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18.2 kB
| diff --git a/datafusion/core/tests/custom_sources_cases/provider_filter_pushdown.rs b/datafusion/core/tests/custom_sources_cases/provider_filter_pushdown.rs | |
| index f68bcfaf1..c80c0b4bf 100644 | |
| --- a/datafusion/core/tests/custom_sources_cases/provider_filter_pushdown.rs | |
| +++ b/datafusion/core/tests/custom_sources_cases/provider_filter_pushdown.rs | |
| impl TableProvider for CustomProvider { | |
| match &filters[0] { | |
| Expr::BinaryExpr(BinaryExpr { right, .. }) => { | |
| let int_value = match &**right { | |
| - Expr::Literal(ScalarValue::Int8(Some(i))) => *i as i64, | |
| - Expr::Literal(ScalarValue::Int16(Some(i))) => *i as i64, | |
| - Expr::Literal(ScalarValue::Int32(Some(i))) => *i as i64, | |
| - Expr::Literal(ScalarValue::Int64(Some(i))) => *i, | |
| + Expr::Literal(ScalarValue::Int8(Some(i)), _) => *i as i64, | |
| + Expr::Literal(ScalarValue::Int16(Some(i)), _) => *i as i64, | |
| + Expr::Literal(ScalarValue::Int32(Some(i)), _) => *i as i64, | |
| + Expr::Literal(ScalarValue::Int64(Some(i)), _) => *i, | |
| Expr::Cast(Cast { expr, data_type: _ }) => match expr.deref() { | |
| - Expr::Literal(lit_value) => match lit_value { | |
| + Expr::Literal(lit_value, _) => match lit_value { | |
| ScalarValue::Int8(Some(v)) => *v as i64, | |
| ScalarValue::Int16(Some(v)) => *v as i64, | |
| ScalarValue::Int32(Some(v)) => *v as i64, | |
| diff --git a/datafusion/core/tests/dataframe/mod.rs b/datafusion/core/tests/dataframe/mod.rs | |
| index aa36de1e5..c737d0f9c 100644 | |
| --- a/datafusion/core/tests/dataframe/mod.rs | |
| +++ b/datafusion/core/tests/dataframe/mod.rs | |
| async fn join_on_filter_datatype() -> Result<()> { | |
| let join = left.clone().join_on( | |
| right.clone(), | |
| JoinType::Inner, | |
| - Some(Expr::Literal(ScalarValue::Null)), | |
| + Some(Expr::Literal(ScalarValue::Null, None)), | |
| )?; | |
| assert_snapshot!(join.into_optimized_plan().unwrap(), @"EmptyRelation"); | |
| async fn consecutive_projection_same_schema() -> Result<()> { | |
| // Add `t` column full of nulls | |
| let df = df | |
| - .with_column("t", cast(Expr::Literal(ScalarValue::Null), DataType::Int32)) | |
| + .with_column( | |
| + "t", | |
| + cast(Expr::Literal(ScalarValue::Null, None), DataType::Int32), | |
| + ) | |
| .unwrap(); | |
| df.clone().show().await.unwrap(); | |
| diff --git a/datafusion/core/tests/execution/logical_plan.rs b/datafusion/core/tests/execution/logical_plan.rs | |
| index 97bb2a727..f5a8a30e0 100644 | |
| --- a/datafusion/core/tests/execution/logical_plan.rs | |
| +++ b/datafusion/core/tests/execution/logical_plan.rs | |
| async fn count_only_nulls() -> Result<()> { | |
| let input = Arc::new(LogicalPlan::Values(Values { | |
| schema: input_schema, | |
| values: vec![ | |
| - vec![Expr::Literal(ScalarValue::Null)], | |
| - vec![Expr::Literal(ScalarValue::Null)], | |
| - vec![Expr::Literal(ScalarValue::Null)], | |
| + vec![Expr::Literal(ScalarValue::Null, None)], | |
| + vec![Expr::Literal(ScalarValue::Null, None)], | |
| + vec![Expr::Literal(ScalarValue::Null, None)], | |
| ], | |
| })); | |
| let input_col_ref = Expr::Column(Column { | |
| diff --git a/datafusion/core/tests/expr_api/simplification.rs b/datafusion/core/tests/expr_api/simplification.rs | |
| index 34e0487f3..91a507bdf 100644 | |
| --- a/datafusion/core/tests/expr_api/simplification.rs | |
| +++ b/datafusion/core/tests/expr_api/simplification.rs | |
| fn select_date_plus_interval() -> Result<()> { | |
| let date_plus_interval_expr = to_timestamp_expr(ts_string) | |
| .cast_to(&DataType::Date32, schema)? | |
| - + Expr::Literal(ScalarValue::IntervalDayTime(Some(IntervalDayTime { | |
| - days: 123, | |
| - milliseconds: 0, | |
| - }))); | |
| + + Expr::Literal( | |
| + ScalarValue::IntervalDayTime(Some(IntervalDayTime { | |
| + days: 123, | |
| + milliseconds: 0, | |
| + })), | |
| + None, | |
| + ); | |
| let plan = LogicalPlanBuilder::from(table_scan.clone()) | |
