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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.
//! Remove redundant collections of distinct elements from joins.
//!
//! This analysis looks for joins in which one collection contains distinct
//! elements, and it can be determined that the join would only restrict the
//! results, and that the restriction is redundant (the other results would
//! not be reduced by the join).
//!
//! This type of optimization shows up often in subqueries, where distinct
//! collections are used in decorrelation, and afterwards often distinct
//! collections are then joined against the results.
// If statements seem a bit clearer in this case. Specialized methods
// that replace simple and common alternatives frustrate developers.
#![allow(clippy::comparison_chain, clippy::filter_next)]
use std::collections::BTreeMap;
use itertools::Itertools;
use mz_expr::visit::Visit;
use mz_expr::{Id, JoinInputMapper, LocalId, MirRelationExpr, MirScalarExpr, RECURSION_LIMIT};
use mz_ore::stack::{CheckedRecursion, RecursionGuard};
use mz_ore::{assert_none, soft_panic_or_log};
use crate::{all, TransformCtx};
/// Remove redundant collections of distinct elements from joins.
#[derive(Debug)]
pub struct RedundantJoin {
recursion_guard: RecursionGuard,
}
impl Default for RedundantJoin {
fn default() -> RedundantJoin {
RedundantJoin {
recursion_guard: RecursionGuard::with_limit(RECURSION_LIMIT),
}
}
}
impl CheckedRecursion for RedundantJoin {
fn recursion_guard(&self) -> &RecursionGuard {
&self.recursion_guard
}
}
impl crate::Transform for RedundantJoin {
#[mz_ore::instrument(
target = "optimizer",
level = "debug",
fields(path.segment = "redundant_join")
)]
fn transform(
&self,
relation: &mut MirRelationExpr,
_: &mut TransformCtx,
) -> Result<(), crate::TransformError> {
let mut ctx = ProvInfoCtx::default();
ctx.extend_uses(relation);
let result = self.action(relation, &mut ctx);
mz_repr::explain::trace_plan(&*relation);
result.map(|_| ())
}
}
impl RedundantJoin {
/// Remove redundant collections of distinct elements from joins.
///
/// This method tracks "provenance" information for each collections,
/// those being column-wise relationships to identified collections
/// (either imported collections, or let-bound collections). These
/// relationships state that when projected on to these columns, the
/// records of the one collection are contained in the records of the
/// identified collection.
///
/// This provenance information is then used for the `MirRelationExpr::Join`
/// variant to remove "redundant" joins, those that can be determined to
/// neither restrict nor augment one of the input relations. Consult the
/// `find_redundancy` method and its documentation for more detail.
pub fn action(
&self,
relation: &mut MirRelationExpr,
ctx: &mut ProvInfoCtx,
) -> Result<Vec<ProvInfo>, crate::TransformError> {
let mut result = self.checked_recur(|_| {
match relation {
MirRelationExpr::Let { id, value, body } => {
// Recursively determine provenance of the value.
let value_prov = self.action(value, ctx)?;
// Clear uses from the just visited binding definition.
ctx.remove_uses(value);
// Extend the lets context with an entry for this binding.
let prov_old = ctx.insert(*id, value_prov);
assert_none!(prov_old, "No shadowing");
// Determine provenance of the body.
let result = self.action(body, ctx)?;
ctx.remove_uses(body);
// Remove the lets entry for this binding from the context.
ctx.remove(id);
Ok(result)
}
MirRelationExpr::LetRec {
ids,
values,
limits: _,
body,
} => {
// As a first approximation, we naively extend the `lets`
// context with the empty vec![] for each id.
for id in ids.iter() {
let prov_old = ctx.insert(*id, vec![]);
assert_none!(prov_old, "No shadowing");
}
// In other words, we don't attempt to derive additional
// provenance information for a binding from its `value`.
