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Demonstrate unions can't be null #11314

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137 changes: 135 additions & 2 deletions datafusion/core/tests/dataframe/mod.rs
Original file line number Diff line number Diff line change
Expand Up @@ -29,8 +29,9 @@ use arrow::{
},
record_batch::RecordBatch,
};
use arrow_array::Float32Array;
use arrow_schema::ArrowError;
use arrow_array::{Array, Float32Array, Float64Array, UnionArray};
use arrow_buffer::ScalarBuffer;
use arrow_schema::{ArrowError, UnionFields, UnionMode};
use datafusion_functions_aggregate::count::count_udaf;
use object_store::local::LocalFileSystem;
use std::fs;
Expand Down Expand Up @@ -2195,3 +2196,135 @@ async fn write_parquet_results() -> Result<()> {

Ok(())
}

fn union_fields() -> UnionFields {
[
(0, Arc::new(Field::new("A", DataType::Int32, false))),
(1, Arc::new(Field::new("B", DataType::Float64, false))),
]
.into_iter()
.collect()
}

#[tokio::test]
async fn sparse_union_is_null() {
// union of [{A=1}, null, {B=3.2}, {A=34}]
let int_array = Int32Array::from(vec![Some(1), None, None, Some(34)]);
let float_array = Float64Array::from(vec![None, None, Some(3.2), None]);
let type_ids = [0, 0, 1, 0].into_iter().collect::<ScalarBuffer<i8>>();

let children = vec![Arc::new(int_array) as Arc<dyn Array>, Arc::new(float_array)];

let array = UnionArray::try_new(union_fields(), type_ids, None, children).unwrap();

let schema = Arc::new(Schema::new(vec![Field::new(
"my_union",
DataType::Union(union_fields(), UnionMode::Sparse),
false,
)]));

let batch = RecordBatch::try_new(schema, vec![Arc::new(array)]).unwrap();

let ctx = SessionContext::new();

ctx.register_batch("union_batch", batch).unwrap();

let df = ctx.table("union_batch").await.unwrap();

// view_all
let expected = [
"+----------+",
"| my_union |",
"+----------+",
"| {A=1} |",
"| {A=34} |",
"| {A=} |",
"| {B=3.2} |",
"+----------+",
];
assert_batches_sorted_eq!(expected, &df.clone().collect().await.unwrap());

// filter where is null
let result_df = df.filter(col("my_union").is_null()).unwrap();
let expected = [
"+----------+",
"| my_union |",
"+----------+",
"| {A=} |",
"+----------+",
];
assert_batches_sorted_eq!(expected, &result_df.collect().await.unwrap());
}

#[tokio::test]
async fn dense_union_is_null() {
// union of [{A=1}, null, {B=3.2}, {A=34}]
let int_array = Int32Array::from(vec![Some(1), None, Some(34)]);
let float_array = Float64Array::from(vec![3.2]);
let type_ids = [0, 0, 1, 0].into_iter().collect::<ScalarBuffer<i8>>();
let offsets = [0, 1, 0, 2].into_iter().collect::<ScalarBuffer<i32>>();

let children = vec![Arc::new(int_array) as Arc<dyn Array>, Arc::new(float_array)];

let array =
UnionArray::try_new(union_fields(), type_ids, Some(offsets), children).unwrap();

let schema = Arc::new(Schema::new(vec![Field::new(
"my_union",
DataType::Union(union_fields(), UnionMode::Dense),
false,
)]));

let batch = RecordBatch::try_new(schema, vec![Arc::new(array)]).unwrap();

let ctx = SessionContext::new();

ctx.register_batch("union_batch", batch).unwrap();

let df = ctx.table("union_batch").await.unwrap();

// view_all
let expected = [
"+----------+",
"| my_union |",
"+----------+",
"| {A=1} |",
"| {A=34} |",
"| {A=} |",
"| {B=3.2} |",
"+----------+",
];
assert_batches_sorted_eq!(expected, &df.clone().collect().await.unwrap());

// filter where is null
let result_df = df.filter(col("my_union").is_null()).unwrap();
let expected = [
"+----------+",
"| my_union |",
"+----------+",
"| {A=} |",
"+----------+",
];
assert_batches_sorted_eq!(expected, &result_df.collect().await.unwrap());
}

/// these should definitely be moved somewhere else, but I'm just adding it here for simplicity now
#[tokio::test]
async fn sparse_union_is_null_scalar() {
let sparse_scalar = ScalarValue::Union(
Some((0_i8, Box::new(ScalarValue::Int32(None)))),
union_fields(),
UnionMode::Sparse,
);
assert!(sparse_scalar.is_null());
}

#[tokio::test]
async fn dense_union_is_null_scalar() {
let dense_scalar = ScalarValue::Union(
Some((0_i8, Box::new(ScalarValue::Int32(None)))),
union_fields(),
UnionMode::Dense,
);
assert!(dense_scalar.is_null());
}
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