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//
//   http://www.apache.org/licenses/LICENSE-2.0
//
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//! [`EliminateLimit`] eliminates `LIMIT` when possible
use crate::optimizer::ApplyOrder;
use crate::{OptimizerConfig, OptimizerRule};
use datafusion_common::tree_node::Transformed;
use datafusion_common::Result;
use datafusion_expr::logical_plan::{tree_node::unwrap_arc, EmptyRelation, LogicalPlan};
use std::sync::Arc;

/// Optimizer rule to replace `LIMIT 0` or `LIMIT` whose ancestor LIMIT's skip is
/// greater than or equal to current's fetch
///
/// It can cooperate with `propagate_empty_relation` and `limit_push_down`. on a
/// plan with an empty relation.
///
/// This rule also removes OFFSET 0 from the [LogicalPlan]
#[derive(Default)]
pub struct EliminateLimit;

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

impl OptimizerRule for EliminateLimit {
    fn name(&self) -> &str {
        "eliminate_limit"
    }

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

    fn supports_rewrite(&self) -> bool {
        true
    }

    fn rewrite(
        &self,
        plan: LogicalPlan,
        _config: &dyn OptimizerConfig,
    ) -> Result<
        datafusion_common::tree_node::Transformed<LogicalPlan>,
        datafusion_common::DataFusionError,
    > {
        match plan {
            LogicalPlan::Limit(limit) => {
                if let Some(fetch) = limit.fetch {
                    if fetch == 0 {
                        return Ok(Transformed::yes(LogicalPlan::EmptyRelation(
                            EmptyRelation {
                                produce_one_row: false,
                                schema: Arc::clone(limit.input.schema()),
                            },
                        )));
                    }
                } else if limit.skip == 0 {
                    // input also can be Limit, so we should apply again.
                    return Ok(self.rewrite(unwrap_arc(limit.input), _config).unwrap());
                }
                Ok(Transformed::no(LogicalPlan::Limit(limit)))
            }
            _ => Ok(Transformed::no(plan)),
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::optimizer::Optimizer;
    use crate::test::*;
    use crate::OptimizerContext;
    use datafusion_common::Column;
    use datafusion_expr::{
        col,
        logical_plan::{builder::LogicalPlanBuilder, JoinType},
    };
    use std::sync::Arc;

    use crate::push_down_limit::PushDownLimit;
    use datafusion_expr::test::function_stub::sum;

    fn observe(_plan: &LogicalPlan, _rule: &dyn OptimizerRule) {}
    fn assert_optimized_plan_eq(plan: LogicalPlan, expected: &str) -> Result<()> {
        let optimizer = Optimizer::with_rules(vec![Arc::new(EliminateLimit::new())]);
        let optimized_plan =
            optimizer.optimize(plan, &OptimizerContext::new(), observe)?;

        let formatted_plan = format!("{optimized_plan}");
        assert_eq!(formatted_plan, expected);
        Ok(())
    }

    fn assert_optimized_plan_eq_with_pushdown(
        plan: LogicalPlan,
        expected: &str,
    ) -> Result<()> {
        fn observe(_plan: &LogicalPlan, _rule: &dyn OptimizerRule) {}
        let config = OptimizerContext::new().with_max_passes(1);
        let optimizer = Optimizer::with_rules(vec![
            Arc::new(PushDownLimit::new()),
            Arc::new(EliminateLimit::new()),
        ]);
        let optimized_plan = optimizer
            .optimize(plan, &config, observe)
            .expect("failed to optimize plan");
        let formatted_plan = format!("{optimized_plan}");
        assert_eq!(formatted_plan, expected);
        Ok(())
    }

    #[test]
    fn limit_0_root() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, Some(0))?
            .build()?;
        // No aggregate / scan / limit
        let expected = "EmptyRelation";
        assert_optimized_plan_eq(plan, expected)
    }

    #[test]
    fn limit_0_nested() -> Result<()> {
        let table_scan = test_table_scan()?;
        let plan1 = LogicalPlanBuilder::from(table_scan.clone())
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .build()?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, Some(0))?
            .union(plan1)?
            .build()?;

        // Left side is removed
        let expected = "Union\
            \n  EmptyRelation\
            \n  Aggregate: groupBy=[[test.a]], aggr=[[sum(test.b)]]\
            \n    TableScan: test";
        assert_optimized_plan_eq(plan, expected)
    }

    #[test]
    fn limit_fetch_with_ancestor_limit_skip() -> Result<()> {
        let table_scan = test_table_scan()?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, Some(2))?
            .limit(2, None)?
            .build()?;

        // No aggregate / scan / limit
        let expected = "EmptyRelation";
        assert_optimized_plan_eq_with_pushdown(plan, expected)
    }

    #[test]
    fn multi_limit_offset_sort_eliminate() -> Result<()> {
        let table_scan = test_table_scan()?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, Some(2))?
            .sort(vec![col("a")])?
            .limit(2, Some(1))?
            .build()?;

        // After remove global-state, we don't record the parent <skip, fetch>
        // So, bottom don't know parent info, so can't eliminate.
        let expected = "Limit: skip=2, fetch=1\
        \n  Sort: test.a, fetch=3\
        \n    Limit: skip=0, fetch=2\
        \n      Aggregate: groupBy=[[test.a]], aggr=[[sum(test.b)]]\
        \n        TableScan: test";
        assert_optimized_plan_eq_with_pushdown(plan, expected)
    }

    #[test]
    fn limit_fetch_with_ancestor_limit_fetch() -> Result<()> {
        let table_scan = test_table_scan()?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, Some(2))?
            .sort(vec![col("a")])?
            .limit(0, Some(1))?
            .build()?;

        let expected = "Limit: skip=0, fetch=1\
            \n  Sort: test.a\
            \n    Limit: skip=0, fetch=2\
            \n      Aggregate: groupBy=[[test.a]], aggr=[[sum(test.b)]]\
            \n        TableScan: test";
        assert_optimized_plan_eq(plan, expected)
    }

    #[test]
    fn limit_with_ancestor_limit() -> Result<()> {
        let table_scan = test_table_scan().unwrap();
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(2, Some(1))?
            .sort(vec![col("a")])?
            .limit(3, Some(1))?
            .build()?;

        let expected = "Limit: skip=3, fetch=1\
        \n  Sort: test.a\
        \n    Limit: skip=2, fetch=1\
        \n      Aggregate: groupBy=[[test.a]], aggr=[[sum(test.b)]]\
        \n        TableScan: test";
        assert_optimized_plan_eq(plan, expected)
    }

    #[test]
    fn limit_join_with_ancestor_limit() -> Result<()> {
        let table_scan = test_table_scan()?;
        let table_scan_inner = test_table_scan_with_name("test1")?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .limit(2, Some(1))?
            .join_using(
                table_scan_inner,
                JoinType::Inner,
                vec![Column::from_name("a".to_string())],
            )?
            .limit(3, Some(1))?
            .build()?;

        let expected = "Limit: skip=3, fetch=1\
            \n  Inner Join: Using test.a = test1.a\
            \n    Limit: skip=2, fetch=1\
            \n      TableScan: test\
            \n    TableScan: test1";
        assert_optimized_plan_eq(plan, expected)
    }

    #[test]
    fn remove_zero_offset() -> Result<()> {
        let table_scan = test_table_scan()?;
        let plan = LogicalPlanBuilder::from(table_scan)
            .aggregate(vec![col("a")], vec![sum(col("b"))])?
            .limit(0, None)?
            .build()?;

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