Add approx_median() aggregate function

README.md

@@ -328,7 +328,7 @@ This library currently supports many SQL constructs, including
 - `CAST` to change types, including e.g. `Timestamp(Nanosecond, None)`
 - Many mathematical unary and binary expressions such as `+`, `/`, `sqrt`, `tan`, `>=`.
 - `WHERE` to filter
-- `GROUP BY` together with one of the following aggregations: `MIN`, `MAX`, `COUNT`, `SUM`, `AVG`, `CORR`, `VAR`, `COVAR`, `STDDEV` (sample and population)
+- `GROUP BY` together with one of the following aggregations: `MIN`, `MAX`, `COUNT`, `SUM`, `AVG`, `APPROX_PERCENTILE_CONT`, `APPROX_MEDIAN`, `CORR`, `VAR`, `COVAR`, `STDDEV` (sample and population)
 - `ORDER BY` together with an expression and optional `ASC` or `DESC` and also optional `NULLS FIRST` or `NULLS LAST`
 
 ## Supported Functions

ballista/rust/core/proto/ballista.proto

@@ -177,6 +177,7 @@ enum AggregateFunction {
   STDDEV_POP=12;
   CORRELATION=13;
   APPROX_PERCENTILE_CONT = 14;
+  APPROX_MEDIAN=15;
 }
 
 message AggregateExprNode {

ballista/rust/core/src/serde/logical_plan/to_proto.rs

@@ -1100,6 +1100,9 @@ impl TryInto<protobuf::LogicalExprNode> for &Expr {
                     AggregateFunction::Correlation => {
                         protobuf::AggregateFunction::Correlation
                     }
+                    AggregateFunction::ApproxMedian => {
+                        protobuf::AggregateFunction::ApproxMedian
+                    }
                 };
 
                 let aggregate_expr = protobuf::AggregateExprNode {
@@ -1340,6 +1343,7 @@ impl From<&AggregateFunction> for protobuf::AggregateFunction {
             AggregateFunction::StddevPop => Self::StddevPop,
             AggregateFunction::Correlation => Self::Correlation,
             AggregateFunction::ApproxPercentileCont => Self::ApproxPercentileCont,
+            AggregateFunction::ApproxMedian => Self::ApproxMedian,
         }
     }
 }

ballista/rust/core/src/serde/mod.rs

@@ -132,6 +132,7 @@ impl From<protobuf::AggregateFunction> for AggregateFunction {
             protobuf::AggregateFunction::ApproxPercentileCont => {
                 AggregateFunction::ApproxPercentileCont
             }
+            protobuf::AggregateFunction::ApproxMedian => AggregateFunction::ApproxMedian,
         }
     }
 }

datafusion/src/execution/context.rs

@@ -72,13 +72,15 @@ use crate::optimizer::limit_push_down::LimitPushDown;
 use crate::optimizer::optimizer::OptimizerRule;
 use crate::optimizer::projection_push_down::ProjectionPushDown;
 use crate::optimizer::simplify_expressions::SimplifyExpressions;
+use crate::optimizer::single_distinct_to_groupby::SingleDistinctToGroupBy;
+use crate::optimizer::to_approx_perc::ToApproxPerc;
+
 use crate::physical_optimizer::coalesce_batches::CoalesceBatches;
 use crate::physical_optimizer::merge_exec::AddCoalescePartitionsExec;
 use crate::physical_optimizer::repartition::Repartition;
 
 use crate::execution::runtime_env::{RuntimeConfig, RuntimeEnv};
 use crate::logical_plan::plan::Explain;
-use crate::optimizer::single_distinct_to_groupby::SingleDistinctToGroupBy;
 use crate::physical_plan::planner::DefaultPhysicalPlanner;
 use crate::physical_plan::udf::ScalarUDF;
 use crate::physical_plan::ExecutionPlan;
@@ -925,6 +927,7 @@ impl Default for ExecutionConfig {
                 Arc::new(CommonSubexprEliminate::new()),
                 Arc::new(EliminateLimit::new()),
                 Arc::new(ProjectionPushDown::new()),
+                Arc::new(ToApproxPerc::new()),
                 Arc::new(FilterPushDown::new()),
                 Arc::new(LimitPushDown::new()),
                 Arc::new(SingleDistinctToGroupBy::new()),

