egglog_core_relations/free_join/

mod.rs

//! Execute queries against a database using a variant of Free Join.
use std::{
    mem,
    sync::{
        Arc,
        atomic::{AtomicUsize, Ordering},
    },
};

use crate::{
    common::IndexSet,
    hash_index::IndexCatalog,
    numeric_id::{DenseIdMap, DenseIdMapWithReuse, NumericId, define_id},
};
use egglog_concurrency::{NotificationList, ResettableOnceLock};
use smallvec::SmallVec;

use crate::{
    BaseValues, ContainerRebuildSummary, ContainerValues, PoolSet, QueryEntry, TupleIndex, Value,
    action::{
        Bindings, DbView,
        mask::{Mask, MaskIter, ValueSource},
    },
    dependency_graph::DependencyGraph,
    hash_index::{ColumnIndex, Index, IndexBase},
    offsets::Subset,
    parallel,
    parallel_heuristics::parallelize_db_level_op,
    pool::{Pool, Pooled, with_pool_set},
    query::{Query, RuleSetBuilder},
    table_spec::{
        ColumnId, Constraint, MutationBuffer, Table, TableSpec, WrappedTable, WrappedTableRef,
    },
};

use self::plan::Plan;
use crate::action::ExecutionState;

pub(crate) mod execute;
pub(crate) mod frame_update;
pub(crate) mod plan;

define_id!(
    pub AtomId,
    u32,
    "A component of a query consisting of a function and a list of variables or constants"
);
define_id!(pub Variable, u32, "a variable in a query", pretty "Var");

impl Variable {
    pub fn placeholder() -> Variable {
        Variable::new(!0)
    }
}

define_id!(pub TableId, u32, "a table in the database");

impl TableId {
    pub fn dummy() -> TableId {
        TableId::new(u32::MAX)
    }

    pub fn is_dummy(&self) -> bool {
        self.rep == u32::MAX
    }
}

define_id!(pub(crate) ActionId, u32, "an identifier picking out the RHS of a rule");

#[derive(Debug)]
pub(crate) struct ProcessedConstraints {
    /// The subset of the table matching the fast constraints. If there are no
    /// fast constraints then this is the full table.
    pub(crate) subset: Subset,
    /// The constraints that can be evaluated quickly (O(log(n)) or O(1)).
    pub(crate) fast: Pooled<Vec<Constraint>>,
    /// The constraints that require an O(n) scan to evaluate.
    pub(crate) slow: Pooled<Vec<Constraint>>,
}

impl Clone for ProcessedConstraints {
    fn clone(&self) -> Self {
        ProcessedConstraints {
            subset: self.subset.clone(),
            fast: Pooled::cloned(&self.fast),
            slow: Pooled::cloned(&self.slow),
        }
    }
}

impl ProcessedConstraints {
    /// The size of the subset of the table matching the fast constraints.
    fn approx_size(&self) -> usize {
        self.subset.size()
    }

    pub(crate) fn dummy() -> ProcessedConstraints {
        ProcessedConstraints {
            subset: Subset::empty(),
            fast: Pooled::new(Vec::new()),
            slow: Pooled::new(Vec::new()),
        }
    }
}

#[derive(Clone, Debug, PartialEq, Eq)]
pub(crate) struct SubAtom {
    pub(crate) atom: AtomId,
    pub(crate) vars: SmallVec<[ColumnId; 2]>,
}

impl SubAtom {
    pub(crate) fn new(atom: AtomId) -> SubAtom {
        SubAtom {
            atom,
            vars: Default::default(),
        }
    }
}

#[derive(Debug, Clone)]
pub(crate) struct VarInfo {
    pub(crate) occurrences: Vec<SubAtom>,
    /// Whether or not this variable shows up in the "actions" portion of a
    /// rule.
    pub(crate) used_in_rhs: bool,
    pub(crate) defined_in_rhs: bool,
    pub(crate) name: Option<Arc<str>>,
}

pub(crate) type HashIndex = Arc<ResettableOnceLock<Index<TupleIndex>>>;
pub(crate) type HashColumnIndex = Arc<ResettableOnceLock<Index<ColumnIndex>>>;

