Thanks Gopal.
Basically the following is true: 1. The storage layer is HDFS 2. The execution engine is MR, Tez, Spark etc 3. The access layer is Hive When we say the access layer is Hive, is the assumption correct that we are referring to optimiser (loosly related to the optimiser in RDBMS). For example is Hive optimiser aware of the number of underlying partitions. The reason I am asking this question is that with EXPLAIN I only see Table scan and it does refer to any partition or partition elimination? Cheers NOTE: The information in this email is proprietary and confidential. This message is for the designated recipient only, if you are not the intended recipient, you should destroy it immediately. Any information in this message shall not be understood as given or endorsed by Peridale Technology Ltd, its subsidiaries or their employees, unless expressly so stated. It is the responsibility of the recipient to ensure that this email is virus free, therefore neither Peridale Ltd, its subsidiaries nor their employees accept any responsibility. -----Original Message----- From: Gopal Vijayaraghavan [mailto:go...@hortonworks.com] On Behalf Of Gopal Vijayaraghavan Sent: 08 January 2016 09:34 To: user@hive.apache.org Subject: Re: Impact of partitioning on certain queries > Ok we hope that partitioning improves performance where the predicate >is on partitioned columns Nope. Partitioning *only* improves performance if your queries run with set hive.mapred.mode=strict; That's the "use strict" easy way to make sure you're writing good queries. Even then, schema design in hive is something you need to learn with the assumption that neither the storage layer, nor the compute layer is part of "hive". It floats itself in an "access" layer above both. Not sure there's any legacy tech to draw parallels with that. If you haven't seen this before, here's an example of the problem <http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren > http://www.slideshare.net/Hadoop_Summit/hive-at-yahoo-letters-from-the-tren ches/24 Cheers, Gopal