//
// We descend into the values and the body with the naively
// extended context.
for value in values.iter_mut() {
self.action(value, ctx)?;
}
// Clear uses from the just visited recursive binding
// definitions.
for value in values.iter_mut() {
ctx.remove_uses(value);
}
let result = self.action(body, ctx)?;
ctx.remove_uses(body);
// Remove the lets entries for all ids.
for id in ids.iter() {
ctx.remove(id);
}
Ok(result)
}
MirRelationExpr::Get { id, typ, .. } => {
if let Id::Local(id) = id {
// Extract the value provenance (this should always exist).
let mut val_info = ctx.get(id).cloned().unwrap_or_else(|| {
soft_panic_or_log!("no ctx entry for LocalId {id}");
vec![]
});
// Add information about being exactly this let binding too.
val_info.push(ProvInfo::make_leaf(Id::Local(*id), typ.arity()));
Ok(val_info)
} else {
// Add information about being exactly this GlobalId reference.
Ok(vec![ProvInfo::make_leaf(*id, typ.arity())])
}
}
MirRelationExpr::Join {
inputs,
equivalences,
implementation,
} => {
// This logic first applies what it has learned about its input provenance,
// and if it finds a redundant join input it removes it. In that case, it
// also fails to produce exciting provenance information, partly out of
// laziness and the challenge of ensuring it is correct. Instead, if it is
// unable to find a redundant join it produces meaningful provenance information.
// Recursively apply transformation, and determine the provenance of inputs.
let mut input_prov = Vec::new();
for i in inputs.iter_mut() {
input_prov.push(self.action(i, ctx)?);
}
// Determine useful information about the structure of the inputs.
let mut input_types = inputs.iter().map(|i| i.typ()).collect::<Vec<_>>();
let old_input_mapper = JoinInputMapper::new_from_input_types(&input_types);
// If we find an input that can be removed, we should do so!
// We only do this once per invocation to keep our sanity, but we could
// rewrite it to iterate. We can avoid looking for any relation that
// does not have keys, as it cannot be redundant in that case.
if let Some((remove_input_idx, mut bindings)) = (0..input_types.len())
.rev()
.filter(|i| !input_types[*i].keys.is_empty())
.flat_map(|i| {
find_redundancy(
i,
&input_types[i].keys,
&old_input_mapper,
equivalences,
&input_prov[..],
)
.map(|b| (i, b))
})
.next()
{
// Clear uses from the removed input.
ctx.remove_uses(&inputs[remove_input_idx]);
inputs.remove(remove_input_idx);
input_types.remove(remove_input_idx);
// Update the column offsets in the binding expressions to catch
// up with the removal of `remove_input_idx`.
for expr in bindings.iter_mut() {
expr.visit_pre_mut(|e| {
if let MirScalarExpr::Column(c) = e {
let (_local_col, input_relation) =
old_input_mapper.map_column_to_local(*c);
if input_relation > remove_input_idx {
*c -= old_input_mapper.input_arity(remove_input_idx);
}
}
});
}
// Replace column references from `remove_input_idx` with the corresponding
// binding expression. Update the offsets of the column references
// from inputs after `remove_input_idx`.
for equivalence in equivalences.iter_mut() {
for expr in equivalence.iter_mut() {
expr.visit_mut_post(&mut |e| {
if let MirScalarExpr::Column(c) = e {
let (local_col, input_relation) =
old_input_mapper.map_column_to_local(*c);
if input_relation == remove_input_idx {
*e = bindings[local_col].clone();
} else if input_relation > remove_input_idx {
*c -= old_input_mapper.input_arity(remove_input_idx);
}
}
})?;
}
}
mz_expr::canonicalize::canonicalize_equivalences(
equivalences,
input_types.iter().map(|t| &t.column_types),
);
// Build a projection that leaves the binding expressions in the same
// position as the columns of the removed join input they are replacing.
let new_input_mapper = JoinInputMapper::new_from_input_types(&input_types);
let mut projection = Vec::new();
let new_join_arity = new_input_mapper.total_columns();
for i in 0..old_input_mapper.total_inputs() {
if i != remove_input_idx {
projection.extend(
new_input_mapper.global_columns(if i < remove_input_idx {
i
} else {
i - 1
}),
);
} else {
projection.extend(new_join_arity..new_join_arity + bindings.len());
}
}
// Unset implementation, as irrevocably hosed by this transformation.
*implementation = mz_expr::JoinImplementation::Unimplemented;
*relation = relation.take_dangerous().map(bindings).project(projection);
// The projection will gum up provenance reasoning anyhow, so don't work hard.
// We will return to this expression again with the same analysis.
