2017-03-06 22:40:10 +00:00
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// Copyright 2016 Mozilla
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//
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not use
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// this file except in compliance with the License. You may obtain a copy of the
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// License at http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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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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#[macro_use]
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extern crate error_chain;
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extern crate rusqlite;
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extern crate mentat_core;
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extern crate mentat_db; // For value conversion.
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extern crate mentat_query;
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extern crate mentat_query_algebrizer;
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extern crate mentat_query_sql;
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extern crate mentat_sql;
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use std::iter;
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use rusqlite::{
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Row,
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Rows,
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};
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use mentat_core::{
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SQLValueType,
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TypedValue,
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};
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use mentat_db::{
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TypedSQLValue,
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};
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use mentat_query::{
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Element,
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FindSpec,
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PlainSymbol,
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Variable,
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};
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use mentat_query_algebrizer::{
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AlgebraicQuery,
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DatomsColumn,
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QualifiedAlias,
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/*
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ConjoiningClauses,
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DatomsTable,
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SourceAlias,
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*/
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};
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use mentat_query_sql::{
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ColumnOrExpression,
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/*
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Constraint,
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FromClause,
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*/
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Name,
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Projection,
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ProjectedColumn,
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/*
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SelectQuery,
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TableList,
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*/
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};
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error_chain! {
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types {
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Error, ErrorKind, ResultExt, Result;
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}
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foreign_links {
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Rusqlite(rusqlite::Error);
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}
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links {
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DbError(mentat_db::Error, mentat_db::ErrorKind);
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}
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}
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#[derive(Debug)]
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pub enum QueryResults {
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Scalar(Option<TypedValue>),
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Tuple(Option<Vec<TypedValue>>),
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Coll(Vec<TypedValue>),
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Rel(Vec<Vec<TypedValue>>),
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}
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impl QueryResults {
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pub fn len(&self) -> usize {
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use QueryResults::*;
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match self {
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&Scalar(ref o) => if o.is_some() { 1 } else { 0 },
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&Tuple(ref o) => if o.is_some() { 1 } else { 0 },
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&Coll(ref v) => v.len(),
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&Rel(ref v) => v.len(),
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}
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}
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pub fn is_empty(&self) -> bool {
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use QueryResults::*;
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match self {
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&Scalar(ref o) => o.is_none(),
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&Tuple(ref o) => o.is_none(),
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&Coll(ref v) => v.is_empty(),
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&Rel(ref v) => v.is_empty(),
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}
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}
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pub fn empty(spec: &FindSpec) -> QueryResults {
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use self::FindSpec::*;
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match spec {
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&FindScalar(_) => QueryResults::Scalar(None),
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&FindTuple(_) => QueryResults::Tuple(None),
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&FindColl(_) => QueryResults::Coll(vec![]),
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&FindRel(_) => QueryResults::Rel(vec![]),
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}
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}
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pub fn empty_factory(spec: &FindSpec) -> Box<Fn() -> QueryResults> {
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use self::FindSpec::*;
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match spec {
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&FindScalar(_) => Box::new(|| QueryResults::Scalar(None)),
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&FindTuple(_) => Box::new(|| QueryResults::Tuple(None)),
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&FindColl(_) => Box::new(|| QueryResults::Coll(vec![])),
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&FindRel(_) => Box::new(|| QueryResults::Rel(vec![])),
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}
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}
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2017-03-06 22:40:10 +00:00
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}
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type Index = i32; // See rusqlite::RowIndex.
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type ValueTypeTag = i32;
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enum TypedIndex {
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Known(Index, ValueTypeTag),
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Unknown(Index, Index),
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}
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impl TypedIndex {
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/// Look up this index and type(index) pair in the provided row.
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/// This function will panic if:
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///
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/// - This is an `Unknown` and the retrieved type code isn't an i32.
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/// - If the retrieved value can't be coerced to a rusqlite `Value`.
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/// - Either index is out of bounds.
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///
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/// Because we construct our SQL projection list, the code that stored the data, and this
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/// consumer, a panic here implies that we have a bad bug — we put data of a very wrong type in
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/// a row, and thus can't coerce to Value, we're retrieving from the wrong place, or our
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/// generated SQL is junk.
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///
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/// This function will return a runtime error if the type code is unknown, or the value is
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/// otherwise not convertible by the DB layer.
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fn lookup<'a, 'stmt>(&self, row: &Row<'a, 'stmt>) -> Result<TypedValue> {
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use TypedIndex::*;
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match self {
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&Known(value_index, value_type) => {
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let v: rusqlite::types::Value = row.get(value_index);
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TypedValue::from_sql_value_pair(v, value_type).map_err(|e| e.into())
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},
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&Unknown(value_index, type_index) => {
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let v: rusqlite::types::Value = row.get(value_index);
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let value_type_tag: i32 = row.get(type_index);
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TypedValue::from_sql_value_pair(v, value_type_tag).map_err(|e| e.into())
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},
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}
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}
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}
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fn column_name(var: &Variable) -> Name {
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let &Variable(PlainSymbol(ref s)) = var;
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s.clone()
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}
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fn value_type_tag_name(var: &Variable) -> Name {
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let &Variable(PlainSymbol(ref s)) = var;
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format!("{}_value_type_tag", s)
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}
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/// Walk an iterator of `Element`s, collecting projector templates and columns.
