mentat/query-projector/src/translate.rs

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// Copyright 2016 Mozilla
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use
// this file except in compliance with the License. You may obtain a copy of the
// License at http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
use core_traits::{TypedValue, ValueType, ValueTypeSet};
use mentat_core::{SQLTypeAffinity, SQLValueType, SQLValueTypeSet, Schema, ValueTypeTag};
use mentat_core::util::Either;
use edn::query::Limit;
use mentat_query_algebrizer::{
AlgebraicQuery, ColumnAlternation, ColumnConstraint, ColumnConstraintOrAlternation,
ColumnIntersection, ColumnName, ComputedTable, ConjoiningClauses, DatomsColumn, DatomsTable,
OrderBy, QualifiedAlias, QueryValue, SourceAlias, TableAlias, VariableColumn,
};
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use crate::{
projected_column_for_var, query_projection, CombinedProjection, ConstantProjector, Projector,
};
use mentat_query_sql::{
ColumnOrExpression, Constraint, FromClause, GroupBy, Op, ProjectedColumn, Projection,
SelectQuery, TableList, TableOrSubquery, Values,
};
use std::collections::HashMap;
use super::Result;
trait ToConstraint {
fn to_constraint(self) -> Constraint;
}
trait ToColumn {
fn to_column(self) -> ColumnOrExpression;
}
impl ToColumn for QualifiedAlias {
fn to_column(self) -> ColumnOrExpression {
ColumnOrExpression::Column(self)
}
}
impl ToConstraint for ColumnIntersection {
fn to_constraint(self) -> Constraint {
Constraint::And {
constraints: self.into_iter().map(|x| x.to_constraint()).collect(),
}
}
}
impl ToConstraint for ColumnAlternation {
fn to_constraint(self) -> Constraint {
Constraint::Or {
constraints: self.into_iter().map(|x| x.to_constraint()).collect(),
}
}
}
impl ToConstraint for ColumnConstraintOrAlternation {
fn to_constraint(self) -> Constraint {
use self::ColumnConstraintOrAlternation::*;
match self {
Alternation(alt) => alt.to_constraint(),
Constraint(c) => c.to_constraint(),
}
}
}
fn affinity_count(tag: i32) -> usize {
ValueTypeSet::any()
.into_iter()
.filter(|t| t.value_type_tag() == tag)
.count()
}
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#[allow(clippy::ptr_arg)]
fn type_constraint(
table: &TableAlias,
tag: i32,
to_check: Option<Vec<SQLTypeAffinity>>,
) -> Constraint {
let type_column = QualifiedAlias::new(table.clone(), DatomsColumn::ValueTypeTag).to_column();
let check_type_tag = Constraint::equal(type_column, ColumnOrExpression::Integer(tag));
if let Some(affinities) = to_check {
let check_affinities = Constraint::Or {
constraints: affinities
.into_iter()
.map(|affinity| Constraint::TypeCheck {
value: QualifiedAlias::new(table.clone(), DatomsColumn::Value).to_column(),
affinity,
})
.collect(),
};
Constraint::And {
constraints: vec![check_type_tag, check_affinities],
}
} else {
check_type_tag
}
}
// Returns a map of tags to a vector of all the possible affinities that those tags can represent
// given the types in `value_types`.
fn possible_affinities(value_types: ValueTypeSet) -> HashMap<ValueTypeTag, Vec<SQLTypeAffinity>> {
let mut result = HashMap::with_capacity(value_types.len());
for ty in value_types {
let (tag, affinity_to_check) = ty.sql_representation();
let affinities = result.entry(tag).or_insert_with(Vec::new);
if let Some(affinity) = affinity_to_check {
affinities.push(affinity);
}
}
result
}
impl ToConstraint for ColumnConstraint {
fn to_constraint(self) -> Constraint {
use self::ColumnConstraint::*;
match self {
Equals(qa, QueryValue::Entid(entid)) => {
Constraint::equal(qa.to_column(), ColumnOrExpression::Entid(entid))
}
Equals(qa, QueryValue::TypedValue(tv)) => {
Constraint::equal(qa.to_column(), ColumnOrExpression::Value(tv))
}
Equals(left, QueryValue::Column(right)) => {
Constraint::equal(left.to_column(), right.to_column())
}
Equals(qa, QueryValue::PrimitiveLong(value)) => {
let tag_column = qa
.for_associated_type_tag()
.expect("an associated type tag alias")
.to_column();
let value_column = qa.to_column();
// A bare long in a query might match a ref, an instant, a long (obviously), or a
// double. If it's negative, it can't match a ref, but that's OK -- it won't!
//
// However, '1' and '0' are used to represent booleans, and some integers are also
// used to represent FTS values. We don't want to accidentally match those.
