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 ...

Apache Spark, the in-memory and real-time data processing framework for Hadoop, turned heads and opened eyes after version 1.0 debuted. The feature changes in 1.2 show Spark working not only to ...

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 ...