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///
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/// Returns a pair: the SQL projection (which should always be a `Projection::Columns`)
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/// and a `Vec` of `TypedIndex` 'keys' to use when looking up values.
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///
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/// Callers must ensure that every `Element` is distinct -- a query like
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///
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/// ```edn
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/// [:find ?x ?x :where [?x _ _]]
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/// ```
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///
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/// should fail to parse. See #358.
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fn project_elements<'a, I: IntoIterator<Item = &'a Element>>(
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count: usize,
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elements: I,
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query: &AlgebraicQuery) -> (Projection, Vec<TypedIndex>) {
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let mut cols = Vec::with_capacity(count);
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let mut i: i32 = 0;
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let mut templates = vec![];
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for e in elements {
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match e {
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// Each time we come across a variable, we push a SQL column
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// into the SQL projection, aliased to the name of the variable,
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// and we push an annotated index into the projector.
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&Element::Variable(ref var) => {
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// Every variable should be bound by the top-level CC to at least
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// one column in the query. If that constraint is violated it's a
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// bug in our code, so it's appropriate to panic here.
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let columns = query.cc
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.column_bindings
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.get(var)
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.expect("Every variable has a binding");
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let qa = columns[0].clone();
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let name = column_name(var);
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if let Some(t) = query.cc.known_type(var) {
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cols.push(ProjectedColumn(ColumnOrExpression::Column(qa), name));
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let tag = t.value_type_tag();
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templates.push(TypedIndex::Known(i, tag));
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i += 1; // We used one SQL column.
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} else {
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let table = qa.0.clone();
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cols.push(ProjectedColumn(ColumnOrExpression::Column(qa), name));
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templates.push(TypedIndex::Unknown(i, i + 1));
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i += 2; // We used two SQL columns.
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// Also project the type from the SQL query.
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let type_name = value_type_tag_name(var);
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let type_qa = QualifiedAlias(table, DatomsColumn::ValueTypeTag);
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cols.push(ProjectedColumn(ColumnOrExpression::Column(type_qa), type_name));
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}
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}
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}
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}
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(Projection::Columns(cols), templates)
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}
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pub trait Projector {
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fn project<'stmt>(&self, rows: Rows<'stmt>) -> Result<QueryResults>;
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}
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2017-03-07 04:18:38 +00:00
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/// A projector that produces a `QueryResult` containing fixed data.
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/// Takes a boxed function that should return an empty result set of the desired type.
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struct ConstantProjector {
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results_factory: Box<Fn() -> QueryResults>,
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}
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impl ConstantProjector {
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fn new(results_factory: Box<Fn() -> QueryResults>) -> ConstantProjector {
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ConstantProjector { results_factory: results_factory }
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}
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}
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impl Projector for ConstantProjector {
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fn project<'stmt>(&self, _: Rows<'stmt>) -> Result<QueryResults> {
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Ok((self.results_factory)())
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}
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}
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struct ScalarProjector {
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template: TypedIndex,
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}
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impl ScalarProjector {
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fn with_template(template: TypedIndex) -> ScalarProjector {
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ScalarProjector {
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template: template,
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}
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}
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fn combine(sql: Projection, mut templates: Vec<TypedIndex>) -> CombinedProjection {
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let template = templates.pop().expect("Expected a single template");
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CombinedProjection {
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sql_projection: sql,
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datalog_projector: Box::new(ScalarProjector::with_template(template)),
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}
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}
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}
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impl Projector for ScalarProjector {
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fn project<'stmt>(&self, mut rows: Rows<'stmt>) -> Result<QueryResults> {
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if let Some(r) = rows.next() {
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let row = r?;
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let binding = self.template.lookup(&row)?;
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Ok(QueryResults::Scalar(Some(binding)))
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} else {
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Ok(QueryResults::Scalar(None))
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}
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}
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}
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/// A tuple projector produces a single vector. It's the single-result version of rel.
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struct TupleProjector {
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len: usize,
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templates: Vec<TypedIndex>,
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}
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impl TupleProjector {
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fn with_templates(len: usize, templates: Vec<TypedIndex>) -> TupleProjector {
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TupleProjector {
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len: len,
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templates: templates,
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}
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}
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// This is exactly the same as for rel.
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fn collect_bindings<'a, 'stmt>(&self, row: Row<'a, 'stmt>) -> Result<Vec<TypedValue>> {
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assert_eq!(row.column_count(), self.len as i32);
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self.templates
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.iter()
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.map(|ti| ti.lookup(&row))
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.collect::<Result<Vec<TypedValue>>>()
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}
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fn combine(column_count: usize, sql: Projection, templates: Vec<TypedIndex>) -> CombinedProjection {
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let p = TupleProjector::with_templates(column_count, templates);
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CombinedProjection {
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sql_projection: sql,
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datalog_projector: Box::new(p),
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}
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}
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}
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impl Projector for TupleProjector {
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fn project<'stmt>(&self, mut rows: Rows<'stmt>) -> Result<QueryResults> {
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if let Some(r) = rows.next() {
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let row = r?;
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let bindings = self.collect_bindings(row)?;
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Ok(QueryResults::Tuple(Some(bindings)))
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} else {
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Ok(QueryResults::Tuple(None))
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}
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}
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}
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/// A rel projector produces a vector of vectors.
