Algebrize simple or
joins. (#304) r=nalexander
This commit is contained in:
commit
1636134a72
11 changed files with 927 additions and 243 deletions
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@ -8,11 +8,6 @@
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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use std::fmt::{
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Debug,
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Formatter,
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};
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use std::collections::{
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BTreeMap,
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BTreeSet,
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@ -21,6 +16,11 @@ use std::collections::{
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use std::collections::btree_map::Entry;
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use std::fmt::{
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Debug,
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Formatter,
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};
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use mentat_core::{
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Attribute,
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Entid,
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@ -29,6 +29,8 @@ use mentat_core::{
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ValueType,
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};
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use mentat_core::counter::RcCounter;
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use mentat_query::{
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NamespacedKeyword,
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NonIntegerConstant,
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@ -73,24 +75,39 @@ impl<T: Clone> RcCloned<T> for ::std::rc::Rc<T> {
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}
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}
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/// A thing that's capable of aliasing a table name for us.
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/// This exists so that we can obtain predictable names in tests.
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pub type TableAliaser = Box<FnMut(DatomsTable) -> TableAlias>;
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pub fn default_table_aliaser() -> TableAliaser {
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let mut i = -1;
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Box::new(move |table| {
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i += 1;
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format!("{}{:02}", table.name(), i)
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})
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}
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fn unit_type_set(t: ValueType) -> HashSet<ValueType> {
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let mut s = HashSet::with_capacity(1);
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s.insert(t);
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s
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}
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trait Contains<K, T> {
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fn when_contains<F: FnOnce() -> T>(&self, k: &K, f: F) -> Option<T>;
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}
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trait Intersection<K> {
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fn with_intersected_keys(&self, ks: &BTreeSet<K>) -> Self;
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}
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impl<K: Ord, T> Contains<K, T> for BTreeSet<K> {
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fn when_contains<F: FnOnce() -> T>(&self, k: &K, f: F) -> Option<T> {
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if self.contains(k) {
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Some(f())
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} else {
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None
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}
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}
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}
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impl<K: Clone + Ord, V: Clone> Intersection<K> for BTreeMap<K, V> {
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/// Return a clone of the map with only keys that are present in `ks`.
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fn with_intersected_keys(&self, ks: &BTreeSet<K>) -> Self {
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self.iter()
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.filter_map(|(k, v)| ks.when_contains(k, || (k.clone(), v.clone())))
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.collect()
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}
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}
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/// A `ConjoiningClauses` (CC) is a collection of clauses that are combined with `JOIN`.
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/// The topmost form in a query is a `ConjoiningClauses`.
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///
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@ -115,12 +132,11 @@ fn unit_type_set(t: ValueType) -> HashSet<ValueType> {
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/// * Inline expressions?
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///---------------------------------------------------------------------------------------
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pub struct ConjoiningClauses {
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/// `true` if this set of clauses cannot yield results in the context of the current schema.
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pub is_known_empty: bool,
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/// `Some` if this set of clauses cannot yield results in the context of the current schema.
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pub empty_because: Option<EmptyBecause>,
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/// A function used to generate an alias for a table -- e.g., from "datoms" to "datoms123".
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aliaser: TableAliaser,
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/// A data source used to generate an alias for a table -- e.g., from "datoms" to "datoms123".
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alias_counter: RcCounter,
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/// A vector of source/alias pairs used to construct a SQL `FROM` list.
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pub from: Vec<SourceAlias>,
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@ -161,7 +177,7 @@ pub struct ConjoiningClauses {
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impl Debug for ConjoiningClauses {
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fn fmt(&self, fmt: &mut Formatter) -> ::std::fmt::Result {
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fmt.debug_struct("ConjoiningClauses")
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.field("is_known_empty", &self.is_known_empty)
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.field("empty_because", &self.empty_because)
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.field("from", &self.from)
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.field("wheres", &self.wheres)
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.field("column_bindings", &self.column_bindings)
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@ -177,9 +193,8 @@ impl Debug for ConjoiningClauses {
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impl Default for ConjoiningClauses {
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fn default() -> ConjoiningClauses {
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ConjoiningClauses {
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is_known_empty: false,
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empty_because: None,
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aliaser: default_table_aliaser(),
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alias_counter: RcCounter::new(),
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from: vec![],
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wheres: ColumnIntersection::default(),
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input_variables: BTreeSet::new(),
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@ -191,6 +206,36 @@ impl Default for ConjoiningClauses {
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}
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}
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/// Cloning.
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impl ConjoiningClauses {
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fn make_receptacle(&self) -> ConjoiningClauses {
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let mut concrete = ConjoiningClauses::default();
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concrete.empty_because = self.empty_because.clone();
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concrete.input_variables = self.input_variables.clone();
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concrete.value_bindings = self.value_bindings.clone();
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concrete.known_types = self.known_types.clone();
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concrete.extracted_types = self.extracted_types.clone();
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concrete
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}
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/// Make a new CC populated with the relevant variable associations in this CC.
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/// The CC shares an alias count with all of its copies.
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fn use_as_template(&self, vars: &BTreeSet<Variable>) -> ConjoiningClauses {
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let mut template = ConjoiningClauses::default();
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template.alias_counter = self.alias_counter.clone(); // Rc ftw.
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template.empty_because = self.empty_because.clone();
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template.input_variables = self.input_variables.intersection(vars).cloned().collect();
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template.value_bindings = self.value_bindings.with_intersected_keys(&vars);
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template.known_types = self.known_types.with_intersected_keys(&vars);
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template.extracted_types = self.extracted_types.with_intersected_keys(&vars);
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template
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}
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}
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impl ConjoiningClauses {
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#[allow(dead_code)]
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fn with_value_bindings(bindings: BTreeMap<Variable, TypedValue>) -> ConjoiningClauses {
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@ -201,7 +246,8 @@ impl ConjoiningClauses {
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// Pre-fill our type mappings with the types of the input bindings.
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cc.known_types
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.extend(cc.value_bindings.iter()
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.extend(cc.value_bindings
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.iter()
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.map(|(k, v)| (k.clone(), unit_type_set(v.value_type()))));
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cc
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}
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@ -304,46 +350,13 @@ impl ConjoiningClauses {
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numeric_types.insert(ValueType::Double);
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numeric_types.insert(ValueType::Long);
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let entry = self.known_types.entry(variable);
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match entry {
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Entry::Vacant(vacant) => {
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vacant.insert(numeric_types);
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},
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Entry::Occupied(mut occupied) => {
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let narrowed: HashSet<ValueType> = numeric_types.intersection(occupied.get()).cloned().collect();
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match narrowed.len() {
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0 => {
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// TODO: can't borrow as mutable more than once!
