Fix the schema mismatch between logical and physical for aggregate fu…

…nction, add `AggregateUDFImpl::is_null` (apache#11989) * schema assertion and fix the mismatch from logical and physical Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * add more msg Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * cleanup Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm test1 Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * nullable for scalar func Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * nullable Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm field Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm unsafe block and use internal error Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm func_name Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm nullable option Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * add test Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * add more msg Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * fix test Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * rm row number Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * Update datafusion/expr/src/udaf.rs Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org> * Update datafusion/expr/src/udaf.rs Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org> * fix failed test from apache#12050 Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * cleanup Signed-off-by: jayzhan211 <jayzhan211@gmail.com> * add doc Signed-off-by: jayzhan211 <jayzhan211@gmail.com> --------- Signed-off-by: jayzhan211 <jayzhan211@gmail.com> Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
influxdata · Oct 4, 2024 · f4ba6a2 · f4ba6a2
1 parent 8800611
commit f4ba6a2
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diff --git a/datafusion/core/src/physical_optimizer/enforce_sorting.rs b/datafusion/core/src/physical_optimizer/enforce_sorting.rs
@@ -845,17 +845,17 @@ mod tests {
 
         let physical_plan = bounded_window_exec("non_nullable_col", sort_exprs, filter);
 
-        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  FilterExec: NOT non_nullable_col@1",
             "    SortExec: expr=[non_nullable_col@1 ASC NULLS LAST], preserve_partitioning=[false]",
-            "      BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "      BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "        CoalesceBatchesExec: target_batch_size=128",
             "          SortExec: expr=[non_nullable_col@1 DESC], preserve_partitioning=[false]",
             "            MemoryExec: partitions=1, partition_sizes=[0]"];
 
-        let expected_optimized = ["WindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: CurrentRow, end_bound: Following(NULL), is_causal: false }]",
+        let expected_optimized = ["WindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: CurrentRow, end_bound: Following(NULL), is_causal: false }]",
             "  FilterExec: NOT non_nullable_col@1",
-            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "      CoalesceBatchesExec: target_batch_size=128",
             "        SortExec: expr=[non_nullable_col@1 DESC], preserve_partitioning=[false]",
             "          MemoryExec: partitions=1, partition_sizes=[0]"];
@@ -1722,15 +1722,15 @@ mod tests {
         // corresponding SortExecs together. Also, the inputs of these `SortExec`s
         // are not necessarily the same to be able to remove them.
         let expected_input = [
-            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortPreservingMergeExec: [nullable_col@0 DESC NULLS LAST]",
             "    UnionExec",
             "      SortExec: expr=[nullable_col@0 DESC NULLS LAST], preserve_partitioning=[false]",
             "        ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC, non_nullable_col@1 ASC]",
             "      SortExec: expr=[nullable_col@0 DESC NULLS LAST], preserve_partitioning=[false]",
             "        ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC]"];
         let expected_optimized = [
-            "WindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: CurrentRow, end_bound: Following(NULL), is_causal: false }]",
+            "WindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: CurrentRow, end_bound: Following(NULL), is_causal: false }]",
             "  SortPreservingMergeExec: [nullable_col@0 ASC]",
             "    UnionExec",
             "      ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC, non_nullable_col@1 ASC]",
@@ -1760,14 +1760,14 @@ mod tests {
 
         // The `WindowAggExec` can get its required sorting from the leaf nodes directly.
         // The unnecessary SortExecs should be removed
-        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortPreservingMergeExec: [nullable_col@0 ASC,non_nullable_col@1 ASC]",
             "    UnionExec",
             "      SortExec: expr=[nullable_col@0 ASC,non_nullable_col@1 ASC], preserve_partitioning=[false]",
             "        ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC]",
             "      SortExec: expr=[nullable_col@0 ASC,non_nullable_col@1 ASC], preserve_partitioning=[false]",
             "        ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC]"];
-        let expected_optimized = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+        let expected_optimized = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortPreservingMergeExec: [nullable_col@0 ASC]",
             "    UnionExec",
             "      ParquetExec: file_groups={1 group: [[x]]}, projection=[nullable_col, non_nullable_col], output_ordering=[nullable_col@0 ASC]",
@@ -2060,15 +2060,15 @@ mod tests {
         let physical_plan =
             bounded_window_exec("non_nullable_col", sort_exprs1, window_agg2);
 
-        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
-            "  BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
-            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+        let expected_input = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "  BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "      SortExec: expr=[nullable_col@0 ASC], preserve_partitioning=[false]",
             "        MemoryExec: partitions=1, partition_sizes=[0]"];
 
-        let expected_optimized = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
-            "  BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
-            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+        let expected_optimized = ["BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "  BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "      SortExec: expr=[nullable_col@0 ASC,non_nullable_col@1 ASC], preserve_partitioning=[false]",
             "        MemoryExec: partitions=1, partition_sizes=[0]"];
         assert_optimized!(expected_input, expected_optimized, physical_plan, true);
@@ -2134,7 +2134,7 @@ mod tests {
         let expected_input = vec![
             "SortExec: expr=[nullable_col@0 ASC], preserve_partitioning=[false]",
             "  RepartitionExec: partitioning=RoundRobinBatch(10), input_partitions=1",
-            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "    BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "      MemoryExec: partitions=1, partition_sizes=[0]",
         ];
         assert_eq!(
@@ -2386,15 +2386,15 @@ mod tests {
         let physical_plan = bounded_window_exec("a", sort_exprs, spm);
 
