Part 6: implement decision tree for processing simple alternation.
This commit is contained in:
Richard Newman
parent
74f188df9b
commit
2b2b5cf696
1 changed files with 307 additions and 4 deletions
|
|
@ -20,12 +20,16 @@ use mentat_core::{
|
|||
|
||||
use mentat_query::{
|
||||
NonIntegerConstant,
|
||||
OrJoin,
|
||||
OrWhereClause,
|
||||
Pattern,
|
||||
PatternValuePlace,
|
||||
PatternNonValuePlace,
|
||||
PlainSymbol,
|
||||
Predicate,
|
||||
SrcVar,
|
||||
UnifyVars,
|
||||
WhereClause,
|
||||
};
|
||||
|
||||
use clauses::ConjoiningClauses;
|
||||
|
|
@ -43,16 +47,12 @@ use types::{
|
|||
DatomsTable,
|
||||
EmptyBecause,
|
||||
NumericComparison,
|
||||
OrJoinKind,
|
||||
QualifiedAlias,
|
||||
QueryValue,
|
||||
SourceAlias,
|
||||
TableAlias,
|
||||
};
|
||||
|
||||
|
||||
|
||||
|
||||
/// 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) {
|
||||
|
|
@ -78,3 +78,306 @@ fn _simply_matches_value_place(left: &PatternValuePlace, right: &PatternValuePla
|
|||
_ => true,
|
||||
}
|
||||
}
|
||||
|
||||
pub enum DeconstructedOrJoin {
|
||||
KnownSuccess,
|
||||
KnownEmpty(EmptyBecause),
|
||||
Unit(OrWhereClause),
|
||||
UnitPattern(Pattern),
|
||||
Simple(Vec<Pattern>),
|
||||
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(())
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
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.
|
||||
match or_join.clauses.len() {
|
||||
0 => Ok(()),
|
||||
1 => self.apply_or_where_clause(schema, or_join.clauses.pop().unwrap()),
|
||||
_ => 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`.
|
||||
assert_eq!(or_join.unify_vars, UnifyVars::Implicit);
|
||||
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.
|
||||
let mut clauses = or_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();
|
||||
|
||||
return DeconstructedOrJoin::Complex(OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: 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()),
|
||||
_ => DeconstructedOrJoin::Simple(patterns),
|
||||
}
|
||||
}
|
||||
|
||||
/// Only call this with an `or_join` with 2 or more patterns.
|
||||
fn apply_non_trivial_or_join(&mut self, schema: &Schema, or_join: OrJoin) -> Result<()> {
|
||||
assert!(or_join.clauses.len() >= 2);
|
||||
|
||||
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(())
|
||||
},
|
||||
DeconstructedOrJoin::Simple(patterns) => {
|
||||
// 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.
|
||||
// TODO
|
||||
self.apply_simple_or_join(schema, patterns)
|
||||
},
|
||||
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')
|
||||
/// ```
|
||||
///
|
||||
fn apply_simple_or_join(&mut self, schema: &Schema, patterns: Vec<Pattern>) -> Result<()> {
|
||||
assert!(patterns.len() >= 2);
|
||||
|
||||
// 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.
|
||||
// If one of the alternations requires a type that is impossible in the CC, then we can
|
||||
// discard that alternate:
|
||||
//
|
||||
// ```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]]
|
||||
// ```
|
||||
//
|
||||
// Similarly, if the value place is constant, it must be of a type that doesn't determine
|
||||
// a different table for any of the patterns.
|
||||
// TODO
|
||||
|
||||
// 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.
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in a new issue