mentat/query-algebrizer/src/clauses/or.rs

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// Copyright 2016 Mozilla
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use
// this file except in compliance with the License. You may obtain a copy of the
// License at http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
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use std::collections::btree_map::Entry;
use std::collections::BTreeSet;
use mentat_core::{
Schema,
};
use mentat_query::{
OrJoin,
OrWhereClause,
Pattern,
PatternValuePlace,
PatternNonValuePlace,
UnifyVars,
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Variable,
WhereClause,
};
use clauses::ConjoiningClauses;
use errors::{
Result,
};
use types::{
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ColumnConstraintOrAlternation,
ColumnAlternation,
ColumnIntersection,
DatomsTable,
EmptyBecause,
};
/// Return true if both left and right are the same variable or both are non-variable.
fn _simply_matches_place(left: &PatternNonValuePlace, right: &PatternNonValuePlace) -> bool {
match (left, right) {
(&PatternNonValuePlace::Variable(ref a), &PatternNonValuePlace::Variable(ref b)) => a == b,
(&PatternNonValuePlace::Placeholder, &PatternNonValuePlace::Placeholder) => true,
(&PatternNonValuePlace::Entid(_), &PatternNonValuePlace::Entid(_)) => true,
(&PatternNonValuePlace::Entid(_), &PatternNonValuePlace::Ident(_)) => true,
(&PatternNonValuePlace::Ident(_), &PatternNonValuePlace::Ident(_)) => true,
(&PatternNonValuePlace::Ident(_), &PatternNonValuePlace::Entid(_)) => true,
_ => false,
}
}
/// Return true if both left and right are the same variable or both are non-variable.
fn _simply_matches_value_place(left: &PatternValuePlace, right: &PatternValuePlace) -> bool {
match (left, right) {
(&PatternValuePlace::Variable(ref a), &PatternValuePlace::Variable(ref b)) => a == b,
(&PatternValuePlace::Placeholder, &PatternValuePlace::Placeholder) => true,
(&PatternValuePlace::Variable(_), _) => false,
(_, &PatternValuePlace::Variable(_)) => false,
(&PatternValuePlace::Placeholder, _) => false,
(_, &PatternValuePlace::Placeholder) => false,
_ => true,
}
}
pub enum DeconstructedOrJoin {
KnownSuccess,
KnownEmpty(EmptyBecause),
Unit(OrWhereClause),
UnitPattern(Pattern),
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Simple(Vec<Pattern>, BTreeSet<Variable>),
Complex(OrJoin),
}
/// Application of `or`. Note that this is recursive!
impl ConjoiningClauses {
fn apply_or_where_clause(&mut self, schema: &Schema, clause: OrWhereClause) -> Result<()> {
match clause {
OrWhereClause::Clause(clause) => self.apply_clause(schema, clause),
// A query might be:
// [:find ?x :where (or (and [?x _ 5] [?x :foo/bar 7]))]
// which is equivalent to dropping the `or` _and_ the `and`!
OrWhereClause::And(clauses) => {
for clause in clauses {
self.apply_clause(schema, clause)?;
}
Ok(())
},
}
}
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pub fn apply_or_join(&mut self, schema: &Schema, mut or_join: OrJoin) -> Result<()> {
// Simple optimization. Empty `or` clauses disappear. Unit `or` clauses
// are equivalent to just the inner clause.
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// Pre-cache mentioned variables. We use these in a few places.
or_join.mentioned_variables();
match or_join.clauses.len() {
0 => Ok(()),
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1 if or_join.is_fully_unified() => {
let clause = or_join.clauses.pop().expect("there's a clause");
self.apply_or_where_clause(schema, clause)
},
// Either there's only one clause pattern, and it's not fully unified, or we
// have multiple clauses.
// In the former case we can't just apply it: it includes a variable that we don't want
// to join with the rest of the query.
// Notably, this clause might be an `and`, making this a complex pattern, so we can't
// necessarily rewrite it in place.
// In the latter case, we still need to do a bit more work.
_ => self.apply_non_trivial_or_join(schema, or_join),
}
}
/// Find out if the `OrJoin` is simple. A simple `or` is one in
/// which:
/// - Every arm is a pattern, so that we can use a single table alias for all.
/// - Each pattern should run against the same table, for the same reason.
/// - Each pattern uses the same variables. (That's checked by validation.)
