datafusion 6.0.0

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// to you under the Apache License, Version 2.0 (the
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// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
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// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

//! Eliminate common sub-expression.

use crate::error::Result;
use crate::execution::context::ExecutionProps;
use crate::logical_plan::{
    col, DFField, DFSchema, Expr, ExprRewriter, ExpressionVisitor, LogicalPlan,
    Recursion, RewriteRecursion,
};
use crate::optimizer::optimizer::OptimizerRule;
use crate::optimizer::utils;
use arrow::datatypes::DataType;
use std::collections::{HashMap, HashSet};
use std::sync::Arc;

/// A map from expression's identifier to tuple including
/// - the expression itself (cloned)
/// - counter
/// - DataType of this expression.
type ExprSet = HashMap<Identifier, (Expr, usize, DataType)>;

/// Identifier type. Current implementation use describe of a expression (type String) as
/// Identifier.
///
/// A Identifier should (ideally) be able to "hash", "accumulate", "equal" and "have no
/// collision (as low as possible)"
///
/// Since a identifier is likely to be copied many times, it is better that a identifier
/// is small or "copy". otherwise some kinds of reference count is needed. String description
/// here is not such a good choose.
type Identifier = String;

/// Perform Common Sub-expression Elimination optimization.
///
/// Currently only common sub-expressions within one logical plan will
/// be eliminated.
pub struct CommonSubexprEliminate {}

impl OptimizerRule for CommonSubexprEliminate {
    fn optimize(
        &self,
        plan: &LogicalPlan,
        execution_props: &ExecutionProps,
    ) -> Result<LogicalPlan> {
        optimize(plan, execution_props)
    }

    fn name(&self) -> &str {
        "common_sub_expression_eliminate"
    }
}

impl CommonSubexprEliminate {
    #[allow(missing_docs)]
    pub fn new() -> Self {
        Self {}
    }
}

fn optimize(plan: &LogicalPlan, execution_props: &ExecutionProps) -> Result<LogicalPlan> {
    let mut expr_set = ExprSet::new();

    match plan {
        LogicalPlan::Projection {
            expr,
            input,
            schema,
            alias,
        } => {
            let arrays = to_arrays(expr, input, &mut expr_set)?;

            let (mut new_expr, new_input) = rewrite_expr(
                &[expr],
                &[&arrays],
                input,
                &mut expr_set,
                schema,
                execution_props,
            )?;

            Ok(LogicalPlan::Projection {
                expr: new_expr.pop().unwrap(),
                input: Arc::new(new_input),
                schema: schema.clone(),
                alias: alias.clone(),
            })
        }
        LogicalPlan::Filter { predicate, input } => {
            let schemas = plan.all_schemas();
            let all_schema =
                schemas.into_iter().fold(DFSchema::empty(), |mut lhs, rhs| {
                    lhs.merge(rhs);
                    lhs
                });
            let data_type = predicate.get_type(&all_schema)?;

            let mut id_array = vec![];
            expr_to_identifier(predicate, &mut expr_set, &mut id_array, data_type)?;

            let (mut new_expr, new_input) = rewrite_expr(
                &[&[predicate.clone()]],
                &[&[id_array]],
                input,
                &mut expr_set,
                input.schema(),
                execution_props,
            )?;

            Ok(LogicalPlan::Filter {
                predicate: new_expr.pop().unwrap().pop().unwrap(),
                input: Arc::new(new_input),
            })
        }
        LogicalPlan::Window {
            input,
            window_expr,
            schema,
        } => {
            let arrays = to_arrays(window_expr, input, &mut expr_set)?;

            let (mut new_expr, new_input) = rewrite_expr(
                &[window_expr],
                &[&arrays],
                input,
                &mut expr_set,
                schema,
                execution_props,
            )?;

            Ok(LogicalPlan::Window {
                input: Arc::new(new_input),
                window_expr: new_expr.pop().unwrap(),
                schema: schema.clone(),
            })
        }
        LogicalPlan::Aggregate {
            input,
            group_expr,
            aggr_expr,
            schema,
        } => {
            let group_arrays = to_arrays(group_expr, input, &mut expr_set)?;
            let aggr_arrays = to_arrays(aggr_expr, input, &mut expr_set)?;

            let (mut new_expr, new_input) = rewrite_expr(
                &[group_expr, aggr_expr],
                &[&group_arrays, &aggr_arrays],
                input,
                &mut expr_set,
                schema,
                execution_props,
            )?;
            // note the reversed pop order.
            let new_aggr_expr = new_expr.pop().unwrap();
            let new_group_expr = new_expr.pop().unwrap();

