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During the development of JSP 2.0, the JavaServer Faces technology was released which also needed an expression language, but the expression language defined in the JSP 2.0 specification didn't satisfy all the needs for development with JSF technology.
A stream can be used similarly to a list, but later elements are only calculated when needed. Streams can therefore represent infinite sequences and series. [1] In the Smalltalk standard library and in other programming languages as well, a stream is an external iterator. As in Scheme, streams can represent finite or infinite sequences.
Because changing the kernel is a rather expensive operation the stream architecture also incurs penalties for small streams, a behaviour referred to as the short stream effect. Pipelining is a very widespread and heavily used practice on stream processors, with GPUs featuring pipelines exceeding 200 stages. The cost for switching settings is ...
Reactive Streams were proposed to become part of Java 9 by Doug Lea, leader of JSR 166 [8] as a new Flow class [9] that would include the interfaces currently provided by Reactive Streams. [5] [10] After a successful 1.0 release of Reactive Streams and growing adoption, the proposal was accepted and Reactive Streams was included in JDK9 via the ...
Apache Beam: Java/Scala SDK that unifies streaming (and batch) processing with several execution engines supported (Apache Spark, Apache Flink, Google Dataflow etc.) Apache Flink: Java/Scala library that allows streaming (and batch) computations to be run atop a distributed Hadoop (or other) cluster; Apache Spark
Standard input is a stream from which a program reads its input data. The program requests data transfers by use of the read operation. Not all programs require stream input. For example, the dir and ls programs (which display file names contained in a directory) may take command-line arguments, but perform their operations without any stream ...
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In computing, reactive programming is a declarative programming paradigm concerned with data streams and the propagation of change. With this paradigm, it is possible to express static (e.g., arrays) or dynamic (e.g., event emitters) data streams with ease, and also communicate that an inferred dependency within the associated execution model exists, which facilitates the automatic propagation ...
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