pub struct TableInfo {
    pub(crate) name: Option<Arc<str>>,
    pub(crate) spec: TableSpec,
    pub(crate) table: WrappedTable,
    pub(crate) indexes: IndexCatalog<SmallVec<[ColumnId; 4]>, HashIndex>,
    pub(crate) column_indexes: IndexCatalog<ColumnId, HashColumnIndex>,
}

impl TableInfo {
    pub fn table(&self) -> &WrappedTable {
        &self.table
    }

    pub fn name(&self) -> Option<&str> {
        self.name.as_deref()
    }

    pub fn spec(&self) -> &TableSpec {
        &self.spec
    }
}

impl Clone for TableInfo {
    fn clone(&self) -> Self {
        fn deep_clone_map<K: Clone + std::hash::Hash + Eq, TI: IndexBase + Clone>(
            map: &IndexCatalog<K, Arc<ResettableOnceLock<Index<TI>>>>,
            table: WrappedTableRef,
        ) -> IndexCatalog<K, Arc<ResettableOnceLock<Index<TI>>>> {
            map.map(|table_ref| {
                let (k, v) = table_ref;
                let v: Index<TI> = v
                    .get_or_update(|index| {
                        index.refresh(table);
                    })
                    .clone();
                (k.clone(), Arc::new(ResettableOnceLock::new(v)))
            })
        }
        TableInfo {
            name: self.name.clone(),
            spec: self.spec.clone(),
            table: self.table.dyn_clone(),
            indexes: deep_clone_map(&self.indexes, self.table.as_ref()),
            column_indexes: deep_clone_map(&self.column_indexes, self.table.as_ref()),
        }
    }
}

define_id!(pub CounterId, u32, "A counter accessible to actions, useful for generating unique Ids.");
define_id!(pub ExternalFunctionId, u32, "A user-defined operation that can be invoked from a query");

/// External functions allow external callers to manipulate database state in
/// near-arbitrary ways.
///
/// This is a useful, if low-level, interface for extending this database with
/// functionality and state not built into the core model.
pub trait ExternalFunction: dyn_clone::DynClone + Send + Sync {
    /// Invoke the function with mutable access to the database. If a value is
    /// not returned, halt the execution of the current rule.
    fn invoke(&self, state: &mut ExecutionState, args: &[Value]) -> Option<Value>;
}

/// Automatically generate an `ExternalFunction` implementation from a function.
pub fn make_external_func<
    F: Fn(&mut ExecutionState, &[Value]) -> Option<Value> + Clone + Send + Sync,
>(
    f: F,
) -> impl ExternalFunction {
    #[derive(Clone)]
    struct Wrapped<F>(F);
    impl<F> ExternalFunction for Wrapped<F>
    where
        F: Fn(&mut ExecutionState, &[Value]) -> Option<Value> + Clone + Send + Sync,
    {
        fn invoke(&self, state: &mut ExecutionState, args: &[Value]) -> Option<Value> {
            (self.0)(state, args)
        }
    }
    Wrapped(f)
}

/// A vectorized variant of [`ExternalFunction::invoke`] to avoid repeated dynamic dispatch.
pub(crate) fn invoke_batch(
    this: &dyn ExternalFunction,
    state: &mut ExecutionState,
    mask: &mut Mask,
    bindings: &mut Bindings,
    args: &[QueryEntry],
    out_var: Variable,
) {
    let pool: Pool<Vec<Value>> = with_pool_set(|ps| ps.get_pool());
    let mut out = pool.get();
    out.reserve(mask.len());
    for_each_binding_with_mask!(mask, args, bindings, |iter| {
        iter.fill_vec(&mut out, Value::stale, |_, args| {
            this.invoke(state, args.as_slice())
        });
    });
    bindings.insert(out_var, &out);
}

/// A variant of [`invoke_batch`] that overwrites the output variable,
/// rather than assigning all new values.
///
/// *Panics* This method will panic if `out_var` doesn't already have an appropriately-sized
/// vector bound in `bindings`.
pub(crate) fn invoke_batch_assign(
    this: &dyn ExternalFunction,
    state: &mut ExecutionState,
    mask: &mut Mask,
    bindings: &mut Bindings,
    args: &[QueryEntry],
    out_var: Variable,
) {
    let mut out = bindings.take(out_var).expect("out_var must be bound");
    for_each_binding_with_mask!(mask, args, bindings, |iter| {
        iter.assign_vec_and_retain(&mut out.vals, |_, args| this.invoke(state, &args))
    });
    bindings.replace(out);
}

