The core drivers of a Hadoop deployment have traditionally been scale, flexibility and economics. Flexibility is often touted as the ability to add a new dimension, dataset, or complex line of questioning without investing in a expensive, difficult multimonth project. It is true that Hadoop’s flexibility gives us the ability to collapse these projects into tasks and shorten the window by which they can be deliverer, but how far can we push this?
Graham Gear draws on real-world processes and systems to explain how it’s possible to apply continuous delivery techniques to advanced analytics, realizing business value earlier and more safely. Along the way Graham shows just how far we can push the flexibility of a modern advanced analytics platform.
Graham Gear is director of system engineering at Cloudera and an Apache Hadoop committer. Having thirstily read the Google papers that inspired Hadoop and watched as the community coalesced, Graham could clearly see the huge potential of the Hadoop ecosystem and has been contributing to the Hadoop ecosystem and helping organizations take advantage of it for many years. Previously, Graham delivered large-scale distributed systems with a keen analytical focus; he began his career implementing sonar algorithms leveraging MPI on large Beowulf clusters at a defense research institution.
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