/// - Each pattern has the same shape, so we can extract bindings from the same columns
/// regardless of which clause matched.
///
/// Like this:
///
/// ```edn
/// [:find ?x
/// :where (or [?x :foo/knows "John"]
/// [?x :foo/parent "Ámbar"]
/// [?x :foo/knows "Daphne"])]
/// ```
///
/// While we're doing this diagnosis, we'll also find out if:
/// - No patterns can match: the enclosing CC is known-empty.
/// - Some patterns can't match: they are discarded.
/// - Only one pattern can match: the `or` can be simplified away.
fn deconstruct_or_join(&self, schema: &Schema, or_join: OrJoin) -> DeconstructedOrJoin {
// If we have explicit non-maximal unify-vars, we *can't* simply run this as a
// single pattern --
// ```
// [:find ?x :where [?x :foo/bar ?y] (or-join [?x] [?x :foo/baz ?y])]
// ```
// is *not* equivalent to
// ```
// [:find ?x :where [?x :foo/bar ?y] [?x :foo/baz ?y]]
// ```
if !or_join.is_fully_unified() {
// It's complex because we need to make sure that non-unified vars
// mentioned in the body of the `or-join` do not unify with variables
// outside the `or-join`. We can't naïvely collect clauses into the
// same CC. TODO: pay attention to the unify list when generating
// constraints. Temporarily shadow variables within each `or` branch.
return DeconstructedOrJoin::Complex(or_join);
}
match or_join.clauses.len() {
0 => DeconstructedOrJoin::KnownSuccess,
// It's safe to simply 'leak' the entire clause, because we know every var in it is
// supposed to unify with the enclosing form.
1 => DeconstructedOrJoin::Unit(or_join.clauses.into_iter().next().unwrap()),
_ => self._deconstruct_or_join(schema, or_join),
}
}
/// This helper does the work of taking a known-non-trivial `or` or `or-join`,
/// walking the contained patterns to decide whether it can be translated simply
/// -- as a collection of constraints on a single table alias -- or if it needs to
/// be implemented as a `UNION`.
///
/// See the description of `deconstruct_or_join` for more details. This method expects
/// to be called _only_ by `deconstruct_or_join`.
fn _deconstruct_or_join(&self, schema: &Schema, or_join: OrJoin) -> DeconstructedOrJoin {
// Preconditions enforced by `deconstruct_or_join`.
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assert!(or_join.is_fully_unified());
assert!(or_join.clauses.len() >= 2);
// We're going to collect into this.
// If at any point we hit something that's not a suitable pattern, we'll
// reconstruct and return a complex `OrJoin`.
let mut patterns: Vec<Pattern> = Vec::with_capacity(or_join.clauses.len());
// Keep track of the table we need every pattern to use.
let mut expected_table: Option<DatomsTable> = None;
// Technically we might have several reasons, but we take the last -- that is, that's the
// reason we don't have at least one pattern!
// We'll return this as our reason if no pattern can return results.
let mut empty_because: Option<EmptyBecause> = None;
// Walk each clause in turn, bailing as soon as we know this can't be simple.
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let (join_clauses, mentioned_vars) = or_join.dismember();
let mut clauses = join_clauses.into_iter();
while let Some(clause) = clauses.next() {
// If we fail half-way through processing, we want to reconstitute the input.
// Keep a handle to the clause itself here to smooth over the moved `if let` below.
let last: OrWhereClause;
if let OrWhereClause::Clause(WhereClause::Pattern(p)) = clause {
// Compute the table for the pattern. If we can't figure one out, it means
// the pattern cannot succeed; we drop it.
// Inside an `or` it's not a failure for a pattern to be unable to match, which
// manifests as a table being unable to be found.
let table = self.table_for_places(schema, &p.attribute, &p.value);
match table {
Err(e) => {
empty_because = Some(e);
// Do not accumulate this pattern at all. Add lightness!
continue;
},
Ok(table) => {
// Check the shape of the pattern against a previous pattern.
let same_shape =
if let Some(template) = patterns.get(0) {
template.source == p.source && // or-arms all use the same source anyway.