// Implements `Clone` for `Box<dyn ExternalFunction>`.
dyn_clone::clone_trait_object!(ExternalFunction);

pub(crate) type ExternalFunctions =
    DenseIdMapWithReuse<ExternalFunctionId, Box<dyn ExternalFunction>>;

#[derive(Default)]
pub(crate) struct Counters(DenseIdMap<CounterId, AtomicUsize>);

impl Clone for Counters {
    fn clone(&self) -> Counters {
        let mut map = DenseIdMap::new();
        for (k, v) in self.0.iter() {
            // NB: we may want to experiment with Ordering::Relaxed here.
            map.insert(k, AtomicUsize::new(v.load(Ordering::SeqCst)));
        }
        Counters(map)
    }
}

impl Counters {
    pub(crate) fn read(&self, ctr: CounterId) -> usize {
        self.0[ctr].load(Ordering::Acquire)
    }
    pub(crate) fn inc(&self, ctr: CounterId) -> usize {
        // We synchronize with `read_counter` but not with other increments.
        // NB: we may want to experiment with Ordering::Relaxed here.
        self.0[ctr].fetch_add(1, Ordering::Release)
    }
}

/// A collection of tables and indexes over them.
///
/// A database also owns the memory pools used by its tables.
#[derive(Clone, Default)]
pub struct Database {
    // NB: some fields are pub(crate) to allow some internal modules to avoid
    // borrowing the whole table.
    pub(crate) tables: DenseIdMap<TableId, TableInfo>,
    // TODO: having a single AtomicUsize per counter can lead to contention. We
    // should look into prefetching counters when creating a new ExecutionState
    // and incrementing locally. Note that the batch size shouldn't be too big
    // because we keep an array per id in the UF.
    pub(crate) counters: Counters,
    pub(crate) external_functions: ExternalFunctions,
    container_values: ContainerValues,
    /// `notification_list` contains the list of tables that have been modified since the last call
    /// to [`Database::merge_all`].
    notification_list: NotificationList<TableId>,
    // Tracks the relative dependencies between tables during merge operations.
    deps: DependencyGraph,
    base_values: BaseValues,
    /// A rough estimate of the total size of the database.
    ///
    /// This is primarily used to determine whether or not to attempt to do some operations in
    /// parallel.
    total_size_estimate: usize,
}

impl Database {
    /// Create an empty Database.
    ///
    /// Queries use the currently installed egglog thread pool. If no pool is
    /// installed, queries run single-threaded.
    pub fn new() -> Database {
        Database::default()
    }

    /// Initialize a new rulse set to run against this database.
    pub fn new_rule_set(&mut self) -> RuleSetBuilder<'_> {
        RuleSetBuilder::new(self)
    }

    /// Add a new external function to the database.
    pub fn add_external_function(
        &mut self,
        f: Box<dyn ExternalFunction + 'static>,
    ) -> ExternalFunctionId {
        self.external_functions.push(f)
    }

    /// Free an existing external function. Make sure not to use `id` afterwards.
    pub fn free_external_function(&mut self, id: ExternalFunctionId) {
        self.external_functions.take(id);
    }

    pub fn base_values(&self) -> &BaseValues {
        &self.base_values
    }

    pub fn base_values_mut(&mut self) -> &mut BaseValues {
        &mut self.base_values
    }

    pub fn container_values(&self) -> &ContainerValues {
        &self.container_values
    }

    pub fn container_values_mut(&mut self) -> &mut ContainerValues {
        &mut self.container_values
    }

    pub fn rebuild_containers(&mut self, table_id: TableId) -> ContainerRebuildSummary {
        let mut containers = mem::take(&mut self.container_values);
        let table = &self.tables[table_id].table;
        let res = self.with_execution_state(|state| containers.rebuild_all(table_id, table, state));
        self.container_values = containers;
        res
    }