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//self.mark_known_empty(EmptyBecause::TypeMismatch(occupied.key().clone(), occupied.get().clone(), ValueType::Double)); // I know…
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},
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1 => {
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// Hooray!
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self.extracted_types.remove(occupied.key());
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},
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_ => {
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},
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};
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occupied.insert(narrowed);
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},
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}
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self.narrow_types_for_var(variable, numeric_types);
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}
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/// Constrains the var if there's no existing type.
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/// Marks as known-empty if it's impossible for this type to apply because there's a conflicting
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/// type already known.
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fn constrain_var_to_type(&mut self, variable: Variable, this_type: ValueType) {
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// If this variable now has a known attribute, we can unhook extracted types for
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// any other instances of that variable.
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// For example, given
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//
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// ```edn
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// [:find ?v :where [?x ?a ?v] [?y :foo/int ?v]]
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// ```
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//
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// we will initially choose to extract the type tag for `?v`, but on encountering
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// the second pattern we can avoid that.
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self.extracted_types.remove(&variable);
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// Is there an existing mapping for this variable?
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// Any known inputs have already been added to known_types, and so if they conflict we'll
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// spot it here.
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@ -355,6 +368,81 @@ impl ConjoiningClauses {
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}
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}
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/// Like `constrain_var_to_type` but in reverse: this expands the set of types
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/// with which a variable is associated.
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///
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/// N.B.,: if we ever call `broaden_types` after `empty_because` has been set, we might
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/// actually move from a state in which a variable can have no type to one that can
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/// yield results! We never do so at present -- we carefully set-union types before we
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/// set-intersect them -- but this is worth bearing in mind.
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pub fn broaden_types(&mut self, additional_types: BTreeMap<Variable, HashSet<ValueType>>) {
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for (var, new_types) in additional_types {
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match self.known_types.entry(var) {
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Entry::Vacant(e) => {
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if new_types.len() == 1 {
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self.extracted_types.remove(e.key());
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}
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e.insert(new_types);
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},
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Entry::Occupied(mut e) => {
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if e.get().is_empty() && self.empty_because.is_some() {
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panic!("Uh oh: we failed this pattern, probably because {:?} couldn't match, but now we're broadening its type.",
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e.get());
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}
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e.get_mut().extend(new_types.into_iter());
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},
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}
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}
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}
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/// Restrict the known types for `var` to intersect with `types`.
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/// If no types are already known -- `var` could have any type -- then this is equivalent to
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/// simply setting the known types to `types`.
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/// If the known types don't intersect with `types`, mark the pattern as known-empty.
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fn narrow_types_for_var(&mut self, var: Variable, types: HashSet<ValueType>) {
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if types.is_empty() {
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// We hope this never occurs; we should catch this case earlier.
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self.mark_known_empty(EmptyBecause::NoValidTypes(var));
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return;
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}
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// We can't mutate `empty_because` while we're working with the `Entry`, so do this instead.
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let mut empty_because: Option<EmptyBecause> = None;
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match self.known_types.entry(var) {
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Entry::Vacant(e) => {
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e.insert(types);
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},
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Entry::Occupied(mut e) => {
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// TODO: we shouldn't need to clone here.
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let intersected: HashSet<_> = types.intersection(e.get()).cloned().collect();
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if intersected.is_empty() {
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let mismatching_type = types.iter().next().unwrap().clone();
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let reason = EmptyBecause::TypeMismatch(e.key().clone(),
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e.get().clone(),
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mismatching_type);
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empty_because = Some(reason);
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}
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// Always insert, even if it's empty!
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e.insert(intersected);
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},
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}
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if let Some(e) = empty_because {
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self.mark_known_empty(e);
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}
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}
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/// Restrict the sets of types for the provided vars to the provided types.
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/// See `narrow_types_for_var`.
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pub fn narrow_types(&mut self, additional_types: BTreeMap<Variable, HashSet<ValueType>>) {
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if additional_types.is_empty() {
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return;
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}
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for (var, new_types) in additional_types {
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self.narrow_types_for_var(var, new_types);
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}
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}
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/// Ensure that the given place has the correct types to be a tx-id.
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/// Right now this is mostly unimplemented: we fail hard if anything but a placeholder is
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/// present.
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@ -376,8 +464,12 @@ impl ConjoiningClauses {
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}
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}
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#[inline]
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pub fn is_known_empty(&self) -> bool {
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self.empty_because.is_some()
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}
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fn mark_known_empty(&mut self, why: EmptyBecause) {
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self.is_known_empty = true;
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if self.empty_because.is_some() {
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return;
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}
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@ -484,25 +576,43 @@ impl ConjoiningClauses {
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}
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}
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pub fn next_alias_for_table(&mut self, table: DatomsTable) -> TableAlias {
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format!("{}{:02}", table.name(), self.alias_counter.next())
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}
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/// Produce a (table, alias) pair to handle the provided pattern.
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/// This is a mutating method because it mutates the aliaser function!
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/// Note that if this function decides that a pattern cannot match, it will flip
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/// `is_known_empty`.
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/// `empty_because`.
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fn alias_table<'s, 'a>(&mut self, schema: &'s Schema, pattern: &'a Pattern) -> Option<SourceAlias> {
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self.table_for_places(schema, &pattern.attribute, &pattern.value)
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.map_err(|reason| {
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self.mark_known_empty(reason);
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})
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.map(|table| SourceAlias(table, (self.aliaser)(table)))
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.map(|table: DatomsTable| SourceAlias(table, self.next_alias_for_table(table)))
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.ok()
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}
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fn get_attribute_for_value<'s>(&self, schema: &'s Schema, value: &TypedValue) -> Option<&'s Attribute> {
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match value {
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&TypedValue::Ref(id) => schema.attribute_for_entid(id),
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&TypedValue::Keyword(ref kw) => schema.attribute_for_ident(kw),
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_ => None,
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}
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}
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fn get_attribute<'s, 'a>(&self, schema: &'s Schema, pattern: &'a Pattern) -> Option<&'s Attribute> {
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match pattern.attribute {
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PatternNonValuePlace::Entid(id) =>
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schema.attribute_for_entid(id),
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PatternNonValuePlace::Ident(ref kw) =>
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schema.attribute_for_ident(kw),
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PatternNonValuePlace::Variable(ref var) =>
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// If the pattern has a variable, we've already determined that the binding -- if
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// any -- is acceptable and yields a table. Here, simply look to see if it names
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// an attribute so we can find out the type.
