Hive - A Warehousing Solution Over a Map-Reduce Framework

By Ashish Thusoo, Joydeep Sen Sarma, Namit Jain, Zheng Shao, Prasad Chakka, Suresh Anthony, H. Liu, P. Wyckoff, R. Murthy. Proceedings of the VLDB Endowment, 2009

1,917 citations recorded by the source corpus.

Subfields: Information Systems, Management Information Systems

View Paper: https://www.semanticscholar.org/paper/19a22753a1ef61c2bd19e97961f8ed1b5a073c2c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

In Management Information Systems

Citations in the corpus

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce (2013, methodology): “By integrating the framework with Hive, Hadoop-GIS provides an expressive spatial query language by extending HiveQL [33] with spatial constructs, and automates spatial query translation and execution.”
A Survey of Large Scale Data Management Approaches in Cloud Environments (2011, methodology): “The SMS planner extends the HiveQL translator [73] (Section IV-C1) and transforms SQL into MapReduce jobs that connect to tables stored as files in”
CIEL: A Universal Execution Engine for Distributed Data-Flow Computing (2011, methodology): “Hive enables SQL-like queries to be executed on large datasets using Hadoop [10] 2.”
Big Data: A Survey (2014, background): “In order to improve the programming efficiency, some advanced language systems have been proposed, e.g., Sawzall [98] of Google, Pig Latin [99] of Yahoo, Hive [100] of Facebook, and Scope [87] of Microsoft.”
Data management in cloud environments: NoSQL and NewSQL data stores (2013, background): “Solutions such as Hive [72] have provided a great help in this direction, but their use is still limited to only a few data stores such as HBase and Cassandra.”
BigBench V2: The New and Improved BigBench (2017, methodology): “Apache Hive [31] [33] is the engine in which we implemented all 30 BigBench V2 queries and performed experiments with scale factors (SF) 1.”
Bootstrapping data arrays of arbitrary order (2011, methodology): “Using software for Hive (Thusoo et al., 2009), a Hadoop-based map–reduce data warehousing and parallel computing environment, we can compute each of these four means for a number of bootstrap reweightings of the data, while visiting each observation only once.”
An unobtrusive behavioral model of "gross national happiness" (2010, methodology): “I used the Hive data warehousing infrastructure atop the Hadoop framework [18], an open-source system that allows massively parallel processing of custom database queries (i.”
Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training (2021, methodology): “Each training sample is represented as a row, containing dense and sparse features, stored in partitioned Hive [46] tables.”
Nephele/PACTs: a programming model and execution framework for web-scale analytical processing (2010, background): “Pig [12, 11], JAQL [3], and Hive [17] generate map/reduce jobs for Hadoop from declarative queries.”
Accelerating SQL database operations on a GPU with CUDA (2010, methodology): “Promoted by Facebook, the Hive project implements HiveQL, a declarative language that intersects with SQL, and provides ways to structure data [38].”
Multi-resource packing for cluster schedulers (2014, background): “Dates 12/2013, two days 1/2012, 1month Cluster Size ousands 3000 Framework Dryad [17] Hadoop [1] Script Scope [30] Hive [24] DAG Depth Large 2 File System Cosmos HDFS Network Links 10Gbps 1Gbps Oversubscription <2 4”
The Stratosphere platform for big data analytics (2014, background): “MapReduce has been the compilation target of SQL subsets [19,64], as well as other languages inspired by scripting languages [57,58] or XQuery [13].”