Ok(Vec::new())
} else {
// Provenance information should be the union of input provenance information,
// with columns updated. Because rows may be dropped in the join, all `exact`
// bits should be un-set.
let mut results = Vec::new();
for (input, input_prov) in input_prov.into_iter().enumerate() {
for mut prov in input_prov {
prov.exact = false;
let mut projection = vec![None; old_input_mapper.total_columns()];
for (local_col, global_col) in
old_input_mapper.global_columns(input).enumerate()
{
projection[global_col]
.clone_from(&prov.dereferenced_projection[local_col]);
}
prov.dereferenced_projection = projection;
results.push(prov);
}
}
Ok(results)
}
}
MirRelationExpr::Filter { input, .. } => {
// Filter may drop records, and so we unset `exact`.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
prov.exact = false;
}
Ok(result)
}
MirRelationExpr::Map { input, scalars } => {
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
for scalar in scalars.iter() {
let dereferenced_scalar = prov.strict_dereference(scalar);
prov.dereferenced_projection.push(dereferenced_scalar);
}
}
Ok(result)
}
MirRelationExpr::Union { base, inputs } => {
let mut prov = self.action(base, ctx)?;
for input in inputs {
let input_prov = self.action(input, ctx)?;
// To merge a new list of provenances, we look at the cross
// produce of things we might know about each source.
// TODO(mcsherry): this can be optimized to use datastructures
// keyed by the source identifier.
let mut new_prov = Vec::new();
for l in prov {
new_prov.extend(input_prov.iter().flat_map(|r| l.meet(r)))
}
prov = new_prov;
}
Ok(prov)
}
MirRelationExpr::Constant { .. } => Ok(Vec::new()),
MirRelationExpr::Reduce {
input,
group_key,
aggregates,
..
} => {
// Reduce yields its first few columns as a key, and produces
// all key tuples that were present in its input.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
let mut projection = group_key
.iter()
.map(|key| prov.strict_dereference(key))
.collect_vec();
projection.extend((0..aggregates.len()).map(|_| None));
prov.dereferenced_projection = projection;
}
// TODO: For min, max aggregates, we could preserve provenance
// if the expression references a column. We would need to un-set
// the `exact` bit in that case, and so we would want to keep both
// sets of provenance information.
Ok(result)
}
MirRelationExpr::Threshold { input } => {
// Threshold may drop records, and so we unset `exact`.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
prov.exact = false;
}
Ok(result)
}
MirRelationExpr::TopK { input, .. } => {
// TopK may drop records, and so we unset `exact`.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
prov.exact = false;
}
Ok(result)
}
MirRelationExpr::Project { input, outputs } => {
// Projections re-order, drop, and duplicate columns,
// but they neither drop rows nor invent values.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
let projection = outputs
.iter()
.map(|c| prov.dereference(&MirScalarExpr::Column(*c)))
.collect_vec();
prov.dereferenced_projection = projection;
}
Ok(result)
}
MirRelationExpr::FlatMap { input, func, .. } => {
// FlatMap may drop records, and so we unset `exact`.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
prov.exact = false;
prov.dereferenced_projection
.extend((0..func.output_type().column_types.len()).map(|_| None));
}
Ok(result)
}
MirRelationExpr::Negate { input } => {
// Negate does not guarantee that the multiplicity of
// each source record it at least one. This could have
// been a problem in `Union`, where we might report
// that the union of positive and negative records is
// "exact": cancellations would make this false.
let mut result = self.action(input, ctx)?;
for prov in result.iter_mut() {
prov.exact = false;
}
Ok(result)
}
MirRelationExpr::ArrangeBy { input, .. } => self.action(input, ctx),
}
})?;
result.retain(|info| !info.is_trivial());
// Uncomment the following lines to trace the individual steps:
// println!("{}", relation.pretty());
// println!("result = {result:?}");
// println!("lets: {lets:?}");
// println!("---------------------");
Ok(result)
}
}
/// A relationship between a collections columns and some source columns.
///
/// An instance of this type indicates that some of the bearer's columns
/// derive from `id`. In particular, the non-`None` elements in
/// `dereferenced_projection` correspond to columns that can be derived
/// from `id`'s projection.