            Ok(LogicalPlan::Aggregate {
                input: Arc::new(new_input),
                group_expr: new_group_expr,
                aggr_expr: new_aggr_expr,
                schema: schema.clone(),
            })
        }
        LogicalPlan::Sort { expr, input } => {
            let arrays = to_arrays(expr, input, &mut expr_set)?;

            let (mut new_expr, new_input) = rewrite_expr(
                &[expr],
                &[&arrays],
                input,
                &mut expr_set,
                input.schema(),
                execution_props,
            )?;

            Ok(LogicalPlan::Sort {
                expr: new_expr.pop().unwrap(),
                input: Arc::new(new_input),
            })
        }
        LogicalPlan::Join { .. }
        | LogicalPlan::CrossJoin { .. }
        | LogicalPlan::Repartition { .. }
        | LogicalPlan::Union { .. }
        | LogicalPlan::TableScan { .. }
        | LogicalPlan::Values { .. }
        | LogicalPlan::EmptyRelation { .. }
        | LogicalPlan::Limit { .. }
        | LogicalPlan::CreateExternalTable { .. }
        | LogicalPlan::Explain { .. }
        | LogicalPlan::Analyze { .. }
        | LogicalPlan::CreateMemoryTable { .. }
        | LogicalPlan::DropTable { .. }
        | LogicalPlan::Extension { .. } => {
            // apply the optimization to all inputs of the plan
            let expr = plan.expressions();
            let inputs = plan.inputs();
            let new_inputs = inputs
                .iter()
                .map(|input_plan| optimize(input_plan, execution_props))
                .collect::<Result<Vec<_>>>()?;

            utils::from_plan(plan, &expr, &new_inputs)
        }
    }
}

fn to_arrays(
    expr: &[Expr],
    input: &LogicalPlan,
    mut expr_set: &mut ExprSet,
) -> Result<Vec<Vec<(usize, String)>>> {
    expr.iter()
        .map(|e| {
            let data_type = e.get_type(input.schema())?;
            let mut id_array = vec![];
            expr_to_identifier(e, &mut expr_set, &mut id_array, data_type)?;

            Ok(id_array)
        })
        .collect::<Result<Vec<_>>>()
}

/// Build the "intermediate" projection plan that evaluates the extracted common expressions.
///
/// This projection plan will merge all fields in the `input.schema()` into its own schema.
/// Redundant project fields are expected to be removed in other optimize phase (like
/// `projection_push_down`).
fn build_project_plan(
    input: LogicalPlan,
    affected_id: HashSet<Identifier>,
    expr_set: &ExprSet,
) -> Result<LogicalPlan> {
    let mut project_exprs = vec![];
    let mut fields = vec![];

    for id in affected_id {
        let (expr, _, data_type) = expr_set.get(&id).unwrap();
        // todo: check `nullable`
        fields.push(DFField::new(None, &id, data_type.clone(), true));
        project_exprs.push(expr.clone().alias(&id));
    }

    fields.extend_from_slice(input.schema().fields());
    input.schema().fields().iter().for_each(|field| {
        project_exprs.push(Expr::Column(field.qualified_column()));
    });

    let mut schema = DFSchema::new(fields)?;
    schema.merge(input.schema());

    Ok(LogicalPlan::Projection {
        expr: project_exprs,
        input: Arc::new(input),
        schema: Arc::new(schema),
        alias: None,
    })
}

#[inline]
fn rewrite_expr(
    exprs_list: &[&[Expr]],
    arrays_list: &[&[Vec<(usize, String)>]],
    input: &LogicalPlan,
    expr_set: &mut ExprSet,
    schema: &DFSchema,
    execution_props: &ExecutionProps,
) -> Result<(Vec<Vec<Expr>>, LogicalPlan)> {
    let mut affected_id = HashSet::<Identifier>::new();

    let rewrote_exprs = exprs_list
        .iter()
        .zip(arrays_list.iter())
        .map(|(exprs, arrays)| {
            exprs
                .iter()
                .cloned()
                .zip(arrays.iter())
                .map(|(expr, id_array)| {
                    replace_common_expr(
                        expr,
                        id_array,
                        expr_set,
                        &mut affected_id,
                        schema,
                    )
                })
                .collect::<Result<Vec<_>>>()
        })
        .collect::<Result<Vec<_>>>()?;

    let mut new_input = optimize(input, execution_props)?;
    if !affected_id.is_empty() {
        new_input = build_project_plan(new_input, affected_id, expr_set)?;
    }

