mentat/query-projector/src/project.rs
Richard Newman e21156a754
Implement simple pull expressions (#638) r=nalexander
* Refactor AttributeCache populator code for use from pull.

* Pre: add to_value_rc to Cloned.

* Pre: add From<StructuredMap> for Binding.

* Pre: clarify Store::open_empty.

* Pre: StructuredMap cleanup.

* Pre: clean up a doc test.

* Split projector crate. Pass schema to projector.

* CLI support for printing bindings.

* Add and use ConjoiningClauses::derive_types_from_find_spec.

* Define pull types.

* Implement pull on top of the attribute cache layer.

* Add pull support to the projector.

* Parse pull expressions.

* Add simple pull support to connection objects.

* Tests for pull.

* Compile with Rust 1.25.

The only choice involved in this commit is that of replacing the
anonymous lifetime '_ with a named lifetime for the cache; since we're
accepting a Known, which includes the cache in question, I think it's
clear that we expect the function to apply to any given cache
lifetime.

* Review comments.

* Bail on unnamed attribute.

* Make assert_parse_failure_contains safe to use.

* Rework query parser to report better errors for pull.

* Test for mixed wildcard and simple attribute.
2018-05-04 12:56:00 -07:00

522 lines
20 KiB
Rust

// Copyright 2018 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 std::collections::{
BTreeSet,
};
use indexmap::{
IndexSet,
};
use mentat_core::{
SQLValueType,
SQLValueTypeSet,
ValueTypeSet,
};
use mentat_core::util::{
Either,
};
use mentat_query::{
Element,
Pull,
Variable,
};
use mentat_query_algebrizer::{
AlgebraicQuery,
ColumnName,
ConjoiningClauses,
QualifiedAlias,
VariableColumn,
};
use mentat_query_sql::{
ColumnOrExpression,
GroupBy,
Name,
Projection,
ProjectedColumn,
};
use aggregates::{
SimpleAggregation,
projected_column_for_simple_aggregate,
};
use errors::{
ErrorKind,
Result,
};
use projectors::{
Projector,
};
use pull::{
PullIndices,
PullOperation,
PullTemplate,
};
use super::{
CombinedProjection,
TypedIndex,
};
/// An internal temporary struct to pass between the projection 'walk' and the
/// resultant projector.
/// Projection accumulates four things:
/// - Two SQL projection lists. We need two because aggregate queries are nested
/// in order to apply DISTINCT to values prior to aggregation.
/// - A collection of templates for the projector to use to extract values.
/// - A list of columns to use for grouping. Grouping is a property of the projection!
pub(crate) struct ProjectedElements {
pub sql_projection: Projection,
pub pre_aggregate_projection: Option<Projection>,
pub templates: Vec<TypedIndex>,
// TODO: when we have an expression like
// [:find (pull ?x [:foo/name :foo/age]) (pull ?x [:foo/friend]) …]
// it would be more efficient to combine them.
pub pulls: Vec<PullTemplate>,
pub group_by: Vec<GroupBy>,
}
impl ProjectedElements {
pub(crate) fn combine(self, projector: Box<Projector>, distinct: bool) -> Result<CombinedProjection> {
Ok(CombinedProjection {
sql_projection: self.sql_projection,
pre_aggregate_projection: self.pre_aggregate_projection,
datalog_projector: projector,
distinct: distinct,
group_by_cols: self.group_by,
})
}
// We need the templates to make a projector that we can then hand to `combine`. This is the easy
// way to get it.
pub(crate) fn take_templates(&mut self) -> Vec<TypedIndex> {
let mut out = vec![];
::std::mem::swap(&mut out, &mut self.templates);
out
}
pub(crate) fn take_pulls(&mut self) -> Vec<PullTemplate> {
let mut out = vec![];
::std::mem::swap(&mut out, &mut self.pulls);
out
}
}
fn candidate_type_column(cc: &ConjoiningClauses, var: &Variable) -> Result<(ColumnOrExpression, Name)> {
cc.extracted_types
.get(var)
.cloned()
.map(|alias| {
let type_name = VariableColumn::VariableTypeTag(var.clone()).column_name();
(ColumnOrExpression::Column(alias), type_name)
})
.ok_or_else(|| ErrorKind::UnboundVariable(var.name()).into())
}
fn cc_column(cc: &ConjoiningClauses, var: &Variable) -> Result<QualifiedAlias> {
cc.column_bindings
.get(var)
.and_then(|cols| cols.get(0).cloned())
.ok_or_else(|| ErrorKind::UnboundVariable(var.name()).into())
}
fn candidate_column(cc: &ConjoiningClauses, var: &Variable) -> Result<(ColumnOrExpression, Name)> {
// Every variable should be bound by the top-level CC to at least
