Skip to content

feat: Support binary data types for SortMergeJoin on clause (#17431) #74

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

feat: Support binary data types for SortMergeJoin on clause (#17431) #74

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
155 changes: 154 additions & 1 deletion datafusion/physical-plan/src/joins/sort_merge_join.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2503,6 +2503,10 @@ fn compare_join_arrays(
DataType::Utf8 => compare_value!(StringArray),
DataType::Utf8View => compare_value!(StringViewArray),
DataType::LargeUtf8 => compare_value!(LargeStringArray),
DataType::Binary => compare_value!(BinaryArray),
Copy link
Collaborator Author

@alamb alamb Sep 8, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

The code changes are very small, most of this PR is tests

DataType::BinaryView => compare_value!(BinaryViewArray),
DataType::FixedSizeBinary(_) => compare_value!(FixedSizeBinaryArray),
DataType::LargeBinary => compare_value!(LargeBinaryArray),
DataType::Decimal128(..) => compare_value!(Decimal128Array),
DataType::Timestamp(time_unit, None) => match time_unit {
TimeUnit::Second => compare_value!(TimestampSecondArray),
Expand Down Expand Up @@ -2571,6 +2575,10 @@ fn is_join_arrays_equal(
DataType::Utf8 => compare_value!(StringArray),
DataType::Utf8View => compare_value!(StringViewArray),
DataType::LargeUtf8 => compare_value!(LargeStringArray),
DataType::Binary => compare_value!(BinaryArray),
DataType::BinaryView => compare_value!(BinaryViewArray),
DataType::FixedSizeBinary(_) => compare_value!(FixedSizeBinaryArray),
DataType::LargeBinary => compare_value!(LargeBinaryArray),
DataType::Decimal128(..) => compare_value!(Decimal128Array),
DataType::Timestamp(time_unit, None) => match time_unit {
TimeUnit::Second => compare_value!(TimestampSecondArray),
Expand Down Expand Up @@ -2600,7 +2608,8 @@ mod tests {

use arrow::array::{
builder::{BooleanBuilder, UInt64Builder},
BooleanArray, Date32Array, Date64Array, Int32Array, RecordBatch, UInt64Array,
BinaryArray, BooleanArray, Date32Array, Date64Array, FixedSizeBinaryArray,
Int32Array, RecordBatch, UInt64Array,
};
use arrow::compute::{concat_batches, filter_record_batch, SortOptions};
use arrow::datatypes::{DataType, Field, Schema};
Expand Down Expand Up @@ -2694,6 +2703,56 @@ mod tests {
TestMemoryExec::try_new_exec(&[vec![batch]], schema, None).unwrap()
}

fn build_binary_table(
a: (&str, &Vec<&[u8]>),
b: (&str, &Vec<i32>),
c: (&str, &Vec<i32>),
) -> Arc<dyn ExecutionPlan> {
let schema = Schema::new(vec![
Field::new(a.0, DataType::Binary, false),
Field::new(b.0, DataType::Int32, false),
Field::new(c.0, DataType::Int32, false),
]);

let batch = RecordBatch::try_new(
Arc::new(schema),
vec![
Arc::new(BinaryArray::from(a.1.clone())),
Arc::new(Int32Array::from(b.1.clone())),
Arc::new(Int32Array::from(c.1.clone())),
],
)
.unwrap();

let schema = batch.schema();
TestMemoryExec::try_new_exec(&[vec![batch]], schema, None).unwrap()
}

fn build_fixed_size_binary_table(
a: (&str, &Vec<&[u8]>),
b: (&str, &Vec<i32>),
c: (&str, &Vec<i32>),
) -> Arc<dyn ExecutionPlan> {
let schema = Schema::new(vec![
Field::new(a.0, DataType::FixedSizeBinary(3), false),
Field::new(b.0, DataType::Int32, false),
Field::new(c.0, DataType::Int32, false),
]);

let batch = RecordBatch::try_new(
Arc::new(schema),
vec![
Arc::new(FixedSizeBinaryArray::from(a.1.clone())),
Arc::new(Int32Array::from(b.1.clone())),
Arc::new(Int32Array::from(c.1.clone())),
],
)
.unwrap();

let schema = batch.schema();
TestMemoryExec::try_new_exec(&[vec![batch]], schema, None).unwrap()
}

/// returns a table with 3 columns of i32 in memory
pub fn build_table_i32_nullable(
a: (&str, &Vec<Option<i32>>),
Expand Down Expand Up @@ -3932,6 +3991,100 @@ mod tests {
Ok(())
}

#[tokio::test]
async fn join_binary() -> Result<()> {
let left = build_binary_table(
(
"a1",
&vec![
&[0xc0, 0xff, 0xee],
&[0xde, 0xca, 0xde],
&[0xfa, 0xca, 0xde],
],
),
("b1", &vec![5, 10, 15]), // this has a repetition
("c1", &vec![7, 8, 9]),
);
let right = build_binary_table(
(
"a1",
&vec![
&[0xc0, 0xff, 0xee],
&[0xde, 0xca, 0xde],
&[0xfa, 0xca, 0xde],
],
),
("b2", &vec![105, 110, 115]),
("c2", &vec![70, 80, 90]),
);

let on = vec![(
Arc::new(Column::new_with_schema("a1", &left.schema())?) as _,
Arc::new(Column::new_with_schema("a1", &right.schema())?) as _,
)];

let (_, batches) = join_collect(left, right, on, Inner).await?;

