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.
Barbara Liskov keynoted at QCon London 2013 on the power of abstraction. Afterwards, InfoQ caught up with up with her to ask her about language design, modularity and distributed computation.
Duncan Coutts on Parallelism and Concurrency with Haskell, Distributed Programming with Cloud Haskell
Duncan Coutts explains the nature of Concurrency and Parallelism in Haskell, its threading and STM implementation, Erlang OTP's influence on CloudHaskell for distributed programming, Monads, and more.
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.
Viktor Klang talks about the features of Akka 2.x and future releases, Akka's approach to fault tolerance, the effort to unify Futures in Scala, and the state of functional programming.
In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.
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.
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.
In this interview recorded at JavaOne 2011 Conference, Spring Hadoop project lead Costin Leau talks about the current state and upcoming features of Spring Data and Spring Hadoop projects. He also talks about the Caching and Data Grid architecture patterns.
Jonas Bonér and Kresten Krab Thorup on Bringing Erlang's Fault Tolerance and Distribution to Java with Akka and Erjang
Jonas Bonér and Kresten Krab Thorup discuss some key aspects of Erlang like fault tolerance and reliability and how the Akka and Erjang projects try to bring them to the JVM.
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.
Francesco Cesarini and Simon Thompson discuss how Erlang's design allows fault tolerance and resilience, modular error handling, details of the actor model implementation and distributed programming.