Treffer: StarFlow: A Script-Centric Data Analysis Environment

Title:
StarFlow: A Script-Centric Data Analysis Environment
Authors:
Angelino, Elaine Lee, Yamins, Daniel Louis Kanef, Seltzer, Margo
Publisher Information:
Springer
Publication Year:
2010
Collection:
Harvard University: DASH - Digital Access to Scholarship at Harvard
Subject Terms:
automatic parallelization, automatic updating, computational workflows, control flow, data-flow, data analysis, dependency tracking, provenance, Python, workflow abstraction
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
application/pdf
Language:
English
ISBN:
978-3-642-17818-4
3-642-17818-9
Relation:
dx.doi.org/10.1007/978-3-642-17819-1_27; http://www.eecs.harvard.edu/~elaine/pubs/ipaw10.pdf; http://tw.rpi.edu/proj/portal.wiki/images/9/94/IPAW2010_FP_Angelino.pdf; Lecture Notes in Computer Science
DOI:
10.1007/978-3-642-17819-1_27
Availability:
http://nrs.harvard.edu/urn-3:HUL.InstRepos:4797264
https://doi.org/10.1007/978-3-642-17819-1_27
Accession Number:
edsbas.FDF3688F
Database:
BASE

Weitere Informationen

We introduce StarFlow, a script-centric environment for data analysis. StarFlow has four main features: (1) extraction of control and data-flow dependencies through a novel combination of static analysis, dynamic runtime analysis, and user annotations, (2) command-line tools for exploring and propagating changes through the resulting dependency network, (3) support for workflow abstractions enabling robust parallel executions of complex analysis pipelines, and (4) a seamless interface with the Python scripting language. We describe a range of real applications of StarFlow, including automatic parallelization of complex workflows in the cloud. ; Engineering and Applied Sciences ; Accepted Manuscript