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self.value_bindings.get(var)
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.and_then(|val| self.get_attribute_for_value(schema, val)),
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_ =>
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None,
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}
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|
@ -546,6 +656,19 @@ impl ConjoiningClauses {
|
|||
}
|
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}
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/// Eliminate any type extractions for variables whose types are definitely known.
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pub fn prune_extracted_types(&mut self) {
|
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if self.extracted_types.is_empty() || self.known_types.is_empty() {
|
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return;
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}
|
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for (var, types) in self.known_types.iter() {
|
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if types.len() == 1 {
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self.extracted_types.remove(var);
|
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}
|
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}
|
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}
|
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|
||||
|
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/// When a CC has accumulated all patterns, generate value_type_tag entries in `wheres`
|
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/// to refine value types for which two things are true:
|
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///
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|
@ -582,9 +705,8 @@ impl ConjoiningClauses {
|
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self.apply_predicate(schema, p)
|
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},
|
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WhereClause::OrJoin(o) => {
|
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validate_or_join(&o)
|
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//?;
|
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//self.apply_or_join(schema, o)
|
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validate_or_join(&o)?;
|
||||
self.apply_or_join(schema, o)
|
||||
},
|
||||
_ => unimplemented!(),
|
||||
}
|
||||
|
@ -607,3 +729,21 @@ fn add_attribute(schema: &mut Schema, e: Entid, a: Attribute) {
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pub fn ident(ns: &str, name: &str) -> PatternNonValuePlace {
|
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PatternNonValuePlace::Ident(::std::rc::Rc::new(NamespacedKeyword::new(ns, name)))
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
// Our alias counter is shared between CCs.
|
||||
#[test]
|
||||
fn test_aliasing_through_template() {
|
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let mut starter = ConjoiningClauses::default();
|
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let alias_zero = starter.next_alias_for_table(DatomsTable::Datoms);
|
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let mut first = starter.use_as_template(&BTreeSet::new());
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let mut second = starter.use_as_template(&BTreeSet::new());
|
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let alias_one = first.next_alias_for_table(DatomsTable::Datoms);
|
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let alias_two = second.next_alias_for_table(DatomsTable::Datoms);
|
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assert!(alias_zero != alias_one);
|
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assert!(alias_one != alias_two);
|
||||
}
|
||||
}
|
|
@ -8,27 +8,21 @@
|
|||
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
||||
// specific language governing permissions and limitations under the License.
|
||||
|
||||
// WIP
|
||||
#![allow(dead_code, unused_imports, unused_variables)]
|
||||
use std::collections::btree_map::Entry;
|
||||
use std::collections::BTreeSet;
|
||||
|
||||
use mentat_core::{
|
||||
Entid,
|
||||
Schema,
|
||||
TypedValue,
|
||||
ValueType,
|
||||
};
|
||||
|
||||
use mentat_query::{
|
||||
NonIntegerConstant,
|
||||
OrJoin,
|
||||
OrWhereClause,
|
||||
Pattern,
|
||||
PatternValuePlace,
|
||||
PatternNonValuePlace,
|
||||
PlainSymbol,
|
||||
Predicate,
|
||||
SrcVar,
|
||||
UnifyVars,
|
||||
Variable,
|
||||
WhereClause,
|
||||
};
|
||||
|
||||
|
@ -36,21 +30,14 @@ use clauses::ConjoiningClauses;
|
|||
|
||||
use errors::{
|
||||
Result,
|
||||
Error,
|
||||
ErrorKind,
|
||||
};
|
||||
|
||||
use types::{
|
||||
ColumnConstraint,
|
||||
ColumnConstraintOrAlternation,
|
||||
ColumnAlternation,
|
||||
ColumnIntersection,
|
||||
DatomsColumn,
|
||||
DatomsTable,
|
||||
EmptyBecause,
|
||||
NumericComparison,
|
||||
QualifiedAlias,
|
||||
QueryValue,
|
||||
SourceAlias,
|
||||
TableAlias,
|
||||
};
|
||||
|
||||
/// Return true if both left and right are the same variable or both are non-variable.
|
||||
|
@ -84,7 +71,7 @@ pub enum DeconstructedOrJoin {
|
|||
KnownEmpty(EmptyBecause),
|
||||
Unit(OrWhereClause),
|
||||
UnitPattern(Pattern),
|
||||
Simple(Vec<Pattern>),
|
||||
Simple(Vec<Pattern>, BTreeSet<Variable>),
|
||||
Complex(OrJoin),
|
||||
}
|
||||
|
||||
|
@ -106,12 +93,26 @@ impl ConjoiningClauses {
|
|||
}
|
||||
}
|
||||
|
||||
fn apply_or_join(&mut self, schema: &Schema, mut or_join: OrJoin) -> Result<()> {
|
||||
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.
|
||||
|
||||
// Pre-cache mentioned variables. We use these in a few places.
|
||||
or_join.mentioned_variables();
|
||||
|
||||
match or_join.clauses.len() {
|
||||
0 => Ok(()),
|
||||
1 => self.apply_or_where_clause(schema, or_join.clauses.pop().unwrap()),
|
||||
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),
|
||||
}
|
||||
}
|
||||
|
@ -175,7 +176,7 @@ impl ConjoiningClauses {
|
|||
/// 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.is_fully_unified());
|
||||
assert!(or_join.clauses.len() >= 2);
|
||||
|
||||
// We're going to collect into this.
|
||||
|
@ -192,7 +193,8 @@ impl ConjoiningClauses {
|
|||
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();
|
||||
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.
|
||||
|
@ -259,10 +261,10 @@ impl ConjoiningClauses {
|
|||
.chain(clauses)
|
||||
.collect();
|
||||
|
||||
return DeconstructedOrJoin::Complex(OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: reconstructed,
|
||||
});
|
||||
return DeconstructedOrJoin::Complex(OrJoin::new(
|
||||
UnifyVars::Implicit,
|
||||
reconstructed,
|
||||
));
|
||||
}
|
||||
|
||||
// If we got here without returning, then `patterns` is what we're working with.
|
||||
|
@ -273,14 +275,11 @@ impl ConjoiningClauses {
|
|||
DeconstructedOrJoin::KnownEmpty(empty_because.unwrap())
|
||||
},
|
||||
1 => DeconstructedOrJoin::UnitPattern(patterns.pop().unwrap()),
|
||||
_ => DeconstructedOrJoin::Simple(patterns),
|
||||
_ => DeconstructedOrJoin::Simple(patterns, mentioned_vars),
|
||||
}
|
||||
}
|
||||
|
||||
/// 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.
