* Existence of tools beyond Map/Reduce in use at Google, does not imply that Map/Reduce's "days are numbered."
Map/Reduce is still enormously useful for many tasks even when other approaches (BSP, traditional distributed RDBMS techniques like Dremel) are available.
* Hadoop is not restricted to Map/Reduce. HDFS, cluster management, and more can be used and are used by other applications.
I am not too heavily involved with the query-processing side of Hadoop, but as far as as I understand the long term idea is that Map/Reduce will become just another application (of many) running on top of Hadoop's cluster management and storage infrastructure. See http://hadoop.apache.org/common/docs/r0.23.0/hadoop-yarn/had...
* Existence of tools beyond Map/Reduce in use at Google, does not imply that Map/Reduce's "days are numbered."
Map/Reduce is still enormously useful for many tasks even when other approaches (BSP, traditional distributed RDBMS techniques like Dremel) are available.
* Hadoop is not restricted to Map/Reduce. HDFS, cluster management, and more can be used and are used by other applications.
I am not too heavily involved with the query-processing side of Hadoop, but as far as as I understand the long term idea is that Map/Reduce will become just another application (of many) running on top of Hadoop's cluster management and storage infrastructure. See http://hadoop.apache.org/common/docs/r0.23.0/hadoop-yarn/had...
(Disclosure: I contribute to HDFS and HBase)