PUBLIC MARKS with tags concurrent & java

Kilim is a message-passing framework for Java that provides ultra-lightweight threads and facilities for fast, safe, zero-copy messaging between these threads.

Erjang is a virtual machine for Erlang, which runs on Java

ScalaCheck is a powerful tool for automatic unit testing of Scala and Java programs. It features automatic test case generation and minimization of failing test cases. ScalaCheck started out as a Scala port of the Haskell library QuickCheck, and has since evolved and been extended with features not found in Haskell QuickCheck.

Scala is an exciting, modern, multi-paradigm language for the JVM. You can use it to write traditional, imperative, object-oriented code. But you can also leverage its higher level of abstraction to take full advantage of modern, multicore systems. Programming Scala will show you how to use this powerful functional programming language to create highly scalable, highly concurrent applications on the Java Platform.

Java to Scala with the Help of Experts

Scala is a general purpose programming language designed to express common programming patterns in a concise, elegant, and type-safe way. It smoothly integrates features of object-oriented and functional languages, enabling Java and other programmers to be more productive. Code sizes are typically reduced by a factor of two to three when compared to an equivalent Java application

Clojure is a dynamic programming language that targets the Java Virtual Machine. It is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Every feature supported by Clojure is supported at runtime. Clojure provides easy access to the Java frameworks, with optional type hints and type inference, to ensure that calls to Java can avoid reflection.

EventMachine is a library for Ruby, C , and Java programs. It provides event-driven I/O using the Reactor pattern. EventMachine is designed to simultaneously meet two key needs: * Extremely high scalability, performance and stability for the most demanding production environments; and * An API that eliminates the complexities of high-performance threaded network programming, allowing engineers to concentrate on their application logic. This unique combination makes EventMachine a premier choice for designers of critical networked applications, including web servers and proxies, email and IM production systems, authentication/authorization processors, and many more.

Even though the Hadoop framework is written in Java, programs for Hadoop need not to be coded in Java but can also be developed in other languages like Python or C (the latter since version 0.14.1). However, the documentation and the most prominent Python example on the Hadoop home page could make you think that you must translate your Python code using Jython into a Java jar file. Obviously, this is not very convenient and can even be problematic if you depend on Python features not provided by Jython. Another issue of the Jython approach is the overhead of writing your Python program in such a way that it can interact with Hadoop - just have a look at the example in ${HADOOP_INSTALL}/src/examples/python/WordCount.py and you see what I mean. I still recommend to have at least a look at the Jython approach and maybe even at the new C MapReduce API called Pipes, it's really interesting. Having that said, the ground is prepared for the purpose of this tutorial: writing a Hadoop MapReduce program in a more Pythonic way, i.e. in a way you should be familiar with.