Title
Engine independence for logical analytic flows.
Abstract
A complex analytic flow in a modern enterprise may perform multiple, logically independent, tasks where each task uses a different processing engine. We term these multi-engine flows hybrid flows. Using multiple processing engines has advantages such as rapid deployment, better performance, lower cost, and so on. However, as the number and variety of these engines grows, developing and maintaining hybrid flows is a significant challenge because they are specified at a physical level and, so are hard to design and may break as the infrastructure evolves. We address this problem by enabling flow design at a logical level and automatic translation to physical flows. There are three main challenges. First, we describe how flows can be represented at a logical level, abstracting away details of any underlying processing engine. Second, we show how a physical flow, expressed in a programming language or some design GUI, can be imported and converted to a logical flow. In particular, we show how a hybrid flow comprising subflows in different languages can be imported and composed as a single, logical flow for subsequent manipulation. Third, we describe how a logical flow is translated into one or more physical flows for execution by the processing engines. The paper concludes with experimental results and example transformations that demonstrate the correctness and utility of our system.
Year
DOI
Venue
2014
10.1109/ICDE.2014.6816723
ICDE
Keywords
Field
DocType
business data processing,directed graphs,design GUI,engine independence,enterprise,flow design,graphical user interface,hybrid flow,logical analytic flows,multiengine flow,physical flow,processing engine,programming language
Data mining,Programming language,Software deployment,Computer science,Flow (psychology),Correctness,Theoretical computer science,Automatic translation,Database,Semantics,Encoding (memory)
Conference
ISSN
Citations 
PageRank 
1084-4627
7
0.51
References 
Authors
14
3
Name
Order
Citations
PageRank
Petar Jovanovic1627.78
Alkis Simitsis2166594.62
Kevin Wilkinson326114.87