Dataflow Programming Languages [closed]

Question

What is a dataflow programming language? Why use it? and are there any benefits to it?

Answer 1

Dataflow programming languages propose to isolate some local behaviors in so called "actors", that are supposed to run in parallel and exchange data through point-to-point channels. There is no notion of central memory (both for code and data) unlike Von Neumann model of computers.

These actors consume data tokens on their inputs and produce new data on their outputs.

This definition does not impose the means to run this in practice. However, the production/consumption of data needs to be analyzed with care : for example, if an actor B does not consume at the same speed as the actor A that produce the data, then a potentially unbounded memory (fifo) is required between them. Many other problems can arise like deadlocks.

In many cases, this analysis will fail because the interleaving of the internal behaviors is intractable (beyond reach of today formal methods).

Despite this, dataflow programming languages remain attractive in many domains :

• for instance to define reference models for video encoding : a pure C program won't do the job because it makes the assumption that everything run as a sequence of operations, which is not true in computers (pipeline, VLIW, mutlicores, VLSI). Maybe you could have a look at this : recent PhD thesis. CAL dataflow language is proposed as a unifying language for next generation video encoders/decoders reference.
• Mission critical where safety is required : if you add some strong assumptions on the production/consumption of data, then you get a language with strong potential in terms of code generation, proofs etc (see synchronous languages)

Answer 2

Mozart has support for dataflow-like synchronization, and it does have some commercial applications. You could also argue that make is a dataflow programming language

Answer 3

You could try Cameleon: www.shinoe.org/cameleon which seems to be simple to use. It's a graphical language for functional programming which has a data(work)-flow approach.

Its written in C++ but can call any type of local or distant programs written in any programming language.

It has a multi-scale approach and seems to be turing complete (this is a petri net extension).

Answer 4

Dataflow programming languages are ones that focus on the state of the program and cause operations to occur according to any change in the state. Dataflow programming languages are inherently parallel, because the operations rely on inputs that when met will cause the operation to execute. This means unlike a normal program where one operation is followed by the next operation, in a dataflow program operations will execute as long as the inputs are met and thus there is no set order.

Often dataflow programming languages use a large hashtable where the keys are the data of the program and the values of the table are pointers to the operations of the program. This makes multicore programs easier to create in a dataflow programming language, since each core would only need the hashtable to work.

A common example of a dataflow programming language is a spread sheet program which has columns of data that are affected by other columns of data. Should the data in one column change, other data in the other columns will probably change with it. Although the spread sheet program is the most common example of a dataflow programming language, most of them tend to be graphical languages.

Answer 5

Many ETL tools are also in this realm. The dataflow tasks in MS SSIS are a good example. Graphical tool in this case.

Answer 6

Excel (and other spreadsheets) are essentially dataflow languages. Dataflow languages are a lot like functional programming languages, except that the values at the leaves of the whole program graph are not values at all, but variables (or value streams), so that when they change, the changes ripple and flow up the graph.