//! Snapshot executor for conjunctive-query plans.
//!
//! Takes a structural plan (a DAG of `Scan` and `Join` nodes), the input
//! tables it scans, and walks the DAG via [`query_ops::atom::scan_atom`],
//! [`query_ops::join::semijoin`], and [`query_ops::join::natural_join`].
//! The result is a binding [`Relation`](query_ops::relation::Relation) over
//! the query's variables.
//!
//! The runner is intentionally backend-agnostic: it depends only on
//! `query-ops`, and the planner that emits the JSON IR is decoupled from
//! the storage backend that produced the facts. To execute a plan against
//! a [`Storage`](storage::Storage) backend, materialize each input table
//! with [`storage::scan_as_table`] and call [`execute`] with the resulting
//! map. The in-tree `tests/storage_roundtrip.rs` is the canonical example.
//!
//! The JSON IR mirrors `Geolog.DB.Plan.PlanGraph` and
//! `Geolog.DB.InMemory.QAtom` from the `external/geolog` submodule, but the
//! shape is the contract: any frontend that emits this JSON can use the
//! runner.
//!
//! Operator mapping from the Haskell planner:
//!
//! | `Geolog.DB.Plan`            | this crate                                    |
//! |-----------------------------|-----------------------------------------------|
//! | `PlanEvalAtom`              | [`Action::Scan`] → `scan_atom`                |
//! | `PlanJoin LeftJoin a b`     | [`Action::Join`] with [`JoinOp::Left`] → `semijoin(rel[a], rel[b])` |
//! | `PlanJoin RightJoin a b`    | [`Action::Join`] with [`JoinOp::Right`] → `semijoin(rel[b], rel[a])` |
//! | `PlanJoin NaturalJoin a b`  | [`Action::Join`] with [`JoinOp::Natural`] → `natural_join(rel[a], rel[b])` |
//!
//! The atom side covers `evalAtom` (`Geolog.DB.InMemory`): a [`Term::Var`]
//! repeated across positions enforces equality, [`Term::Lit`] filters by
//! constant, and distinct variables project in first-occurrence order.

use std::collections::HashMap;

use serde::Deserialize;

use query_ops::atom::{AtomPattern, Term, scan_atom};
use query_ops::join::{natural_join, semijoin};
use query_ops::relation::Relation;
use storage::table::Table;
use storage::value::Value;
use storage::{Storage, StorageError, scan_as_table};

/// A single fixture: schema, ground facts, and a query plan to execute.
#[derive(Debug, Clone, Deserialize)]
pub struct Plan {
    /// Relation name → arity (column count).
    pub schema: HashMap<String, usize>,
    /// Relation name → list of ground tuples to insert before execution.
    pub facts: HashMap<String, Vec<Vec<JsonValue>>>,
    /// The join DAG itself.
    pub query: Query,
    /// Optional oracle: if present, [`verify`] cross-checks an executed
    /// [`Relation`] against this projection. The exporter lifts the
    /// scenario's `expected_bindings` block into this field.
    #[serde(default)]
    pub expected_bindings: Option<ExpectedBindings>,
}

/// Expected query result, projected to a named subset of variables. The
/// columns named here must all appear in the runner's output; any extra
/// columns (typically per-atom wildcards) are ignored.
#[derive(Debug, Clone, Deserialize)]
pub struct ExpectedBindings {
    pub columns: Vec<String>,
    pub rows: Vec<Vec<JsonValue>>,
}

/// Mirrors `Geolog.DB.Plan.PlanGraph`: a set of nodes plus the id of the
/// rooted result node (the last node in topological order).
#[derive(Debug, Clone, Deserialize)]
pub struct Query {
    pub root: u32,
    pub nodes: Vec<Node>,
}

/// One node of the plan DAG. `id`s don't need to start at any particular
/// value, mirroring the Haskell `PlanNodeId`.
#[derive(Debug, Clone, Deserialize)]
pub struct Node {
    pub id: u32,
    pub action: Action,
}