    /// Apply the value-level rebuild encoded by `func_id` to all the tables in `to_rebuild`.
    ///
    /// The native [`Table::apply_rebuild`] method takes a `next_ts` argument for filling in new
    /// values in a table like [`crate::SortedWritesTable`] where values in a certain column need
    /// to be inserted in sorted order; the `next_ts` argument to this method is passed to
    /// `apply_rebuild` for this purpose.
    pub fn apply_rebuild(
        &mut self,
        func_id: TableId,
        to_rebuild: &[TableId],
        next_ts: Value,
    ) -> bool {
        let func = self.tables.take(func_id).unwrap();
        self.run_on_tables(to_rebuild, |_, info, view| {
            info.table.apply_rebuild(
                func_id,
                &func.table,
                next_ts,
                &mut ExecutionState::new(*view, Default::default()),
            )
        });
        self.tables.insert(func_id, func);
        self.merge_all()
    }

    pub fn refresh_rows_for_values(
        &mut self,
        to_refresh: &[TableId],
        dirty_ids: &[Value],
        next_ts: Value,
    ) -> bool {
        if dirty_ids.is_empty() {
            return false;
        }
        // This is the follow-up for `ContainerRebuildSummary::dirty_ids()`.
        // These ids changed semantics without changing identity, so parent
        // rows can become newly matchable without getting an ordinary table
        // delta.
        //
        // It must run after ordinary table rebuild, which already handles
        // changed-id cases by rewriting parent rows to the new id.
        self.run_on_tables(to_refresh, |_, info, _| {
            info.table.refresh_rows_for_values(dirty_ids, next_ts)
        });
        self.merge_all()
    }

    fn run_on_tables(
        &mut self,
        table_ids: &[TableId],
        run: impl for<'a> Fn(TableId, &mut TableInfo, &DbView<'a>) -> bool + Sync,
    ) {
        if parallelize_db_level_op(self.total_size_estimate) {
            let mut tables = Vec::with_capacity(table_ids.len());
            for id in table_ids {
                tables.push((*id, self.tables.take(*id).unwrap()));
            }
            let view = self.read_only_view();
            parallel::for_each_mut(&mut tables, |_, (id, info)| {
                if run(*id, info, &view) {
                    self.notification_list.notify(*id);
                }
            });
            for (id, info) in tables {
                self.tables.insert(id, info);
            }
        } else {
            for id in table_ids {
                let mut info = self.tables.take(*id).unwrap();
                let changed = {
                    let view = self.read_only_view();
                    run(*id, &mut info, &view)
                };
                if changed {
                    self.notification_list.notify(*id);
                }
                self.tables.insert(*id, info);
            }
        }
    }

    /// Run `f` with access to an `ExecutionState` mapped to this database.
    pub fn with_execution_state<R>(&self, f: impl FnOnce(&mut ExecutionState) -> R) -> R {
        let mut state = ExecutionState::new(self.read_only_view(), Default::default());
        f(&mut state)
    }

    /// Like [`Database::with_execution_state`], but also reports whether `f`
    /// staged any mutation through the execution state. Callers can use the
    /// flag to skip a subsequent `merge_all` when the closure was read-only.
    pub fn with_execution_state_tracked<R>(
        &self,
        f: impl FnOnce(&mut ExecutionState) -> R,
    ) -> (R, bool) {
        let mut state = ExecutionState::new(self.read_only_view(), Default::default());
        let result = f(&mut state);
        (result, state.changed)
    }

    pub(crate) fn read_only_view(&self) -> DbView<'_> {
        DbView {
            table_info: &self.tables,
            counters: &self.counters,
            external_funcs: &self.external_functions,
            bases: &self.base_values,
            containers: &self.container_values,
            notification_list: &self.notification_list,
        }
    }

    /// Estimate the size of the table. If a constraint is provided, return an
    /// estimate of the size of the subset of the table matching the constraint.
    pub fn estimate_size(&self, table: TableId, c: Option<Constraint>) -> usize {
        let table_info = self
            .tables
            .get(table)
            .expect("table must be declared in the current database");
        let table = &table_info.table;
        if let Some(c) = c {
            if let Some(sub) = table.fast_subset(&c) {
                // In the case where a the constraint can be computed quickly,
                // we do not filter for staleness, which may over-approximate.
                sub.size()
            } else {
                table.refine_one(table.refine_live(table.all()), &c).size()
            }
        } else {
            table.len()
        }
    }

