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By definition the Internet is a worldwide, publicly accessible series of interconnected computer networks
that transmit data by packet switching using the standard Internet Protocol
Server Responses
100: Informational
100: Continue - Server receives request headers and client should proceed to send body
This will be a quick guide to get you introduced with one of the most popular and effective tools used for working with big data. Apache Spark is a cluster computing platform designed to be fast and general-purpose. On the speed side, Spark extends the popular MapReduce model to efficiently suport more types of computations, including interactive queries and stream processing.
Getting Spark
Unlike Hadoop, it is very easy to get Spark installed and running on your computer locally. But we have provided a pre-configured VM to get Spark and IPython notebook running quickly on your machine.
A VagrantFile is provided in the repository which will instantiate an Ubuntu virtual machine for you. The steps for running a vagrant VM has been explained in the previous assignment.
Once we have the machine up and running and you have ssh-ed into it, you will see a file spark-notebook.py in /home/vagrant directory.
Simply run this script using the command python spark_notebook.py. This wi
(This guide is meant for beginners.
If you have solved 100+ problems and are looking for guidance on
how to solve problems involving algorithms and data structures,
this document is not for you.)
Competitive Programming is an interesting activity which mixes problem solving with programming.
It is not only enjoyable but also very demanded in placements.
Competitive programming will make you very good at writing efficient programs quickly.
Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.
The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca
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