|
||||
|
@ -301,12 +300,11 @@ impl ConjoiningClauses {
|
|||
self.apply_pattern(schema, pattern);
|
||||
Ok(())
|
||||
},
|
||||
DeconstructedOrJoin::Simple(patterns) => {
|
||||
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.
|
||||
// TODO
|
||||
self.apply_simple_or_join(schema, patterns)
|
||||
self.apply_simple_or_join(schema, patterns, mentioned_vars)
|
||||
},
|
||||
DeconstructedOrJoin::Complex(_) => {
|
||||
// Do this the hard way. TODO
|
||||
|
@ -343,34 +341,12 @@ impl ConjoiningClauses {
|
|||
/// 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);
|
||||
fn apply_simple_or_join(&mut self, schema: &Schema, patterns: Vec<Pattern>, mentioned_vars: BTreeSet<Variable>) -> Result<()> {
|
||||
if self.is_known_empty() {
|
||||
return Ok(())
|
||||
}
|
||||
|
||||
// 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
|
||||
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
|
||||
|
@ -378,6 +354,490 @@ impl ConjoiningClauses {
|
|||
// 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.
|
||||
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()
|
||||
.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);
|
||||
receptacle
|
||||
})
|
||||
.peekable();
|
||||
|
||||
// Let's see if we can grab a reason if every pattern failed.
|
||||
// If every pattern failed, we can just take the first!
|
||||
let reason = receptacles.peek()
|
||||
.map(|r| r.empty_because.clone())
|
||||
.unwrap_or(None);
|
||||
|
||||
// Filter out empties.
|
||||
let mut receptacles = receptacles.filter(|receptacle| !receptacle.is_known_empty())
|
||||
.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.
|
||||
self.mark_known_empty(reason.unwrap_or(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() {
|
||||
self.empty_because = cc.empty_because;
|
||||
}
|
||||
self.wheres.append(&mut cc.wheres);
|
||||
self.narrow_types(cc.known_types);
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[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());
|
||||
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());
|
||||
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());
|
||||
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());
|
||||
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());
|
||||
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());
|
||||
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));
|
||||
}
|
||||
}
|
|
@ -8,8 +8,6 @@
|
|||
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
||||
// specific language governing permissions and limitations under the License.
|
||||
|
||||
use std::rc::Rc;
|
||||
|
||||
use mentat_core::{
|
||||
Schema,
|
||||
TypedValue,
|
||||
|
@ -43,7 +41,7 @@ impl ConjoiningClauses {
|
|||
/// account all information spread across two patterns.
|
||||
///
|
||||
/// If the constraints cannot be satisfied -- for example, if this pattern includes a numeric
|
||||
/// attribute and a string value -- then the `is_known_empty` field on the CC is flipped and
|
||||
/// attribute and a string value -- then the `empty_because` field on the CC is flipped and
|
||||
/// the function returns.
|
||||
///
|
||||
/// A pattern being impossible to satisfy isn't necessarily a bad thing -- this query might
|
||||
|
@ -70,8 +68,10 @@ impl ConjoiningClauses {
|
|||
///
|
||||
/// - A unique-valued attribute can sometimes be rewritten into an
|
||||
/// existence subquery instead of a join.
|
||||
fn apply_pattern_clause_for_alias<'s>(&mut self, schema: &'s Schema, pattern: &Pattern, alias: &SourceAlias) {
|
||||
if self.is_known_empty {
|
||||
///
|
||||
/// This method is only public for use from `or.rs`.
|
||||
pub fn apply_pattern_clause_for_alias<'s>(&mut self, schema: &'s Schema, pattern: &Pattern, alias: &SourceAlias) {
|
||||
if self.is_known_empty() {
|
||||
return;
|
||||
}
|
||||
|
||||
|
@ -154,7 +154,7 @@ impl ConjoiningClauses {
|
|||
// Wouldn't it be nice if we didn't need to clone in the found case?
|
||||
// It doesn't matter too much: collisons won't be too frequent.
|
||||
self.constrain_var_to_type(v.clone(), this_type);
|
||||
if self.is_known_empty {
|
||||
if self.is_known_empty() {
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
@ -265,9 +265,12 @@ impl ConjoiningClauses {
|
|||
|
||||
#[cfg(test)]
|
||||
mod testing {
|
||||
extern crate mentat_query_parser;
|
||||
|
||||
use super::*;
|
||||
|
||||
use std::collections::BTreeMap;
|
||||
use std::rc::Rc;
|
||||
|
||||
use mentat_core::attribute::Unique;
|
||||
use mentat_core::{
|
||||
|
@ -280,6 +283,10 @@ mod testing {
|
|||
Variable,
|
||||
};
|
||||
|
||||
use self::mentat_query_parser::{
|
||||
parse_find_string,
|
||||
};
|
||||
|
||||
use clauses::{
|
||||
add_attribute,
|
||||
associate_ident,
|
||||
|
@ -295,6 +302,13 @@ mod testing {
|
|||
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
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_unknown_ident() {
|
||||
let mut cc = ConjoiningClauses::default();
|
||||
|
@ -308,7 +322,7 @@ mod testing {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
});
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -326,7 +340,7 @@ mod testing {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
});
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -356,7 +370,7 @@ mod testing {
|
|||
let d0_v = QualifiedAlias("datoms00".to_string(), DatomsColumn::Value);
|
||||
|
||||
// After this, we know a lot of things:
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, "datoms00".to_string())]);
|
||||
|
||||
// ?x must be a ref.
|
||||
|
@ -394,7 +408,7 @@ mod testing {
|
|||
let d0_e = QualifiedAlias("datoms00".to_string(), DatomsColumn::Entity);
|
||||
let d0_v = QualifiedAlias("datoms00".to_string(), DatomsColumn::Value);
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, "datoms00".to_string())]);
|
||||
|
||||
// ?x must be a ref.
|
||||
|
@ -443,11 +457,15 @@ mod testing {
|
|||
let d0_e = QualifiedAlias("datoms00".to_string(), DatomsColumn::Entity);
|
||||
let d0_a = QualifiedAlias("datoms00".to_string(), DatomsColumn::Attribute);
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::Datoms, "datoms00".to_string())]);
|
||||
|
||||
// ?x must be a ref.
|
||||
assert_eq!(cc.known_type(&x).unwrap(), ValueType::Ref);
|
||||
// ?x must be a ref, and ?v a boolean.
|
||||
assert_eq!(cc.known_type(&x), Some(ValueType::Ref));
|
||||
|
||||
// We don't need to extract a type for ?v, because the attribute is known.