_simply_matches_place(&template.entity, &p.entity) &&
_simply_matches_place(&template.attribute, &p.attribute) &&
_simply_matches_value_place(&template.value, &p.value) &&
_simply_matches_place(&template.tx, &p.tx)
} else {
// No previous pattern.
true
};
// All of our clauses that _do_ yield a table -- that are possible --
// must use the same table in order for this to be a simple `or`!
if same_shape {
if expected_table == Some(table) {
patterns.push(p);
continue;
}
if expected_table.is_none() {
expected_table = Some(table);
patterns.push(p);
continue;
}
}
// Otherwise, we need to keep this pattern so we can reconstitute.
// We'll fall through to reconstruction.
}
}
last = OrWhereClause::Clause(WhereClause::Pattern(p));
} else {
last = clause;
}
// If we get here, it means one of our checks above failed. Reconstruct and bail.
let reconstructed: Vec<OrWhereClause> =
// Non-empty patterns already collected…
patterns.into_iter()
.map(|p| OrWhereClause::Clause(WhereClause::Pattern(p)))
// … then the clause we just considered…
.chain(::std::iter::once(last))
// … then the rest of the iterator.
.chain(clauses)
.collect();
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return DeconstructedOrJoin::Complex(OrJoin::new(
UnifyVars::Implicit,
reconstructed,
));
}
// If we got here without returning, then `patterns` is what we're working with.
// If `patterns` is empty, it means _none_ of the clauses in the `or` could succeed.
match patterns.len() {
0 => {
assert!(empty_because.is_some());
DeconstructedOrJoin::KnownEmpty(empty_because.unwrap())
},
1 => DeconstructedOrJoin::UnitPattern(patterns.pop().unwrap()),
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_ => DeconstructedOrJoin::Simple(patterns, mentioned_vars),
}
}
fn apply_non_trivial_or_join(&mut self, schema: &Schema, or_join: OrJoin) -> Result<()> {
match self.deconstruct_or_join(schema, or_join) {
DeconstructedOrJoin::KnownSuccess => {
// The pattern came to us empty -- `(or)`. Do nothing.
Ok(())
},
DeconstructedOrJoin::KnownEmpty(reason) => {
// There were no arms of the join that could be mapped to a table.
// The entire `or`, and thus the CC, cannot yield results.
self.mark_known_empty(reason);
Ok(())
},
DeconstructedOrJoin::Unit(clause) => {
// There was only one clause. We're unifying all variables, so we can just apply here.
self.apply_or_where_clause(schema, clause)
},
DeconstructedOrJoin::UnitPattern(pattern) => {
// Same, but simpler.
self.apply_pattern(schema, pattern);
Ok(())
},
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DeconstructedOrJoin::Simple(patterns, mentioned_vars) => {
// Hooray! Fully unified and plain ol' patterns that all use the same table.
// Go right ahead and produce a set of constraint alternations that we can collect,
// using a single table alias.
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self.apply_simple_or_join(schema, patterns, mentioned_vars)
},
DeconstructedOrJoin::Complex(_) => {
// Do this the hard way. TODO
unimplemented!();
},
}
}
/// A simple `or` join is effectively a single pattern in which an individual column's bindings
/// are not a single value. Rather than a pattern like
///
/// ```edn
/// [?x :foo/knows "John"]
/// ```
///
/// we have
///
/// ```edn
/// (or [?x :foo/knows "John"]
/// [?x :foo/hates "Peter"])
/// ```
///
/// but the generated SQL is very similar: the former is
///
/// ```sql
/// WHERE datoms00.a = 99 AND datoms00.v = 'John'
/// ```
///
/// with the latter growing to
///
/// ```sql
/// WHERE (datoms00.a = 99 AND datoms00.v = 'John')
/// OR (datoms00.a = 98 AND datoms00.v = 'Peter')
/// ```
///
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fn apply_simple_or_join(&mut self, schema: &Schema, patterns: Vec<Pattern>, mentioned_vars: BTreeSet<Variable>) -> Result<()> {
if self.is_known_empty() {
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return Ok(())
}
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assert!(patterns.len() >= 2);
// Begin by building a base CC that we'll use to produce constraints from each pattern.
// Populate this base CC with whatever variables are already known from the CC to which
// we're applying this `or`.
// This will give us any applicable type constraints or column mappings.
// Then generate a single table alias, based on the first pattern, and use that to make any
// new variable mappings we will need to extract values.