| .project(vec![date_plus_interval_expr])? | |
| diff --git a/datafusion/core/tests/user_defined/expr_planner.rs b/datafusion/core/tests/user_defined/expr_planner.rs | |
| index 1fc6d14c5..07d289cab 100644 | |
| --- a/datafusion/core/tests/user_defined/expr_planner.rs | |
| +++ b/datafusion/core/tests/user_defined/expr_planner.rs | |
| impl ExprPlanner for MyCustomPlanner { | |
| } | |
| BinaryOperator::Question => { | |
| Ok(PlannerResult::Planned(Expr::Alias(Alias::new( | |
| - Expr::Literal(ScalarValue::Boolean(Some(true))), | |
| + Expr::Literal(ScalarValue::Boolean(Some(true)), None), | |
| None::<&str>, | |
| format!("{} ? {}", expr.left, expr.right), | |
| )))) | |
| diff --git a/datafusion/core/tests/user_defined/user_defined_plan.rs b/datafusion/core/tests/user_defined/user_defined_plan.rs | |
| index b68ef6aca..4d3916c17 100644 | |
| --- a/datafusion/core/tests/user_defined/user_defined_plan.rs | |
| +++ b/datafusion/core/tests/user_defined/user_defined_plan.rs | |
| impl MyAnalyzerRule { | |
| .map(|e| { | |
| e.transform(|e| { | |
| Ok(match e { | |
| - Expr::Literal(ScalarValue::Int64(i)) => { | |
| + Expr::Literal(ScalarValue::Int64(i), _) => { | |
| // transform to UInt64 | |
| - Transformed::yes(Expr::Literal(ScalarValue::UInt64( | |
| - i.map(|i| i as u64), | |
| - ))) | |
| + Transformed::yes(Expr::Literal( | |
| + ScalarValue::UInt64(i.map(|i| i as u64)), | |
| + None, | |
| + )) | |
| } | |
| _ => Transformed::no(e), | |
| }) | |
| diff --git a/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs b/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs | |
| index 25458efa4..3e8fafc7a 100644 | |
| --- a/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs | |
| +++ b/datafusion/core/tests/user_defined/user_defined_scalar_functions.rs | |
| use std::collections::HashMap; | |
| use std::hash::{DefaultHasher, Hash, Hasher}; | |
| use std::sync::Arc; | |
| -use arrow::array::{as_string_array, record_batch, Int8Array, UInt64Array}; | |
| +use arrow::array::{as_string_array, create_array, record_batch, Int8Array, UInt64Array}; | |
| use arrow::array::{ | |
| builder::BooleanBuilder, cast::AsArray, Array, ArrayRef, Float32Array, Float64Array, | |
| Int32Array, RecordBatch, StringArray, | |
| use datafusion_common::{ | |
| }; | |
| use datafusion_expr::simplify::{ExprSimplifyResult, SimplifyInfo}; | |
| use datafusion_expr::{ | |
| - Accumulator, ColumnarValue, CreateFunction, CreateFunctionBody, LogicalPlanBuilder, | |
| - OperateFunctionArg, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDF, ScalarUDFImpl, | |
| - Signature, Volatility, | |
| + lit_with_metadata, Accumulator, ColumnarValue, CreateFunction, CreateFunctionBody, | |
| + LogicalPlanBuilder, OperateFunctionArg, ReturnFieldArgs, ScalarFunctionArgs, | |
| + ScalarUDF, ScalarUDFImpl, Signature, Volatility, | |
| }; | |
| use datafusion_functions_nested::range::range_udf; | |
| use parking_lot::Mutex; | |
| async fn test_metadata_based_udf() -> Result<()> { | |
| Ok(()) | |
| } | |
| +#[tokio::test] | |
| +async fn test_metadata_based_udf_with_literal() -> Result<()> { | |
| + let ctx = SessionContext::new(); | |
| + let input_metadata: HashMap<String, String> = | |
| + [("modify_values".to_string(), "double_output".to_string())] | |
| + .into_iter() | |
| + .collect(); | |
| + let df = ctx.sql("select 0;").await?.select(vec![ | |
| + lit(5u64).alias_with_metadata("lit_with_doubling", Some(input_metadata.clone())), | |
| + lit(5u64).alias("lit_no_doubling"), | |
| + lit_with_metadata(5u64, Some(input_metadata)) | |
| + .alias("lit_with_double_no_alias_metadata"), | |
| + ])?; | |
| + | |
| + let output_metadata: HashMap<String, String> = | |
| + [("output_metatype".to_string(), "custom_value".to_string())] | |
| + .into_iter() | |
| + .collect(); | |
| + let custom_udf = ScalarUDF::from(MetadataBasedUdf::new(output_metadata.clone())); | |
| + | |
| + let plan = LogicalPlanBuilder::from(df.into_optimized_plan()?) | |
| + .project(vec![ | |
| + custom_udf | |
| + .call(vec![col("lit_with_doubling")]) | |