    Ok((rewrote_exprs, new_input))
}

/// Go through an expression tree and generate identifier.
///
/// An identifier contains information of the expression itself and its sub-expression.
/// This visitor implementation use a stack `visit_stack` to track traversal, which
/// lets us know when a sub-tree's visiting is finished. When `pre_visit` is called
/// (traversing to a new node), an `EnterMark` and an `ExprItem` will be pushed into stack.
/// And try to pop out a `EnterMark` on leaving a node (`post_visit()`). All `ExprItem`
/// before the first `EnterMark` is considered to be sub-tree of the leaving node.
///
/// This visitor also records identifier in `id_array`. Makes the following traverse
/// pass can get the identifier of a node without recalculate it. We assign each node
/// in the expr tree a series number, start from 1, maintained by `series_number`.
/// Series number represents the order we left (`post_visit`) a node. Has the property
/// that child node's series number always smaller than parent's. While `id_array` is
/// organized in the order we enter (`pre_visit`) a node. `node_count` helps us to
/// get the index of `id_array` for each node.
///
/// `Expr` without sub-expr (column, literal etc.) will not have identifier
/// because they should not be recognized as common sub-expr.
struct ExprIdentifierVisitor<'a> {
    // param
    expr_set: &'a mut ExprSet,
    /// series number (usize) and identifier.
    id_array: &'a mut Vec<(usize, Identifier)>,
    data_type: DataType,

    // inner states
    visit_stack: Vec<VisitRecord>,
    /// increased in pre_visit, start from 0.
    node_count: usize,
    /// increased in post_visit, start from 1.
    series_number: usize,
}

/// Record item that used when traversing a expression tree.
enum VisitRecord {
    /// `usize` is the monotone increasing series number assigned in pre_visit().
    /// Starts from 0. Is used to index the identifier array `id_array` in post_visit().
    EnterMark(usize),
    /// Accumulated identifier of sub expression.
    ExprItem(Identifier),
}

impl ExprIdentifierVisitor<'_> {
    fn desc_expr(expr: &Expr) -> String {
        let mut desc = String::new();
        match expr {
            Expr::Column(column) => {
                desc.push_str("Column-");
                desc.push_str(&column.flat_name());
            }
            Expr::ScalarVariable(var_names) => {
                desc.push_str("ScalarVariable-");
                desc.push_str(&var_names.join("."));
            }
            Expr::Alias(_, alias) => {
                desc.push_str("Alias-");
                desc.push_str(alias);
            }
            Expr::Literal(value) => {
                desc.push_str("Literal");
                desc.push_str(&value.to_string());
            }
            Expr::BinaryExpr { op, .. } => {
                desc.push_str("BinaryExpr-");
                desc.push_str(&op.to_string());
            }
            Expr::Not(_) => {
                desc.push_str("Not-");
            }
            Expr::IsNotNull(_) => {
                desc.push_str("IsNotNull-");
            }
            Expr::IsNull(_) => {
                desc.push_str("IsNull-");
            }
            Expr::Negative(_) => {
                desc.push_str("Negative-");
            }
            Expr::Between { negated, .. } => {
                desc.push_str("Between-");
                desc.push_str(&negated.to_string());
            }
            Expr::Case { .. } => {
                desc.push_str("Case-");
            }
            Expr::Cast { data_type, .. } => {
                desc.push_str("Cast-");
                desc.push_str(&format!("{:?}", data_type));
            }
            Expr::TryCast { data_type, .. } => {
                desc.push_str("TryCast-");
                desc.push_str(&format!("{:?}", data_type));
            }
            Expr::Sort {
                asc, nulls_first, ..
            } => {
                desc.push_str("Sort-");
                desc.push_str(&format!("{}{}", asc, nulls_first));
            }
            Expr::ScalarFunction { fun, .. } => {
                desc.push_str("ScalarFunction-");
                desc.push_str(&fun.to_string());
            }
            Expr::ScalarUDF { fun, .. } => {
                desc.push_str("ScalarUDF-");
                desc.push_str(&fun.name);
            }
            Expr::WindowFunction {
                fun, window_frame, ..
            } => {
                desc.push_str("WindowFunction-");
                desc.push_str(&fun.to_string());
                desc.push_str(&format!("{:?}", window_frame));
            }
            Expr::AggregateFunction { fun, distinct, .. } => {
                desc.push_str("AggregateFunction-");
                desc.push_str(&fun.to_string());
                desc.push_str(&distinct.to_string());
            }
            Expr::AggregateUDF { fun, .. } => {
                desc.push_str("AggregateUDF-");
                desc.push_str(&fun.name);
            }
            Expr::InList { negated, .. } => {
                desc.push_str("InList-");
                desc.push_str(&negated.to_string());
            }
            Expr::Wildcard => {
                desc.push_str("Wildcard-");
            }
            Expr::GetIndexedField { key, .. } => {
                desc.push_str("GetIndexedField-");
                desc.push_str(&key.to_string());
            }
        }