|
||||
assert!(!cc.extracted_types.contains_key(&v));
|
||||
assert_eq!(cc.known_type(&v), Some(ValueType::Boolean));
|
||||
|
||||
// ?x is bound to datoms0.e.
|
||||
assert_eq!(cc.column_bindings.get(&x).unwrap(), &vec![d0_e.clone()]);
|
||||
|
@ -477,7 +495,7 @@ mod testing {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
});
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
assert_eq!(cc.empty_because.unwrap(), EmptyBecause::InvalidBinding(DatomsColumn::Attribute, hello));
|
||||
}
|
||||
|
||||
|
@ -503,7 +521,7 @@ mod testing {
|
|||
|
||||
let d0_e = QualifiedAlias("all_datoms00".to_string(), DatomsColumn::Entity);
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::AllDatoms, "all_datoms00".to_string())]);
|
||||
|
||||
// ?x must be a ref.
|
||||
|
@ -534,7 +552,7 @@ mod testing {
|
|||
let d0_e = QualifiedAlias("all_datoms00".to_string(), DatomsColumn::Entity);
|
||||
let d0_v = QualifiedAlias("all_datoms00".to_string(), DatomsColumn::Value);
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![SourceAlias(DatomsTable::AllDatoms, "all_datoms00".to_string())]);
|
||||
|
||||
// ?x must be a ref.
|
||||
|
@ -597,7 +615,7 @@ mod testing {
|
|||
let d1_e = QualifiedAlias("datoms01".to_string(), DatomsColumn::Entity);
|
||||
let d1_a = QualifiedAlias("datoms01".to_string(), DatomsColumn::Attribute);
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
assert_eq!(cc.from, vec![
|
||||
SourceAlias(DatomsTable::Datoms, "datoms00".to_string()),
|
||||
SourceAlias(DatomsTable::Datoms, "datoms01".to_string()),
|
||||
|
@ -697,7 +715,7 @@ mod testing {
|
|||
});
|
||||
|
||||
// The type of the provided binding doesn't match the type of the attribute.
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -729,7 +747,7 @@ mod testing {
|
|||
});
|
||||
|
||||
// The type of the provided binding doesn't match the type of the attribute.
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -772,13 +790,13 @@ mod testing {
|
|||
// Finally, expand column bindings to get the overlaps for ?x.
|
||||
cc.expand_column_bindings();
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
assert_eq!(cc.empty_because.unwrap(),
|
||||
EmptyBecause::TypeMismatch(y.clone(), unit_type_set(ValueType::String), ValueType::Boolean));
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[should_panic(expected = "assertion failed: cc.is_known_empty")]
|
||||
#[should_panic(expected = "assertion failed: cc.is_known_empty()")]
|
||||
/// This test needs range inference in order to succeed: we must deduce that ?y must
|
||||
/// simultaneously be a boolean-valued attribute and a ref-valued attribute, and thus
|
||||
/// the CC can never return results.
|
||||
|
@ -810,8 +828,26 @@ mod testing {
|
|||
// Finally, expand column bindings to get the overlaps for ?x.
|
||||
cc.expand_column_bindings();
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
assert_eq!(cc.empty_because.unwrap(),
|
||||
EmptyBecause::TypeMismatch(x.clone(), unit_type_set(ValueType::Ref), ValueType::Boolean));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn ensure_extracted_types_is_cleared() {
|
||||
let query = r#"[:find ?e ?v :where [_ _ ?v] [?e :foo/bar ?v]]"#;
|
||||
let mut schema = Schema::default();
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("foo", "bar"), 99);
|
||||
add_attribute(&mut schema, 99, Attribute {
|
||||
value_type: ValueType::Boolean,
|
||||
..Default::default()
|
||||
});
|
||||
let e = Variable::from_valid_name("?e");
|
||||
let v = Variable::from_valid_name("?v");
|
||||
let cc = alg(&schema, query);
|
||||
assert_eq!(cc.known_types.get(&e), Some(&unit_type_set(ValueType::Ref)));
|
||||
assert_eq!(cc.known_types.get(&v), Some(&unit_type_set(ValueType::Boolean)));
|
||||
assert!(!cc.extracted_types.contains_key(&e));
|
||||
assert!(!cc.extracted_types.contains_key(&v));
|
||||
}
|
||||
}
|
||||
|
|
|
@ -140,7 +140,7 @@ mod testing {
|
|||
value: PatternValuePlace::Variable(y.clone()),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
});
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
|
||||
let op = PlainSymbol::new("<");
|
||||
let comp = NumericComparison::from_datalog_operator(op.plain_name()).unwrap();
|
||||
|
@ -150,11 +150,11 @@ mod testing {
|
|||
FnArg::Variable(Variable::from_valid_name("?y")), FnArg::EntidOrInteger(10),
|
||||
]}).is_ok());
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
|
||||
// Finally, expand column bindings to get the overlaps for ?x.
|
||||
cc.expand_column_bindings();
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
|
||||
// After processing those two clauses, we know that ?y must be numeric, but not exactly
|
||||
// which type it must be.
|
||||
|
@ -200,7 +200,7 @@ mod testing {
|
|||
value: PatternValuePlace::Variable(y.clone()),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
});
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
|
||||
let op = PlainSymbol::new(">=");
|
||||
let comp = NumericComparison::from_datalog_operator(op.plain_name()).unwrap();
|
||||
|
@ -210,7 +210,7 @@ mod testing {
|
|||
FnArg::Variable(Variable::from_valid_name("?y")), FnArg::EntidOrInteger(10),
|
||||
]}).is_ok());
|
||||
|
||||
assert!(!cc.is_known_empty);
|
||||
assert!(!cc.is_known_empty());
|
||||
cc.apply_pattern(&schema, Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(x.clone()),
|
||||
|
@ -222,7 +222,7 @@ mod testing {
|
|||
// Finally, expand column bindings to get the overlaps for ?x.
