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30:52

Jeremy Pollack of Ancestry.com on Test-driven Development and More

Posted by Jeremy Pollack on  Feb 15, 2014

Hadoop, the distributive file system and MapReduce are just a few of the topics covered in this interview recorded live at QCon San Francisco 2013. Industry-standard Agile implementation and a lot of testing, assures the development team at Ancestry.com that they have an app that can handle the large traffic demands of the popular genealogy site.

29:36

Cliff Click on In-Memory Processing, 0xdata H20, Efficient Low Latency Java and GCs

Posted by Cliff Click on  Jan 10, 2014 1

Cliff Click explains 0xdata's H20, a clustering and in-memory math and statistics solution (available for Hadoop and standalone), writing H20's memory representation and compression in Java, low latency Java vs GCs, and much more.

27:41

Eva Andreasson on Hadoop, the Hadoop Ecosystem, Impala

Posted by Eva Andreasson on  Nov 11, 2013 1

Eva Andreasson explains the various Hadoop technologies and how they interact, real-time queries with Impala, the Hadoop ecosystem including Hue, Oozie, YARN, and much more.

Eli Collins on Hadoop

Posted by Eli Collins on  Aug 17, 2012

Eli Collins discusses Cloudera's CDH4 release, which tasks are well suited for Hadoop, Hadoop and MapReduce vs SQL, the state of Hadoop, and much more.

Stuart Halloway on Datomic, Clojure, Reducers

Posted by Stuart Halloway on  Aug 15, 2012

Stuart Halloway explains Datomic, programming transactional behavior with Datomic, Datalog and logic programming, programming with values, Clojure Reducers and much more.

Hadoop and NoSQL in a Big Data Environment

Posted by Ron Bodkin on  Feb 03, 2012

Ron Bodkin of Big Data Analytics discusses early adoption of Hadoop, NoSQL and big data technologies. He discusses common patterns and explains how developers can write low-level primitives to optimize MapReduce function. Other topics include Hive, Pig, multi tenancy, and security.

All things Hadoop

Posted by Ted Dunning on  Feb 02, 2012 2

In this interview Ted Dunning talk about Hadoop, its current usage and its future. He explains the reasons for Hadoop's success and make recommendations on how to start using it.

Ville Tuulos on Big Data and Map/Reduce in Erlang and Python with Disco

Posted by Ville Tuulos on  Jun 24, 2011

Ville Tuulos talks about Disco, the Map/Reduce framework for Python and Erlang, real-world data mining with Python, the advantages of Erlang for distributed and fault tolerant software, and more.

Rob Pike on Parallelism and Concurrency in Programming Languages

Posted by Rob Pike on  Feb 17, 2011 3

Rob Pike discusses concurrency in programming languages: CSP, channels, the role of coroutines, Plan 9, MapReduce and Sawzall, processes vs threads in Unix, and more programming language history.

Ron Bodkin on Big Data and Analytics

Posted by Ron Bodkin on  Jan 27, 2011

Ron Bodkin discusses big data architecture, real-time analytics, batch processing, map-reduce, and data science.

Laforge and Rocher Discuss the future of Groovy, Grails and Java

Posted by Graeme Rocher and Guillaume Laforge on  Dec 03, 2010

In this interview, Graeme Rocher and Guillaume Laforge of SpringSource talk about the present and future of the Grails framework and the Groovy language. Rocher talks about Grails 1.4 and some of its enhancements such as improvements to GORM. And Laforge discusses Groovy 1.8, which features new DSL authoring capabilities, among other things. They look at how Java’s future impacts their projects.

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