The in-memory batch-processing framework sheds more JVM performance bottlenecks as a major Hadoop vendor eyes Spark as a full-blown replacement for the aging MapReduce Apache Spark, the in-memory data ...

The MapReduce paradigm has emerged as a transformative framework for processing vast datasets by decomposing complex tasks into simpler map and reduce functions. This approach has been instrumental in ...

Clusters must be tuned properly to run memory-intensive systems like Spark, H2O, and Impala alongside traditional MapReduce jobs. This Hadoop Summit 2015 talk describes Altiscale’s experience running ...

An Insider’s Guide to Apache Spark is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new computing framework. As one of the ...

Apache Spark brings high-speed, in-memory analytics to Hadoop clusters, crunching large-scale data sets in minutes instead of hours Apache Spark got its start in 2009 at UC Berkeley’s AMPLab as a way ...

BERKELEY, Calif., Oct. 10 — Databricks, the company founded by the creators of popular open-source Big Data processing engine Apache Spark, announced today that it has broken the world record for the ...

Back in the early 1990s, you would sometimes hear this gag: “Two major products that came out of Berkeley: LSD and UNIX. We don’t believe this to be a coincidence.” Although wildly inaccurate, this ...