| + .alias("doubled_output"), | |
| + custom_udf | |
| + .call(vec![col("lit_no_doubling")]) | |
| + .alias("not_doubled_output"), | |
| + custom_udf | |
| + .call(vec![col("lit_with_double_no_alias_metadata")]) | |
| + .alias("double_without_alias_metadata"), | |
| + ])? | |
| + .build()?; | |
| + | |
| + let actual = DataFrame::new(ctx.state(), plan).collect().await?; | |
| + | |
| + let schema = Arc::new(Schema::new(vec![ | |
| + Field::new("doubled_output", DataType::UInt64, false) | |
| + .with_metadata(output_metadata.clone()), | |
| + Field::new("not_doubled_output", DataType::UInt64, false) | |
| + .with_metadata(output_metadata.clone()), | |
| + Field::new("double_without_alias_metadata", DataType::UInt64, false) | |
| + .with_metadata(output_metadata.clone()), | |
| + ])); | |
| + | |
| + let expected = RecordBatch::try_new( | |
| + schema, | |
| + vec![ | |
| + create_array!(UInt64, [10]), | |
| + create_array!(UInt64, [5]), | |
| + create_array!(UInt64, [10]), | |
| + ], | |
| + )?; | |
| + | |
| + assert_eq!(expected, actual[0]); | |
| + | |
| + Ok(()) | |
| +} | |
| + | |
| /// This UDF is to test extension handling, both on the input and output | |
| /// sides. For the input, we will handle the data differently if there is | |
| /// the canonical extension type Bool8. For the output we will add a | |
| diff --git a/datafusion/core/tests/user_defined/user_defined_table_functions.rs b/datafusion/core/tests/user_defined/user_defined_table_functions.rs | |
| index e4aff0b00..2c6611f38 100644 | |
| --- a/datafusion/core/tests/user_defined/user_defined_table_functions.rs | |
| +++ b/datafusion/core/tests/user_defined/user_defined_table_functions.rs | |
| impl TableFunctionImpl for SimpleCsvTableFunc { | |
| let mut filepath = String::new(); | |
| for expr in exprs { | |
| match expr { | |
| - Expr::Literal(ScalarValue::Utf8(Some(ref path))) => { | |
| + Expr::Literal(ScalarValue::Utf8(Some(ref path)), _) => { | |
| filepath.clone_from(path); | |
| } | |
| expr => new_exprs.push(expr.clone()), | |
| diff --git a/datafusion/proto/tests/cases/roundtrip_logical_plan.rs b/datafusion/proto/tests/cases/roundtrip_logical_plan.rs | |
| index 3edf152f4..993cc6f87 100644 | |
| --- a/datafusion/proto/tests/cases/roundtrip_logical_plan.rs | |
| +++ b/datafusion/proto/tests/cases/roundtrip_logical_plan.rs | |
| fn roundtrip_case_with_null() { | |
| let test_expr = Expr::Case(Case::new( | |
| Some(Box::new(lit(1.0_f32))), | |
| vec![(Box::new(lit(2.0_f32)), Box::new(lit(3.0_f32)))], | |
| - Some(Box::new(Expr::Literal(ScalarValue::Null))), | |
| + Some(Box::new(Expr::Literal(ScalarValue::Null, None))), | |
| )); | |
| let ctx = SessionContext::new(); | |
| fn roundtrip_case_with_null() { | |
| #[test] | |
| fn roundtrip_null_literal() { | |
| - let test_expr = Expr::Literal(ScalarValue::Null); | |
| + let test_expr = Expr::Literal(ScalarValue::Null, None); | |
| let ctx = SessionContext::new(); | |
| roundtrip_expr_test(test_expr, ctx); | |
| diff --git a/datafusion/proto/tests/cases/serialize.rs b/datafusion/proto/tests/cases/serialize.rs | |
| index ed9915083..c9ef4377d 100644 | |
| --- a/datafusion/proto/tests/cases/serialize.rs | |
| +++ b/datafusion/proto/tests/cases/serialize.rs | |
| fn test_expression_serialization_roundtrip() { | |
| use datafusion_proto::logical_plan::from_proto::parse_expr; | |
| let ctx = SessionContext::new(); | |
| - let lit = Expr::Literal(ScalarValue::Utf8(None)); | |
| + let lit = Expr::Literal(ScalarValue::Utf8(None), None); | |
| for function in string::functions() { | |
| // default to 4 args (though some exprs like substr have error checking) | |
| let num_args = 4; | |
| diff --git a/datafusion/sqllogictest/test_files/array.slt b/datafusion/sqllogictest/test_files/array.slt | |
| index d89ba600d..ac96daed0 100644 | |
| --- a/datafusion/sqllogictest/test_files/array.slt | |
| +++ b/datafusion/sqllogictest/test_files/array.slt | |
| physical_plan | |
| 04)------AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] | |
