feat: Support PERCENTILE_CONT planning

Author: MazterQyou

Cargo.lock

@@ -44,4 +44,4 @@ cranelift-module = { version = "0.82.0", optional = true }
 ordered-float = "2.10"
 parquet = { git = 'https://github.com/cube-js/arrow-rs.git', rev = "8fd2aa80114d5c0d4e6a0c370729507a4424e7b3", features = ["arrow"], optional = true }
 pyo3 = { version = "0.16", optional = true }
-sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "6a54d27d3b75a04b9f9cbe309a83078aa54b32fd" }
+sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "f1a97af2f22d9bfe057c77d5c9673038d8cf295b" }

datafusion-cli/Cargo.lock

@@ -79,7 +79,7 @@ pin-project-lite= "^0.2.7"
 pyo3 = { version = "0.16", optional = true }
 rand = "0.8"
 smallvec = { version = "1.6", features = ["union"] }
-sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "6a54d27d3b75a04b9f9cbe309a83078aa54b32fd" }
+sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "f1a97af2f22d9bfe057c77d5c9673038d8cf295b" }
 tempfile = "3"
 tokio = { version = "1.0", features = ["macros", "rt", "rt-multi-thread", "sync", "fs", "parking_lot"] }
 tokio-stream = "0.1"

datafusion/common/Cargo.toml

@@ -239,6 +239,14 @@ pub fn create_aggregate_expr(
                     .to_string(),
             ));
         }
+        (AggregateFunction::PercentileCont, _) => {
+            Arc::new(expressions::PercentileCont::new(
+                // Pass in the desired percentile expr
+                name,
+                coerced_phy_exprs,
+                return_type,
+            )?)
+        }
         (AggregateFunction::ApproxMedian, false) => {
             Arc::new(expressions::ApproxMedian::new(
                 coerced_phy_exprs[0].clone(),

datafusion/core/Cargo.toml

@@ -56,7 +56,7 @@ use datafusion_expr::expr::GroupingSet;
 use sqlparser::ast::{
     ArrayAgg, BinaryOperator, DataType as SQLDataType, DateTimeField, Expr as SQLExpr,
     Fetch, FunctionArg, FunctionArgExpr, Ident, Join, JoinConstraint, JoinOperator,
-    ObjectName, Offset as SQLOffset, Query, Select, SelectItem, SetExpr, SetOperator,
+    ObjectName, Offset as SQLOffset, PercentileCont, Query, Select, SelectItem, SetExpr, SetOperator,
     ShowStatementFilter, TableFactor, TableWithJoins, TrimWhereField, UnaryOperator,
     Value, Values as SQLValues,
 };
@@ -1440,22 +1440,22 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
 
         let order_by_rex = order_by
             .into_iter()
-            .map(|e| self.order_by_to_sort_expr(e, plan.schema()))
+            .map(|e| self.order_by_to_sort_expr(e, plan.schema(), true))
             .collect::<Result<Vec<_>>>()?;
 
         LogicalPlanBuilder::from(plan).sort(order_by_rex)?.build()
     }
 
     /// convert sql OrderByExpr to Expr::Sort
-    fn order_by_to_sort_expr(&self, e: OrderByExpr, schema: &DFSchema) -> Result<Expr> {
+    fn order_by_to_sort_expr(&self, e: OrderByExpr, schema: &DFSchema, parse_indexes: bool) -> Result<Expr> {
         let OrderByExpr {
             asc,
             expr,
             nulls_first,
         } = e;
 
         let expr = match expr {
-            SQLExpr::Value(Value::Number(v, _)) => {
+            SQLExpr::Value(Value::Number(v, _)) if parse_indexes => {
                 let field_index = v
                     .parse::<usize>()
                     .map_err(|err| DataFusionError::Plan(err.to_string()))?;
@@ -2313,7 +2313,7 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
                     let order_by = window
                         .order_by
                         .into_iter()
-                        .map(|e| self.order_by_to_sort_expr(e, schema))
+                        .map(|e| self.order_by_to_sort_expr(e, schema, true))
                         .collect::<Result<Vec<_>>>()?;
                     let window_frame = window
                         .window_frame
@@ -2441,6 +2441,8 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
 
             SQLExpr::ArrayAgg(array_agg) => self.parse_array_agg(array_agg, schema),
 
+            SQLExpr::PercentileCont(percentile_cont) => self.parse_percentile_cont(percentile_cont, schema),
+
             _ => Err(DataFusionError::NotImplemented(format!(
                 "Unsupported ast node {:?} in sqltorel",
                 sql
@@ -2494,6 +2496,36 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
         })
     }
 
+    fn parse_percentile_cont(
+        &self,
+        percentile_cont: PercentileCont,
+        input_schema: &DFSchema,
+    ) -> Result<Expr> {
+        let PercentileCont {
+            expr,
+            within_group,
+        } = percentile_cont;
+
+        // Some dialects have special syntax for percentile_cont. DataFusion only supports it like a function.
+        let expr = self.sql_expr_to_logical_expr(*expr, input_schema)?;
+        let (order_by_expr, asc, nulls_first) = match self.order_by_to_sort_expr(*within_group, input_schema, false)? {
+            Expr::Sort { expr, asc, nulls_first } => (expr, asc, nulls_first),
+            _ => return Err(DataFusionError::Internal("PercentileCont expected Sort expression in ORDER BY".to_string())),
+        };
+        let asc_expr = Expr::Literal(ScalarValue::Boolean(Some(asc)));
+        let nulls_first_expr = Expr::Literal(ScalarValue::Boolean(Some(nulls_first)));
+
+        let args = vec![expr, *order_by_expr, asc_expr, nulls_first_expr];
+        // next, aggregate built-ins
+        let fun = aggregates::AggregateFunction::PercentileCont;
+
+        Ok(Expr::AggregateFunction {
+            fun,
+            distinct: false,
+            args,
+        })
+    }
+
     fn function_args_to_expr(
         &self,
         args: Vec<FunctionArg>,
@@ -4133,6 +4165,15 @@ mod tests {
         quick_test(sql, expected);
     }
 
