Benchmarking Big Data systems is nontrivial. Avoid these traps!
Here at Cloudera, we know how hard it is to get reliable performance benchmarking results. Benchmarking matters because one of the defining characteristics of Big Data systems is the ability to process large datasets faster. “How large” and “how fast” drive technology choices, purchasing decisions, and cluster operations. Even with the best intentions, performance benchmarking is fraught with pitfalls—easy to get numbers,
Welcome to our sixth edition of “This Month in the Ecosystem,” a digest of highlights from December 2013 (never intended to be comprehensive; for completeness, see the excellent Hadoop Weekly).
With the close of 2013, we also thought it appropriate to include some high points from across the year (not listed in any particular order):
One of the common questions I get from students and developers in my classes relates to IDEs and MapReduce: How do you create a MapReduce project in Eclipse and then debug it?
To answer that question, I have created a screencast showing you how, using Cloudera’s QuickStart VM. The QuickStart VM helps developers get started writing MapReduce code without having to worry about software installs and configuration. Everything is installed and ready to go.
Last week at Strata + Hadoop World 2012, we announced a new data science training and certification program. I am very excited to have been part of the team that put the program together, and I would like to answer some of the most frequently asked questions about the course and the certification that we will be offering.
Why is Cloudera offering data science training?
The primary bottleneck on the success of Hadoop is the number of people who are capable of using it effectively to solve business problems.
When most people first hear about data science, it’s usually in the context of how prominent web companies work with very large data sets in order to predict clickthrough rates, make personalized recommendations, or analyze UI experiments. The solutions to these problems require expertise with statistics and machine learning, and so there is a general perception that data science is intimately tied to these fields. However, in my conversations at academic conferences and with Cloudera customers,