|
Apache Beehive
Apache Beehive is a discontinued Java Application Framework that was designed to simplify the development of Java EE-based applications. It makes use of various open-source projects at Apache such as XMLBeans. Apache Beehive uses Java 5, including JSR-175, a facility for annotating fields, methods, and classes so that they can be treated in special ways by runtime tools. It builds on the framework developed for BEA Systems Weblogic Workshop for its 8.1 series. BEA later decided to donate the code to Apache. History Version 8.1 of BEA's Weblogic Workshop includes a number of improvements over version 7.0. The previous version was focused on creating industrial-strength web services quickly, and it failed due to low adoption and use. For version 8.1, BEA created a whole new Integrated Development Environment ( IDE) which helped programmers to develop Java EE-based applications more quickly. The improvements in 8.1 over version 7 garnered several awards. Although Workshop 8.1 o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
 |
Hadoop
Apache Hadoop () is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Hadoop was originally designed for computer clusters built from commodity hardware, which is still the common use. It has since also found use on clusters of higher-end hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework. The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part which is a MapReduce programming model. Hadoop splits files into large blocks and distributes them across nodes in a cluster. It then transfers packaged code into nodes to process the data in parallel. Thi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |