SciBORQ: Scientific Data Management With Bounds On Runtime and Quality

Data warehouses underlying virtual observatories stress the capabilities of database management systems in many ways. They are filled, on a daily basis, with large amounts of factual information derived from intensive data scrubbing and computational feature extraction pipelines. The predominant data processing techniques focus on parallel loads and map-reduce feature extraction algorithms. Querying these huge databases require a sizable computing cluster, while ideally the initial investigation should run interactively, using as few resources as possible.

Provided by: CWI Topic: Big Data Date Added: Jan 2011 Format: PDF

Find By Topic