//
// We ask `SQLValueType` whether this value is in range for how booleans are
// represented in the database.
//
// We only hit this code path when the attribute is unknown, so we're querying
// `all_datoms`. That means we don't see FTS IDs at all -- they're transparently
// replaced by their strings. If that changes, then you should also exclude the
// string type code (10) here.
let must_exclude_boolean = ValueType::Boolean.accommodates_integer(value);
if must_exclude_boolean {
Constraint::And {
constraints: vec![
Constraint::equal(
value_column,
ColumnOrExpression::Value(TypedValue::Long(value)),
),
Constraint::not_equal(
tag_column,
ColumnOrExpression::Integer(ValueType::Boolean.value_type_tag()),
),
],
}
} else {
Constraint::equal(
value_column,
ColumnOrExpression::Value(TypedValue::Long(value)),
)
}
}
Inequality {
operator,
left,
right,
} => Constraint::Infix {
op: Op(operator.to_sql_operator()),
left: left.into(),
right: right.into(),
},
Matches(left, right) => Constraint::Infix {
op: Op("MATCH"),
left: ColumnOrExpression::Column(left),
right: right.into(),
},
HasTypes {
value: table,
value_types,
check_value,
} => {
let constraints = if check_value {
possible_affinities(value_types)
.into_iter()
.map(|(tag, affinities)| {
let to_check = if affinities.is_empty()
|| affinities.len() == affinity_count(tag)
{
None
} else {
Some(affinities)
};
type_constraint(&table, tag, to_check)
})
.collect()
} else {
value_types
.into_iter()
.map(|vt| type_constraint(&table, vt.value_type_tag(), None))
.collect()
};
Constraint::Or { constraints }
}
Parse and Algebrize `not` & `not-join`. (#302) (Closes #303, #389, #422 ) r=rnewman * Part 1 - Parse `not` and `not-join` * Part 2 - Validate `not` and `not-join` pre-algebrization * Address review comments rnewman. * Remove `WhereNotClause` and populate `NotJoin` with `WhereClause`. * Fix validation for `not` and `not-join`, removing tests that were invalid. * Address rustification comments. * Rebase against `rust` branch. * Part 3 - Add required types for NotJoin. * Implement `PartialEq` for `ConjoiningClauses` so `ComputedTable` can be included inside `ColumnConstraint::NotExists` * Part 4 - Implement `apply_not_join` * Part 5 - Call `apply_not_join` from inside `apply_clause` * Part 6 - Translate `not-join` into `NOT EXISTS` SQL * Address review comments. * Rename `projected` to `unified` to better describe the fact that we are not projecting any variables. * Check for presence of each unified var in either `column_bindings` or `input_bindings` and bail if not there. * Copy over `input_bindings` for each var in `unified`. * Only copy over the first `column_binding` for each variable in `unified` rather than the whole list. * Update tests. * Address review comments. * Make output from Debug for NotExists more useful * Clear up misunderstanding. Any single failing clause in the not will cause the entire not to be considered empty * Address review comments. * Remove Limit requirement from cc_to_exists. * Use Entry.or_insert instead of matching on the entry to add to column_bindings. * Move addition of value_bindings to before apply_clauses on template. * Tidy up tests with some variable reuse. * Addressed nits, * Address review comments. * Move addition of column_bindings to above apply_clause. * Update tests. * Add test to ensure that unbound vars fail * Improve test for unbound variable to check for correct variable and error * address nits
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NotExists(computed_table) => {
let subquery = table_for_computed(computed_table, TableAlias::new());
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Constraint::NotExists { subquery }
}
}
}
}
pub enum ProjectedSelect {
Constant(ConstantProjector),
Query {
query: Box<SelectQuery>,
projector: Box<dyn Projector>,
},
}
// Nasty little hack to let us move out of indexed context.
struct ConsumableVec<T> {
inner: Vec<Option<T>>,
}
impl<T> From<Vec<T>> for ConsumableVec<T> {
fn from(vec: Vec<T>) -> ConsumableVec<T> {
ConsumableVec {
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inner: vec.into_iter().map(Some).collect(),
}
}
}
impl<T> ConsumableVec<T> {
fn take_dangerously(&mut self, i: usize) -> T {
::std::mem::replace(&mut self.inner[i], None).expect("each value to only be fetched once")
}
}
fn table_for_computed(computed: ComputedTable, alias: TableAlias) -> TableOrSubquery {
match computed {
ComputedTable::Union {
projection,
type_extraction,
arms,
} => {
// The projection list for each CC must have the same shape and the same names.
// The values we project might be fixed or they might be columns.