///
/// The guarantee is that projected on to these columns, the distinct values
/// of the bearer are contained in the set of distinct values of projected
/// columns of `id`. In the case that `exact` is set, the two sets are equal.
#[derive(Clone, Debug, Ord, Eq, PartialOrd, PartialEq)]
pub struct ProvInfo {
/// The Id (local or global) of the source.
id: Id,
/// The projection of the bearer written in terms of the columns projected
/// by the underlying Get operator. Set to `None` for columns that cannot
/// be expressed as scalar expression referencing only columns of the
/// underlying Get operator.
dereferenced_projection: Vec<Option<MirScalarExpr>>,
/// If true, all distinct projected source rows are present in the rows of
/// the projection of the current collection. This constraint is lost as soon
/// as a transformation may drop records.
exact: bool,
}
impl ProvInfo {
fn make_leaf(id: Id, arity: usize) -> Self {
Self {
id,
dereferenced_projection: (0..arity)
.map(|c| Some(MirScalarExpr::column(c)))
.collect::<Vec<_>>(),
exact: true,
}
}
/// Rewrite `expr` so it refers to the columns of the original source instead
/// of the columns of the projected source.
fn dereference(&self, expr: &MirScalarExpr) -> Option<MirScalarExpr> {
match expr {
MirScalarExpr::Column(c) => {
if let Some(expr) = &self.dereferenced_projection[*c] {
Some(expr.clone())
} else {
None
}
}
MirScalarExpr::CallUnary { func, expr } => self.dereference(expr).and_then(|expr| {
Some(MirScalarExpr::CallUnary {
func: func.clone(),
expr: Box::new(expr),
})
}),
MirScalarExpr::CallBinary { func, expr1, expr2 } => {
self.dereference(expr1).and_then(|expr1| {
self.dereference(expr2).and_then(|expr2| {
Some(MirScalarExpr::CallBinary {
func: func.clone(),
expr1: Box::new(expr1),
expr2: Box::new(expr2),
})
})
})
}
MirScalarExpr::CallVariadic { func, exprs } => {
let new_exprs = exprs.iter().flat_map(|e| self.dereference(e)).collect_vec();
if new_exprs.len() == exprs.len() {
Some(MirScalarExpr::CallVariadic {
func: func.clone(),
exprs: new_exprs,
})
} else {
None
}
}
MirScalarExpr::Literal(..) | MirScalarExpr::CallUnmaterializable(..) => {
Some(expr.clone())
}
MirScalarExpr::If { cond, then, els } => self.dereference(cond).and_then(|cond| {
self.dereference(then).and_then(|then| {
self.dereference(els).and_then(|els| {
Some(MirScalarExpr::If {
cond: Box::new(cond),
then: Box::new(then),
els: Box::new(els),
})
})
})
}),
}
}
/// Like `dereference` but only returns expressions that actually depend on
/// the original source.
fn strict_dereference(&self, expr: &MirScalarExpr) -> Option<MirScalarExpr> {
let derefed = self.dereference(expr);
match derefed {
Some(ref expr) if !expr.support().is_empty() => derefed,
_ => None,
}
}
/// Merge two constraints to find a constraint that satisfies both inputs.
///
/// This method returns nothing if no columns are in common (either because
/// difference sources are identified, or just no columns in common) and it
/// intersects bindings and the `exact` bit.
fn meet(&self, other: &Self) -> Option<Self> {
if self.id == other.id {
let resulting_projection = self
.dereferenced_projection
.iter()
.zip(other.dereferenced_projection.iter())
.map(|(e1, e2)| if e1 == e2 { e1.clone() } else { None })
.collect_vec();
if resulting_projection.iter().any(|e| e.is_some()) {
Some(ProvInfo {
id: self.id,
dereferenced_projection: resulting_projection,
exact: self.exact && other.exact,
})
} else {
None
}
} else {
None
}
}
/// Check if all entries of the dereferenced projection are missing.
///
/// If this is the case keeping the `ProvInfo` entry around is meaningless.
fn is_trivial(&self) -> bool {
all![
!self.dereferenced_projection.is_empty(),
self.dereferenced_projection.iter().all(|x| x.is_none()),
]
}
}
/// Attempts to find column bindings that make `input` redundant.