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let template = self.use_as_template(&mentioned_vars);
// We expect this to always work: if it doesn't, it means we should never have got to this
// point.
let source_alias = self.alias_table(schema, &patterns[0]).expect("couldn't get table");
// This is where we'll collect everything we eventually add to the destination CC.
let mut folded = ConjoiningClauses::default();
// Scoped borrow of source_alias.
{
// Clone this CC once for each pattern.
// Apply each pattern to its CC with the _same_ table alias.
// Each pattern's derived types are intersected with any type constraints in the
// template, sourced from the destination CC. If a variable cannot satisfy both type
// constraints, the new CC cannot match. This prunes the 'or' arms:
//
// ```edn
// [:find ?x
// :where [?a :some/int ?x]
// (or [_ :some/otherint ?x]
// [_ :some/string ?x])]
// ```
//
// can simplify to
//
// ```edn
// [:find ?x
// :where [?a :some/int ?x]
// [_ :some/otherint ?x]]
// ```
let mut receptacles =
patterns.into_iter()
.filter_map(|pattern| {
let mut receptacle = template.make_receptacle();
println!("Applying pattern with attribute {:?}", pattern.attribute);
receptacle.apply_pattern_clause_for_alias(schema, &pattern, &source_alias);
if receptacle.is_known_empty() {
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println!("Receptacle is empty.");
let reason = receptacle.empty_because;
None
} else {
Some(receptacle)
}
})
.peekable();
// We need to copy the column bindings from one of the receptacles. Because this is a simple
// or, we know that they're all the same.
// Because we just made an empty template, and created a new alias from the destination CC,
// we know that we can blindly merge: collisions aren't possible.
if let Some(first) = receptacles.peek() {
for (v, cols) in &first.column_bindings {
println!("Adding {:?}: {:?}", v, cols);
match self.column_bindings.entry(v.clone()) {
Entry::Vacant(e) => {
e.insert(cols.clone());
},
Entry::Occupied(mut e) => {
e.get_mut().append(&mut cols.clone());
},
}
}
} else {
// No non-empty receptacles? The destination CC is known-empty, because or([]) is false.
// TODO: get the reason out.
self.mark_known_empty(EmptyBecause::AttributeLookupFailed);
return Ok(());
}
// Otherwise, we fold together the receptacles.
//
// Merge together the constraints from each receptacle. Each bundle of constraints is
// combined into a `ConstraintIntersection`, and the collection of intersections is
// combined into a `ConstraintAlternation`. (As an optimization, this collection can be
// simplified.)
//
// Each receptacle's known types are _unioned_. Strictly speaking this is a weakening:
// we might know that if `?x` is an integer then `?y` is a string, or vice versa, but at
// this point we'll simply state that `?x` and `?y` can both be integers or strings.
fn vec_for_iterator<T, I, U>(iter: &I) -> Vec<T> where I: Iterator<Item=U> {
match iter.size_hint().1 {
None => Vec::new(),
Some(expected) => Vec::with_capacity(expected),
}
}
let mut alternates: Vec<ColumnIntersection> = vec_for_iterator(&receptacles);
for r in receptacles {
folded.broaden_types(r.known_types);
alternates.push(r.wheres);
}
if alternates.len() == 1 {
// Simplify.
folded.wheres = alternates.pop().unwrap();
} else {
let alternation = ColumnAlternation(alternates);
let mut container = ColumnIntersection::default();
container.add(ColumnConstraintOrAlternation::Alternation(alternation));
folded.wheres = container;
}
}
// Collect the source alias: we use a single table join to represent the entire `or`.
self.from.push(source_alias);
// Add in the known types and constraints.
// Each constant attribute might _expand_ the set of possible types of the value-place
// variable. We thus generate a set of possible types, and we intersect it with the
// types already possible in the CC. If the resultant set is empty, the pattern cannot
// match. If the final set isn't unit, we must project a type tag column.
