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#![cfg(test)]
use crate::Iteration;
use crate::Relation;
use crate::RelationLeaper;
use proptest::prelude::*;
use proptest::{proptest, proptest_helper};
fn inputs() -> impl Strategy<Value = Vec<(u32, u32)>> {
prop::collection::vec((0_u32..100, 0_u32..100), 1..500)
}
/// The original way to use datafrog -- computes reachable nodes from a set of edges
fn reachable_with_var_join(edges: &[(u32, u32)]) -> Relation<(u32, u32)> {
let edges: Relation<_> = edges.iter().collect();
let mut iteration = Iteration::new();
let edges_by_successor = iteration.variable::<(u32, u32)>("edges_invert");
edges_by_successor.extend(edges.iter().map(|&(n1, n2)| (n2, n1)));
let reachable = iteration.variable::<(u32, u32)>("reachable");
reachable.insert(edges);
while iteration.changed() {
// reachable(N1, N3) :- edges(N1, N2), reachable(N2, N3).
reachable.from_join(&reachable, &edges_by_successor, |&_, &n3, &n1| (n1, n3));
}
reachable.complete()
}
/// Like `reachable`, but using a relation as an input to `from_join`
fn reachable_with_relation_join(edges: &[(u32, u32)]) -> Relation<(u32, u32)> {
let edges: Relation<_> = edges.iter().collect();
let mut iteration = Iteration::new();
// NB. Changed from `reachable_with_var_join`:
let edges_by_successor: Relation<_> = edges.iter().map(|&(n1, n2)| (n2, n1)).collect();
let reachable = iteration.variable::<(u32, u32)>("reachable");
reachable.insert(edges);
while iteration.changed() {
// reachable(N1, N3) :- edges(N1, N2), reachable(N2, N3).
reachable.from_join(&reachable, &edges_by_successor, |&_, &n3, &n1| (n1, n3));
}
reachable.complete()
}
fn reachable_with_leapfrog(edges: &[(u32, u32)]) -> Relation<(u32, u32)> {
let edges: Relation<_> = edges.iter().collect();
let mut iteration = Iteration::new();
let edges_by_successor: Relation<_> = edges.iter().map(|&(n1, n2)| (n2, n1)).collect();
let reachable = iteration.variable::<(u32, u32)>("reachable");
reachable.insert(edges);
while iteration.changed() {
// reachable(N1, N3) :- edges(N1, N2), reachable(N2, N3).
reachable.from_leapjoin(
&reachable,
edges_by_successor.extend_with(|&(n2, _)| n2),
|&(_, n3), &n1| (n1, n3),
);
}
reachable.complete()
}
/// Computes a join where the values are summed -- uses iteration
/// variables (the original datafrog technique).
fn sum_join_via_var(
input1_slice: &[(u32, u32)],
input2_slice: &[(u32, u32)],
) -> Relation<(u32, u32)> {
let mut iteration = Iteration::new();
let input1 = iteration.variable::<(u32, u32)>("input1");
input1.extend(input1_slice);
let input2 = iteration.variable::<(u32, u32)>("input1");
input2.extend(input2_slice);
let output = iteration.variable::<(u32, u32)>("output");
while iteration.changed() {
// output(K1, V1 * 100 + V2) :- input1(K1, V1), input2(K1, V2).
output.from_join(&input1, &input2, |&k1, &v1, &v2| (k1, v1 * 100 + v2));
}
output.complete()
}
/// Computes a join where the values are summed -- uses iteration
/// variables (the original datafrog technique).
fn sum_join_via_relation(
input1_slice: &[(u32, u32)],
input2_slice: &[(u32, u32)],
) -> Relation<(u32, u32)> {
let input1: Relation<_> = input1_slice.iter().collect();
let input2: Relation<_> = input2_slice.iter().collect();
Relation::from_join(&input1, &input2, |&k1, &v1, &v2| (k1, v1 * 100 + v2))
}
proptest! {
#[test]
fn reachable_leapfrog_vs_var_join(edges in inputs()) {
let reachable1 = reachable_with_var_join(&edges);
let reachable2 = reachable_with_leapfrog(&edges);
assert_eq!(reachable1.elements, reachable2.elements);
}
#[test]
fn reachable_rel_join_vs_var_join(edges in inputs()) {
let reachable1 = reachable_with_var_join(&edges);
let reachable2 = reachable_with_relation_join(&edges);
assert_eq!(reachable1.elements, reachable2.elements);
}
#[test]
fn sum_join_from_var_vs_rel((set1, set2) in (inputs(), inputs())) {
let output1 = sum_join_via_var(&set1, &set2);
let output2 = sum_join_via_relation(&set1, &set2);
assert_eq!(output1.elements, output2.elements);
}
/// Test the behavior of `filter_anti` used on its own in a
/// leapjoin -- effectively it becomes an "intersection"
/// operation.
#[test]
fn filter_with_on_its_own((set1, set2) in (inputs(), inputs())) {
let input1: Relation<(u32, u32)> = set1.iter().collect();
let input2: Relation<(u32, u32)> = set2.iter().collect();
let intersection1 = Relation::from_leapjoin(
&input1,
input2.filter_with(|&tuple| tuple),
|&tuple, &()| tuple,
);
let intersection2: Relation<(u32, u32)> = input1.elements.iter()
.filter(|t| input2.elements.binary_search(&t).is_ok())
.collect();
assert_eq!(intersection1.elements, intersection2.elements);
}
/// Test the behavior of `filter_anti` used on its own in a
/// leapjoin -- effectively it becomes a "set minus" operation.
#[test]
fn filter_anti_on_its_own((set1, set2) in (inputs(), inputs())) {
let input1: Relation<(u32, u32)> = set1.iter().collect();
let input2: Relation<(u32, u32)> = set2.iter().collect();
let difference1 = Relation::from_leapjoin(
&input1,
input2.filter_anti(|&tuple| tuple),
|&tuple, &()| tuple,
);
let difference2: Relation<(u32, u32)> = input1.elements.iter()
.filter(|t| input2.elements.binary_search(&t).is_err())
.collect();
assert_eq!(difference1.elements, difference2.elements);
}
}
/// Test that `from_leapjoin` matches against the tuples from an
/// `extend` that precedes first iteration.
///
/// This was always true, but wasn't immediately obvious to me until I
/// re-read the code more carefully. -nikomatsakis
#[test]
fn leapjoin_from_extend() {
let doubles: Relation<(u32, u32)> = (0..10).map(|i| (i, i * 2)).collect();
let mut iteration = Iteration::new();
let variable = iteration.variable::<(u32, u32)>("variable");
variable.extend(Some((2, 2)));
while iteration.changed() {
variable.from_leapjoin(
&variable,
doubles.extend_with(|&(i, _)| i),
|&(i, _), &j| (i, j),
);
}
let variable = variable.complete();
assert_eq!(variable.elements, vec![(2, 2), (2, 4)]);
}
|