datafusion/src/optimizer/mod.rs

@@ -27,4 +27,5 @@ pub mod optimizer;
 pub mod projection_push_down;
 pub mod simplify_expressions;
 pub mod single_distinct_to_groupby;
+pub mod to_approx_perc;
 pub mod utils;

datafusion/src/optimizer/to_approx_perc.rs

@@ -0,0 +1,161 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! espression/function to approx_percentile optimizer rule
+
+use crate::error::Result;
+use crate::execution::context::ExecutionProps;
+use crate::logical_plan::plan::Aggregate;
+use crate::logical_plan::{Expr, LogicalPlan};
+use crate::optimizer::optimizer::OptimizerRule;
+use crate::optimizer::utils;
+use crate::physical_plan::aggregates;
+use crate::scalar::ScalarValue;
+
+/// espression/function to approx_percentile optimizer rule
+///  ```text
+///    SELECT F1(s)
+///    ...
+///
+///    Into
+///
+///    SELECT APPROX_PERCENTILE_CONT(s, lit(n)) as "F1(s)"
+///    ...
+///  ```
+pub struct ToApproxPerc {}
+
+impl ToApproxPerc {
+    #[allow(missing_docs)]
+    pub fn new() -> Self {
+        Self {}
+    }
+}
+
+impl Default for ToApproxPerc {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+fn optimize(plan: &LogicalPlan) -> Result<LogicalPlan> {
+    match plan {
+        LogicalPlan::Aggregate(Aggregate {
+            input,
+            aggr_expr,
+            schema,
+            group_expr,
+        }) => {
+            let new_aggr_expr = aggr_expr
+                .iter()
+                .map(|agg_expr| replace_with_percentile(agg_expr).unwrap())
+                .collect::<Vec<_>>();
+
+            Ok(LogicalPlan::Aggregate(Aggregate {
+                input: input.clone(),
+                aggr_expr: new_aggr_expr,
+                schema: schema.clone(),
+                group_expr: group_expr.clone(),
+            }))
+        }
+        _ => optimize_children(plan),
+    }
+}
+
+fn optimize_children(plan: &LogicalPlan) -> Result<LogicalPlan> {
+    let expr = plan.expressions();
+    let inputs = plan.inputs();
+    let new_inputs = inputs
+        .iter()
+        .map(|plan| optimize(plan))
+        .collect::<Result<Vec<_>>>()?;
+    utils::from_plan(plan, &expr, &new_inputs)
+}
+
+fn replace_with_percentile(expr: &Expr) -> Result<Expr> {
+    match expr {
+        Expr::AggregateFunction {
+            fun,
+            args,
+            distinct,
+        } => {
+            let mut new_args = args.clone();
+            let mut new_func = fun.clone();
+            if fun == &aggregates::AggregateFunction::ApproxMedian {
+                new_args.push(Expr::Literal(ScalarValue::Float64(Some(0.5_f64))));
+                new_func = aggregates::AggregateFunction::ApproxPercentileCont;
+            }
+
+            Ok(Expr::AggregateFunction {
+                fun: new_func,
+                args: new_args,
+                distinct: *distinct,
+            })
+        }
+        _ => Ok(expr.clone()),
+    }
+}
+
+impl OptimizerRule for ToApproxPerc {
+    fn optimize(
+        &self,
+        plan: &LogicalPlan,
+        _execution_props: &ExecutionProps,
+    ) -> Result<LogicalPlan> {
+        optimize(plan)
+    }
+    fn name(&self) -> &str {
+        "ToApproxPerc"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::logical_plan::{col, LogicalPlanBuilder};
+    use crate::physical_plan::aggregates;
+    use crate::test::*;
+
+    fn assert_optimized_plan_eq(plan: &LogicalPlan, expected: &str) {
+        let rule = ToApproxPerc::new();
+        let optimized_plan = rule
+            .optimize(plan, &ExecutionProps::new())
+            .expect("failed to optimize plan");
+        let formatted_plan = format!("{}", optimized_plan.display_indent_schema());
+        assert_eq!(formatted_plan, expected);
+    }
+
+    #[test]
+    fn median_1() -> Result<()> {
+        let table_scan = test_table_scan()?;
+        let expr = Expr::AggregateFunction {
+            fun: aggregates::AggregateFunction::ApproxMedian,
+            distinct: false,
+            args: vec![col("b")],
+        };
+
+        let plan = LogicalPlanBuilder::from(table_scan)
+            .aggregate(Vec::<Expr>::new(), vec![expr])?
+            .build()?;
+
+        // Do nothing
+        let expected = "Aggregate: groupBy=[[]], aggr=[[APPROXPERCENTILECONT(#test.b, Float64(0.5))]] [APPROXMEDIAN(test.b):UInt32;N]\
+                            \n  TableScan: test projection=None [a:UInt32, b:UInt32, c:UInt32]";
+
+        assert_optimized_plan_eq(&plan, expected);
+        Ok(())
+    }
+}