    /// Create a new counter for this database.
    ///
    /// These counters can be used to generate unique ids as part of an action.
    pub fn add_counter(&mut self) -> CounterId {
        self.counters.0.push(AtomicUsize::new(0))
    }

    /// Increment the given counter and return its previous value.
    pub fn inc_counter(&self, counter: CounterId) -> usize {
        self.counters.inc(counter)
    }

    /// Get the current value of the given counter.
    pub fn read_counter(&self, counter: CounterId) -> usize {
        self.counters.read(counter)
    }

    /// A helper for merging all pending updates. Used to write to the database after updates have
    /// been staged. Returns true if any tuples were added.
    ///
    /// Exposed for testing purposes.
    ///
    /// Useful for out-of-band insertions into the database.
    pub fn merge_all(&mut self) -> bool {
        let mut ever_changed = false;
        let do_parallel = parallelize_db_level_op(self.total_size_estimate);
        let mut to_merge = IndexSet::default();
        loop {
            to_merge.clear();
            let to_merge_vec = self.notification_list.reset();
            if to_merge_vec.len() < 4 {
                ever_changed |= self.merge_simple(to_merge_vec);
                break;
            }
            for table in to_merge_vec {
                to_merge.insert(table);
            }

            let mut changed = false;
            let mut tables_merging = DenseIdMap::<
                TableId,
                (
                    // The info needed to merge this table.
                    Option<TableInfo>,
                    // Pre-allocated write buffers, according to the tables declared write
                    // dependencies.
                    DenseIdMap<TableId, Box<dyn MutationBuffer>>,
                ),
            >::with_capacity(self.tables.n_ids());
            for stratum in self.deps.strata() {
                // Initialize the write dependencies first.
                for table in stratum.intersection(&to_merge).copied() {
                    let mut bufs = DenseIdMap::default();
                    for dep in self.deps.write_deps(table) {
                        if let Some(info) = self.tables.get(dep) {
                            bufs.insert(dep, info.table.new_buffer());
                        }
                    }
                    tables_merging.insert(table, (None, bufs));
                }
                // Then initialize read dependencies (this two-phase structure is why we have an
                // Option in the tables_merging map).
                for table in stratum.intersection(&to_merge).copied() {
                    tables_merging[table].0 = Some(self.tables.unwrap_val(table));
                }
                let db = self.read_only_view();
                changed |= if do_parallel {
                    parallel::map_dense_id_map_mut(&mut tables_merging, |_, (info, buffers)| {
                        let mut es = ExecutionState::new(db, mem::take(buffers));
                        info.as_mut().unwrap().table.merge(&mut es).added || es.changed
                    })
                    .into_iter()
                    .any(|changed| changed)
                } else {
                    tables_merging
                        .iter_mut()
                        .map(|(_, (info, buffers))| {
                            let mut es = ExecutionState::new(db, mem::take(buffers));
                            info.as_mut().unwrap().table.merge(&mut es).added || es.changed
                        })
                        .max()
                        .unwrap_or(false)
                };
                for (id, (table, _)) in tables_merging.drain() {
                    self.tables.insert(id, table.unwrap());
                }
            }
            ever_changed |= changed;
        }
        // Reset all indexes to force an update on the next access.
        let mut size_estimate = 0;
        for (_, info) in self.tables.iter_mut() {
            info.column_indexes.update(|_, ti| {
                Arc::get_mut(ti).unwrap().reset();
            });
            info.indexes.update(|_, ti| {
                Arc::get_mut(ti).unwrap().reset();
            });
            size_estimate += info.table.len();
        }
        self.total_size_estimate = size_estimate;
        ever_changed
    }

    /// A "fast path" merge method that is not optimized for parallelism and does not respect read
    /// and write dependencies. This ends up being faster than the full "strata-aware" option in
    /// the body of `merge_all`.
    fn merge_simple(&mut self, mut to_merge: SmallVec<[TableId; 4]>) -> bool {
        let mut changed = false;
        while !to_merge.is_empty() {
            for table_id in to_merge.iter().copied() {
                let mut info = self.tables.unwrap_val(table_id);
                let mut es = ExecutionState::new(self.read_only_view(), Default::default());
                changed |= info.table.merge(&mut es).added || es.changed;
                self.tables.insert(table_id, info);
            }
            to_merge = self.notification_list.reset();
        }
        changed
    }