///
/// This method attempts to determine that `input` may be redundant by searching
/// the join structure for another relation `other` with provenance that contains some
/// provenance of `input`, and keys for `input` that are equated by the join to the
/// corresponding columns of `other` under their provenance. The `input` provenance
/// must also have its `exact` bit set.
///
/// In these circumstances, the claim is that because the key columns are equated and
/// determine non-key columns, any matches between `input` and
/// `other` will neither introduce new information to `other`, nor restrict the rows
/// of `other`, nor alter their multplicity.
fn find_redundancy(
input: usize,
keys: &[Vec<usize>],
input_mapper: &JoinInputMapper,
equivalences: &[Vec<MirScalarExpr>],
input_provs: &[Vec<ProvInfo>],
) -> Option<Vec<MirScalarExpr>> {
// Whether the `equivalence` contains an expression that only references
// `input` that leads to the same as `root_expr` once dereferenced.
let contains_equivalent_expr_from_input = |equivalence: &[MirScalarExpr],
root_expr: &MirScalarExpr,
input: usize,
provenance: &ProvInfo|
-> bool {
equivalence.iter().any(|expr| {
Some(input) == input_mapper.single_input(expr)
&& provenance
.dereference(&input_mapper.map_expr_to_local(expr.clone()))
.as_ref()
== Some(root_expr)
})
};
for input_prov in input_provs[input].iter() {
// We can only elide if the input contains all records, and binds all columns.
if input_prov.exact
&& input_prov
.dereferenced_projection
.iter()
.all(|e| e.is_some())
{
// examine all *other* inputs that have not been removed...
for other in (0..input_mapper.total_inputs()).filter(|other| other != &input) {
for other_prov in input_provs[other].iter().filter(|p| p.id == input_prov.id) {
let all_key_columns_equated = |key: &Vec<usize>| {
key.iter().all(|key_col| {
// The root expression behind the key column, ie.
// the expression re-written in terms of elements in
// the projection of the Get operator.
let root_expr =
input_prov.dereference(&MirScalarExpr::column(*key_col));
// Check if there is a join equivalence that joins
// 'input' and 'other' on expressions that lead to
// the same root expression as the key column.
root_expr.as_ref().map_or(false, |root_expr| {
equivalences.iter().any(|equivalence| {
all![
contains_equivalent_expr_from_input(
equivalence,
root_expr,
input,
input_prov,
),
contains_equivalent_expr_from_input(
equivalence,
root_expr,
other,
other_prov,
),
]
})
})
})
};
// Find an unique key for input that has all columns equated to other.
if keys.iter().any(all_key_columns_equated) {
// Find out whether we can produce input's projection strictly with
// elements in other's projection.
let expressions = input_prov
.dereferenced_projection
.iter()
.enumerate()
.flat_map(|(c, _)| {
// Check if the expression under input's 'c' column can be built
// with elements in other's projection.
input_prov.dereferenced_projection[c].as_ref().map_or(
None,
|root_expr| {
try_build_expression_using_other(
root_expr,
other,
other_prov,
input_mapper,
)
},
)
})
.collect_vec();
if expressions.len() == input_prov.dereferenced_projection.len() {
return Some(expressions);
}
}
}
}
}
}
None
}
/// Tries to build `root_expr` using elements from other's projection.
fn try_build_expression_using_other(
root_expr: &MirScalarExpr,
other: usize,
other_prov: &ProvInfo,
input_mapper: &JoinInputMapper,
) -> Option<MirScalarExpr> {
if root_expr.is_literal() {
return Some(root_expr.clone());
}
// Check if 'other' projects a column that lead to `root_expr`.
for (other_col, derefed) in other_prov.dereferenced_projection.iter().enumerate() {
if let Some(derefed) = derefed {
if derefed == root_expr {
return Some(MirScalarExpr::Column(
input_mapper.map_column_to_global(other_col, other),
));
}
}
}
// Otherwise, try to build root_expr's sub-expressions recursively
// other's projection.