+    #[test]
+    fn select_percentile_cont() {
+        let sql = "SELECT percentile_cont(0.5) WITHIN GROUP (ORDER BY age) FROM person";
+        let expected = "Projection: #PERCENTILECONT(Float64(0.5),person.age,Boolean(true),Boolean(false))\
+                        \n  Aggregate: groupBy=[[]], aggr=[[PERCENTILECONT(Float64(0.5), #person.age, Boolean(true), Boolean(false))]]\
+                        \n    TableScan: person projection=None";
+        quick_test(sql, expected);
+    }
+
     #[test]
     fn select_scalar_func() {
         let sql = "SELECT sqrt(age) FROM person";

datafusion/core/src/physical_plan/aggregates.rs

@@ -38,4 +38,4 @@ path = "src/lib.rs"
 ahash = { version = "0.7", default-features = false }
 arrow = { git = 'https://github.com/cube-js/arrow-rs.git', rev = "8fd2aa80114d5c0d4e6a0c370729507a4424e7b3", features = ["prettyprint"] }
 datafusion-common = { path = "../common", version = "7.0.0" }
-sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "6a54d27d3b75a04b9f9cbe309a83078aa54b32fd" }
+sqlparser = { git = 'https://github.com/cube-js/sqlparser-rs.git', rev = "f1a97af2f22d9bfe057c77d5c9673038d8cf295b" }

datafusion/core/src/sql/planner.rs

@@ -84,6 +84,8 @@ pub enum AggregateFunction {
     ApproxPercentileCont,
     /// Approximate continuous percentile function with weight
     ApproxPercentileContWithWeight,
+    /// Continuous percentile function
+    PercentileCont,
     /// ApproxMedian
     ApproxMedian,
     /// BoolAnd
@@ -124,6 +126,7 @@ impl FromStr for AggregateFunction {
             "approx_percentile_cont_with_weight" => {
                 AggregateFunction::ApproxPercentileContWithWeight
             }
+            "percentile_cont" => AggregateFunction::PercentileCont,
             "approx_median" => AggregateFunction::ApproxMedian,
             "bool_and" => AggregateFunction::BoolAnd,
             "bool_or" => AggregateFunction::BoolOr,
@@ -178,6 +181,7 @@ pub fn return_type(
         AggregateFunction::ApproxPercentileContWithWeight => {
             Ok(coerced_data_types[0].clone())
         }
+        AggregateFunction::PercentileCont => Ok(coerced_data_types[1].clone()),
         AggregateFunction::ApproxMedian => Ok(coerced_data_types[0].clone()),
         AggregateFunction::BoolAnd | AggregateFunction::BoolOr => Ok(DataType::Boolean),
     }
@@ -324,6 +328,33 @@ pub fn coerce_types(
             }
             Ok(input_types.to_vec())
         }
+        AggregateFunction::PercentileCont => {
+            if !matches!(input_types[0], DataType::Float64) {
+                return Err(DataFusionError::Plan(format!(
+                    "The percentile argument for {:?} must be Float64, not {:?}.",
+                    agg_fun, input_types[0]
+                )));
+            }
+            if !is_approx_percentile_cont_supported_arg_type(&input_types[1]) {
+                return Err(DataFusionError::Plan(format!(
+                    "The function {:?} does not support inputs of type {:?}.",
+                    agg_fun, input_types[1]
+                )));
+            }
+            if !matches!(input_types[2], DataType::Boolean) {
+                return Err(DataFusionError::Plan(format!(
+                    "The asc argument for {:?} must be Boolean, not {:?}.",
+                    agg_fun, input_types[2]
+                )));
+            }
+            if !matches!(input_types[3], DataType::Boolean) {
+                return Err(DataFusionError::Plan(format!(
+                    "The nulls_first argument for {:?} must be Boolean, not {:?}.",
+                    agg_fun, input_types[3]
+                )));
+            }
+            Ok(input_types.to_vec())
+        }
         AggregateFunction::ApproxMedian => {
             if !is_approx_percentile_cont_supported_arg_type(&input_types[0]) {
                 return Err(DataFusionError::Plan(format!(
@@ -395,6 +426,14 @@ pub fn signature(fun: &AggregateFunction) -> Signature {
                 .collect(),
             Volatility::Immutable,
         ),
+        AggregateFunction::PercentileCont => Signature::one_of(
+            // Accept a float64 percentile paired with any numeric value, plus bool values
+            NUMERICS
+                .iter()
+                .map(|t| TypeSignature::Exact(vec![DataType::Float64, t.clone(), DataType::Boolean, DataType::Boolean]))
+                .collect(),
+            Volatility::Immutable,
+        ),
         AggregateFunction::BoolAnd | AggregateFunction::BoolOr => {
             Signature::exact(vec![DataType::Boolean], Volatility::Immutable)
         }

datafusion/expr/Cargo.toml

@@ -49,6 +49,7 @@ mod not;
 mod nth_value;
 mod nullif;
 mod outer_column;
+mod percentile_cont;
 mod rank;
 mod row_number;
 mod stats;
@@ -95,6 +96,7 @@ pub use not::{not, NotExpr};
 pub use nth_value::NthValue;
 pub use nullif::nullif_func;
 pub use outer_column::OuterColumn;
+pub use percentile_cont::PercentileCont;
 pub use rank::{dense_rank, percent_rank, rank};
 pub use row_number::RowNumber;
 pub use stats::StatsType;