datafusion/src/physical_plan/aggregates.rs

@@ -82,6 +82,8 @@ pub enum AggregateFunction {
     Correlation,
     /// Approximate continuous percentile function
     ApproxPercentileCont,
+    /// ApproxMedian
+    ApproxMedian,
 }
 
 impl fmt::Display for AggregateFunction {
@@ -113,6 +115,7 @@ impl FromStr for AggregateFunction {
             "covar_pop" => AggregateFunction::CovariancePop,
             "corr" => AggregateFunction::Correlation,
             "approx_percentile_cont" => AggregateFunction::ApproxPercentileCont,
+            "approx_median" => AggregateFunction::ApproxMedian,
             _ => {
                 return Err(DataFusionError::Plan(format!(
                     "There is no built-in function named {}",
@@ -161,6 +164,7 @@ pub fn return_type(
             true,
         )))),
         AggregateFunction::ApproxPercentileCont => Ok(coerced_data_types[0].clone()),
+        AggregateFunction::ApproxMedian => Ok(coerced_data_types[0].clone()),
     }
 }
 
@@ -349,6 +353,18 @@ pub fn create_aggregate_expr(
                     .to_string(),
             ));
         }
+        (AggregateFunction::ApproxMedian, false) => {
+            Arc::new(expressions::ApproxMedian::new(
+                coerced_phy_exprs[0].clone(),
+                name,
+                return_type,
+            ))
+        }
+        (AggregateFunction::ApproxMedian, true) => {
+            return Err(DataFusionError::NotImplemented(
+                "MEDIAN(DISTINCT) aggregations are not available".to_string(),
+            ));
+        }
     })
 }
 
@@ -398,7 +414,8 @@ pub(super) fn signature(fun: &AggregateFunction) -> Signature {
         | AggregateFunction::Variance
         | AggregateFunction::VariancePop
         | AggregateFunction::Stddev
-        | AggregateFunction::StddevPop => {
+        | AggregateFunction::StddevPop
+        | AggregateFunction::ApproxMedian => {
             Signature::uniform(1, NUMERICS.to_vec(), Volatility::Immutable)
         }
         AggregateFunction::Covariance | AggregateFunction::CovariancePop => {
@@ -422,8 +439,9 @@ pub(super) fn signature(fun: &AggregateFunction) -> Signature {
 mod tests {
     use super::*;
     use crate::physical_plan::expressions::{
-        ApproxDistinct, ApproxPercentileCont, ArrayAgg, Avg, Correlation, Count,
-        Covariance, DistinctArrayAgg, DistinctCount, Max, Min, Stddev, Sum, Variance,
+        ApproxDistinct, ApproxMedian, ApproxPercentileCont, ArrayAgg, Avg, Correlation,
+        Count, Covariance, DistinctArrayAgg, DistinctCount, Max, Min, Stddev, Sum,
+        Variance,
     };
     use crate::{error::Result, scalar::ScalarValue};
 
