Foreword
One point that I attempt to impress upon people learning about Big Data is that while Apache Hadoop is quite useful, and most certainly quite successful as a technology, the underlying premise has become dated. Consider the timeline: MapReduce implementation by Google came from work that dates back to 2002, published in 2004. Yahoo! began to sponsor the Hadoop project in 2006. MR is based on the economics of data centers from a decade ago. Since that time, so much has changed: multi-core processors, large memory spaces, 10G networks, SSDs, and such, have become cost-effective in the years since. These dramatically alter the trade-offs for building fault-tolerant distributed systems at scale on commodity hardware.
Moreover, even our notions ...
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