|
||||
cc.expand_column_bindings();
|
||||
|
||||
assert!(cc.is_known_empty);
|
||||
assert!(cc.is_known_empty());
|
||||
assert_eq!(cc.empty_because.unwrap(),
|
||||
EmptyBecause::TypeMismatch(y.clone(),
|
||||
vec![ValueType::Double, ValueType::Long].into_iter()
|
||||
|
|
|
@ -63,8 +63,9 @@ impl AlgebraicQuery {
|
|||
};
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn is_known_empty(&self) -> bool {
|
||||
self.cc.is_known_empty
|
||||
self.cc.is_known_empty()
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -77,6 +78,8 @@ pub fn algebrize(schema: &Schema, parsed: FindQuery) -> Result<AlgebraicQuery> {
|
|||
for where_clause in where_clauses {
|
||||
cc.apply_clause(schema, where_clause)?;
|
||||
}
|
||||
cc.expand_column_bindings();
|
||||
cc.prune_extracted_types();
|
||||
|
||||
let limit = if parsed.find_spec.is_unit_limited() { Some(1) } else { None };
|
||||
Ok(AlgebraicQuery {
|
||||
|
|
|
@ -100,7 +100,7 @@ impl QualifiedAlias {
|
|||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Eq)]
|
||||
#[derive(PartialEq, Eq, Clone)]
|
||||
pub enum QueryValue {
|
||||
Column(QualifiedAlias),
|
||||
Entid(Entid),
|
||||
|
@ -233,16 +233,28 @@ impl IntoIterator for ColumnIntersection {
|
|||
}
|
||||
|
||||
impl ColumnIntersection {
|
||||
#[inline]
|
||||
pub fn len(&self) -> usize {
|
||||
self.0.len()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.0.is_empty()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn add(&mut self, constraint: ColumnConstraintOrAlternation) {
|
||||
self.0.push(constraint);
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn add_intersection(&mut self, constraint: ColumnConstraint) {
|
||||
self.0.push(ColumnConstraintOrAlternation::Constraint(constraint));
|
||||
self.add(ColumnConstraintOrAlternation::Constraint(constraint));
|
||||
}
|
||||
|
||||
pub fn append(&mut self, other: &mut Self) {
|
||||
self.0.append(&mut other.0)
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -301,6 +313,7 @@ impl Debug for ColumnConstraint {
|
|||
pub enum EmptyBecause {
|
||||
// Var, existing, desired.
|
||||
TypeMismatch(Variable, HashSet<ValueType>, ValueType),
|
||||
NoValidTypes(Variable),
|
||||
NonNumericArgument,
|
||||
NonStringFulltextValue,
|
||||
UnresolvedIdent(NamespacedKeyword),
|
||||
|
@ -319,6 +332,9 @@ impl Debug for EmptyBecause {
|
|||
write!(f, "Type mismatch: {:?} can't be {:?}, because it's already {:?}",
|
||||
var, desired, existing)
|
||||
},
|
||||
&NoValidTypes(ref var) => {
|
||||
write!(f, "Type mismatch: {:?} has no valid types", var)
|
||||
},
|
||||
&NonNumericArgument => {
|
||||
write!(f, "Non-numeric argument in numeric place")
|
||||
},
|
||||
|
|
|
@ -160,11 +160,7 @@ def_parser!(Where, or_clause, WhereClause, {
|
|||
.of_exactly(Where::or()
|
||||
.with(many1(Where::or_where_clause()))
|
||||
.map(|clauses| {
|
||||
WhereClause::OrJoin(
|
||||
OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: clauses,
|
||||
})
|
||||
WhereClause::OrJoin(OrJoin::new(UnifyVars::Implicit, clauses))
|
||||
}))
|
||||
});
|
||||
|
||||
|
@ -174,11 +170,7 @@ def_parser!(Where, or_join_clause, WhereClause, {
|
|||
.with(Where::rule_vars())
|
||||
.and(many1(Where::or_where_clause()))
|
||||
.map(|(vars, clauses)| {
|
||||
WhereClause::OrJoin(
|
||||
OrJoin {
|
||||
unify_vars: UnifyVars::Explicit(vars),
|
||||
clauses: clauses,
|
||||
})
|
||||
WhereClause::OrJoin(OrJoin::new(UnifyVars::Explicit(vars), clauses))
|
||||
}))
|
||||
});
|
||||
|
||||
|
@ -508,17 +500,15 @@ mod test {
|
|||
edn::Value::PlainSymbol(v.clone())])].into_iter().collect());
|
||||
assert_parses_to!(Where::or_clause, input,
|
||||
WhereClause::OrJoin(
|
||||
OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: vec![OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(variable(e)),
|
||||
attribute: PatternNonValuePlace::Variable(variable(a)),
|
||||
value: PatternValuePlace::Variable(variable(v)),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
}))],
|
||||
}));
|
||||
OrJoin::new(UnifyVars::Implicit,
|
||||
vec![OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(variable(e)),
|
||||
attribute: PatternNonValuePlace::Variable(variable(a)),
|
||||
value: PatternValuePlace::Variable(variable(v)),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
}))])));
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -535,17 +525,15 @@ mod test {
|
|||
edn::Value::PlainSymbol(v.clone())])].into_iter().collect());
|
||||
assert_parses_to!(Where::or_join_clause, input,
|
||||
WhereClause::OrJoin(
|
||||
OrJoin {
|
||||
unify_vars: UnifyVars::Explicit(vec![variable(e.clone())]),
|
||||
clauses: vec![OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(variable(e)),
|
||||
attribute: PatternNonValuePlace::Variable(variable(a)),
|
||||
value: PatternValuePlace::Variable(variable(v)),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
}))],
|
||||
}));
|
||||
OrJoin::new(UnifyVars::Explicit(vec![variable(e.clone())]),
|
||||
vec![OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(variable(e)),
|
||||
attribute: PatternNonValuePlace::Variable(variable(a)),
|
||||
value: PatternValuePlace::Variable(variable(v)),
|
||||
tx: PatternNonValuePlace::Placeholder,
|
||||
}))])));
