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MapReduce is a programming model for processing vast amounts of data. One of the reasons that it works so well is because it exploits a sweet spot of modern disk drive technology trends. In essence MapReduce works by repeatedly sorting and merging data that is streamed to and from disk at the transfer rate of the disk. Contrast this to accessing data from a relational database that operates at the
Grid Appliance Downloads
We have added several new tutorials to this site. Here is a roadmap to help you find out how to get started using the appliance based on your goals: Quick start (~30 minutes) – try out the appliance and familiarize with its basic functionalityDeploy a small pool of your own (~1-2 hours) – run an independent Grid appliance pool in your own resourcesDeploy a local desktop Grid (hours/days) – run med
Scaling Hadoop to 4000 nodes at Yahoo! (Hadoop and Distributed Computing at Yahoo!)
We recently ran Hadoop on what we believe is the single largest Hadoop installation, ever: • 4000 nodes • 2 quad core Xeons @ 2.5ghz per node • 4x1TB SATA disks per node • 8G RAM per node • 1 gigabit ethernet on each node • 40 nodes per rack • 4 gigabit ethernet uplinks from each rack to the core (unfortunately a misconfiguration, we usually do 8 uplinks) • Red Hat Enterprise Linux AS relea
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