self.intersect(folded)
}
fn intersect(&mut self, mut cc: ConjoiningClauses) -> Result<()> {
if cc.is_known_empty() {
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self.empty_because = cc.empty_because;
}
self.wheres.append(&mut cc.wheres);
self.narrow_types(cc.known_types);
Ok(())
}
}
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#[cfg(test)]
mod testing {
extern crate mentat_query_parser;
use super::*;
use mentat_core::{
Attribute,
TypedValue,
ValueType,
};
use mentat_query::{
NamespacedKeyword,
Variable,
};
use self::mentat_query_parser::{
parse_find_string,
};
use clauses::{
add_attribute,
associate_ident,
};
use types::{
ColumnConstraint,
DatomsColumn,
DatomsTable,
NumericComparison,
QualifiedAlias,
QueryValue,
SourceAlias,
};
use algebrize;
fn alg(schema: &Schema, input: &str) -> ConjoiningClauses {
let parsed = parse_find_string(input).expect("parse failed");
algebrize(schema.into(), parsed).expect("algebrize failed").cc
}
fn compare_ccs(left: ConjoiningClauses, right: ConjoiningClauses) {
assert_eq!(left.wheres, right.wheres);
assert_eq!(left.from, right.from);
}
fn prepopulated_schema() -> Schema {
let mut schema = Schema::default();
associate_ident(&mut schema, NamespacedKeyword::new("foo", "name"), 65);
associate_ident(&mut schema, NamespacedKeyword::new("foo", "knows"), 66);
associate_ident(&mut schema, NamespacedKeyword::new("foo", "parent"), 67);
associate_ident(&mut schema, NamespacedKeyword::new("foo", "age"), 68);
associate_ident(&mut schema, NamespacedKeyword::new("foo", "height"), 69);
add_attribute(&mut schema, 65, Attribute {
value_type: ValueType::String,
multival: false,
..Default::default()
});
add_attribute(&mut schema, 66, Attribute {
value_type: ValueType::String,
multival: true,
..Default::default()
});
add_attribute(&mut schema, 67, Attribute {
value_type: ValueType::String,
multival: true,
..Default::default()
});
add_attribute(&mut schema, 68, Attribute {
value_type: ValueType::Long,
multival: false,
..Default::default()
});
add_attribute(&mut schema, 69, Attribute {
value_type: ValueType::Long,
multival: false,
..Default::default()
});
schema
}
/// Test that if all the attributes in an `or` fail to resolve, the entire thing fails.
#[test]
fn test_schema_based_failure() {
let schema = Schema::default();
let query = r#"
[:find ?x
:where (or [?x :foo/nope1 "John"]
[?x :foo/nope2 "Ámbar"]
[?x :foo/nope3 "Daphne"])]"#;
let cc = alg(&schema, query);
assert!(cc.is_known_empty());
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assert_eq!(cc.empty_because, Some(EmptyBecause::InvalidAttributeIdent(NamespacedKeyword::new("foo", "nope3"))));
}
/// Test that if only one of the attributes in an `or` resolves, it's equivalent to a simple query.
#[test]
fn test_only_one_arm_succeeds() {
let schema = prepopulated_schema();
let query = r#"
[:find ?x
:where (or [?x :foo/nope "John"]
[?x :foo/parent "Ámbar"]
[?x :foo/nope "Daphne"])]"#;
let cc = alg(&schema, query);
assert!(!cc.is_known_empty());
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compare_ccs(cc, alg(&schema, r#"[:find ?x :where [?x :foo/parent "Ámbar"]]"#));
}
// Simple alternation.
#[test]
fn test_simple_alternation() {
let schema = prepopulated_schema();
let query = r#"
[:find ?x
:where (or [?x :foo/knows "John"]
[?x :foo/parent "Ámbar"]
[?x :foo/knows "Daphne"])]"#;
let cc = alg(&schema, query);
let vx = Variable::from_valid_name("?x");
let d0 = "datoms00".to_string();
let d0e = QualifiedAlias(d0.clone(), DatomsColumn::Entity);
let d0a = QualifiedAlias(d0.clone(), DatomsColumn::Attribute);
let d0v = QualifiedAlias(d0.clone(), DatomsColumn::Value);
let knows = QueryValue::Entid(66);
let parent = QueryValue::Entid(67);
let john = QueryValue::TypedValue(TypedValue::typed_string("John"));
let ambar = QueryValue::TypedValue(TypedValue::typed_string("Ámbar"));
let daphne = QueryValue::TypedValue(TypedValue::typed_string("Daphne"));
assert!(!cc.is_known_empty());
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assert_eq!(cc.wheres, ColumnIntersection(vec![
ColumnConstraintOrAlternation::Alternation(
ColumnAlternation(vec![
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), knows.clone())),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0v.clone(), john))]),
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), parent)),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0v.clone(), ambar))]),
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), knows)),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0v.clone(), daphne))]),
]))]));
assert_eq!(cc.column_bindings.get(&vx), Some(&vec![d0e]));
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, d0)]);
}
// Alternation with a pattern.