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/// Each inner vector is the same size, and sourced from the same columns.
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/// One inner vector is produced per `Row`.
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/// Each column in the inner vector is the result of taking one or two columns from
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/// the `Row`: one for the value and optionally one for the type tag.
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struct RelProjector {
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len: usize,
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templates: Vec<TypedIndex>,
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}
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impl RelProjector {
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fn with_templates(len: usize, templates: Vec<TypedIndex>) -> RelProjector {
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RelProjector {
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len: len,
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templates: templates,
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}
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}
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fn collect_bindings<'a, 'stmt>(&self, row: Row<'a, 'stmt>) -> Result<Vec<TypedValue>> {
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assert_eq!(row.column_count(), self.len as i32);
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self.templates
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.iter()
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.map(|ti| ti.lookup(&row))
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.collect::<Result<Vec<TypedValue>>>()
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}
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fn combine(column_count: usize, sql: Projection, templates: Vec<TypedIndex>) -> CombinedProjection {
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let p = RelProjector::with_templates(column_count, templates);
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CombinedProjection {
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sql_projection: sql,
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datalog_projector: Box::new(p),
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}
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}
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}
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impl Projector for RelProjector {
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fn project<'stmt>(&self, mut rows: Rows<'stmt>) -> Result<QueryResults> {
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let mut out: Vec<Vec<TypedValue>> = vec![];
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while let Some(r) = rows.next() {
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let row = r?;
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let bindings = self.collect_bindings(row)?;
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out.push(bindings);
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}
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Ok(QueryResults::Rel(out))
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}
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}
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/// A coll projector produces a vector of values.
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/// Each value is sourced from the same column.
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struct CollProjector {
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template: TypedIndex,
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}
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impl CollProjector {
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fn with_template(template: TypedIndex) -> CollProjector {
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CollProjector {
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template: template,
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}
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}
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fn combine(sql: Projection, mut templates: Vec<TypedIndex>) -> CombinedProjection {
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let template = templates.pop().expect("Expected a single template");
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CombinedProjection {
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sql_projection: sql,
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datalog_projector: Box::new(CollProjector::with_template(template)),
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}
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}
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}
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impl Projector for CollProjector {
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fn project<'stmt>(&self, mut rows: Rows<'stmt>) -> Result<QueryResults> {
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let mut out: Vec<TypedValue> = vec![];
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while let Some(r) = rows.next() {
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let row = r?;
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let binding = self.template.lookup(&row)?;
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out.push(binding);
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}
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Ok(QueryResults::Coll(out))
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}
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}
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/// Combines the two things you need to turn a query into SQL and turn its results into
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/// `QueryResults`.
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pub struct CombinedProjection {
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/// A SQL projection, mapping columns mentioned in the body of the query to columns in the
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/// output.
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pub sql_projection: Projection,
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/// A Datalog projection. This consumes rows of the appropriate shape (as defined by
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/// the SQL projection) to yield one of the four kinds of Datalog query result.
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pub datalog_projector: Box<Projector>,
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}
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/// Compute a suitable SQL projection for an algebrized query.
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/// This takes into account a number of things:
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/// - The variable list in the find spec.
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/// - The presence of any aggregate operations in the find spec. TODO: for now we only handle
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/// simple variables
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/// - The bindings established by the topmost CC.
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/// - The types known at algebrizing time.
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/// - The types extracted from the store for unknown attributes.
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pub fn query_projection(query: &AlgebraicQuery) -> CombinedProjection {
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use self::FindSpec::*;
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2017-03-07 04:18:38 +00:00
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if query.is_known_empty() {
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// Do a few gyrations to produce empty results of the right kind for the query.
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let empty = QueryResults::empty_factory(&query.find_spec);
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let constant_projector = ConstantProjector::new(empty);
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CombinedProjection {
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sql_projection: Projection::One,
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datalog_projector: Box::new(constant_projector),
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}
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} else {
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match query.find_spec {
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FindColl(ref element) => {
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let (cols, templates) = project_elements(1, iter::once(element), query);
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CollProjector::combine(cols, templates)
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},
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FindScalar(ref element) => {
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let (cols, templates) = project_elements(1, iter::once(element), query);
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ScalarProjector::combine(cols, templates)
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},
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FindRel(ref elements) => {
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|
let column_count = query.find_spec.expected_column_count();
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let (cols, templates) = project_elements(column_count, elements, query);
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RelProjector::combine(column_count, cols, templates)
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|
},
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FindTuple(ref elements) => {
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|
|
let column_count = query.find_spec.expected_column_count();
|
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|
let (cols, templates) = project_elements(column_count, elements, query);
|
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|
|
TupleProjector::combine(column_count, cols, templates)
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|
},
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|
}
|
2017-03-06 22:40:10 +00:00
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}
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|
}
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