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Support zero copy hash repartitioning for Hash Join #2

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fdd001f
introduce selection vector repartitioning
goldmedal Mar 25, 2025
d3e7cbe
finish the phsyical plan side
goldmedal Mar 26, 2025
9fe2975
add config
goldmedal Mar 26, 2025
b1a26f9
support for proto
goldmedal Mar 26, 2025
58c4b05
add sqllogictests
goldmedal Mar 26, 2025
0c4c77f
fix fmt and clippy
goldmedal Mar 26, 2025
dbce649
rename column and address comment
goldmedal Mar 26, 2025
0d4cf09
fix config test
goldmedal Mar 27, 2025
0609ea1
remove hash join test
goldmedal Mar 27, 2025
4e1949c
fix typo
goldmedal Mar 28, 2025
47aa074
add back the join test
goldmedal Mar 28, 2025
bd8364b
add HashPartitionMode
goldmedal Mar 29, 2025
1d8f15c
update sqllogictests
goldmedal Mar 29, 2025
6df2b4b
fix fmt
goldmedal Mar 29, 2025
b7b6a55
add todo comment
goldmedal Mar 29, 2025
b8534b3
fix typo
goldmedal Mar 29, 2025
7accad0
address review comment
goldmedal Mar 29, 2025
f298bd8
fix compile and ehance doc
goldmedal Mar 29, 2025
d3d9ca8
rename config
goldmedal Mar 29, 2025
1ad9181
fix fmt
goldmedal Mar 29, 2025
a9e1f52
fix test
goldmedal Mar 29, 2025
c6b33da
fix sqllogictests
goldmedal Mar 29, 2025
2f3b714
add selection vector mode in hash join PartitionMode
Mar 31, 2025
6353a27
add with_selection_vector flag in HashJoinStream
Mar 31, 2025
6dedfaf
filter SELECTION_FIELD_NAME in try_new HashJoinExec
Mar 31, 2025
5790ea3
add selection vector planner logic
Mar 31, 2025
07dc9e1
fix fmt
Mar 31, 2025
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8 changes: 8 additions & 0 deletions datafusion/common/src/config.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -671,6 +671,14 @@ config_namespace! {
/// HashJoin can work more efficiently than SortMergeJoin but consumes more memory
pub prefer_hash_join: bool, default = true

/// When set to true, the physical plan optimizer will prefer HashSelectionVectorPartitioning for HashAggregate
/// over HashPartitioning. HashSelectionVectorPartitioning can work without data copying.
pub prefer_hash_selection_vector_partitioning_agg: bool, default = false

/// When set to true, the physical plan optimizer will prefer HashSelectionVectorPartitioning for HashJoin
/// over HashPartitioning. HashSelectionVectorPartitioning can work without data copying.
pub prefer_hash_selection_vector_partitioning_join: bool, default = false

/// The maximum estimated size in bytes for one input side of a HashJoin
/// will be collected into a single partition
pub hash_join_single_partition_threshold: usize, default = 1024 * 1024
Expand Down
62 changes: 49 additions & 13 deletions datafusion/core/src/physical_planner.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -82,7 +82,7 @@ use datafusion_expr::{
};
use datafusion_physical_expr::aggregate::{AggregateExprBuilder, AggregateFunctionExpr};
use datafusion_physical_expr::expressions::Literal;
use datafusion_physical_expr::LexOrdering;
use datafusion_physical_expr::{HashPartitionMode, LexOrdering};
use datafusion_physical_optimizer::PhysicalOptimizerRule;
use datafusion_physical_plan::execution_plan::InvariantLevel;
use datafusion_physical_plan::placeholder_row::PlaceholderRowExec;
Expand Down Expand Up @@ -741,8 +741,17 @@ impl DefaultPhysicalPlanner {
let updated_aggregates = initial_aggr.aggr_expr().to_vec();

let next_partition_mode = if can_repartition {
let mode = if session_state
.config_options()
.optimizer
.prefer_hash_selection_vector_partitioning_agg
{
HashPartitionMode::SelectionVector
} else {
HashPartitionMode::HashPartitioned
};
// construct a second aggregation with 'AggregateMode::FinalPartitioned'
AggregateMode::FinalPartitioned
AggregateMode::FinalPartitioned(mode)
} else {
// construct a second aggregation, keeping the final column name equal to the
// first aggregation and the expressions corresponding to the respective aggregate
Expand Down Expand Up @@ -804,7 +813,15 @@ impl DefaultPhysicalPlanner {
)
})
.collect::<Result<Vec<_>>>()?;
Partitioning::Hash(runtime_expr, *n)
if session_state
.config_options()
.optimizer
.prefer_hash_selection_vector_partitioning_agg
{
Partitioning::HashSelectionVector(runtime_expr, *n)
} else {
Partitioning::Hash(runtime_expr, *n)
}
}
LogicalPartitioning::DistributeBy(_) => {
return not_impl_err!(
Expand Down Expand Up @@ -1135,16 +1152,35 @@ impl DefaultPhysicalPlanner {
&& session_state.config().repartition_joins()
&& prefer_hash_join
{
Arc::new(HashJoinExec::try_new(
physical_left,
physical_right,
join_on,
join_filter,
join_type,
None,
PartitionMode::Auto,
null_equals_null,
)?)
if session_state
.config_options()
.optimizer
.prefer_hash_selection_vector_partitioning_join
{
Arc::new(HashJoinExec::try_new(
physical_left,
physical_right,
join_on,
join_filter,
join_type,
None,
PartitionMode::Partitioned(
HashPartitionMode::SelectionVector,
),
null_equals_null,
)?)
} else {
Arc::new(HashJoinExec::try_new(
physical_left,
physical_right,
join_on,
join_filter,
join_type,
None,
PartitionMode::Auto,
null_equals_null,
)?)
}
} else {
Arc::new(HashJoinExec::try_new(
physical_left,
Expand Down
46 changes: 23 additions & 23 deletions datafusion/core/tests/dataframe/mod.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -2514,7 +2514,7 @@ async fn test_count_wildcard_on_sort() -> Result<()> {

