InfoQ eMag: Hadoop
Apache Hadoop is proving useful in deriving insights out of large amounts of data, and is seeing rapid improvements. Hadoop 2 now goes beyond Map-Reduce; it is more modular, pluggable and flexible and it fits a variety of use cases better. We explore this as well as some tools that can help utilize Hadoop better.
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Dean Wampler on Scalding, NoSQL, Scala, Functional Programming and Big Data
Dec 16, 2013
Dean Wampler explains Scalding and the other Hadoop support libraries, the return of SQL, how (big) data is the killer application for functional programming, Java 8 vs Scala, and much more.
Optimizing for Big Data at Facebook
Apr 17, 2012
Hive co-creator Ashish Thusoo describes the Big Data challenges Facebook faced and presents solutions in 2 areas: Reduction in the data footprint and CPU utilization. Generating 300 to 400 terabytes per day, they store RC files as blocks, but store as columns within a block to get better compression. He also talks about the current Big Data ecosystem and trends for companies going forward.
Hadoop Summit 2014 Day One - On the Path to Enterprise Grade Hadoop by Jeevak Kasarkod Posted on Jun 04, 2014
Hortonworks Announces Hive 0.13 with Vectorized Query Execution and Hive on Tez by Matt Kapilevich Posted on May 13, 2014
Interactive SQL in Apache Hadoop with Impala and Hive by Alex Giamas Posted on Feb 07, 2014
Greenplum Pivotal HD Combines the Strengths of SQL and Hadoop by Abel Avram Posted on Feb 27, 2013
Competition between Real-time Hadoop Implementations Heats Up by Boris Lublinsky Posted on Feb 25, 2013 7