Cloudera Engineering Blog · Hadoop Posts

Customer Spotlight: Persado Makes Marketing a Data Science

It’s common to hear people describe themselves as being “left-brained” or “right-brained” based on their tendency to be more logical and mathematically driven (left-brained), or, conversely, to be intuitive and creatively driven (right-brained). For example, people who prefer math over art are often considered left-brained. People who get a higher verbal score on their SATs than for math are often considered right-brained.

In general, language and creative writing are considered right-brained exercises. Many people also associate marketing and advertising as a right-brained function, whereas engineering is considered very left-brained.

Meet the Project Founder: Josh Wills

In this installment of “Meet the Project Founder,” we speak with Josh Wills (@josh_wills), Cloudera’s Senior Director of Data Science and founder of Apache Crunch and Cloudera ML.

What led you to your project idea(s)?
When I first started at Cloudera in 2011, I had a fairly vague job description, no real responsibilities, and wasn’t all that familiar with the Apache Hadoop stack, so I started working on various pet projects in order to learn more about the tools and the use cases in domains like healthcare and energy.

Hadoop Administrator Training Gets Hands-On

I’ve always held a strong bias that education is most effective when the student learns by doing. As a developer of technical curricula, my goal is to have training participants engage with real and relevant problems as much as possible through hands-on exercises. The high rate at which Apache Hadoop is changing, both as a technology and as an ecosystem, makes developing Cloudera training courses not only demanding but also seriously fun and rewarding.

I recently undertook the challenge of upgrading the Cloudera Administrator Training for Apache Hadoop. I more than quadrupled the amount of hands-on exercises from the previous version, adding a full day to the course. At four days, it’s now the most thorough training for Hadoop administrators and truly the best way to start building expertise.

Secrets of Cloudera Support: Impala and Search Make the Customer Experience Even Better

In December 2012, we described how an internal application built on CDH called Cloudera Support Interface (CSI), which drastically improves Cloudera’s ability to optimally support our customers, is a unique and instructive use case for Apache Hadoop. In this post, we’ll follow up by describing two new differentiating CSI capabilities that have made Cloudera Support yet more responsive for customers:

Email Indexing Using Cloudera Search

Why would any company be interested in searching through its vast trove of email? A better question is: Why wouldn’t everybody be interested? 

Email has become the most widespread method of communication we have, so there is much value to be extracted by making all emails searchable and readily available for further analysis. Some common use cases that involve email analysis are fraud detection, customer sentiment and churn, lawsuit prevention, and that’s just the tip of the iceberg. Each and every company can extract tremendous value based on its own business needs. 

Next Stops for The Cloudera Sessions: Jersey City, Miami, Denver, Milwaukee

Cloudera Sessions

In its first leg of its tour of the United States earlier this year (see photos here), The Cloudera Sessions proved to be an invaluable single-day event for business and technical leaders exploring practical applications of Apache Hadoop. So valuable, in fact, that we’ve extended the tour with dates/cities this September and October.

This Month in the Ecosystem (August 2013)

Welcome to our second edition of “This Month in the Ecosystem.” (See the inaugural edition here.) Although August was not as busy as July, there are some very notable highlights to report.

How-to: Select the Right Hardware for Your New Hadoop Cluster

One of the first questions Cloudera customers raise when getting started with Apache Hadoop is how to select appropriate hardware for their new Hadoop clusters.

Although Hadoop is designed to run on industry-standard hardware, recommending an ideal cluster configuration is not as easy as delivering a list of hardware specifications. Selecting hardware that provides the best balance of performance and economy for a given workload requires testing and validation. (For example, users with IO-intensive workloads will invest in more spindles per core.)

Hadoop 2 is Now a Beta

As announced last Sunday (Aug. 25) on the project mailing list, Apache Hadoop 2.1.0 is the first beta release for Hadoop 2. (See the Release Notes for full list of new features and fixes.) Our congratulations to the Hadoop community for reaching this important milestone in the ongoing adoption of the core Hadoop platform!

With the release of this new beta, and the follow-on GA release on the horizon, we expect to see more customers exploring Hadoop 2 for production use cases. In fact, the upcoming CDH5 beta will be based on the Hadoop 2 GA release, delivering features that we’ve thoroughly tested against enterprise requirements, including (but not limited to):

Visualization on Impala: Big, Real-Time, and Raw

The guest post below is provided by Justin Langseth, Founder & CEO of Zoomdata, Inc. Thanks, Justin!

What if you could affordably manage billions of rows of raw Big Data and let typical business people analyze it at the speed of thought in beautiful, interactive visuals? What if you could do all the above without worrying about structuring that data in a data warehouse schema, moving it, and pre-defining reports and dashboards? With the approach I’ll describe below, you can.

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