Graph Reachability
In this example we cover:
- Implementing a recursive algorithm (graph reachability) via cyclic dataflow
- Operators to union data from multiple inputs (
union
), and send data to multiple outputs (tee
)- Indexing multi-output operators by appending a bracket expression
- An example of how a cyclic dataflow in one stratum executes to completion before starting the next stratum.
To expand from graph neighbors to graph reachability, we want to find vertices that are connected not just to origin
,
but also to vertices reachable transitively from origin
. Said differently, a vertex is reachable from origin
if it is
one of two cases:
- a neighbor of
origin
or - a neighbor of some other vertex that is itself reachable from
origin
.
It turns out this is a very small change to our Hydroflow program! Essentially we want to take all the reached vertices we found in our graph neighbors program,
and treat them recursively just as we treated origin
.
To do this in a language like Hydroflow, we introduce a cycle in the flow:
we take the join output and have it
flow back into the join input. The modified intuitive graph looks like this:
Note that we added a Reached Vertices
box to the diagram to union the two inbound edges corresponding to our
two cases above. Similarly note that the join box V ⨝ E
now has two outbound edges; the sketch omits the operator
to copy ("tee") the output along
two paths.
Now lets look at a modified version of our graph neighbor code that implements this full program, including the loop as well as the Hydroflow union
and tee
.
Modify src/main.rs to look like this:
use hydroflow::hydroflow_syntax;
pub fn main() {
// An edge in the input data = a pair of `usize` vertex IDs.
let (edges_send, edges_recv) = hydroflow::util::unbounded_channel::<(usize, usize)>();
let mut flow = hydroflow_syntax! {
// inputs: the origin vertex (vertex 0) and stream of input edges
origin = source_iter(vec![0]);
stream_of_edges = source_stream(edges_recv);
reached_vertices = union();
origin -> [0]reached_vertices;
// the join
my_join_tee = join() -> flat_map(|(src, ((), dst))| [src, dst]) -> tee();
reached_vertices -> map(|v| (v, ())) -> [0]my_join_tee;
stream_of_edges -> [1]my_join_tee;
// the loop and the output
my_join_tee[0] -> [1]reached_vertices;
my_join_tee[1] -> unique() -> for_each(|x| println!("Reached: {}", x));
};
println!(
"{}",
flow.meta_graph()
.expect("No graph found, maybe failed to parse.")
.to_mermaid()
);
edges_send.send((0, 1)).unwrap();
edges_send.send((2, 4)).unwrap();
edges_send.send((3, 4)).unwrap();
edges_send.send((1, 2)).unwrap();
edges_send.send((0, 3)).unwrap();
edges_send.send((0, 3)).unwrap();
flow.run_available();
}
And now we get the full set of vertices reachable from 0
:
cargo run
<build output>
<graph output>
Reached: 3
Reached: 0
Reached: 2
Reached: 4
Reached: 1
Examining the Hydroflow Code
Let's review the significant changes here. First, in setting up the inputs we have the
addition of the reached_vertices
variable, which uses the union()
op to union the output of two operators into one.
We route the origin
vertex into it as one input right away:
reached_vertices = union();
origin -> [0]reached_vertices;
Note the square-bracket syntax for differentiating the multiple inputs to union()
is the same as that of join()
(except that union can have an unbounded number of inputs,
whereas join()
is defined to only have two.)
Now, join()
is defined to only have one output. In our program, we want to copy
the joined output
output to two places: to the original for_each
from above to print output, and also
back to the union
operator we called reached_vertices
.
We feed the join()
output
through a flat_map()
as before, and then we feed the result into a tee()
operator,
which is the mirror image of union()
: instead of merging many inputs to one output,
it copies one input to many different outputs. Each input element is cloned, in Rust terms, and
given to each of the outputs. The syntax for the outputs of tee()
mirrors that of union: we append
an output index in square brackets to the tee
or variable. In this example we have
my_join_tee[0] ->
and my_join_tee[1] ->
.
Finally, we process the output of the join
as passed through the tee
.
One branch pushes reached vertices back up into the reached_vertices
variable (which begins with a union
), while the other
prints out all the reached vertices as in the simple program.
my_join_tee[0] -> [1]reached_vertices;
my_join_tee[1] -> for_each(|x| println!("Reached: {}", x));
Note the syntax for differentiating the outputs of a tee()
is symmetric to that of union()
,
showing up to the right of the variable rather than the left.
Below is the diagram rendered by mermaid showing the structure of the full flow:
This is similar to the flow for graph neighbors, but has a few more operators that make it look
more complex. In particular, it includes the union
and tee
operators, and a cycle-forming back-edge
that passes through an auto-generated handoff
operator. This handoff
is not a stratum boundary (after all, it connects stratum 0 to itself!) It simply enforces the rule that a push producer and a pull consumer must be separated by a handoff
.
Meanwhile, note that there is once again a stratum boundary between the stratum 0 with its recursive loop, and stratum 1 that computes unique
, with the blocking input. This means that Hydroflow will first run the loop of stratum 0 repeatedly until all the transitive reached vertices are found, before moving on to compute the unique reached vertices.