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
|
|
@ -70,9 +70,9 @@ fn can_parse_simple_or() {
|
|||
FindSpec::FindScalar(Element::Variable(Variable::from_valid_name("?x"))));
|
||||
assert_eq!(p.where_clauses,
|
||||
vec![
|
||||
WhereClause::OrJoin(OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: vec![
|
||||
WhereClause::OrJoin(OrJoin::new(
|
||||
UnifyVars::Implicit,
|
||||
vec![
|
||||
OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
|
@ -90,7 +90,7 @@ fn can_parse_simple_or() {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
})),
|
||||
],
|
||||
}),
|
||||
)),
|
||||
]);
|
||||
}
|
||||
|
||||
|
@ -103,9 +103,9 @@ fn can_parse_unit_or_join() {
|
|||
FindSpec::FindScalar(Element::Variable(Variable::from_valid_name("?x"))));
|
||||
assert_eq!(p.where_clauses,
|
||||
vec![
|
||||
WhereClause::OrJoin(OrJoin {
|
||||
unify_vars: UnifyVars::Explicit(vec![Variable::from_valid_name("?x")]),
|
||||
clauses: vec![
|
||||
WhereClause::OrJoin(OrJoin::new(
|
||||
UnifyVars::Explicit(vec![Variable::from_valid_name("?x")]),
|
||||
vec![
|
||||
OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
|
@ -115,7 +115,7 @@ fn can_parse_unit_or_join() {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
})),
|
||||
],
|
||||
}),
|
||||
)),
|
||||
]);
|
||||
}
|
||||
|
||||
|
@ -128,9 +128,9 @@ fn can_parse_simple_or_join() {
|
|||
FindSpec::FindScalar(Element::Variable(Variable::from_valid_name("?x"))));
|
||||
assert_eq!(p.where_clauses,
|
||||
vec![
|
||||
WhereClause::OrJoin(OrJoin {
|
||||
unify_vars: UnifyVars::Explicit(vec![Variable::from_valid_name("?x")]),
|
||||
clauses: vec![
|
||||
WhereClause::OrJoin(OrJoin::new(
|
||||
UnifyVars::Explicit(vec![Variable::from_valid_name("?x")]),
|
||||
vec![
|
||||
OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
|
@ -148,7 +148,7 @@ fn can_parse_simple_or_join() {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
})),
|
||||
],
|
||||
}),
|
||||
)),
|
||||
]);
|
||||
}
|
||||
|
||||
|
@ -166,9 +166,9 @@ fn can_parse_simple_or_and_join() {
|
|||
FindSpec::FindScalar(Element::Variable(Variable::from_valid_name("?x"))));
|
||||
assert_eq!(p.where_clauses,
|
||||
vec![
|
||||
WhereClause::OrJoin(OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: vec![
|
||||
WhereClause::OrJoin(OrJoin::new(
|
||||
UnifyVars::Implicit,
|
||||
vec![
|
||||
OrWhereClause::Clause(
|
||||
WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
|
@ -179,9 +179,9 @@ fn can_parse_simple_or_and_join() {
|
|||
})),
|
||||
OrWhereClause::And(
|
||||
vec![
|
||||
WhereClause::OrJoin(OrJoin {
|
||||
unify_vars: UnifyVars::Implicit,
|
||||
clauses: vec![
|
||||
WhereClause::OrJoin(OrJoin::new(
|
||||
UnifyVars::Implicit,
|
||||
vec![
|
||||
OrWhereClause::Clause(WhereClause::Pattern(Pattern {
|
||||
source: None,
|
||||
entity: PatternNonValuePlace::Variable(Variable::from_valid_name("?x")),
|
||||
|
@ -197,7 +197,7 @@ fn can_parse_simple_or_and_join() {
|
|||
tx: PatternNonValuePlace::Placeholder,
|
||||
})),
|
||||
],
|
||||
}),
|
||||
)),
|
||||
|
||||
WhereClause::Pred(Predicate { operator: PlainSymbol::new("<"), args: vec![
|
||||
FnArg::Variable(Variable::from_valid_name("?y")), FnArg::EntidOrInteger(1),
|
||||
|
@ -205,6 +205,6 @@ fn can_parse_simple_or_and_join() {
|
|||
],
|
||||
)
|
||||
],
|
||||
}),
|
||||
)),
|
||||
]);
|
||||
}
|
||||
|
|
|
@ -8,21 +8,12 @@
|
|||
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
|
||||
// specific language governing permissions and limitations under the License.
|
||||
|
||||
#![allow(dead_code, unused_imports)]
|
||||
|
||||
use mentat_core::{
|
||||
SQLValueType,
|
||||
TypedValue,
|
||||
ValueType,
|
||||
};
|
||||
|
||||
use mentat_query::{
|
||||
Element,
|
||||
FindSpec,
|
||||
PlainSymbol,
|
||||
Variable,
|
||||
};
|
||||
|
||||
use mentat_query_algebrizer::{
|
||||
AlgebraicQuery,
|
||||
ColumnAlternation,
|
||||
|
@ -31,10 +22,8 @@ use mentat_query_algebrizer::{
|
|||
ColumnIntersection,
|
||||
ConjoiningClauses,
|
||||
DatomsColumn,
|
||||
DatomsTable,
|
||||
QualifiedAlias,
|
||||
QueryValue,
|
||||
SourceAlias,
|
||||
};
|
||||
|
||||
use mentat_query_projector::{
|
||||
|
@ -47,10 +36,8 @@ use mentat_query_sql::{
|
|||
ColumnOrExpression,
|
||||
Constraint,
|
||||
FromClause,
|
||||
Name,
|
||||
Op,
|
||||
Projection,
|
||||
ProjectedColumn,
|
||||
SelectQuery,
|
||||
TableList,
|
||||
};
|
||||
|
@ -171,7 +158,7 @@ fn cc_to_select_query<T: Into<Option<u64>>>(projection: Projection, cc: Conjoini
|
|||
FromClause::TableList(TableList(cc.from))
|
||||
};
|
||||
|
||||
let limit = if cc.is_known_empty { Some(0) } else { limit.into() };
|
||||
let limit = if cc.empty_because.is_some() { Some(0) } else { limit.into() };
|
||||
SelectQuery {
|
||||
distinct: distinct,
|
||||
projection: projection,
|
||||
|
@ -187,7 +174,7 @@ fn cc_to_select_query<T: Into<Option<u64>>>(projection: Projection, cc: Conjoini
|
|||
/// Return a query that projects `1` if the `cc` matches the store, and returns no results
|
||||
/// if it doesn't.
|
||||
pub fn cc_to_exists(cc: ConjoiningClauses) -> SelectQuery {
|
||||
if cc.is_known_empty {
|
||||
if cc.is_known_empty() {
|
||||
// In this case we can produce a very simple query that returns no results.