// The output order is important as SMJ preserves sortedness
assert_snapshot!(batches_to_string(&batches), @r#"
+--------+----+----+--------+-----+----+
| a1 | b1 | c1 | a1 | b2 | c2 |
+--------+----+----+--------+-----+----+
| c0ffee | 5 | 7 | c0ffee | 105 | 70 |
| decade | 10 | 8 | decade | 110 | 80 |
| facade | 15 | 9 | facade | 115 | 90 |
+--------+----+----+--------+-----+----+
"#);
Ok(())
}

#[tokio::test]
async fn join_fixed_size_binary() -> Result<()> {
let left = build_fixed_size_binary_table(
(
"a1",
&vec![
&[0xc0, 0xff, 0xee],
&[0xde, 0xca, 0xde],
&[0xfa, 0xca, 0xde],
],
),
("b1", &vec![5, 10, 15]), // this has a repetition
("c1", &vec![7, 8, 9]),
);
let right = build_fixed_size_binary_table(
(
"a1",
&vec![
&[0xc0, 0xff, 0xee],
&[0xde, 0xca, 0xde],
&[0xfa, 0xca, 0xde],
],
),
("b2", &vec![105, 110, 115]),
("c2", &vec![70, 80, 90]),
);

let on = vec![(
Arc::new(Column::new_with_schema("a1", &left.schema())?) as _,
Arc::new(Column::new_with_schema("a1", &right.schema())?) as _,
)];

let (_, batches) = join_collect(left, right, on, Inner).await?;

// The output order is important as SMJ preserves sortedness
assert_snapshot!(batches_to_string(&batches), @r#"
+--------+----+----+--------+-----+----+
| a1 | b1 | c1 | a1 | b2 | c2 |
+--------+----+----+--------+-----+----+
| c0ffee | 5 | 7 | c0ffee | 105 | 70 |
| decade | 10 | 8 | decade | 110 | 80 |
| facade | 15 | 9 | facade | 115 | 90 |
+--------+----+----+--------+-----+----+
"#);
Ok(())
}

#[tokio::test]
async fn join_left_sort_order() -> Result<()> {
let left = build_table(
Expand Down
58 changes: 55 additions & 3 deletions datafusion/sqllogictest/test_files/sort_merge_join.slt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -833,9 +833,61 @@ t2 as (
11 14
12 15

# return sql params back to default values
statement ok
set datafusion.optimizer.prefer_hash_join = true;
set datafusion.execution.batch_size = 8192;


######
## Tests for Binary, LargeBinary, BinaryView, FixedSizeBinary join keys
######
statement ok
set datafusion.execution.batch_size = 8192;
create table t1(x varchar, id1 int) as values ('aa', 1), ('bb', 2), ('aa', 3), (null, 4), ('ee', 5);

statement ok
create table t2(y varchar, id2 int) as values ('ee', 10), ('bb', 20), ('cc', 30), ('cc', 40), (null, 50);

# Binary join keys
query ?I?I
with t1 as (select arrow_cast(x, 'Binary') as x, id1 from t1),
t2 as (select arrow_cast(y, 'Binary') as y, id2 from t2)
select * from t1 join t2 on t1.x = t2.y order by id1, id2
----
6262 2 6262 20
6565 5 6565 10

# LargeBinary join keys
query ?I?I
with t1 as (select arrow_cast(x, 'LargeBinary') as x, id1 from t1),
t2 as (select arrow_cast(y, 'LargeBinary') as y, id2 from t2)
select * from t1 join t2 on t1.x = t2.y order by id1, id2
----
6262 2 6262 20
6565 5 6565 10

# BinaryView join keys
query ?I?I
with t1 as (select arrow_cast(x, 'BinaryView') as x, id1 from t1),
t2 as (select arrow_cast(y, 'BinaryView') as y, id2 from t2)
select * from t1 join t2 on t1.x = t2.y order by id1, id2
----
6262 2 6262 20
6565 5 6565 10

# FixedSizeBinary join keys
query ?I?I
with t1 as (select arrow_cast(arrow_cast(x, 'Binary'), 'FixedSizeBinary(2)') as x, id1 from t1),
t2 as (select arrow_cast(arrow_cast(y, 'Binary'), 'FixedSizeBinary(2)') as y, id2 from t2)
select * from t1 join t2 on t1.x = t2.y order by id1, id2
----
6262 2 6262 20
6565 5 6565 10

statement ok
drop table t1;

statement ok
drop table t2;

# return sql params back to default values
statement ok
set datafusion.optimizer.prefer_hash_join = true;
Loading