#[test]
fn test_alternation_with_pattern() {
let schema = prepopulated_schema();
let query = r#"
[:find [?x ?name]
:where
[?x :foo/name ?name]
(or [?x :foo/knows "John"]
[?x :foo/parent "Ámbar"]
[?x :foo/knows "Daphne"])]"#;
let cc = alg(&schema, query);
let vx = Variable::from_valid_name("?x");
let d0 = "datoms00".to_string();
let d1 = "datoms01".to_string();
let d0e = QualifiedAlias(d0.clone(), DatomsColumn::Entity);
let d0a = QualifiedAlias(d0.clone(), DatomsColumn::Attribute);
let d1e = QualifiedAlias(d1.clone(), DatomsColumn::Entity);
let d1a = QualifiedAlias(d1.clone(), DatomsColumn::Attribute);
let d1v = QualifiedAlias(d1.clone(), DatomsColumn::Value);
let name = QueryValue::Entid(65);
let knows = QueryValue::Entid(66);
let parent = QueryValue::Entid(67);
let john = QueryValue::TypedValue(TypedValue::typed_string("John"));
let ambar = QueryValue::TypedValue(TypedValue::typed_string("Ámbar"));
let daphne = QueryValue::TypedValue(TypedValue::typed_string("Daphne"));
assert!(!cc.is_known_empty());
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assert_eq!(cc.wheres, ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), name.clone())),
ColumnConstraintOrAlternation::Alternation(
ColumnAlternation(vec![
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), knows.clone())),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1v.clone(), john))]),
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), parent)),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1v.clone(), ambar))]),
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), knows)),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1v.clone(), daphne))]),
])),
// The outer pattern joins against the `or`.
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0e.clone(), QueryValue::Column(d1e.clone()))),
]));
assert_eq!(cc.column_bindings.get(&vx), Some(&vec![d0e, d1e]));
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, d0),
SourceAlias(DatomsTable::Datoms, d1)]);
}
// Alternation with a pattern and a predicate.
#[test]
fn test_alternation_with_pattern_and_predicate() {
let schema = prepopulated_schema();
let query = r#"
[:find ?x ?age
:where
[?x :foo/age ?age]
[[< ?age 30]]
(or [?x :foo/knows "John"]
[?x :foo/knows "Daphne"])]"#;
let cc = alg(&schema, query);
let vx = Variable::from_valid_name("?x");
let d0 = "datoms00".to_string();
let d1 = "datoms01".to_string();
let d0e = QualifiedAlias(d0.clone(), DatomsColumn::Entity);
let d0a = QualifiedAlias(d0.clone(), DatomsColumn::Attribute);
let d0v = QualifiedAlias(d0.clone(), DatomsColumn::Value);
let d1e = QualifiedAlias(d1.clone(), DatomsColumn::Entity);
let d1a = QualifiedAlias(d1.clone(), DatomsColumn::Attribute);
let d1v = QualifiedAlias(d1.clone(), DatomsColumn::Value);
let knows = QueryValue::Entid(66);
let age = QueryValue::Entid(68);
let john = QueryValue::TypedValue(TypedValue::typed_string("John"));
let daphne = QueryValue::TypedValue(TypedValue::typed_string("Daphne"));
assert!(!cc.is_known_empty());
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assert_eq!(cc.wheres, ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), age.clone())),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::NumericInequality {
operator: NumericComparison::LessThan,
left: QueryValue::Column(d0v.clone()),
right: QueryValue::TypedValue(TypedValue::Long(30)),
}),
ColumnConstraintOrAlternation::Alternation(
ColumnAlternation(vec![
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), knows.clone())),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1v.clone(), john))]),
ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), knows)),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1v.clone(), daphne))]),
])),
// The outer pattern joins against the `or`.