/// What to compute at a node. Tagged externally so JSON reads as
/// `{"action": {"scan": {...}}}` or `{"action": {"join": {...}}}`.
#[derive(Debug, Clone, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum Action {
    Scan(Atom),
    Join(Join),
}

/// A flat atom pattern, one entry per column of the target relation.
/// Matches the `toFlatArgs` view used by `Geolog.DB.InMemory.evalAtom`:
/// `qaValues` positions are filled in directly, and the entity-id column
/// (if any) appears at the last position. Wildcard positions in the
/// Haskell `QAtom` (a `Map Int QVal` with a missing key) translate to a
/// fresh, unique variable name on this side, which the operator binds but
/// never joins against.
#[derive(Debug, Clone, Deserialize)]
pub struct Atom {
    pub table: String,
    pub columns: Vec<JsonTerm>,
}

#[derive(Debug, Clone, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum JsonTerm {
    Var(String),
    Lit(JsonValue),
}

/// Wire-level value tag. Restricted to what
/// [`storage::value::Value`](storage::value::Value) carries. Entity identities from
/// the Haskell side (`ValEntity path id`) round-trip through `Str` using a
/// `"path:id"` convention; that's a fixture concern, not a runner concern.
#[derive(Debug, Clone, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum JsonValue {
    Int(i64),
    Str(String),
}

#[derive(Debug, Clone, Deserialize)]
pub struct Join {
    pub op: JoinOp,
    pub left: u32,
    pub right: u32,
}

#[derive(Debug, Clone, Copy, Deserialize)]
#[serde(rename_all = "snake_case")]
pub enum JoinOp {
    /// `Geolog.DB.Plan.LeftJoin`: result is `left` rows whose shared columns
    /// appear in `right`. Lowered to `semijoin(left, right)`.
    Left,
    /// `Geolog.DB.Plan.RightJoin`: result is `right` rows whose shared
    /// columns appear in `left`. Lowered to `semijoin(right, left)`.
    Right,
    /// `Geolog.DB.Plan.NaturalJoin`. Lowered to `natural_join(left, right)`.
    Natural,
}

/// Errors produced by [`verify`] when actual bindings don't match the
/// scenario's `expected_bindings` projection.
#[derive(Debug)]
pub enum VerifyError {
    /// An expected column wasn't produced by the plan.
    MissingColumn(String),
    /// An expected row's width didn't match the column count.
    ExpectedRowArity { expected: usize, got: usize },
    /// The expected and actual rows (after projection) differ as multisets.
    BindingsMismatch {
        expected: Vec<Vec<Value>>,
        actual: Vec<Vec<Value>>,
    },
}

impl std::fmt::Display for VerifyError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            Self::MissingColumn(name) => {
                write!(f, "expected column {name:?} not in plan output")
            }
            Self::ExpectedRowArity { expected, got } => write!(
                f,
                "expected row has {got} cells but columns has {expected} entries"
            ),
            Self::BindingsMismatch { expected, actual } => write!(
                f,
                "bindings mismatch:\n  expected: {expected:?}\n  actual:   {actual:?}"
            ),
        }
    }
}

