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// Copyright Materialize, Inc. and contributors. All rights reserved.
//
// Use of this software is governed by the Business Source License
// included in the LICENSE file.
//
// As of the Change Date specified in that file, in accordance with
// the Business Source License, use of this software will be governed
// by the Apache License, Version 2.0.
//! Transformation based on pushing demand information about columns toward sources.
use std::collections::{HashMap, HashSet};
use expr::{
AggregateExpr, AggregateFunc, Id, JoinInputMapper, MirRelationExpr, MirScalarExpr,
RECURSION_LIMIT,
};
use ore::stack::{CheckedRecursion, RecursionGuard};
use repr::{Datum, Row};
use crate::TransformArgs;
/// Drive demand from the root through operators.
///
/// This transform alerts operators to their columns that influence the
/// ultimate output of the expression, and gives them permission to swap
/// other columns for dummy values. As part of this, operators should not
/// actually use any of these dummy values, lest they run-time error.
///
/// This transformation primarily informs the `Join` operator, which can
/// simplify its intermediate state when it knows that certain columns are
/// not observed in its output. Internal arrangements need not maintain
/// columns that are no longer required in the join pipeline, which are
/// those columns not required by the output nor any further equalities.
#[derive(Debug)]
pub struct Demand {
recursion_guard: RecursionGuard,
}
impl Default for Demand {
fn default() -> Demand {
Demand {
recursion_guard: RecursionGuard::with_limit(RECURSION_LIMIT),
}
}
}
impl CheckedRecursion for Demand {
fn recursion_guard(&self) -> &RecursionGuard {
&self.recursion_guard
}
}
impl crate::Transform for Demand {
fn transform(
&self,
relation: &mut MirRelationExpr,
_: TransformArgs,
) -> Result<(), crate::TransformError> {
self.action(
relation,
(0..relation.arity()).collect(),
&mut HashMap::new(),
)
}
}
impl Demand {
/// Columns to be produced.
fn action(
&self,
relation: &mut MirRelationExpr,
mut columns: HashSet<usize>,
gets: &mut HashMap<Id, HashSet<usize>>,
) -> Result<(), crate::TransformError> {
self.checked_recur(|_| {
// A valid relation type is only needed for Maps, but we can't borrow
// the relation in the corresponding branch of the match statement, since
// it is already borrowed mutably.
let relation_type = if matches!(relation, MirRelationExpr::Map { .. }) {
Some(relation.typ())
} else {
None
};
match relation {
MirRelationExpr::Constant { .. } => {
// Nothing clever to do with constants, that I can think of.
Ok(())
}
MirRelationExpr::Get { id, .. } => {
gets.entry(*id).or_insert_with(HashSet::new).extend(columns);
Ok(())
}
MirRelationExpr::Let { id, value, body } => {
// Let harvests any requirements of get from its body,
// and pushes the union of the requirements at its value.
let id = Id::Local(*id);
let prior = gets.insert(id, HashSet::new());
self.action(body, columns, gets)?;
let needs = gets.remove(&id).unwrap();
if let Some(prior) = prior {
gets.insert(id, prior);
}
self.action(value, needs, gets)
}
MirRelationExpr::Project { input, outputs } => self.action(
input,
columns.into_iter().map(|c| outputs[c]).collect(),
gets,
),
MirRelationExpr::Map { input, scalars } => {
let relation_type = relation_type.as_ref().unwrap();
let arity = input.arity();
// contains columns whose supports have yet to be explored
let mut new_columns = columns.clone();
new_columns.retain(|c| *c >= arity);
while !new_columns.is_empty() {
// explore supports
new_columns = new_columns
.iter()
.flat_map(|c| scalars[*c - arity].support())
.filter(|c| !columns.contains(c))
.collect();
// add those columns to the seen list
columns.extend(new_columns.clone());
new_columns.retain(|c| *c >= arity);
}
// Replace un-read expressions with literals to prevent evaluation.
for (index, scalar) in scalars.iter_mut().enumerate() {
if !columns.contains(&(arity + index)) {
// Leave literals as they are, to benefit explain.