    /// A low-level helper for merging pending updates to a particular function.
    ///
    /// Callers should prefer `merge_all`, as the process of merging the data
    /// for a particular table may cause other updates to be buffered
    /// elesewhere. The `merge_all` method runs merges to a fixed point to avoid
    /// surprises here.
    pub fn merge_table(&mut self, table: TableId) -> bool {
        let mut info = self.tables.unwrap_val(table);
        self.total_size_estimate = self.total_size_estimate.wrapping_sub(info.table.len());
        let table_changed = info.table.merge(&mut ExecutionState::new(
            self.read_only_view(),
            Default::default(),
        ));
        self.total_size_estimate = self.total_size_estimate.wrapping_add(info.table.len());
        self.tables.insert(table, info);
        table_changed.added
    }

    /// Get id of the next table to be added to the database.
    ///
    /// This can be useful for "knot tying", when tables need to reference their
    /// own id.
    pub fn next_table_id(&self) -> TableId {
        self.tables.next_id()
    }

    /// Add a table with the given schema to the database.
    ///
    /// The table must have a compatible spec with `types` (e.g. same number of
    /// columns).
    pub fn add_table<T: Table + Sized + 'static>(
        &mut self,
        table: T,
        read_deps: impl IntoIterator<Item = TableId>,
        write_deps: impl IntoIterator<Item = TableId>,
    ) -> TableId {
        self.add_table_impl(table, None, read_deps, write_deps)
    }

    pub fn add_table_named<T: Table + Sized + 'static>(
        &mut self,
        table: T,
        name: Arc<str>,
        read_deps: impl IntoIterator<Item = TableId>,
        write_deps: impl IntoIterator<Item = TableId>,
    ) -> TableId {
        self.add_table_impl(table, Some(name), read_deps, write_deps)
    }

    fn add_table_impl<T: Table + Sized + 'static>(
        &mut self,
        table: T,
        name: Option<Arc<str>>,
        read_deps: impl IntoIterator<Item = TableId>,
        write_deps: impl IntoIterator<Item = TableId>,
    ) -> TableId {
        let spec = table.spec();
        let table = WrappedTable::new(table);
        let res = self.tables.push(TableInfo {
            name,
            spec,
            table,
            indexes: IndexCatalog::new(),
            column_indexes: IndexCatalog::new(),
        });
        self.deps.add_table(res, read_deps, write_deps);
        res
    }

    /// Get direct mutable access to the table.
    ///
    /// This method is useful for out-of-band access to databse state.
    ///
    /// **NOTE:** It is legal to call [`Table::new_buffer`] on the returned table handle, and use
    /// that to stage updates to the given table via [`MutationBuffer::stage_insert`] or
    /// [`MutationBuffer::stage_remove`], however this is *likely to be a source of bugs*.
    ///
    /// Updates staged in this way will not cause `table` to be marked as having pending changes in
    /// the next call to [`Database::merge_all`]. Instead, such users should use
    /// [`Database::new_buffer`], which plumbs this signal through correctly, or better yet,
    /// perform all updates through an [`ExecutionState`] or a [`crate::RuleBuilder`]. If these
    /// options do not work, then calling [`Database::merge_table`] directly will force a merge
    /// call on the table.
    pub fn get_table(&self, table: TableId) -> &WrappedTable {
        &self
            .tables
            .get(table)
            .expect("must access a table that has been declared in this database")
            .table
    }

    /// Get a handle on the given table along with metadata about it.
    ///
    ///
    /// **NOTE:** See the note on [`Database::get_table`] around manually staging updates.
    pub fn get_table_info(&self, table: TableId) -> &TableInfo {
        self.tables
            .get(table)
            .expect("must access a table that has been declared in this database")
    }

