datafusion_optimizer/

replace_distinct_aggregate.rs

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// to you under the Apache License, Version 2.0 (the
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//
//   http://www.apache.org/licenses/LICENSE-2.0
//
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//! [`ReplaceDistinctWithAggregate`] replaces `DISTINCT ...` with `GROUP BY ...`

use crate::optimizer::{ApplyOrder, ApplyOrder::BottomUp};
use crate::{OptimizerConfig, OptimizerRule};
use std::sync::Arc;

use datafusion_common::tree_node::Transformed;
use datafusion_common::{Column, Result};
use datafusion_expr::expr_rewriter::normalize_cols;
use datafusion_expr::utils::expand_wildcard;
use datafusion_expr::{col, ExprFunctionExt, LogicalPlanBuilder};
use datafusion_expr::{Aggregate, Distinct, DistinctOn, Expr, LogicalPlan};

/// Optimizer that replaces logical [[Distinct]] with a logical [[Aggregate]]
///
/// ```text
/// SELECT DISTINCT a, b FROM tab
/// ```
///
/// Into
/// ```text
/// SELECT a, b FROM tab GROUP BY a, b
/// ```
///
/// On the other hand, for a `DISTINCT ON` query the replacement is
/// a bit more involved and effectively converts
/// ```text
/// SELECT DISTINCT ON (a) b FROM tab ORDER BY a DESC, c
/// ```
///
/// into
/// ```text
/// SELECT b FROM (
///     SELECT a, FIRST_VALUE(b ORDER BY a DESC, c) AS b
///     FROM tab
///     GROUP BY a
/// )
/// ORDER BY a DESC
/// ```

/// Optimizer that replaces logical [[Distinct]] with a logical [[Aggregate]]
#[derive(Default, Debug)]
pub struct ReplaceDistinctWithAggregate {}

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

impl OptimizerRule for ReplaceDistinctWithAggregate {
    fn supports_rewrite(&self) -> bool {
        true
    }

    fn rewrite(
        &self,
        plan: LogicalPlan,
        config: &dyn OptimizerConfig,
    ) -> Result<Transformed<LogicalPlan>> {
        match plan {
            LogicalPlan::Distinct(Distinct::All(input)) => {
                let group_expr = expand_wildcard(input.schema(), &input, None)?;

                let field_count = input.schema().fields().len();
                for dep in input.schema().functional_dependencies().iter() {
                    // If distinct is exactly the same with a previous GROUP BY, we can
                    // simply remove it:
                    if dep.source_indices.len() >= field_count
                        && dep.source_indices[..field_count]
                            .iter()
                            .enumerate()
                            .all(|(idx, f_idx)| idx == *f_idx)
                    {
                        return Ok(Transformed::yes(input.as_ref().clone()));
                    }
                }

                // Replace with aggregation:
                let aggr_plan = LogicalPlan::Aggregate(Aggregate::try_new(
                    input,
                    group_expr,
                    vec![],
                )?);
                Ok(Transformed::yes(aggr_plan))
            }
            LogicalPlan::Distinct(Distinct::On(DistinctOn {
                select_expr,
                on_expr,
                sort_expr,
                input,
                schema,
            })) => {
                let expr_cnt = on_expr.len();

                // Construct the aggregation expression to be used to fetch the selected expressions.
                let first_value_udaf: Arc<datafusion_expr::AggregateUDF> =
                    config.function_registry().unwrap().udaf("first_value")?;
                let aggr_expr = select_expr.into_iter().map(|e| {
                    if let Some(order_by) = &sort_expr {
                        first_value_udaf
                            .call(vec![e])
                            .order_by(order_by.clone())
                            .build()
                            // guaranteed to be `Expr::AggregateFunction`
                            .unwrap()
                    } else {
                        first_value_udaf.call(vec![e])
                    }
                });

                let aggr_expr = normalize_cols(aggr_expr, input.as_ref())?;
                let group_expr = normalize_cols(on_expr, input.as_ref())?;

                // Build the aggregation plan
                let plan = LogicalPlan::Aggregate(Aggregate::try_new(
                    input, group_expr, aggr_expr,
                )?);
                // TODO use LogicalPlanBuilder directly rather than recreating the Aggregate
                // when https://github.com/apache/datafusion/issues/10485 is available
                let lpb = LogicalPlanBuilder::from(plan);

                let plan = if let Some(mut sort_expr) = sort_expr {
                    // While sort expressions were used in the `FIRST_VALUE` aggregation itself above,
                    // this on it's own isn't enough to guarantee the proper output order of the grouping
                    // (`ON`) expression, so we need to sort those as well.

