Name: Data Architectures for Streaming Applications by O'Reilly Radar in hadoop
Duration: 41 min 5 s
Description: In this episode of the O’Reilly Data Show I sat down with O’Reilly author Dean Wampler, big data architect at Lightbend. We talked about new architectures for stream processing, Scala, and cloud computing.

hadoop

Running from Wisconsin to Indiana: 80 miles, 12 hours, 1 day. Performed by Peter McNernery, with Elana Fishbein, Louis Kornfeld, Julia Hynes, and Teddy Shivers. Based on an interview with Brian Foy. Produced by Jonathan Mitchell.

Keep Running

If competition is an extreme sport, then Amazon is winning. Journalist Brad Stone examines the relentless entrepreneur Jeff Bezos and his company.

Jeff Bezos and Extreme Competition

On this episode of "Speaking of Bitcoin", join hosts Adam B. Levine, Andreas M. Antonopoulos, Stephanie Murphy and Jonathan Mohan for a discussion about loans in the world of crypto.
HODL. It's crypto-land philosophy for not selling your preferred token even when things look their most bleak. But where philosophy intersects with real-world concerns like shelter, food and the niceties of life, tactics have emerged offering both opportunities and risks. From smart contracts to bitcoin collateralized mortgages, the hosts discuss their experiences with loans in the world of crypto.
Credits
Today’s show featured Andreas M. Antonopoulos, Jonathan Mohan, Stephanie Murphy and Adam B. Levine, with editing by Adam B. Levine and music by Gurtybeats.com. Our episode art is a picture provided by The New York Public Library, modified by "Speaking of Bitcoin."
Any questions or comments? Send us an email at adam@speakingofbitcoin.show

SOB #496 The Ups and Downs of Crypto Loans

- Tell us something we don't know!
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- An Iowan on Jeopardy? (Waukee!)
- What's next for the Big 12?

Stranger Things ROCKS "Master of Puppets"!

Wall Street Journal's Josh Zumbrun details how airlines get rid of certain passengers on a flight and how passengers can fight against this issue.

The Science Behind Who Airlines Bump From a Flight—and How to Exploit It

Listen to an excerpt from I'M GLAD MY MOM DIED by Jennette McCurdy, read by the author.

I'M GLAD MY MOM DIED Audiobook Excerpt

The diary of a girl in the 1980s who-- forbidden to go out on dates-- resorts to finding love via the phone. To learn more about Mortified visit getmortified.com.  The Mortified Podcast is a proud member of Radiotopia from PRX. 

02 Sakena: Mr. Telephone Man

Jai Ranganathan, senior director of product management at Cloudera, on trends in the Hadoop ecosystem, cloud computing, the recent surge in interest in all things real time, and hardware trends

Jai Ranganathan On Architecting Big Data Applications In The Cloud

In this episode of the O’Reilly Data Show, I spoke with Fang Yu, co-founder and CTO of DataVisor. We discussed her days as a researcher at Microsoft, the application of data science and distributed computing to security, and hiring and training data scientists and engineers for the security domain.

Using Apache Spark to Predict Attack Vectors Among Billions of Users and Trillions of Events

In this episode of the O’Reilly Data Show I sat down with O’Reilly author Dean Wampler, big data architect at Lightbend. We talked about new architectures for stream processing, Scala, and cloud computing.

Data Architectures for Streaming Applications

In this episode of the O’Reilly Data Show, O’Reilly’s online managing editor Jenn Webb speaks with Natalino Busa on the topic of predictive analytics, the challenges of feature engineering, and a new class of techniques that is enabling features to emerge from patterns within the data. They also discuss the relationship between predictive techniques and high-quality microservices, and how machine learning is being used to improve financial services.

Understanding Predictive Analytics

In this episode I spoke with Michael Franklin, co-director of UC Berkeley’s AMPLab and chair of the Department of Computer Science at the University of Chicago. AMPLab is well-known in the data community for having originated Apache Spark, Alluxio (formerly Tachyon) and many other open source tools. Today marks the start of a two-day symposium commemorating the end of AMPLab, and we took the opportunity to reflect on its impressive accomplishments.

Building the Next-Generation Big Data Analytics Stack

In this episode of the Data Show, I spoke with Jason Dai, CTO of big data technologies at Intel, and co-chair of Strata + Hadoop World Beijing. Dai and his team are prolific and longstanding contributors to the Apache Spark project. Their early contributions to Spark tended to be on the systems side and included Netty-based shuffle, a fair-scheduler, and the “yarn-client” mode. Recently, they have been contributing tools for advanced analytics. In partnership with major cloud providers in China, they’ve written implementations of algorithmic building blocks and machine learning models that let Apache Spark users scale to extremely high-dimensional models and large data sets. They achieve scalability by taking advantage of things like data sparsity and Intel’s MKL software. Along the way, they’ve gained valuable experience and insight into how companies deploy machine learning models in real-world applications.

Deep Learning for Apache Spark

While shooting the cultish webserie “New York Minute”, Samuel Hirsch recorded some urban sounds and voices for this short Afro-American ballad.  
Recorded on March 2010 - Directed by Samuel Hirsch - Produced by http://arteradio.com
Balade sonore à New York, avec sons urbain et voix afro-américaines. Enregistrée et montée par Samuel Hirsch pendant le tournage de "New York Minute", la web série culte produite par ARTE Radio.  

Download : http://bit.ly/1gFFt92


NY state of mind

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

Data Architectures for Streaming Applications

O'Reilly Radar

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