// one column in the query. If that constraint is violated it's a
// bug in our code, so it's appropriate to panic here.
cc_column(cc, var)
.map(|qa| {
let name = VariableColumn::Variable(var.clone()).column_name();
(ColumnOrExpression::Column(qa), name)
})
}
/// Return the projected column -- that is, a value or SQL column and an associated name -- for a
/// given variable. Also return the type.
/// Callers are expected to determine whether to project a type tag as an additional SQL column.
pub fn projected_column_for_var(var: &Variable, cc: &ConjoiningClauses) -> Result<(ProjectedColumn, ValueTypeSet)> {
if let Some(value) = cc.bound_value(&var) {
// If we already know the value, then our lives are easy.
let tag = value.value_type();
let name = VariableColumn::Variable(var.clone()).column_name();
Ok((ProjectedColumn(ColumnOrExpression::Value(value.clone()), name), ValueTypeSet::of_one(tag)))
} else {
// If we don't, then the CC *must* have bound the variable.
let (column, name) = candidate_column(cc, var)?;
Ok((ProjectedColumn(column, name), cc.known_type_set(var)))
}
}
/// Walk an iterator of `Element`s, collecting projector templates and columns.
///
/// Returns a `ProjectedElements`, which combines SQL projections
/// and a `Vec` of `TypedIndex` 'keys' to use when looking up values.
///
/// Callers must ensure that every `Element` is distinct -- a query like
///
/// ```edn
/// [:find ?x ?x :where [?x _ _]]
/// ```
///
/// should fail to parse. See #358.
pub(crate) fn project_elements<'a, I: IntoIterator<Item = &'a Element>>(
count: usize,
elements: I,
query: &AlgebraicQuery) -> Result<ProjectedElements> {
// Give a little padding for type tags.
let mut inner_projection = Vec::with_capacity(count + 2);
// Everything in the outer query will _either_ be an aggregate operation
// _or_ a reference to a name projected from the inner.
// We'll expand them later.
let mut outer_projection: Vec<Either<Name, ProjectedColumn>> = Vec::with_capacity(count + 2);
let mut i: i32 = 0;
let mut min_max_count: usize = 0;
let mut templates = vec![];
let mut pulls: Vec<PullTemplate> = vec![];
let mut aggregates = false;
// Any variable that appears intact in the :find clause, not inside an aggregate expression.
// "Query variables not in aggregate expressions will group the results and appear intact
// in the result."
// We use an ordered set here so that we group in the correct order.
let mut outer_variables = IndexSet::new();
let mut corresponded_variables = IndexSet::new();
// Any variable that we are projecting from the inner query.
let mut inner_variables = BTreeSet::new();
for e in elements {
// Check for and reject duplicates.
match e {
&Element::Variable(ref var) => {
if outer_variables.contains(var) {
bail!(ErrorKind::InvalidProjection(format!("Duplicate variable {} in query.", var)));
}
if corresponded_variables.contains(var) {
bail!(ErrorKind::InvalidProjection(format!("Can't project both {} and `(the {})` from a query.", var, var)));
}
},
&Element::Corresponding(ref var) => {
if outer_variables.contains(var) {
bail!(ErrorKind::InvalidProjection(format!("Can't project both {} and `(the {})` from a query.", var, var)));
}
if corresponded_variables.contains(var) {
bail!(ErrorKind::InvalidProjection(format!("`(the {})` appears twice in query.", var)));
}
},
&Element::Aggregate(_) => {
},
&Element::Pull(_) => {
},
};
// Record variables -- `(the ?x)` and `?x` are different in this regard, because we don't want
// to group on variables that are corresponding-projected.
match e {
&Element::Variable(ref var) => {
outer_variables.insert(var.clone());
},
&Element::Corresponding(ref var) => {
// We will project these later; don't put them in `outer_variables`
// so we know not to group them.
corresponded_variables.insert(var.clone());
},
&Element::Pull(Pull { ref var, patterns: _ }) => {
// We treat `pull` as an ordinary variable extraction,
// and we expand it later.
outer_variables.insert(var.clone());
},
&Element::Aggregate(_) => {
},
};
// Now do the main processing of each element.
match e {
// Each time we come across a variable, we push a SQL column
// into the SQL projection, aliased to the name of the variable,
// and we push an annotated index into the projector.
&Element::Variable(ref var) |
&Element::Corresponding(ref var) => {