        desc
    }

    /// Find the first `EnterMark` in the stack, and accumulates every `ExprItem`
    /// before it.
    fn pop_enter_mark(&mut self) -> (usize, Identifier) {
        let mut desc = String::new();

        while let Some(item) = self.visit_stack.pop() {
            match item {
                VisitRecord::EnterMark(idx) => {
                    return (idx, desc);
                }
                VisitRecord::ExprItem(s) => {
                    desc.push_str(&s);
                }
            }
        }

        unreachable!("Enter mark should paired with node number");
    }
}

impl ExpressionVisitor for ExprIdentifierVisitor<'_> {
    fn pre_visit(mut self, _expr: &Expr) -> Result<Recursion<Self>> {
        self.visit_stack
            .push(VisitRecord::EnterMark(self.node_count));
        self.node_count += 1;
        // put placeholder
        self.id_array.push((0, "".to_string()));
        Ok(Recursion::Continue(self))
    }

    fn post_visit(mut self, expr: &Expr) -> Result<Self> {
        self.series_number += 1;

        let (idx, sub_expr_desc) = self.pop_enter_mark();
        // skip exprs should not be recognize.
        if matches!(
            expr,
            Expr::Literal(..)
                | Expr::Column(..)
                | Expr::ScalarVariable(..)
                | Expr::Alias(..)
                | Expr::Sort { .. }
                | Expr::Wildcard
        ) {
            self.id_array[idx].0 = self.series_number;
            let desc = Self::desc_expr(expr);
            self.visit_stack.push(VisitRecord::ExprItem(desc));
            return Ok(self);
        }
        let mut desc = Self::desc_expr(expr);
        desc.push_str(&sub_expr_desc);

        self.id_array[idx] = (self.series_number, desc.clone());
        self.visit_stack.push(VisitRecord::ExprItem(desc.clone()));
        let data_type = self.data_type.clone();
        self.expr_set
            .entry(desc)
            .or_insert_with(|| (expr.clone(), 0, data_type))
            .1 += 1;
        Ok(self)
    }
}

/// Go through an expression tree and generate identifier for every node in this tree.
fn expr_to_identifier(
    expr: &Expr,
    expr_set: &mut ExprSet,
    id_array: &mut Vec<(usize, Identifier)>,
    data_type: DataType,
) -> Result<()> {
    expr.accept(ExprIdentifierVisitor {
        expr_set,
        id_array,
        data_type,
        visit_stack: vec![],
        node_count: 0,
        series_number: 0,
    })?;

    Ok(())
}

/// Rewrite expression by replacing detected common sub-expression with
/// the corresponding temporary column name. That column contains the
/// evaluate result of replaced expression.
struct CommonSubexprRewriter<'a> {
    expr_set: &'a mut ExprSet,
    id_array: &'a [(usize, Identifier)],
    /// Which identifier is replaced.
    affected_id: &'a mut HashSet<Identifier>,
    schema: &'a DFSchema,

