availability of parallel components = 1 - (1 - X)^ N [3] Using parallel components can exponentially increase the availability of overall system. [2] For example if each of your hosts has only 50% availability, by using 10 of hosts in parallel, you can achieve 99.9023% availability. [3] Note that redundancy doesn’t always lead to higher ...
Solaris Cluster is an example of kernel-level clustering software. Some of the processes it runs are normal system processes on the systems it operates on, but it does have some special access to operating system or kernel functions in the host systems.
MySQL Cluster, also known as MySQL Ndb Cluster is a technology providing shared-nothing clustering and auto-sharding for the MySQL database management system. It is designed to provide high availability and high throughput with low latency, while allowing for near linear scalability. [ 3 ]
The Hazelcast platform can manage memory for many types of applications. It offers an Open Binary Client Protocol to support APIs for any binary programming language. The Hazelcast and open-source community members have created client APIs for programming languages that include Java, .NET, C++, Python, Node.js and Go. [7]
Ordering points to identify the clustering structure (OPTICS) is an algorithm for finding density-based [1] clusters in spatial data. It was presented by Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel and Jörg Sander. [ 2 ]