Introduction
•
Availability of
data controls the computation
•
The structure is
determined by the orderly motion of data from component to component
Variations:
•
Control: push
versus pull
•
Degree of
concurrency
•
Topology
Example of Data Flow style
SUB –STYLE
1.
Pipes and
Filters
2.
Batch Sequential
Processing
Dataflow:
Pipe-and-Filter
Components (Filters)
•
Read input
stream (or streams)
•
Locally
transform data
•
Produce output
stream (or streams) Connectors (Pipes)
Representation
of pipes and filters
Data processed incrementally
as it arrives
•
Output can begin
before input fully consumed Filters must be independent:
•
Filters do not
share state
•
Filters do not
know upstream or downstream filters
Pipe-and-Filter:
discussion
Strengths:
•
Reuse: any two filters can be connected
if they agree on data
•
format
•
Ease of maintenance: filters can be
added or replaced
•
Potential for parallelism: filters
implemented as separate
•
tasks, consuming and producing data
incrementally Weaknesses:
•
Sharing global data expensive or
limiting
•
Scheme is highly dependent on order of
filters
•
Can be difficult to design incremental
filters
•
Not appropriate for interactive
applications
•
Error handling difficult: what if an
intermediate filter
•
crashes?
•
Data type must be greatest common
denominator, e.g. ASCII
Batch Sequential
Processing
•
Frequent
architecture in scientific computing and business data processing
•
Components are
independent programs
•
Connectors are
media, typically files
•
Each step runs
to completion before next step begins
Representation
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