impl std::error::Error for VerifyError {}

/// Cross-check an executed [`Relation`] against a [`Plan`]'s
/// `expected_bindings`. Projects `actual` to the expected columns (so the
/// runner is free to surface wildcard columns the oracle doesn't name) and
/// compares as a multiset.
///
/// Returns `Ok(true)` if the plan carried an oracle and it matched,
/// `Ok(false)` if there was no oracle (caller decides whether that's an
/// error). Returns [`VerifyError`] on mismatch.
///
/// # Errors
/// See [`VerifyError`].
pub fn verify(plan: &Plan, actual: &Relation) -> Result<bool, VerifyError> {
    let Some(expected) = &plan.expected_bindings else {
        return Ok(false);
    };
    let mut projection: Vec<usize> = Vec::with_capacity(expected.columns.len());
    for col in &expected.columns {
        let idx = actual
            .columns
            .iter()
            .position(|c| c == col)
            .ok_or_else(|| VerifyError::MissingColumn(col.clone()))?;
        projection.push(idx);
    }
    let mut actual_proj: Vec<Vec<Value>> = actual
        .rows
        .iter()
        .map(|row| projection.iter().map(|&i| row[i].clone()).collect())
        .collect();
    let mut expected_proj: Vec<Vec<Value>> = Vec::with_capacity(expected.rows.len());
    for row in &expected.rows {
        if row.len() != expected.columns.len() {
            return Err(VerifyError::ExpectedRowArity {
                expected: expected.columns.len(),
                got: row.len(),
            });
        }
        expected_proj.push(row.iter().cloned().map(Value::from).collect());
    }
    // Value is not Ord; use Debug-derived sort keys to compare as a multiset.
    let key = |row: &[Value]| -> String { format!("{row:?}") };
    actual_proj.sort_by_key(|r| key(r));
    expected_proj.sort_by_key(|r| key(r));
    if actual_proj == expected_proj {
        Ok(true)
    } else {
        Err(VerifyError::BindingsMismatch {
            expected: expected_proj,
            actual: actual_proj,
        })
    }
}

/// Errors a runner can produce during plan validation and execution.
#[derive(Debug)]
pub enum RunError {
    /// A fact or scan references a relation that isn't declared in `schema`.
    UnknownRelation(String),
    /// A scan refers to a table that wasn't supplied in the input map.
    MissingTable(String),
    /// A fact row's length doesn't match the schema's declared arity.
    ArityMismatch {
        relation: String,
        expected: usize,
        got: usize,
    },
    /// A scan's atom pattern doesn't match the table's arity.
    PatternArityMismatch {
        table: String,
        table_arity: usize,
        pattern_arity: usize,
    },
    /// A join node references a node id that doesn't exist.
    MissingNode(u32),
    /// `Query.root` doesn't match any node in `nodes`.
    MissingRoot(u32),
    /// Two nodes share the same id.
    DuplicateNode(u32),
    /// A join node references its left or right side before that side has
    /// been computed: the DAG isn't actually topologically sorted by id, or
    /// it has a cycle.
    UnresolvedDependency { node: u32, depends_on: u32 },
    /// A [`Storage`] backend used to materialize tables returned an error.
    Storage(StorageError),
}

impl From<StorageError> for RunError {
    fn from(err: StorageError) -> Self {
        Self::Storage(err)
    }
}

impl std::fmt::Display for RunError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            Self::UnknownRelation(name) => {
                write!(f, "facts reference relation {name:?} not in schema")
            }
            Self::MissingTable(name) => write!(f, "scan references missing table {name:?}"),
            Self::ArityMismatch {
                relation,
                expected,
                got,
            } => write!(
                f,
                "relation {relation:?}: row arity {got} differs from schema arity {expected}"
            ),
            Self::PatternArityMismatch {
                table,
                table_arity,
                pattern_arity,
            } => write!(
                f,
                "scan of {table:?}: pattern has {pattern_arity} columns, table has {table_arity}"
            ),
            Self::MissingNode(id) => write!(f, "plan references missing node id {id}"),
            Self::MissingRoot(id) => write!(f, "plan root id {id} matches no node"),
            Self::DuplicateNode(id) => write!(f, "duplicate node id {id} in plan"),
            Self::UnresolvedDependency { node, depends_on } => write!(
                f,
                "node {node} depends on {depends_on}, which has not been computed yet"
            ),
            Self::Storage(err) => write!(f, "storage backend error: {err}"),
        }
    }
}

impl std::error::Error for RunError {}

impl From<JsonValue> for Value {
    fn from(jv: JsonValue) -> Self {
        match jv {
            JsonValue::Int(n) => Self::Int(n),
            JsonValue::Str(s) => Self::Str(s),
        }
    }
}

impl From<JsonTerm> for Term {
    fn from(t: JsonTerm) -> Self {
        match t {
            JsonTerm::Var(name) => Self::Var(name),
            JsonTerm::Lit(value) => Self::Lit(value.into()),
        }
    }
}

