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Fix the schema mismatch between logical and physical for aggregate function, add AggregateUDFImpl::is_null #11989

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merged 23 commits into from
Aug 21, 2024
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Fix the schema mismatch between logical and physical for aggregate function, add AggregateUDFImpl::is_null #11989

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aed01f0
schema assertion and fix the mismatch from logical and physical
jayzhan211 Aug 14, 2024
cbfefc6
add more msg
jayzhan211 Aug 14, 2024
b3fc2c8
cleanup
jayzhan211 Aug 14, 2024
20d0a5f
rm test1
jayzhan211 Aug 14, 2024
1132686
nullable for scalar func
jayzhan211 Aug 17, 2024
611092e
nullable
jayzhan211 Aug 17, 2024
e732adc
Merge branch 'custom-nullable' into schema-fix
jayzhan211 Aug 17, 2024
ab38a5a
rm field
jayzhan211 Aug 17, 2024
1d299eb
rm unsafe block and use internal error
jayzhan211 Aug 17, 2024
19a1ac7
rm func_name
jayzhan211 Aug 17, 2024
984ced7
rm nullable option
jayzhan211 Aug 17, 2024
9b75540
add test
jayzhan211 Aug 17, 2024
6361bc4
add more msg
jayzhan211 Aug 17, 2024
794ce12
fix test
jayzhan211 Aug 17, 2024
cb63514
Merge branch 'main' of https://github.com/apache/datafusion into sche…
jayzhan211 Aug 17, 2024
9c12566
rm row number
jayzhan211 Aug 17, 2024
a42654c
Update datafusion/expr/src/udaf.rs
jayzhan211 Aug 20, 2024
e45d1bb
Update datafusion/expr/src/udaf.rs
jayzhan211 Aug 20, 2024
83ce363
Merge branch 'main' of https://github.com/apache/datafusion into sche…
jayzhan211 Aug 20, 2024
3519e75
fix failed test from #12050
jayzhan211 Aug 20, 2024
da30827
cleanup
jayzhan211 Aug 20, 2024
356faa8
Merge branch 'main' of https://github.com/apache/datafusion into sche…
jayzhan211 Aug 20, 2024
043c332
add doc
jayzhan211 Aug 21, 2024
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34 changes: 17 additions & 17 deletions datafusion/core/src/physical_optimizer/enforce_sorting.rs
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Expand Up @@ -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]",
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count() is always non nullable, so this change makes sense to mee

" 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]"];
Expand Down Expand Up @@ -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]",
Expand Down Expand Up @@ -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]",
Expand Down Expand Up @@ -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);
Expand Down Expand Up @@ -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!(
Expand Down Expand Up @@ -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",
Expand Down
4 changes: 2 additions & 2 deletions datafusion/core/src/physical_optimizer/sanity_checker.rs
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Expand Up @@ -437,7 +437,7 @@ 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]"
]);
Expand All @@ -460,7 +460,7 @@ 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.
Expand Down
11 changes: 8 additions & 3 deletions datafusion/core/src/physical_planner.rs
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Expand Up @@ -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 {
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🎉

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,
Expand Down Expand Up @@ -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 {
Expand Down Expand Up @@ -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();
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workaround cleanup

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)
Expand Down
26 changes: 18 additions & 8 deletions datafusion/expr/src/expr_schema.rs
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Expand Up @@ -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"
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checking the name is probably fine given we are in the process of removing the enum anyways

This could also check the variants of func here as well

|| func.name() == "NTILE"
|| func.name() == "CUME_DIST"
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I am not sure if this list is complete. What about DenseRank and PercentRank?

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Temporary code, there would be no name checking after #8709 is done. We can see that Row_Number is gone

{
Ok(false)
} else {
Ok(true)
}
}
WindowFunctionDefinition::AggregateUDF(func) => Ok(func.is_nullable()),
WindowFunctionDefinition::WindowUDF(udwf) => Ok(udwf.nullable()),
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this is great

},
Expr::ScalarVariable(_, _)
| Expr::TryCast { .. }
| Expr::ScalarFunction(..)
| Expr::WindowFunction { .. }
| Expr::Unnest(_)
| Expr::Placeholder(_) => Ok(true),
Expr::IsNull(_)
Expand Down
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