| 05)--------ProjectionExec: expr=[] | |
| 06)----------CoalesceBatchesExec: target_batch_size=8192 | |
| -07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278") }, Literal { value: Utf8View("a") }, Literal { value: Utf8View("b") }, Literal { value: Utf8View("c") }]) | |
| +07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278"), field: Field { name: "7f4b18de3cfeb9b4ac78c381ee2ad278", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("a"), field: Field { name: "a", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("b"), field: Field { name: "b", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("c"), field: Field { name: "c", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }]) | |
| 08)--------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 | |
| 09)----------------LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=1, end=100000, batch_size=8192] | |
| physical_plan | |
| 04)------AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] | |
| 05)--------ProjectionExec: expr=[] | |
| 06)----------CoalesceBatchesExec: target_batch_size=8192 | |
| -07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278") }, Literal { value: Utf8View("a") }, Literal { value: Utf8View("b") }, Literal { value: Utf8View("c") }]) | |
| +07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278"), field: Field { name: "7f4b18de3cfeb9b4ac78c381ee2ad278", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("a"), field: Field { name: "a", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("b"), field: Field { name: "b", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("c"), field: Field { name: "c", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }]) | |
| 08)--------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 | |
| 09)----------------LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=1, end=100000, batch_size=8192] | |
| physical_plan | |
| 04)------AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] | |
| 05)--------ProjectionExec: expr=[] | |
| 06)----------CoalesceBatchesExec: target_batch_size=8192 | |
| -07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278") }, Literal { value: Utf8View("a") }, Literal { value: Utf8View("b") }, Literal { value: Utf8View("c") }]) | |
| +07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278"), field: Field { name: "7f4b18de3cfeb9b4ac78c381ee2ad278", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("a"), field: Field { name: "a", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("b"), field: Field { name: "b", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("c"), field: Field { name: "c", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }]) | |
| 08)--------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 | |
| 09)----------------LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=1, end=100000, batch_size=8192] | |
| physical_plan | |
| 04)------AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] | |
| 05)--------ProjectionExec: expr=[] | |
| 06)----------CoalesceBatchesExec: target_batch_size=8192 | |
| -07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278") }, Literal { value: Utf8View("a") }, Literal { value: Utf8View("b") }, Literal { value: Utf8View("c") }]) | |
| +07)------------FilterExec: substr(md5(CAST(value@0 AS Utf8)), 1, 32) IN ([Literal { value: Utf8View("7f4b18de3cfeb9b4ac78c381ee2ad278"), field: Field { name: "7f4b18de3cfeb9b4ac78c381ee2ad278", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("a"), field: Field { name: "a", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("b"), field: Field { name: "b", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }, Literal { value: Utf8View("c"), field: Field { name: "c", data_type: Utf8View, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} } }]) | |
| 08)--------------RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 | |
| 09)----------------LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=1, end=100000, batch_size=8192] | |