    /// Create a new mutation buffer for the table with id `id`.
    ///
    /// This will marked the given table as potentially changed for the next round of merging.
    /// Unlike calling [`Table::new_buffer`] on a table returned from a getter, this method also
    /// triggers change notification metadata that is read by [`Database::merge_all`].
    pub fn new_buffer(&self, id: TableId) -> Box<dyn MutationBuffer> {
        self.notification_list.notify(id);
        self.get_table(id).new_buffer()
    }

    pub(crate) fn process_constraints(
        &self,
        table: TableId,
        cs: &[Constraint],
    ) -> ProcessedConstraints {
        let table_info = &self.tables[table];
        let (mut subset, mut fast, mut slow) = table_info.table.split_fast_slow(cs);
        slow.retain(|c| {
            let (col, val) = match c {
                Constraint::EqConst { col, val } => (*col, *val),
                Constraint::Eq { .. }
                | Constraint::LtConst { .. }
                | Constraint::GtConst { .. }
                | Constraint::LeConst { .. }
                | Constraint::GeConst { .. } => return true,
            };
            // We are looking up by a constant: this is something we can build
            // an index for as long as the column is cacheable.
            if *table_info
                .spec
                .uncacheable_columns
                .get(col)
                .unwrap_or(&false)
            {
                return true;
            }
            // We have or will build an index: upgrade this constraint to
            // 'fast'.
            fast.push(c.clone());
            let index = get_column_index_from_tableinfo(table_info, col);
            match index.get().unwrap().get_subset(&val) {
                Some(s) => {
                    with_pool_set(|ps| subset.intersect(s, &ps.get_pool()));
                }
                None => {
                    // There are no rows matching this key! We can constrain this to nothing.
                    subset = Subset::empty();
                }
            }
            // Remove this constraint from the slow list.
            false
        });
        ProcessedConstraints { subset, fast, slow }
    }

    /// Get direct mutable access to the table.
    ///
    /// This method is useful for out-of-band access to databse state.
    ///
    /// **NOTE:** See the warning around staging updates to handles returned through this method in
    /// the documentation for [`Database::get_table`].
    pub fn get_table_mut(&mut self, id: TableId) -> &mut dyn Table {
        &mut *self
            .tables
            .get_mut(id)
            .expect("must access a table that has been declared in this database")
            .table
    }

    /// Remove every row from the given table.
    ///
    /// This is intended as a faster alternative to staging a per-row
    /// `stage_remove` for every key in the table. The underlying [`Table::clear`]
    /// implementation drops the row storage in bulk and bumps the table's major
    /// generation, so any cached indexes/subsets observed by future readers will
    /// be lazily rebuilt against the now-empty table. Any pending staged
    /// inserts or removes for this table are dropped (they pre-dated the clear,
    /// so they no longer make sense once the table is empty).
    ///
    /// This method also resets the cached column- and key-indexes for the
    /// table so subsequent merges can take the `Arc::get_mut`-based reset path,
    /// matching the invariant maintained by [`Database::merge_all`].
    ///
    /// This does **not** flush pending changes for *other* tables; it is the
    /// caller's responsibility to call [`Database::merge_all`] beforehand if
    /// they need staged updates from a previous step to land before the clear.
    pub fn clear_table(&mut self, table: TableId) {
        let info = self
            .tables
            .get_mut(table)
            .expect("must access a table that has been declared in this database");
        let prev_len = info.table.len();
        info.table.clear();
        // The version bump from `clear` is enough on its own to make the
        // indexes self-refresh on next access (see `Index::refresh`). We still
        // reset them eagerly here so that the next `merge_all` sees the same
        // "indexes are resettable" state it expects after a successful merge.
        info.column_indexes.update(|_, ti| {
            if let Some(arc) = Arc::get_mut(ti) {
                arc.reset();
            }
        });
        info.indexes.update(|_, ti| {
            if let Some(arc) = Arc::get_mut(ti) {
                arc.reset();
            }
        });
        self.total_size_estimate = self.total_size_estimate.wrapping_sub(prev_len);
    }

    pub(crate) fn plan_query(&mut self, query: Query) -> Plan {
        plan::plan_query(query, ColumnCardEst::new(self))
    }
}

impl Drop for Database {
    fn drop(&mut self) {
        // Clean up this thread's ambient memory pool.
        with_pool_set(PoolSet::clear);
    }
}