match root_expr {
MirScalarExpr::Column(_) => None,
MirScalarExpr::CallUnary { func, expr } => {
try_build_expression_using_other(expr, other, other_prov, input_mapper).and_then(
|expr| {
Some(MirScalarExpr::CallUnary {
func: func.clone(),
expr: Box::new(expr),
})
},
)
}
MirScalarExpr::CallBinary { func, expr1, expr2 } => {
try_build_expression_using_other(expr1, other, other_prov, input_mapper).and_then(
|expr1| {
try_build_expression_using_other(expr2, other, other_prov, input_mapper)
.and_then(|expr2| {
Some(MirScalarExpr::CallBinary {
func: func.clone(),
expr1: Box::new(expr1),
expr2: Box::new(expr2),
})
})
},
)
}
MirScalarExpr::CallVariadic { func, exprs } => {
let new_exprs = exprs
.iter()
.flat_map(|e| try_build_expression_using_other(e, other, other_prov, input_mapper))
.collect_vec();
if new_exprs.len() == exprs.len() {
Some(MirScalarExpr::CallVariadic {
func: func.clone(),
exprs: new_exprs,
})
} else {
None
}
}
MirScalarExpr::Literal(..) | MirScalarExpr::CallUnmaterializable(..) => {
Some(root_expr.clone())
}
MirScalarExpr::If { cond, then, els } => {
try_build_expression_using_other(cond, other, other_prov, input_mapper).and_then(
|cond| {
try_build_expression_using_other(then, other, other_prov, input_mapper)
.and_then(|then| {
try_build_expression_using_other(els, other, other_prov, input_mapper)
.and_then(|els| {
Some(MirScalarExpr::If {
cond: Box::new(cond),
then: Box::new(then),
els: Box::new(els),
})
})
})
},
)
}
}
}
/// A context of `ProvInfo` vectors associated with bindings that might still be
/// referenced.
#[derive(Debug, Default)]
pub struct ProvInfoCtx {
/// [`LocalId`] references in the remaining subtree.
///
/// Entries from the `lets` map that are no longer used can be pruned.
uses: BTreeMap<LocalId, usize>,
/// [`ProvInfo`] vectors associated with let binding in scope.
lets: BTreeMap<LocalId, Vec<ProvInfo>>,
}
impl ProvInfoCtx {
/// Extend the `uses` map by the `LocalId`s used in `expr`.
pub fn extend_uses(&mut self, expr: &MirRelationExpr) {
expr.visit_pre(&mut |expr: &MirRelationExpr| match expr {
MirRelationExpr::Get {
id: Id::Local(id), ..
} => {
let count = self.uses.entry(id.clone()).or_insert(0_usize);
*count += 1;
}
_ => (),
});
}
/// Decrement `uses` entries by the `LocalId`s used in `expr` and remove
/// `lets` entries for `uses` that reset to zero.
pub fn remove_uses(&mut self, expr: &MirRelationExpr) {
let mut worklist = vec![expr];
while let Some(expr) = worklist.pop() {
if let MirRelationExpr::Get {
id: Id::Local(id), ..
} = expr
{
if let Some(count) = self.uses.get_mut(id) {
if *count > 0 {
*count -= 1;
}
if *count == 0 {
if self.lets.remove(id).is_none() {
soft_panic_or_log!("ctx.lets[{id}] should exist");
}
}
} else {
soft_panic_or_log!("ctx.uses[{id}] should exist");
}
}
match expr {
MirRelationExpr::Let { .. } | MirRelationExpr::LetRec { .. } => {
// When traversing the tree, don't descend into
// `Let`/`LetRec` sub-terms in order to avoid double
// counting (those are handled by remove_uses calls of
// RedundantJoin::action on subterms that were already
// visited because the action works bottom-up).
}
_ => {
worklist.extend(expr.children().rev());
}
}
}
}
/// Get the `ProvInfo` vector for `id` from the context.
pub fn get(&self, id: &LocalId) -> Option<&Vec<ProvInfo>> {
self.lets.get(id)
}
/// Extend the context with the `id: prov_infos` entry.
pub fn insert(&mut self, id: LocalId, prov_infos: Vec<ProvInfo>) -> Option<Vec<ProvInfo>> {
self.lets.insert(id, prov_infos)
}
/// Remove the entry identified by `id` from the context.
pub fn remove(&mut self, id: &LocalId) -> Option<Vec<ProvInfo>> {
self.lets.remove(id)
}
}