/// Parse a [`Plan`] from a JSON string.
///
/// # Errors
/// Returns a [`serde_json::Error`] if the input isn't valid JSON in the
/// expected shape.
pub fn parse_plan(json: &str) -> Result<Plan, serde_json::Error> {
    serde_json::from_str(json)
}

/// Build the input [`Table`] for each relation declared in a [`Plan`]'s
/// schema, populating rows from the plan's `facts` map. Relations with no
/// facts get an empty table at the declared arity.
///
/// # Errors
/// Returns [`RunError::UnknownRelation`] if `facts` mentions a relation
/// not in `schema`, or [`RunError::ArityMismatch`] if a row's width doesn't
/// match the declared arity.
pub fn build_tables(plan: &Plan) -> Result<HashMap<String, Table>, RunError> {
    let mut tables: HashMap<String, Table> = plan
        .schema
        .iter()
        .map(|(name, arity)| (name.clone(), Table::new(*arity)))
        .collect();
    for (name, rows) in &plan.facts {
        let Some(table) = tables.get_mut(name) else {
            return Err(RunError::UnknownRelation(name.clone()));
        };
        for row in rows {
            if row.len() != table.arity {
                return Err(RunError::ArityMismatch {
                    relation: name.clone(),
                    expected: table.arity,
                    got: row.len(),
                });
            }
            let cells: Vec<Value> = row.iter().cloned().map(Value::from).collect();
            table.push(cells);
        }
    }
    Ok(tables)
}

/// Populate a [`Storage`] backend from a [`Plan`]'s schema and facts, then
/// materialize each declared relation back into an in-memory [`Table`] via
/// [`scan_as_table`]. The returned map is the same shape [`execute`]
/// consumes, so this is the storage-backed analogue of [`build_tables`].
///
/// Adding a new backend means constructing a different `S` at the call
/// site; the body here doesn't need to change.
///
/// # Errors
/// Returns [`RunError::UnknownRelation`] or [`RunError::ArityMismatch`] on
/// the same conditions as [`build_tables`], or [`RunError::Storage`] when
/// the backend itself rejects an operation.
pub fn build_tables_via_storage<S: Storage>(
    plan: &Plan,
    storage: &mut S,
) -> Result<HashMap<String, Table>, RunError> {
    for (name, arity) in &plan.schema {
        storage.create_relation(name, *arity)?;
    }
    {
        let mut tx = storage.transaction()?;
        for (name, rows) in &plan.facts {
            let Some(&arity) = plan.schema.get(name) else {
                return Err(RunError::UnknownRelation(name.clone()));
            };
            for row in rows {
                if row.len() != arity {
                    return Err(RunError::ArityMismatch {
                        relation: name.clone(),
                        expected: arity,
                        got: row.len(),
                    });
                }
                let cells: Vec<Value> = row.iter().cloned().map(Value::from).collect();
                tx.insert(name, cells)?;
            }
        }
        tx.commit()?;
    }
    let mut tables: HashMap<String, Table> = HashMap::with_capacity(plan.schema.len());
    for name in plan.schema.keys() {
        let table = scan_as_table(storage as &dyn Storage, name)?;
        tables.insert(name.clone(), table);
    }
    Ok(tables)
}