TableOrSubquery::Union(
arms.into_iter()
.map(|cc| {
// We're going to end up with the variables being projected and also some
// type tag columns.
let mut columns: Vec<ProjectedColumn> = Vec::with_capacity(projection.len() + type_extraction.len());
// For each variable, find out which column it maps to within this arm, and
// project it as the variable name.
// E.g., SELECT datoms03.v AS `?x`.
for var in projection.iter() {
// TODO: chain results out.
let (projected_column, type_set) = projected_column_for_var(var, &cc).expect("every var to be bound");
columns.push(projected_column);
// Similarly, project type tags if they're not known conclusively in the
// outer query.
// Assumption: we'll never need to project a tag without projecting the value of a variable.
if type_extraction.contains(var) {
let expression =
if let Some(tag) = type_set.unique_type_tag() {
// If we know the type for sure, just project the constant.
// SELECT datoms03.v AS `?x`, 10 AS `?x_value_type_tag`
ColumnOrExpression::Integer(tag)
} else {
// Otherwise, we'll have an established type binding! This'll be
// either a datoms table or, recursively, a subquery. Project
// this:
// SELECT datoms03.v AS `?x`,
// datoms03.value_type_tag AS `?x_value_type_tag`
let extract = cc.extracted_types
.get(var)
.expect("Expected variable to have a known type, or an extracted type");
ColumnOrExpression::Column(extract.clone())
};
let type_column = VariableColumn::VariableTypeTag(var.clone());
let proj = ProjectedColumn(expression, type_column.column_name());
columns.push(proj);
}
}
// Each arm simply turns into a subquery.
// The SQL translation will stuff "UNION" between each arm.
let projection = Projection::Columns(columns);
cc_to_select_query(projection, cc, false, vec![], None, Limit::None)
}).collect(),
alias)
}
Parse and Algebrize `not` & `not-join`. (#302) (Closes #303, #389, #422 ) r=rnewman * Part 1 - Parse `not` and `not-join` * Part 2 - Validate `not` and `not-join` pre-algebrization * Address review comments rnewman. * Remove `WhereNotClause` and populate `NotJoin` with `WhereClause`. * Fix validation for `not` and `not-join`, removing tests that were invalid. * Address rustification comments. * Rebase against `rust` branch. * Part 3 - Add required types for NotJoin. * Implement `PartialEq` for `ConjoiningClauses` so `ComputedTable` can be included inside `ColumnConstraint::NotExists` * Part 4 - Implement `apply_not_join` * Part 5 - Call `apply_not_join` from inside `apply_clause` * Part 6 - Translate `not-join` into `NOT EXISTS` SQL * Address review comments. * Rename `projected` to `unified` to better describe the fact that we are not projecting any variables. * Check for presence of each unified var in either `column_bindings` or `input_bindings` and bail if not there. * Copy over `input_bindings` for each var in `unified`. * Only copy over the first `column_binding` for each variable in `unified` rather than the whole list. * Update tests. * Address review comments. * Make output from Debug for NotExists more useful * Clear up misunderstanding. Any single failing clause in the not will cause the entire not to be considered empty * Address review comments. * Remove Limit requirement from cc_to_exists. * Use Entry.or_insert instead of matching on the entry to add to column_bindings. * Move addition of value_bindings to before apply_clauses on template. * Tidy up tests with some variable reuse. * Addressed nits, * Address review comments. * Move addition of column_bindings to above apply_clause. * Update tests. * Add test to ensure that unbound vars fail * Improve test for unbound variable to check for correct variable and error * address nits
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ComputedTable::Subquery(subquery) => {
TableOrSubquery::Subquery(Box::new(cc_to_exists(*subquery)))
}
ComputedTable::NamedValues { names, values } => {
// We assume column homogeneity, so we won't have any type tag columns.
TableOrSubquery::Values(Values::Named(names, values), alias)
}
}
}
fn empty_query() -> SelectQuery {
SelectQuery {
distinct: false,
projection: Projection::One,
from: FromClause::Nothing,
group_by: vec![],
constraints: vec![],
order: vec![],
limit: Limit::None,
}
}
/// Returns a `SelectQuery` that queries for the provided `cc`. Note that this _always_ returns a
/// query that runs SQL. The next level up the call stack can check for known-empty queries if
/// needed.
fn cc_to_select_query(
projection: Projection,
cc: ConjoiningClauses,
distinct: bool,
group_by: Vec<GroupBy>,
order: Option<Vec<OrderBy>>,
limit: Limit,
) -> SelectQuery {
let from = if cc.from.is_empty() {
FromClause::Nothing
} else {
// Move these out of the CC.
