Hive - a petabyte scale data warehouse using Hadoop

— The size of data sets being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hadoop [1] is a popular open-source map-reduce implementation which is being used in companies like Yahoo, Facebook etc. to store and process extremely large data sets on commodity hardware. However, the map-reduce programming model is very low level and requires developers to write custom programs which are hard to maintain and reuse. In this paper, we present Hive, an open-source data warehousing solution built on top of Hadoop. Hive supports queries expressed in a SQL-like declarative language - HiveQL, which are compiled into mapreduce jobs that are executed using Hadoop. In addition, HiveQL enables users to plug in custom map-reduce scripts into queries. The language includes a type system with support for tables containing primitive types, collections like arrays and maps, and nested compositions of ...

• Type: Conference
• Year: 2010
• Where: ICDE
• Authors: Ashish Thusoo, Joydeep Sen Sarma, Namit Jain, Zheng Shao, Prasad Chakka, Ning Zhang 0002, Suresh Anthony, Hao Liu, Raghotham Murthy
• Keywords: Data Sets, Database, Hive, ICDE 2010, Warehousing Solution