inner_variables.insert(var.clone());
let (projected_column, type_set) = projected_column_for_var(&var, &query.cc)?;
outer_projection.push(Either::Left(projected_column.1.clone()));
inner_projection.push(projected_column);
if let Some(tag) = type_set.unique_type_tag() {
templates.push(TypedIndex::Known(i, tag));
i += 1; // We used one SQL column.
} else {
templates.push(TypedIndex::Unknown(i, i + 1));
i += 2; // We used two SQL columns.
// Also project the type from the SQL query.
let (type_column, type_name) = candidate_type_column(&query.cc, &var)?;
inner_projection.push(ProjectedColumn(type_column, type_name.clone()));
outer_projection.push(Either::Left(type_name));
}
},
&Element::Pull(Pull { ref var, ref patterns }) => {
inner_variables.insert(var.clone());
let (projected_column, type_set) = projected_column_for_var(&var, &query.cc)?;
outer_projection.push(Either::Left(projected_column.1.clone()));
inner_projection.push(projected_column);
if let Some(tag) = type_set.unique_type_tag() {
// We will have at least as many SQL columns as Datalog output columns.
// `i` tracks the former. The length of `templates` is the current latter.
// Projecting pull requires grabbing values, which we can do from the raw
// rows, and then populating the output, so we keep both column indices.
let output_index = templates.len();
assert!(output_index <= i as usize);
templates.push(TypedIndex::Known(i, tag));
pulls.push(PullTemplate {
indices: PullIndices {
sql_index: i,
output_index,
},
op: PullOperation((*patterns).clone()),
});
i += 1; // We used one SQL column.
} else {
// This should be impossible: (pull ?x) implies that ?x is a ref.
unreachable!();
}
},
&Element::Aggregate(ref a) => {
if let Some(simple) = a.to_simple() {
aggregates = true;
use aggregates::SimpleAggregationOp::*;
match simple.op {
Max | Min => {
min_max_count += 1;
},
Avg | Count | Sum => (),
}
// When we encounter a simple aggregate -- one in which the aggregation can be
// implemented in SQL, on a single variable -- we just push the SQL aggregation op.
// We must ensure the following:
// - There's a column for the var.
// - The type of the var is known to be restricted to a sensible input set
// (not necessarily a single type, but e.g., all vals must be Double or Long).
// - The type set must be appropriate for the operation. E.g., `Sum` is not a
// meaningful operation on instants.
let (projected_column, return_type) = projected_column_for_simple_aggregate(&simple, &query.cc)?;
outer_projection.push(Either::Right(projected_column));
if !inner_variables.contains(&simple.var) {
inner_variables.insert(simple.var.clone());
let (projected_column, _type_set) = projected_column_for_var(&simple.var, &query.cc)?;
inner_projection.push(projected_column);
if query.cc.known_type_set(&simple.var).unique_type_tag().is_none() {
// Also project the type from the SQL query.
let (type_column, type_name) = candidate_type_column(&query.cc, &simple.var)?;
inner_projection.push(ProjectedColumn(type_column, type_name.clone()));
}
}
// We might regret using the type tag here instead of the `ValueType`.
templates.push(TypedIndex::Known(i, return_type.value_type_tag()));
i += 1;
} else {
// TODO: complex aggregates.
bail!(ErrorKind::NotYetImplemented("complex aggregates".into()));
}
},
}
}
match (min_max_count, corresponded_variables.len()) {
(0, 0) | (_, 0) => {},
(0, _) => {
bail!(ErrorKind::InvalidProjection("Warning: used `the` without `min` or `max`.".to_string()));
},
(1, _) => {
// This is the success case!
},
(n, c) => {
bail!(ErrorKind::AmbiguousAggregates(n, c));
},
}
// Anything used in ORDER BY (which we're given in `named_projection`)
// needs to be in the SQL column list so we can refer to it by name.
//
// They don't affect projection.
//
// If a variable is of a non-fixed type, also project the type tag column, so we don't
// accidentally unify across types when considering uniqueness!
for var in query.named_projection.iter() {
if outer_variables.contains(var) {
continue;
}
// If it's a fixed value, we need do nothing further.
if query.cc.is_value_bound(&var) {
continue;
}
let already_inner = inner_variables.contains(&var);
let (column, name) = candidate_column(&query.cc, &var)?;
if !already_inner {
inner_projection.push(ProjectedColumn(column, name.clone()));
inner_variables.insert(var.clone());