let from = cc.from;
let mut computed: ConsumableVec<_> = cc.computed_tables.into();
// Why do we put computed tables directly into the `FROM` clause? The alternative is to use
// a CTE (`WITH`). They're typically equivalent, but some SQL systems (notably Postgres)
// treat CTEs as optimization barriers, so a `WITH` can be significantly slower. Given that
// this is easy enough to change later, we'll opt for using direct inclusion in `FROM`.
let tables = from.into_iter().map(|source_alias| match source_alias {
SourceAlias(DatomsTable::Computed(i), alias) => {
let comp = computed.take_dangerously(i);
table_for_computed(comp, alias)
}
_ => TableOrSubquery::Table(source_alias),
});
FromClause::TableList(TableList(tables.collect()))
};
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let order = order.map_or(vec![], |vec| vec.into_iter().collect());
let limit = if cc.empty_because.is_some() {
Limit::Fixed(0)
} else {
limit
};
SelectQuery {
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distinct,
projection,
from,
group_by,
constraints: cc.wheres.into_iter().map(|c| c.to_constraint()).collect(),
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order,
limit,
}
}
/// 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() {
// In this case we can produce a very simple query that returns no results.
empty_query()
} else {
cc_to_select_query(Projection::One, cc, false, vec![], None, Limit::None)
}
}
/// Take a query and wrap it as a subquery of a new query with the provided projection list.
/// All limits, ordering, and grouping move to the outer query. The inner query is marked as
/// distinct.
fn re_project(mut inner: SelectQuery, projection: Projection) -> SelectQuery {
let outer_distinct = inner.distinct;
inner.distinct = true;
let group_by = inner.group_by;
inner.group_by = vec![];
let order_by = inner.order;
inner.order = vec![];
let limit = inner.limit;
inner.limit = Limit::None;
use self::Projection::*;
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let nullable = match projection {
Columns(ref columns) => columns
.iter()
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.filter_map(|pc| match *pc {
ProjectedColumn(ColumnOrExpression::NullableAggregate(_, _), ref name) => {
Some(Constraint::IsNotNull {
value: ColumnOrExpression::ExistingColumn(name.clone()),
})
}
_ => None,
})
.collect(),
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Star => vec![],
One => vec![],
};
if nullable.is_empty() {
return SelectQuery {
distinct: outer_distinct,
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projection,
from: FromClause::TableList(TableList(vec![TableOrSubquery::Subquery(Box::new(
inner,
))])),
constraints: vec![],
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group_by,
order: order_by,
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limit,
};
}
// Our pattern is `SELECT * FROM (SELECT ...) WHERE (nullable aggregate) IS NOT NULL`. If
// there's an `ORDER BY` in the subselect, SQL does not guarantee that the outer select will
// respect that order. But `ORDER BY` is relevant to the subselect when we have a `LIMIT`.
// Thus we lift the `ORDER BY` if theres no `LIMIT` in the subselect, and repeat the `ORDER BY`
// if there is.
let subselect = SelectQuery {
distinct: outer_distinct,
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projection,
from: FromClause::TableList(TableList(vec![TableOrSubquery::Subquery(Box::new(inner))])),
constraints: vec![],
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group_by,
order: match &limit {
&Limit::None => vec![],
&Limit::Fixed(_) | &Limit::Variable(_) => order_by.clone(),
},
limit,
};
SelectQuery {
distinct: false,
projection: Projection::Star,
from: FromClause::TableList(TableList(vec![TableOrSubquery::Subquery(Box::new(
subselect,
))])),
constraints: nullable,
group_by: vec![],
order: order_by,
limit: Limit::None, // Any limiting comes from the internal query.
}
}
/// Consume a provided `AlgebraicQuery` to yield a new
/// `ProjectedSelect`.
pub fn query_to_select(schema: &Schema, query: AlgebraicQuery) -> Result<ProjectedSelect> {
// TODO: we can't pass `query.limit` here if we aggregate during projection.
// SQL-based aggregation -- `SELECT SUM(datoms00.e)` -- is fine.
query_projection(schema, &query).map(|e| match e {
Either::Left(constant) => ProjectedSelect::Constant(constant),
Either::Right(CombinedProjection {
sql_projection,
pre_aggregate_projection,
datalog_projector,
distinct,
group_by_cols,
}) => {
ProjectedSelect::Query {
query: match pre_aggregate_projection {
// If we know we need a nested query for aggregation, build that first.
Some(pre_aggregate) => {
let inner = cc_to_select_query(
pre_aggregate,
query.cc,
distinct,
group_by_cols,
query.order,
query.limit,
);
Box::new(re_project(inner, sql_projection)) // outer
}
None => Box::new(cc_to_select_query(
sql_projection,
query.cc,
distinct,
group_by_cols,
query.order,
query.limit,
)),
},
projector: datalog_projector,
}
}
})
}