|
||||
SelectQuery {
|
||||
distinct: false,
|
||||
|
|
|
@ -51,16 +51,20 @@ fn translate<T: Into<Option<u64>>>(schema: &Schema, input: &'static str, limit:
|
|||
select.query.to_sql_query().unwrap()
|
||||
}
|
||||
|
||||
fn prepopulated_schema() -> Schema {
|
||||
fn prepopulated_typed_schema(foo_type: ValueType) -> Schema {
|
||||
let mut schema = Schema::default();
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("foo", "bar"), 99);
|
||||
add_attribute(&mut schema, 99, Attribute {
|
||||
value_type: ValueType::String,
|
||||
value_type: foo_type,
|
||||
..Default::default()
|
||||
});
|
||||
schema
|
||||
}
|
||||
|
||||
fn prepopulated_schema() -> Schema {
|
||||
prepopulated_typed_schema(ValueType::String)
|
||||
}
|
||||
|
||||
fn make_arg(name: &'static str, value: &'static str) -> (String, Rc<String>) {
|
||||
(name.to_string(), Rc::new(value.to_string()))
|
||||
}
|
||||
|
@ -215,13 +219,7 @@ fn test_numeric_less_than_unknown_attribute() {
|
|||
|
||||
#[test]
|
||||
fn test_numeric_gte_known_attribute() {
|
||||
let mut schema = Schema::default();
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("foo", "bar"), 99);
|
||||
add_attribute(&mut schema, 99, Attribute {
|
||||
value_type: ValueType::Double,
|
||||
..Default::default()
|
||||
});
|
||||
|
||||
let schema = prepopulated_typed_schema(ValueType::Double);
|
||||
let input = r#"[:find ?x :where [?x :foo/bar ?y] [(>= ?y 12.9)]]"#;
|
||||
let SQLQuery { sql, args } = translate(&schema, input, None);
|
||||
assert_eq!(sql, "SELECT DISTINCT `datoms00`.e AS `?x` FROM `datoms` AS `datoms00` WHERE `datoms00`.a = 99 AND `datoms00`.v >= 12.9");
|
||||
|
@ -230,15 +228,34 @@ fn test_numeric_gte_known_attribute() {
|
|||
|
||||
#[test]
|
||||
fn test_numeric_not_equals_known_attribute() {
|
||||
let mut schema = Schema::default();
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("foo", "bar"), 99);
|
||||
add_attribute(&mut schema, 99, Attribute {
|
||||
value_type: ValueType::Long,
|
||||
..Default::default()
|
||||
});
|
||||
|
||||
let schema = prepopulated_typed_schema(ValueType::Long);
|
||||
let input = r#"[:find ?x . :where [?x :foo/bar ?y] [(!= ?y 12)]]"#;
|
||||
let SQLQuery { sql, args } = translate(&schema, input, None);
|
||||
assert_eq!(sql, "SELECT `datoms00`.e AS `?x` FROM `datoms` AS `datoms00` WHERE `datoms00`.a = 99 AND `datoms00`.v <> 12 LIMIT 1");
|
||||
assert_eq!(args, vec![]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_simple_or_join() {
|
||||
let mut schema = Schema::default();
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("page", "url"), 97);
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("page", "title"), 98);
|
||||
associate_ident(&mut schema, NamespacedKeyword::new("page", "description"), 99);
|
||||
for x in 97..100 {
|
||||
add_attribute(&mut schema, x, Attribute {
|
||||
value_type: ValueType::String,
|
||||
..Default::default()
|
||||
});
|
||||
}
|
||||
|
||||
let input = r#"[:find [?url ?description]
|
||||
:where
|
||||
(or-join [?page]
|
||||
[?page :page/url "http://foo.com/"]
|
||||
[?page :page/title "Foo"])
|
||||
[?page :page/url ?url]
|
||||
[?page :page/description ?description]]"#;
|
||||
let SQLQuery { sql, args } = translate(&schema, input, None);
|
||||
assert_eq!(sql, "SELECT `datoms01`.v AS `?url`, `datoms02`.v AS `?description` FROM `datoms` AS `datoms00`, `datoms` AS `datoms01`, `datoms` AS `datoms02` WHERE ((`datoms00`.a = 97 AND `datoms00`.v = $v0) OR (`datoms00`.a = 98 AND `datoms00`.v = $v1)) AND `datoms01`.a = 97 AND `datoms02`.a = 99 AND `datoms00`.e = `datoms01`.e AND `datoms00`.e = `datoms02`.e LIMIT 1");
|
||||
assert_eq!(args, vec![make_arg("$v0", "http://foo.com/"), make_arg("$v1", "Foo")]);
|
||||
}
|
||||
|
|
|
@ -568,6 +568,9 @@ impl OrWhereClause {
|
|||
pub struct OrJoin {
|
||||
pub unify_vars: UnifyVars,
|
||||
pub clauses: Vec<OrWhereClause>,
|
||||
|
||||
/// Caches the result of `collect_mentioned_variables`.
|
||||
mentioned_vars: Option<BTreeSet<Variable>>,
|
||||
}
|
||||
|
||||
#[allow(dead_code)]
|
||||
|
@ -595,6 +598,14 @@ pub struct FindQuery {
|
|||
}
|
||||
|
||||
impl OrJoin {
|
||||
pub fn new(unify_vars: UnifyVars, clauses: Vec<OrWhereClause>) -> OrJoin {
|
||||
OrJoin {
|
||||
unify_vars: unify_vars,
|
||||
clauses: clauses,
|
||||
mentioned_vars: None,
|
||||
}
|
||||
}
|
||||
|
||||
/// Return true if either the `OrJoin` is `UnifyVars::Implicit`, or if
|
||||
/// every variable mentioned inside the join is also mentioned in the `UnifyVars` list.
|
||||
pub fn is_fully_unified(&self) -> bool {
|
||||
|
@ -605,8 +616,12 @@ impl OrJoin {
|
|||
// it would have failed validation. That allows us to simply compare counts here.
|
||||
// TODO: in debug mode, do a full intersection, and verify that our count check
|
||||
// returns the same results.
|
||||
let mentioned = self.collect_mentioned_variables();
|
||||
vars.len() == mentioned.len()
|
||||
// Use the cached list if we have one.
|
||||
if let Some(ref mentioned) = self.mentioned_vars {
|
||||
vars.len() == mentioned.len()
|
||||
} else {
|
||||
vars.len() == self.collect_mentioned_variables().len()
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
@ -654,6 +669,28 @@ impl ContainsVariables for OrJoin {
|
|||
}
|
||||
}
|
||||
|
||||
impl OrJoin {
|
||||
pub fn dismember(self) -> (Vec<OrWhereClause>, BTreeSet<Variable>) {
|
||||
let vars = match self.mentioned_vars {
|
||||
Some(m) => m,
|
||||
None => self.collect_mentioned_variables(),
|
||||
};
|
||||
(self.clauses, vars)
|
||||
}
|
||||
|
||||
pub fn mentioned_variables<'a>(&'a mut self) -> &'a BTreeSet<Variable> {
|
||||
if self.mentioned_vars.is_none() {
|
||||
let m = self.collect_mentioned_variables();
|
||||
self.mentioned_vars = Some(m);
|
||||
}
|
||||
if let Some(ref mentioned) = self.mentioned_vars {
|
||||
mentioned
|
||||
} else {
|
||||
panic!()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl ContainsVariables for Predicate {
|
||||
fn accumulate_mentioned_variables(&self, acc: &mut BTreeSet<Variable>) {
|
||||
for arg in &self.args {
|
||||
|
|
Loading…
Reference in a new issue