from amazon web site: http://aws.amazon.com/elasticmapreduce/faqs/#hive-8
Q: When should I use Hive vs. PIG? Hive and PIG both provide high level data-processing languages with support for complex data types for operating on large datasets. The Hive language is a variant of SQL and so is more accessible to people already familiar with SQL and relational databases. Hive has support for partitioned tables which allow Amazon Elastic MapReduce job flows to pull down only the table partition relevant to the query being executed rather than doing a full table scan. Both PIG and Hive have query plan optimization. PIG is able to optimize across an entire scripts while Hive queries are optimized at the statement level. Ultimately the choice of whether to use Hive or PIG will depend on the exact requirements of the application domain and the preferences of the implementers and those writing queries. On Thu, Oct 4, 2012 at 7:52 AM, Abhishek <abhishek.dod...@gmail.com> wrote: > Hi all, > > Can we discuss performance of pig vs hive > > 1) what hive is good at? > 2) what pig is good at? > 3) Hive optimizer vs pig optimizer > 4) hive limitations vs pig limitations > > Regards > Abhi > > Sent from my iPhone >