                    // truncate the sort_expr to the length of on_expr
                    sort_expr.truncate(expr_cnt);

                    lpb.sort(sort_expr)?.build()?
                } else {
                    lpb.build()?
                };

                // Whereas the aggregation plan by default outputs both the grouping and the aggregation
                // expressions, for `DISTINCT ON` we only need to emit the original selection expressions.

                let project_exprs = plan
                    .schema()
                    .iter()
                    .skip(expr_cnt)
                    .zip(schema.iter())
                    .map(|((new_qualifier, new_field), (old_qualifier, old_field))| {
                        col(Column::from((new_qualifier, new_field)))
                            .alias_qualified(old_qualifier.cloned(), old_field.name())
                    })
                    .collect::<Vec<Expr>>();

                let plan = LogicalPlanBuilder::from(plan)
                    .project(project_exprs)?
                    .build()?;

                Ok(Transformed::yes(plan))
            }
            _ => Ok(Transformed::no(plan)),
        }
    }

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

    fn apply_order(&self) -> Option<ApplyOrder> {
        Some(BottomUp)
    }
}

#[cfg(test)]
mod tests {
    use std::sync::Arc;

    use crate::replace_distinct_aggregate::ReplaceDistinctWithAggregate;
    use crate::test::*;

    use datafusion_common::Result;
    use datafusion_expr::{
        col, logical_plan::builder::LogicalPlanBuilder, Expr, LogicalPlan,
    };
    use datafusion_functions_aggregate::sum::sum;

    fn assert_optimized_plan_equal(plan: &LogicalPlan, expected: &str) -> Result<()> {
        assert_optimized_plan_eq(
            Arc::new(ReplaceDistinctWithAggregate::new()),
            plan.clone(),
            expected,
        )
    }

    #[test]
    fn eliminate_redundant_distinct_simple() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("c")], Vec::<Expr>::new())?
            .project(vec![col("c")])?
            .distinct()?
            .build()?;

        let expected = "Projection: test.c\n  Aggregate: groupBy=[[test.c]], aggr=[[]]\n    TableScan: test";
        assert_optimized_plan_equal(&plan, expected)
    }

    #[test]
    fn eliminate_redundant_distinct_pair() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a"), col("b")], Vec::<Expr>::new())?
            .project(vec![col("a"), col("b")])?
            .distinct()?
            .build()?;

        let expected =
            "Projection: test.a, test.b\n  Aggregate: groupBy=[[test.a, test.b]], aggr=[[]]\n    TableScan: test";
        assert_optimized_plan_equal(&plan, expected)
    }

    #[test]
    fn do_not_eliminate_distinct() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .project(vec![col("a"), col("b")])?
            .distinct()?
            .build()?;

        let expected = "Aggregate: groupBy=[[test.a, test.b]], aggr=[[]]\n  Projection: test.a, test.b\n    TableScan: test";
        assert_optimized_plan_equal(&plan, expected)
    }

    #[test]
    fn do_not_eliminate_distinct_with_aggr() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a"), col("b"), col("c")], vec![sum(col("c"))])?
            .project(vec![col("a"), col("b")])?
            .distinct()?
            .build()?;

        let expected =
            "Aggregate: groupBy=[[test.a, test.b]], aggr=[[]]\n  Projection: test.a, test.b\n    Aggregate: groupBy=[[test.a, test.b, test.c]], aggr=[[sum(test.c)]]\n      TableScan: test";
        assert_optimized_plan_equal(&plan, expected)
    }
}