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This example could be implemented with the Java 8 merge() but it shows the overall lock-free pattern, which is more general. This example is not related to the internals of the ConcurrentMap but to the client code's use of the ConcurrentMap. For example, if we want to multiply a value in the Map by a constant C atomically:
In Haskell, the polymorphic function map :: (a -> b) -> [a] -> [b] is generalized to a polytypic function fmap :: Functor f => (a -> b) -> f a -> f b, which applies to any type belonging the Functor type class. The type constructor of lists [] can be defined as an instance of the Functor type class using the map function from the previous example:
Apache Cayenne, open-source for Java; Apache OpenJPA, open-source for Java; DataNucleus, open-source JDO and JPA implementation (formerly known as JPOX) Ebean, open-source ORM framework; EclipseLink, Eclipse persistence platform; Enterprise JavaBeans (EJB) Enterprise Objects Framework, Mac OS X/Java, part of Apple WebObjects
Object pooling can offer a significant performance boost in situations where the cost of initializing a class instance is high and the rate of instantiation and destruction of a class is high – in this case objects can frequently be reused, and each reuse saves a significant amount of time.
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 ...
Object–relational mapping (ORM, O/RM, and O/R mapping tool) in computer science is a programming technique for converting data between a relational database and the memory (usually the heap) of an object-oriented programming language. This creates, in effect, a virtual object database that can be used from within the programming language.
The goal of the pattern is to keep the in-memory representation and the persistent data store independent of each other and the data mapper itself. This is useful when one needs to model and enforce strict business processes on the data in the domain layer that do not map neatly to the persistent data store. [2]
For example, if the source system lists FirstName but the destination lists PersonGivenName, the mappings will still be made if these data elements are listed as synonyms in the metadata registry. Semantic mapping is only able to discover exact matches between columns of data and will not discover any transformation logic or exceptions between ...