if !scalar.is_literal() {
let typ = relation_type.column_types[arity + index].clone();
*scalar = MirScalarExpr::Literal(
Ok(Row::pack_slice(&[Datum::Dummy])),
typ,
);
}
}
}
columns.retain(|c| *c < arity);
self.action(input, columns, gets)
}
MirRelationExpr::FlatMap {
input,
func: _,
exprs,
} => {
// A FlatMap which returns zero rows acts like a filter
// so we always need to execute it
for expr in exprs {
columns.extend(expr.support());
}
columns.retain(|c| *c < input.arity());
self.action(input, columns, gets)
}
MirRelationExpr::Filter { input, predicates } => {
for predicate in predicates {
for column in predicate.support() {
columns.insert(column);
}
}
self.action(input, columns, gets)
}
MirRelationExpr::Join {
inputs,
equivalences,
implementation: _,
} => {
let input_mapper = JoinInputMapper::new(inputs);
// Each produced column that is equivalent to a prior column should be remapped
// so that upstream uses depend only on the first column, simplifying the demand
// analysis. In principle we could choose any representative, if it turns out
// that some other column would have been more helpful, but we don't have a great
// reason to do that at the moment.
let mut permutation: Vec<usize> = (0..input_mapper.total_columns()).collect();
for equivalence in equivalences.iter() {
let mut first_column = None;
for expr in equivalence.iter() {
if let MirScalarExpr::Column(c) = expr {
if let Some(prior) = &first_column {
permutation[*c] = *prior;
} else {
first_column = Some(*c);
}
}
}
}
let should_permute = columns.iter().any(|c| permutation[*c] != *c);
// Each equivalence class imposes internal demand for columns.
for equivalence in equivalences.iter() {
for expr in equivalence.iter() {
columns.extend(expr.support());
}
}
// Populate child demands from external and internal demands.
let new_columns = input_mapper.split_column_set_by_input(columns.iter());
// Recursively indicate the requirements.
for (input, columns) in inputs.iter_mut().zip(new_columns) {
self.action(input, columns, gets)?;
}
// Install a permutation if any demanded column is not the
// canonical column.
if should_permute {
*relation = relation.take_dangerous().project(permutation);
}
Ok(())
}
MirRelationExpr::Reduce {
input,
group_key,
aggregates,
monotonic: _,
expected_group_size: _,
} => {
let mut new_columns = HashSet::new();
// Group keys determine aggregation granularity and are
// each crucial in determining aggregates and even the
// multiplicities of other keys.
new_columns.extend(group_key.iter().flat_map(|e| e.support()));
for column in columns.iter() {
// No obvious requirements on aggregate columns.
// A "non-empty" requirement, I guess?
if *column >= group_key.len() {
new_columns
.extend(aggregates[*column - group_key.len()].expr.support());
}
}
// Replace un-demanded aggregations with dummies.
let input_type = input.typ();
for index in (0..aggregates.len()).rev() {
if !columns.contains(&(group_key.len() + index)) {
let typ = aggregates[index].typ(&input_type);
aggregates[index] = AggregateExpr {
func: AggregateFunc::Dummy,
expr: MirScalarExpr::literal_ok(Datum::Dummy, typ.scalar_type),
distinct: false,
};
}
}
self.action(input, new_columns, gets)
}
MirRelationExpr::TopK {
input,
group_key,
order_key,
..
} => {
// Group and order keys must be retained, as they define
// which rows are retained.
columns.extend(group_key.iter().cloned());
columns.extend(order_key.iter().map(|o| o.column));
self.action(input, columns, gets)
}
MirRelationExpr::Negate { input } => self.action(input, columns, gets),
MirRelationExpr::DeclareKeys { input, keys: _ } => {
// TODO[btv] - If and when we add a "debug mode" that asserts whether this is truly a key,
// we will probably need to add the key to the set of demanded columns.
self.action(input, columns, gets)
}
MirRelationExpr::Threshold { input } => {
// Threshold requires all columns, as collapsing any distinct values
// has the potential to change how it thresholds counts. This could
// be improved with reasoning about distinctness or non-negativity.
let arity = input.arity();
self.action(input, (0..arity).collect(), gets)
}
MirRelationExpr::Union { base, inputs } => {
self.action(base, columns.clone(), gets)?;
for input in inputs {
self.action(input, columns.clone(), gets)?;
}
Ok(())
}
MirRelationExpr::ArrangeBy { input, keys } => {
for key_set in keys {
for key in key_set {
columns.extend(key.support());
}
}
self.action(input, columns, gets)
}
}
})
}
}