I hardly play the dino game which is created by Google and is available in Chrome browser for playing while there is no Internet connection. But the game itself is popular and can be found in different platforms. Recently I’ve changed two of them and now cacti and birds are ineffective.
I’ve started a project named Onion Harvester for finding the Onion addresses in TOR hidden services which are not exposed by the owners. I believe that the real dark markets and interesting stuff of TOR networks relies in the dark.
In this tutorial I want to write about using Apache Spark on Ubuntu machines where you can develop big data analysis apps with it.
First of all, I want to write a small and quick introduction to Hadoop + Spark environment. Hadoop makes it possible to work with lots of computers in a cluster. Work can be: storing files in cluster (HDFS – Hadoop Distributed File System), storing database in cluster (Apache HBase), or run software in cluster (MapReduce, Spark).
Library and Book management is one of my favorite hobbies. I like to categorize (e)books, Albums, and Movies. It is more better if the contents are in my profession, IT!
Recently I and two of my students, have managed lots of IT Ebooks which I am going to tell it’s story.
Recently I’ve interested in byte code structure of Java and Dalvik. I’ve found some useful tools for playing with them.
Destination Byte Code
Java byte codes are simple to reverse engineering because they compile in run time. i.e. JVM will execute the byte codes in run time, thus Java code is cross platform but executes with more delay than direct compiled machine codes (for example using C++ and gcc).