    /// the max series number we have rewritten. Other expression nodes
    /// with smaller series number is already replaced and shouldn't
    /// do anything with them.
    max_series_number: usize,
    /// current node's information's index in `id_array`.
    curr_index: usize,
}

impl ExprRewriter for CommonSubexprRewriter<'_> {
    fn pre_visit(&mut self, _: &Expr) -> Result<RewriteRecursion> {
        if self.curr_index >= self.id_array.len()
            || self.max_series_number > self.id_array[self.curr_index].0
        {
            return Ok(RewriteRecursion::Stop);
        }

        let curr_id = &self.id_array[self.curr_index].1;
        // skip `Expr`s without identifier (empty identifier).
        if curr_id.is_empty() {
            self.curr_index += 1;
            return Ok(RewriteRecursion::Skip);
        }
        let (_, counter, _) = self.expr_set.get(curr_id).unwrap();
        if *counter > 1 {
            self.affected_id.insert(curr_id.clone());
            Ok(RewriteRecursion::Mutate)
        } else {
            self.curr_index += 1;
            Ok(RewriteRecursion::Skip)
        }
    }

    fn mutate(&mut self, expr: Expr) -> Result<Expr> {
        // This expr tree is finished.
        if self.curr_index >= self.id_array.len() {
            return Ok(expr);
        }

        let (series_number, id) = &self.id_array[self.curr_index];
        self.curr_index += 1;
        // Skip sub-node of a replaced tree, or without identifier, or is not repeated expr.
        if *series_number < self.max_series_number
            || id.is_empty()
            || self.expr_set.get(id).unwrap().1 <= 1
        {
            return Ok(expr);
        }

        self.max_series_number = *series_number;
        // step index to skip all sub-node (which has smaller series number).
        while self.curr_index < self.id_array.len()
            && *series_number > self.id_array[self.curr_index].0
        {
            self.curr_index += 1;
        }

        let expr_name = expr.name(self.schema)?;
        // Alias this `Column` expr to it original "expr name",
        // `projection_push_down` optimizer use "expr name" to eliminate useless
        // projections.
        Ok(col(id).alias(&expr_name))
    }
}

fn replace_common_expr(
    expr: Expr,
    id_array: &[(usize, Identifier)],
    expr_set: &mut ExprSet,
    affected_id: &mut HashSet<Identifier>,
    schema: &DFSchema,
) -> Result<Expr> {
    expr.rewrite(&mut CommonSubexprRewriter {
        expr_set,
        id_array,
        affected_id,
        schema,
        max_series_number: 0,
        curr_index: 0,
    })
}

#[cfg(test)]
mod test {
    use super::*;
    use crate::logical_plan::{
        avg, binary_expr, col, lit, sum, LogicalPlanBuilder, Operator,
    };
    use crate::test::*;
    use std::iter;

    fn assert_optimized_plan_eq(plan: &LogicalPlan, expected: &str) {
        let optimizer = CommonSubexprEliminate {};
        let optimized_plan = optimizer
            .optimize(plan, &ExecutionProps::new())
            .expect("failed to optimize plan");
        let formatted_plan = format!("{:?}", optimized_plan);
        assert_eq!(formatted_plan, expected);
    }

    #[test]
    fn id_array_visitor() -> Result<()> {
        let expr = binary_expr(
            binary_expr(
                sum(binary_expr(col("a"), Operator::Plus, lit("1"))),
                Operator::Minus,
                avg(col("c")),
            ),
            Operator::Multiply,
            lit(2),
        );

        let mut id_array = vec![];
        expr_to_identifier(&expr, &mut HashMap::new(), &mut id_array, DataType::Int64)?;

        let expected = vec![
            (9, "BinaryExpr-*Literal2BinaryExpr--AggregateFunction-AVGfalseColumn-cAggregateFunction-SUMfalseBinaryExpr-+Literal1Column-a"),
            (7, "BinaryExpr--AggregateFunction-AVGfalseColumn-cAggregateFunction-SUMfalseBinaryExpr-+Literal1Column-a"),
            (4, "AggregateFunction-SUMfalseBinaryExpr-+Literal1Column-a"), (3, "BinaryExpr-+Literal1Column-a"),
            (1, ""),
            (2, ""),
            (6, "AggregateFunction-AVGfalseColumn-c"),
            (5, ""),
            (8, ""),
        ]
        .into_iter()
        .map(|(number, id)| (number, id.into()))
        .collect::<Vec<_>>();
        assert_eq!(id_array, expected);

        Ok(())
    }

    #[test]
    fn tpch_q1_simplified() -> Result<()> {
        // SQL:
        //  select
        //      sum(a * (1 - b)),
        //      sum(a * (1 - b) * (1 + c))
        //  from T;
        //
        // The manual assembled logical plan don't contains the outermost `Projection`.