         let expected_input = [
-            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortPreservingMergeExec: [a@0 ASC,b@1 ASC]",
             "    RepartitionExec: partitioning=RoundRobinBatch(10), input_partitions=10, preserve_order=true, sort_exprs=a@0 ASC,b@1 ASC",
             "      RepartitionExec: partitioning=RoundRobinBatch(10), input_partitions=1",
             "        SortExec: expr=[a@0 ASC,b@1 ASC], preserve_partitioning=[false]",
             "          CsvExec: file_groups={1 group: [[x]]}, projection=[a, b, c, d, e], has_header=false",
         ];
         let expected_optimized = [
-            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortExec: expr=[a@0 ASC,b@1 ASC], preserve_partitioning=[false]",
             "    CoalescePartitionsExec",
             "      RepartitionExec: partitioning=RoundRobinBatch(10), input_partitions=10",

diff --git a/datafusion/core/src/physical_optimizer/sanity_checker.rs b/datafusion/core/src/physical_optimizer/sanity_checker.rs
@@ -447,7 +447,7 @@ mod tests {
         let sort = sort_exec(sort_exprs.clone(), source);
         let bw = bounded_window_exec("c9", sort_exprs, sort);
         assert_plan(bw.as_ref(), vec![
-            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  SortExec: expr=[c9@0 ASC NULLS LAST], preserve_partitioning=[false]",
             "    MemoryExec: partitions=1, partition_sizes=[0]"
         ]);
@@ -470,7 +470,7 @@ mod tests {
         )];
         let bw = bounded_window_exec("c9", sort_exprs, source);
         assert_plan(bw.as_ref(), vec![
-            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: true, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
+            "BoundedWindowAggExec: wdw=[count: Ok(Field { name: \"count\", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }), frame: WindowFrame { units: Range, start_bound: Preceding(NULL), end_bound: CurrentRow, is_causal: false }], mode=[Sorted]",
             "  MemoryExec: partitions=1, partition_sizes=[0]"
         ]);
         // Order requirement of the `BoundedWindowAggExec` is not satisfied. We expect to receive error during sanity check.

diff --git a/datafusion/core/src/physical_planner.rs b/datafusion/core/src/physical_planner.rs
@@ -670,6 +670,12 @@ impl DefaultPhysicalPlanner {
                 let input_exec = children.one()?;
                 let physical_input_schema = input_exec.schema();
                 let logical_input_schema = input.as_ref().schema();
+                let physical_input_schema_from_logical: Arc<Schema> =
+                    logical_input_schema.as_ref().clone().into();
+
+                if physical_input_schema != physical_input_schema_from_logical {
+                    return internal_err!("Physical input schema should be the same as the one converted from logical input schema.");
+                }
 
                 let groups = self.create_grouping_physical_expr(
                     group_expr,
@@ -1548,7 +1554,7 @@ pub fn create_aggregate_expr_with_name_and_maybe_filter(
     e: &Expr,
     name: Option<String>,
     logical_input_schema: &DFSchema,
-    _physical_input_schema: &Schema,
+    physical_input_schema: &Schema,
     execution_props: &ExecutionProps,
 ) -> Result<AggregateExprWithOptionalArgs> {
     match e {
@@ -1599,11 +1605,10 @@ pub fn create_aggregate_expr_with_name_and_maybe_filter(
                 let ordering_reqs: Vec<PhysicalSortExpr> =
                     physical_sort_exprs.clone().unwrap_or(vec![]);
 
-                let schema: Schema = logical_input_schema.clone().into();
                 let agg_expr =
                     AggregateExprBuilder::new(func.to_owned(), physical_args.to_vec())
                         .order_by(ordering_reqs.to_vec())
-                        .schema(Arc::new(schema))
+                        .schema(Arc::new(physical_input_schema.to_owned()))
                         .alias(name)
                         .with_ignore_nulls(ignore_nulls)
                         .with_distinct(*distinct)

diff --git a/datafusion/expr/src/expr_schema.rs b/datafusion/expr/src/expr_schema.rs
@@ -335,18 +335,28 @@ impl ExprSchemable for Expr {
                 }
             }
             Expr::Cast(Cast { expr, .. }) => expr.nullable(input_schema),
+            Expr::ScalarFunction(ScalarFunction { func, args }) => {
+                Ok(func.is_nullable(args, input_schema))
+            }
             Expr::AggregateFunction(AggregateFunction { func, .. }) => {
-                // TODO: UDF should be able to customize nullability
-                if func.name() == "count" {
-                    Ok(false)
-                } else {
-                    Ok(true)
-                }
+                Ok(func.is_nullable())
             }
+            Expr::WindowFunction(WindowFunction { fun, .. }) => match fun {
+                WindowFunctionDefinition::BuiltInWindowFunction(func) => {
+                    if func.name() == "RANK"
+                        || func.name() == "NTILE"
+                        || func.name() == "CUME_DIST"
+                    {
+                        Ok(false)
+                    } else {
+                        Ok(true)
+                    }
+                }
+                WindowFunctionDefinition::AggregateUDF(func) => Ok(func.is_nullable()),
+                WindowFunctionDefinition::WindowUDF(udwf) => Ok(udwf.nullable()),
+            },
             Expr::ScalarVariable(_, _)
             | Expr::TryCast { .. }
-            | Expr::ScalarFunction(..)
-            | Expr::WindowFunction { .. }
             | Expr::Unnest(_)
             | Expr::Placeholder(_) => Ok(true),
             Expr::IsNull(_)