/// Execute a query DAG against the supplied input tables, returning the
/// bindings [`Relation`] for the rooted plan node.
///
/// Nodes are executed in ascending `id` order. For a Yannakakis plan as
/// emitted by `Geolog.DB.Plan` this is equivalent to a topological sort,
/// since `insertJoin` only references node ids that have already been
/// allocated. A non-monotone id ordering is rejected with
/// [`RunError::UnresolvedDependency`].
///
/// # Errors
/// Returns [`RunError::DuplicateNode`] for repeated ids,
/// [`RunError::MissingNode`] for join references to unknown ids,
/// [`RunError::MissingRoot`] if `query.root` isn't present,
/// [`RunError::MissingTable`] if a scan references a table not in the map,
/// or [`RunError::PatternArityMismatch`] if a scan's pattern doesn't match
/// the table's arity.
pub fn execute<S: std::hash::BuildHasher>(
    tables: &HashMap<String, Table, S>,
    query: &Query,
) -> Result<Relation, RunError> {
    let mut seen_ids: std::collections::HashSet<u32> =
        std::collections::HashSet::with_capacity(query.nodes.len());
    for node in &query.nodes {
        if !seen_ids.insert(node.id) {
            return Err(RunError::DuplicateNode(node.id));
        }
    }
    if !seen_ids.contains(&query.root) {
        return Err(RunError::MissingRoot(query.root));
    }

    let mut ordered: Vec<&Node> = query.nodes.iter().collect();
    ordered.sort_by_key(|n| n.id);

    let mut results: HashMap<u32, Relation> = HashMap::with_capacity(ordered.len());
    for node in ordered {
        let computed = match &node.action {
            Action::Scan(atom) => {
                let table = tables
                    .get(&atom.table)
                    .ok_or_else(|| RunError::MissingTable(atom.table.clone()))?;
                if atom.columns.len() != table.arity {
                    return Err(RunError::PatternArityMismatch {
                        table: atom.table.clone(),
                        table_arity: table.arity,
                        pattern_arity: atom.columns.len(),
                    });
                }
                let pattern = AtomPattern {
                    columns: atom.columns.iter().cloned().map(Term::from).collect(),
                };
                scan_atom(table, &pattern)
            }
            Action::Join(join) => {
                let left = require_dep(&results, &seen_ids, node.id, join.left)?;
                let right = require_dep(&results, &seen_ids, node.id, join.right)?;
                match join.op {
                    JoinOp::Left => semijoin(left, right),
                    JoinOp::Right => semijoin(right, left),
                    JoinOp::Natural => natural_join(left, right),
                }
            }
        };
        results.insert(node.id, computed);
    }

    results
        .remove(&query.root)
        .ok_or(RunError::MissingRoot(query.root))
}

fn require_dep<'a>(
    results: &'a HashMap<u32, Relation>,
    seen: &std::collections::HashSet<u32>,
    node: u32,
    depends_on: u32,
) -> Result<&'a Relation, RunError> {
    if let Some(rel) = results.get(&depends_on) {
        Ok(rel)
    } else if seen.contains(&depends_on) {
        Err(RunError::UnresolvedDependency { node, depends_on })
    } else {
        Err(RunError::MissingNode(depends_on))
    }
}

/// Convenience: parse JSON, build tables from the embedded facts, and
/// execute, returning the root binding relation. Equivalent to
/// `parse_plan` + [`build_tables`] + [`execute`].
///
/// # Errors
/// Returns a JSON parse error if the input is malformed, or a [`RunError`]
/// for any later step.
pub fn run_json(json: &str) -> Result<Relation, RunFromJsonError> {
    let plan = parse_plan(json).map_err(RunFromJsonError::Parse)?;
    let tables = build_tables(&plan).map_err(RunFromJsonError::Run)?;
    let bindings = execute(&tables, &plan.query).map_err(RunFromJsonError::Run)?;
    Ok(bindings)
}

/// Combined error from [`run_json`].
#[derive(Debug)]
pub enum RunFromJsonError {
    Parse(serde_json::Error),
    Run(RunError),
}

impl std::fmt::Display for RunFromJsonError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            Self::Parse(err) => write!(f, "parse error: {err}"),
            Self::Run(err) => write!(f, "run error: {err}"),
        }
    }
}

impl std::error::Error for RunFromJsonError {
    fn source(&self) -> Option<&(dyn std::error::Error + 'static)> {
        match self {
            Self::Parse(err) => Some(err),
            Self::Run(err) => Some(err),
        }
    }
}