@@ -996,6 +1014,62 @@ mod tests {
         Ok(())
     }
 
+    #[test]
+    fn test_median_expr() -> Result<()> {
+        let funcs = vec![AggregateFunction::ApproxMedian];
+        let data_types = vec![
+            DataType::UInt32,
+            DataType::UInt64,
+            DataType::Int32,
+            DataType::Int64,
+            DataType::Float32,
+            DataType::Float64,
+        ];
+        for fun in funcs {
+            for data_type in &data_types {
+                let input_schema =
+                    Schema::new(vec![Field::new("c1", data_type.clone(), true)]);
+                let input_phy_exprs: Vec<Arc<dyn PhysicalExpr>> = vec![Arc::new(
+                    expressions::Column::new_with_schema("c1", &input_schema).unwrap(),
+                )];
+                let result_agg_phy_exprs = create_aggregate_expr(
+                    &fun,
+                    false,
+                    &input_phy_exprs[0..1],
+                    &input_schema,
+                    "c1",
+                )?;
+
+                if fun == AggregateFunction::ApproxMedian {
+                    assert!(result_agg_phy_exprs.as_any().is::<ApproxMedian>());
+                    assert_eq!("c1", result_agg_phy_exprs.name());
+                    assert_eq!(
+                        Field::new("c1", data_type.clone(), true),
+                        result_agg_phy_exprs.field().unwrap()
+                    );
+                }
+            }
+        }
+        Ok(())
+    }
+
+    #[test]
+    fn test_median() -> Result<()> {
+        let observed = return_type(&AggregateFunction::ApproxMedian, &[DataType::Utf8]);
+        assert!(observed.is_err());
+
+        let observed = return_type(&AggregateFunction::ApproxMedian, &[DataType::Int32])?;
+        assert_eq!(DataType::Int32, observed);
+
+        let observed = return_type(
+            &AggregateFunction::ApproxMedian,
+            &[DataType::Decimal(10, 6)],
+        );
+        assert!(observed.is_err());
+
+        Ok(())
+    }
+
     #[test]
     fn test_min_max() -> Result<()> {
         let observed = return_type(&AggregateFunction::Min, &[DataType::Utf8])?;

datafusion/src/physical_plan/coercion_rule/aggregate_rule.rs

@@ -20,9 +20,10 @@
 use crate::error::{DataFusionError, Result};
 use crate::physical_plan::aggregates::AggregateFunction;
 use crate::physical_plan::expressions::{
-    is_avg_support_arg_type, is_correlation_support_arg_type,
-    is_covariance_support_arg_type, is_stddev_support_arg_type, is_sum_support_arg_type,
-    is_variance_support_arg_type, try_cast,
+    is_approx_median_support_arg_type, is_avg_support_arg_type,
+    is_correlation_support_arg_type, is_covariance_support_arg_type,
+    is_stddev_support_arg_type, is_sum_support_arg_type, is_variance_support_arg_type,
+    try_cast,
 };
 use crate::physical_plan::functions::{Signature, TypeSignature};
 use crate::physical_plan::PhysicalExpr;
@@ -154,6 +155,15 @@ pub(crate) fn coerce_types(
             }
             Ok(input_types.to_vec())
         }
+        AggregateFunction::ApproxMedian => {
+            if !is_approx_median_support_arg_type(&input_types[0]) {
+                return Err(DataFusionError::Plan(format!(
+                    "The function {:?} does not support inputs of type {:?}.",
+                    agg_fun, input_types[0]
+                )));
+            }
+            Ok(input_types.to_vec())
+        }
     }
 }