PUBLIC MARKS from ogrisel with tags java & api

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.

The Java™ Transaction API (JTA) allows applications to perform distributed transactions, that is, transactions that access and update data on two or more networked computer resources. The JTA specifies standard Java interfaces between a transaction manager and the parties involved in a distributed transaction system: the application, the application server, and the resource manager that controls access to the shared resources affected by the transactions. This document provides an overview of that process and how the DataDirect Connect® for JDBC™ drivers relate to it.