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0e.clone(), QueryValue::Column(d1e.clone()))),
]));
assert_eq!(cc.column_bindings.get(&vx), Some(&vec![d0e, d1e]));
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, d0),
SourceAlias(DatomsTable::Datoms, d1)]);
}
// These two are not equivalent:
// [:find ?x :where [?x :foo/bar ?y] (or-join [?x] [?x :foo/baz ?y])]
// [:find ?x :where [?x :foo/bar ?y] [?x :foo/baz ?y]]
#[test]
#[should_panic(expected = "not yet implemented")]
fn test_unit_or_join_doesnt_flatten() {
let schema = prepopulated_schema();
let query = r#"[:find ?x
:where [?x :foo/knows ?y]
(or-join [?x] [?x :foo/parent ?y])]"#;
let cc = alg(&schema, query);
let vx = Variable::from_valid_name("?x");
let vy = Variable::from_valid_name("?y");
let d0 = "datoms00".to_string();
let d1 = "datoms01".to_string();
let d0e = QualifiedAlias(d0.clone(), DatomsColumn::Entity);
let d0a = QualifiedAlias(d0.clone(), DatomsColumn::Attribute);
let d0v = QualifiedAlias(d0.clone(), DatomsColumn::Value);
let d1e = QualifiedAlias(d1.clone(), DatomsColumn::Entity);
let d1a = QualifiedAlias(d1.clone(), DatomsColumn::Attribute);
let knows = QueryValue::Entid(66);
let parent = QueryValue::Entid(67);
assert!(!cc.is_known_empty());
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assert_eq!(cc.wheres, ColumnIntersection(vec![
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0a.clone(), knows.clone())),
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d1a.clone(), parent.clone())),
// The outer pattern joins against the `or` on the entity, but not value -- ?y means
// different things in each place.
ColumnConstraintOrAlternation::Constraint(ColumnConstraint::Equals(d0e.clone(), QueryValue::Column(d1e.clone()))),
]));
assert_eq!(cc.column_bindings.get(&vx), Some(&vec![d0e, d1e]));
// ?y does not have a binding in the `or-join` pattern.
assert_eq!(cc.column_bindings.get(&vy), Some(&vec![d0v]));
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, d0),
SourceAlias(DatomsTable::Datoms, d1)]);
}
// These two are equivalent:
// [:find ?x :where [?x :foo/bar ?y] (or [?x :foo/baz ?y])]
// [:find ?x :where [?x :foo/bar ?y] [?x :foo/baz ?y]]
#[test]
fn test_unit_or_does_flatten() {
let schema = prepopulated_schema();
let or_query = r#"[:find ?x
:where [?x :foo/knows ?y]
(or [?x :foo/parent ?y])]"#;
let flat_query = r#"[:find ?x
:where [?x :foo/knows ?y]
[?x :foo/parent ?y]]"#;
compare_ccs(alg(&schema, or_query),
alg(&schema, flat_query));
}
// Elision of `and`.
#[test]
fn test_unit_or_and_does_flatten() {
let schema = prepopulated_schema();
let or_query = r#"[:find ?x
:where (or (and [?x :foo/parent ?y]
[?x :foo/age 7]))]"#;
let flat_query = r#"[:find ?x
:where [?x :foo/parent ?y]
[?x :foo/age 7]]"#;
compare_ccs(alg(&schema, or_query),
alg(&schema, flat_query));
}
// Alternation with `and`.
/// [:find ?x
/// :where (or (and [?x :foo/knows "John"]
/// [?x :foo/parent "Ámbar"])
/// [?x :foo/knows "Daphne"])]
/// Strictly speaking this can be implemented with a `NOT EXISTS` clause for the second pattern,
/// but that would be a fair amount of analysis work, I think.
#[test]
#[should_panic(expected = "not yet implemented")]
#[allow(dead_code, unused_variables)]
fn test_alternation_with_and() {
let schema = prepopulated_schema();
let query = r#"
[:find ?x
:where (or (and [?x :foo/knows "John"]
[?x :foo/parent "Ámbar"])
[?x :foo/knows "Daphne"])]"#;
let cc = alg(&schema, query);
}
#[test]
fn test_type_based_or_pruning() {
let schema = prepopulated_schema();
// This simplifies to:
// [:find ?x
// :where [?a :some/int ?x]
// [_ :some/otherint ?x]]
let query = r#"
[:find ?x
:where [?a :foo/age ?x]
(or [_ :foo/height ?x]
[_ :foo/name ?x])]"#;
let simple = r#"
[:find ?x
:where [?a :foo/age ?x]
[_ :foo/height ?x]]"#;
compare_ccs(alg(&schema, query), alg(&schema, simple));
}
}