Good point. Shows how personal use cases color how we interpret products.
On Wed, Jul 9, 2014 at 1:08 AM, Sean Owen <so...@cloudera.com> wrote: > On Wed, Jul 9, 2014 at 1:52 AM, Keith Simmons <ke...@pulse.io> wrote: > >> Impala is *not* built on map/reduce, though it was built to replace >> Hive, which is map/reduce based. It has its own distributed query engine, >> though it does load data from HDFS, and is part of the hadoop ecosystem. >> Impala really shines when your >> > > (It was not built to replace Hive. It's purpose-built to make interactive > use with a BI tool feasible -- single-digit second queries on huge data > sets. It's very memory hungry. Hive's architecture choices and legacy code > have been throughput-oriented, and can't really get below minutes at scale, > but, remains a right choice when you are in fact doing ETL!) >