assert_snapshot!(
pretty_format_batches(&sql_results).unwrap(),
@r###"
@r"
+---------------+------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+------------------------------------------------------------------------------------------------------------+
Expand All @@ -2527,37 +2527,37 @@ async fn test_count_wildcard_on_sort() -> Result<()> {
| | SortPreservingMergeExec: [count(Int64(1))@2 ASC NULLS LAST] |
| | SortExec: expr=[count(Int64(1))@2 ASC NULLS LAST], preserve_partitioning=[true] |
| | ProjectionExec: expr=[b@0 as b, count(Int64(1))@1 as count(*), count(Int64(1))@1 as count(Int64(1))] |
| | AggregateExec: mode=FinalPartitioned, gby=[b@0 as b], aggr=[count(Int64(1))] |
| | AggregateExec: mode=FinalPartitioned(HashPartitioned), gby=[b@0 as b], aggr=[count(Int64(1))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=Hash([b@0], 4), input_partitions=4 |
| | RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 |
| | AggregateExec: mode=Partial, gby=[b@0 as b], aggr=[count(Int64(1))] |
| | DataSourceExec: partitions=1, partition_sizes=[1] |
| | |
+---------------+------------------------------------------------------------------------------------------------------------+
"###
"
);

assert_snapshot!(
pretty_format_batches(&df_results).unwrap(),
@r###"
+---------------+--------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+--------------------------------------------------------------------------------+
| logical_plan | Sort: count(*) ASC NULLS LAST |
| | Aggregate: groupBy=[[t1.b]], aggr=[[count(Int64(1)) AS count(*)]] |
| | TableScan: t1 projection=[b] |
| physical_plan | SortPreservingMergeExec: [count(*)@1 ASC NULLS LAST] |
| | SortExec: expr=[count(*)@1 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned, gby=[b@0 as b], aggr=[count(*)] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=Hash([b@0], 4), input_partitions=4 |
| | RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 |
| | AggregateExec: mode=Partial, gby=[b@0 as b], aggr=[count(*)] |
| | DataSourceExec: partitions=1, partition_sizes=[1] |
| | |
+---------------+--------------------------------------------------------------------------------+
"###
@r"
+---------------+--------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+--------------------------------------------------------------------------------------------+
| logical_plan | Sort: count(*) ASC NULLS LAST |
| | Aggregate: groupBy=[[t1.b]], aggr=[[count(Int64(1)) AS count(*)]] |
| | TableScan: t1 projection=[b] |
| physical_plan | SortPreservingMergeExec: [count(*)@1 ASC NULLS LAST] |
| | SortExec: expr=[count(*)@1 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned(HashPartitioned), gby=[b@0 as b], aggr=[count(*)] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=Hash([b@0], 4), input_partitions=4 |
| | RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 |
| | AggregateExec: mode=Partial, gby=[b@0 as b], aggr=[count(*)] |
| | DataSourceExec: partitions=1, partition_sizes=[1] |
| | |
+---------------+--------------------------------------------------------------------------------------------+
"
);
Ok(())
}
Expand Down Expand Up @@ -2870,7 +2870,7 @@ async fn test_count_wildcard_on_where_scalar_subquery() -> Result<()> {
| | HashJoinExec: mode=CollectLeft, join_type=Left, on=[(a@0, a@1)], projection=[a@0, b@1, count(*)@2, __always_true@4] |
| | DataSourceExec: partitions=1, partition_sizes=[1] |
| | ProjectionExec: expr=[count(Int64(1))@1 as count(*), a@0 as a, true as __always_true] |
| | AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[count(Int64(1))] |
| | AggregateExec: mode=FinalPartitioned(HashPartitioned), gby=[a@0 as a], aggr=[count(Int64(1))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=Hash([a@0], 4), input_partitions=4 |
| | RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 |
Expand Down Expand Up @@ -2927,7 +2927,7 @@ async fn test_count_wildcard_on_where_scalar_subquery() -> Result<()> {
| | HashJoinExec: mode=CollectLeft, join_type=Left, on=[(a@0, a@1)], projection=[a@0, b@1, count(*)@2, __always_true@4] |
| | DataSourceExec: partitions=1, partition_sizes=[1] |
| | ProjectionExec: expr=[count(*)@1 as count(*), a@0 as a, true as __always_true] |
| | AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[count(*)] |
| | AggregateExec: mode=FinalPartitioned(HashPartitioned), gby=[a@0 as a], aggr=[count(*)] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=Hash([a@0], 4), input_partitions=4 |
| | RepartitionExec: partitioning=RoundRobinBatch(4), input_partitions=1 |
Expand Down
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