}
outer_projection.push(Either::Left(name));
outer_variables.insert(var.clone());
// We don't care if a column has a single _type_, we care if it has a single type _tag_,
// because that's what we'll use if we're projecting. E.g., Long and Double.
// Single type implies single type tag, and is cheaper, so we check that first.
let types = query.cc.known_type_set(&var);
if !types.has_unique_type_tag() {
let (type_column, type_name) = candidate_type_column(&query.cc, &var)?;
if !already_inner {
inner_projection.push(ProjectedColumn(type_column, type_name.clone()));
}
outer_projection.push(Either::Left(type_name));
}
}
if !aggregates {
// We're done -- we never need to group unless we're aggregating.
return Ok(ProjectedElements {
sql_projection: Projection::Columns(inner_projection),
pre_aggregate_projection: None,
templates,
pulls,
group_by: vec![],
});
}
// OK, on to aggregates.
// We need to produce two SQL projection lists: one for an inner query and one for the outer.
//
// The inner serves these purposes:
// - Projecting variables to avoid duplicates being elided. (:with)
// - Making bindings available to the outermost query for projection, ordering, and grouping.
//
// The outer is consumed by the projector.
//
// We will also be producing:
// - A GROUP BY list to group the output of the inner query by non-aggregate variables
// so that it can be correctly aggregated.
// Turn this collection of vars into a collection of columns from the query.
// We don't allow grouping on anything but a variable bound in the query.
// We group by tag if necessary.
let mut group_by = Vec::with_capacity(outer_variables.len() + 2);
let vars = outer_variables.into_iter().zip(::std::iter::repeat(true));
let corresponds = corresponded_variables.into_iter().zip(::std::iter::repeat(false));
for (var, group) in vars.chain(corresponds) {
if query.cc.is_value_bound(&var) {
continue;
}
if group {
// The GROUP BY goes outside, but it needs every variable and type tag to be
// projected from inside. Collect in both directions here.
let name = VariableColumn::Variable(var.clone()).column_name();
group_by.push(GroupBy::ProjectedColumn(name));
}
let needs_type_projection = !query.cc.known_type_set(&var).has_unique_type_tag();
let already_inner = inner_variables.contains(&var);
if !already_inner {
let (column, name) = candidate_column(&query.cc, &var)?;
inner_projection.push(ProjectedColumn(column, name.clone()));
}
if needs_type_projection {
let type_name = VariableColumn::VariableTypeTag(var.clone()).column_name();
if !already_inner {
let type_col = query.cc
.extracted_types
.get(&var)
.cloned()
.ok_or_else(|| ErrorKind::NoTypeAvailableForVariable(var.name().clone()))?;
inner_projection.push(ProjectedColumn(ColumnOrExpression::Column(type_col), type_name.clone()));
}
if group {
group_by.push(GroupBy::ProjectedColumn(type_name));
}
};
}
for var in query.with.iter() {
// We never need to project a constant.
if query.cc.is_value_bound(&var) {
continue;
}
// We don't need to add inner projections for :with if they are already there.
if !inner_variables.contains(&var) {
let (projected_column, type_set) = projected_column_for_var(&var, &query.cc)?;
inner_projection.push(projected_column);
if type_set.unique_type_tag().is_none() {
// Also project the type from the SQL query.
let (type_column, type_name) = candidate_type_column(&query.cc, &var)?;
inner_projection.push(ProjectedColumn(type_column, type_name.clone()));
}
}
}
// At this point we know we have a double-layer projection. Collect the outer.
//
// If we have an inner and outer layer, the inner layer will name its
// variables, and the outer will re-project them.
// If we only have one layer, then the outer will do the naming.
// (We could try to not use names in the inner query, but then what would we do for
// `ground` and known values?)
// Walk the projection, switching the outer columns to use the inner names.
let outer_projection = outer_projection.into_iter().map(|c| {
match c {
Either::Left(name) => {
ProjectedColumn(ColumnOrExpression::ExistingColumn(name.clone()),
name)
},
Either::Right(pc) => pc,
}
}).collect();
Ok(ProjectedElements {
sql_projection: Projection::Columns(outer_projection),
pre_aggregate_projection: Some(Projection::Columns(inner_projection)),
templates,
pulls,
group_by,
})
}