        let table_scan = test_table_scan()?;

        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(
                iter::empty::<Expr>(),
                vec![
                    sum(binary_expr(
                        col("a"),
                        Operator::Multiply,
                        binary_expr(lit(1), Operator::Minus, col("b")),
                    )),
                    sum(binary_expr(
                        binary_expr(
                            col("a"),
                            Operator::Multiply,
                            binary_expr(lit(1), Operator::Minus, col("b")),
                        ),
                        Operator::Multiply,
                        binary_expr(lit(1), Operator::Plus, col("c")),
                    )),
                ],
            )?
            .build()?;

        let expected = "Aggregate: groupBy=[[]], aggr=[[SUM(#BinaryExpr-*BinaryExpr--Column-test.bLiteral1Column-test.a AS test.a * Int32(1) - test.b), SUM(#BinaryExpr-*BinaryExpr--Column-test.bLiteral1Column-test.a AS test.a * Int32(1) - test.b * Int32(1) + #test.c)]]\
        \n  Projection: #test.a * Int32(1) - #test.b AS BinaryExpr-*BinaryExpr--Column-test.bLiteral1Column-test.a, #test.a, #test.b, #test.c\
        \n    TableScan: test projection=None";

        assert_optimized_plan_eq(&plan, expected);

        Ok(())
    }

    #[test]
    fn aggregate() -> Result<()> {
        let table_scan = test_table_scan()?;

        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(
                iter::empty::<Expr>(),
                vec![
                    binary_expr(lit(1), Operator::Plus, avg(col("a"))),
                    binary_expr(lit(1), Operator::Minus, avg(col("a"))),
                ],
            )?
            .build()?;

        let expected = "Aggregate: groupBy=[[]], aggr=[[Int32(1) + #AggregateFunction-AVGfalseColumn-test.a AS AVG(test.a), Int32(1) - #AggregateFunction-AVGfalseColumn-test.a AS AVG(test.a)]]\
        \n  Projection: AVG(#test.a) AS AggregateFunction-AVGfalseColumn-test.a, #test.a, #test.b, #test.c\
        \n    TableScan: test projection=None";

        assert_optimized_plan_eq(&plan, expected);

        Ok(())
    }

    #[test]
    fn subexpr_in_same_order() -> Result<()> {
        let table_scan = test_table_scan()?;

        let plan = LogicalPlanBuilder::from(table_scan)
            .project(vec![
                binary_expr(lit(1), Operator::Plus, col("a")).alias("first"),
                binary_expr(lit(1), Operator::Plus, col("a")).alias("second"),
            ])?
            .build()?;

        let expected = "Projection: #BinaryExpr-+Column-test.aLiteral1 AS Int32(1) + test.a AS first, #BinaryExpr-+Column-test.aLiteral1 AS Int32(1) + test.a AS second\
        \n  Projection: Int32(1) + #test.a AS BinaryExpr-+Column-test.aLiteral1, #test.a, #test.b, #test.c\
        \n    TableScan: test projection=None";

        assert_optimized_plan_eq(&plan, expected);

        Ok(())
    }

    #[test]
    fn subexpr_in_different_order() -> Result<()> {
        let table_scan = test_table_scan()?;

        let plan = LogicalPlanBuilder::from(table_scan)
            .project(vec![
                binary_expr(lit(1), Operator::Plus, col("a")),
                binary_expr(col("a"), Operator::Plus, lit(1)),
            ])?
            .build()?;

        let expected = "Projection: Int32(1) + #test.a, #test.a + Int32(1)\
        \n  TableScan: test projection=None";

        assert_optimized_plan_eq(&plan, expected);

        Ok(())
    }

    #[test]
    fn cross_plans_subexpr() -> Result<()> {
        let table_scan = test_table_scan()?;

        let plan = LogicalPlanBuilder::from(table_scan)
            .project(vec![binary_expr(lit(1), Operator::Plus, col("a"))])?
            .project(vec![binary_expr(lit(1), Operator::Plus, col("a"))])?
            .build()?;

        let expected = "Projection: #Int32(1) + test.a\
        \n  Projection: Int32(1) + #test.a\
        \n    TableScan: test projection=None";

        assert_optimized_plan_eq(&plan, expected);

        Ok(())
    }
}