/// The core logic behind getting and updating a hash index.
///
/// This is in a separate function to allow us to reuse it while already
/// borrowing a `TableInfo`.
fn get_index_from_tableinfo(table_info: &TableInfo, cols: &[ColumnId]) -> HashIndex {
    let index: Arc<_> = table_info.indexes.get_or_insert(cols.into(), || {
        Arc::new(ResettableOnceLock::new(Index::new(
            cols.to_vec(),
            TupleIndex::new(cols.len()),
        )))
    });
    index.get_or_update(|index| {
        index.refresh(table_info.table.as_ref());
    });
    debug_assert!(
        !index
            .get()
            .unwrap()
            .needs_refresh(table_info.table.as_ref())
    );
    index
}

/// The core logic behind getting and updating a column index.
///
/// This is the single-column analog to [`get_index_from_tableinfo`].
fn get_column_index_from_tableinfo(table_info: &TableInfo, col: ColumnId) -> HashColumnIndex {
    let index: Arc<_> = table_info.column_indexes.get_or_insert(col, || {
        Arc::new(ResettableOnceLock::new(Index::new(
            vec![col],
            ColumnIndex::new(),
        )))
    });
    index.get_or_update(|index| {
        index.refresh(table_info.table.as_ref());
    });
    debug_assert!(
        !index
            .get()
            .unwrap()
            .needs_refresh(table_info.table.as_ref())
    );
    index
}

#[derive(Clone)]
pub struct ColumnCardEst<'a> {
    db: &'a Database,
}

impl ColumnCardEst<'_> {
    pub fn new(db: &Database) -> ColumnCardEst<'_> {
        ColumnCardEst { db }
    }

    pub fn col_uniqueness(&self, table: TableId, col: ColumnId) -> ColUniqueness {
        let col_idx = get_column_index_from_tableinfo(&self.db.tables[table], col);
        let table = &self.db.tables[table].table;
        ColUniqueness {
            col_size: col_idx.get().unwrap().len(),
            table_size: table.len(),
        }
    }
}

impl std::fmt::Debug for ColumnCardEst<'_> {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("ColumnCardEst").finish_non_exhaustive()
    }
}

/// A coarse cardinality estimate for a column of a table, used by the query
/// planner to decide which variable to eliminate next during tree
/// decomposition.
///
/// `table_size` is the number of rows in the (sub)table and `col_size` is the
/// number of distinct values in the column. Their ratio
/// (`table_size / col_size`) approximates the average number of rows that share
/// a given value of the column: a smaller ratio means the column is closer to
/// being unique and therefore cheaper to join on. [`ColUniqueness`] is ordered
/// by this ratio (see the [`Ord`] impl), so the planner prefers variables with
/// the most selective (most unique) columns.
#[derive(Copy, Clone, Debug)]
pub struct ColUniqueness {
    table_size: usize,
    col_size: usize,
}

impl Default for ColUniqueness {
    fn default() -> ColUniqueness {
        ColUniqueness {
            table_size: 1,
            col_size: 1,
        }
    }
}

impl ColUniqueness {
    #[allow(dead_code)] // not yet wired up into the planner
    fn scale(&self, subset_size: usize) -> ColUniqueness {
        if self.table_size == 0 || subset_size == 0 {
            return ColUniqueness {
                table_size: 0,
                col_size: 0,
            };
        }
        ColUniqueness {
            table_size: subset_size,
            col_size: self.col_size.saturating_mul(subset_size) / self.table_size,
        }
    }
    fn join(&self, other: &ColUniqueness) -> ColUniqueness {
        ColUniqueness {
            table_size: self.table_size.saturating_mul(other.table_size),
            col_size: self.col_size.max(other.col_size),
        }
    }

    #[allow(dead_code)] // not yet wired up into the planner
    fn col_size(&self) -> usize {
        self.col_size
    }
}

impl PartialEq for ColUniqueness {
    fn eq(&self, other: &Self) -> bool {
        self.cmp(other) == std::cmp::Ordering::Equal
    }
}

impl Eq for ColUniqueness {}

impl PartialOrd for ColUniqueness {
    fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
        Some(self.cmp(other))
    }
}

impl Ord for ColUniqueness {
    fn cmp(&self, other: &Self) -> std::cmp::Ordering {
        (self.table_size.saturating_mul(other.col_size))
            .cmp(&(other.table_size.saturating_mul(self.col_size)))
    }
}