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  186. <h1>Welcome to Hadoop!</h1>
  187. <div id="minitoc-area">
  188. <ul class="minitoc">
  189. <li>
  190. <a href="#Getting+Started"> Getting Started </a>
  191. </li>
  192. <li>
  193. <a href="#Getting+Involved"> Getting Involved </a>
  194. </li>
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  197. <p>
  198. Hadoop is a software platform that lets one easily write and run
  199. applications that process vast amounts of data.</p>
  200. <p>Here's what makes Hadoop especially useful:</p>
  201. <ul>
  202. <li>
  203. <strong>Scalable:</strong>
  204. Hadoop can reliably store and process petabytes.</li>
  205. <li>
  206. <strong>Economical:</strong>
  207. It distributes the data and processing across clusters of
  208. commonly available computers. These clusters can number into the
  209. thousands of nodes.</li>
  210. <li>
  211. <strong>Efficient:</strong>
  212. By distributing the data, Hadoop can process it in parallel on
  213. the nodes where the data is located. This makes it extremely
  214. rapid.</li>
  215. <li>
  216. <strong>Reliable:</strong>
  217. Hadoop automatically maintains multiple copies of data and
  218. automatically redeploys computing tasks based on failures.</li>
  219. </ul>
  220. <p>
  221. Hadoop implements <a href="http://wiki.apache.org/lucene-hadoop/HadoopMapReduce">MapReduce</a>,
  222. using the Hadoop Distributed File System (<a href="hdfs_design.html"><acronym title="Hadoop Distributed File System">HDFS</acronym></a>) (see figure below.) MapReduce divides
  223. applications into many small blocks of work. HDFS creates
  224. multiple replicas of data blocks for reliability, placing them on
  225. compute nodes around the cluster. MapReduce can then process the
  226. data where it is located.
  227. </p>
  228. <p>Hadoop has been demonstrated on clusters with 2000 nodes.
  229. The current design target is 10,000 node clusters.</p>
  230. <p>Hadoop is a <a href="http://lucene.apache.org/">Lucene</a> sub-project
  231. that contains the distributed computing platform that was
  232. formerly a part of <a href="http://lucene.apache.org/nutch/">Nutch</a>.
  233. </p>
  234. <p>For more information about Hadoop, please see the <a href="http://wiki.apache.org/lucene-hadoop/">Hadoop wiki.</a>
  235. </p>
  236. <div id="" style="text-align: center;">
  237. <img id="" class="figure" alt="architecture" src="images/architecture.gif"></div>
  238. <a name="N1004E"></a><a name="Getting+Started"></a>
  239. <h2 class="h3"> Getting Started </h2>
  240. <div class="section">
  241. <p>
  242. The Hadoop project plans to scale Hadoop up to handling thousands of computers. However, to begin with you can start by installing in on a single machine or a very small cluster.
  243. </p>
  244. <ol>
  245. <li>
  246. <a href="documentation.html">Learn about</a> Hadoop by reading the documentation.</li>
  247. <li>
  248. <a href="releases.html">Download</a> Hadoop from the release page.</li>
  249. <li>Hadoop <a href="quickstart.html">Quickstart</a>.</li>
  250. <li>
  251. <a href="cluster_setup.html">Hadoop Cluster Setup</a>.</li>
  252. <li>
  253. <a href="mailing_lists.html">Discuss it</a> on the mailing list.</li>
  254. </ol>
  255. </div>
  256. <a name="N1007A"></a><a name="Getting+Involved"></a>
  257. <h2 class="h3"> Getting Involved </h2>
  258. <div class="section">
  259. <p>
  260. Hadoop is an open source volunteer project under the Apache Software Foundation. We encourage you to learn about the project and contribute your expertise. Here are some starter links:
  261. </p>
  262. <ol>
  263. <li>See our <a href="http://wiki.apache.org/lucene-hadoop/HowToContribute">How to Contribute to Hadoop</a> page.</li>
  264. <li>Give us <a href="issue_tracking.html">feedback</a>: What can we do better?</li>
  265. <li>Join the <a href="mailing_lists.html">mailing list</a>: Meet the community.</li>
  266. </ol>
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