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Posted to commits@datafusion.apache.org by gi...@apache.org on 2026/06/26 03:45:08 UTC
(datafusion) branch gh-readonly-queue/main/pr-23140-32e27acb9f647c40c93e8f208b8805cd7c779ff6 created (now ff677c4a8b)
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at ff677c4a8b fix: Fix peak memory display in `EXPLAIN ANALYZE` for multiple operators (#23140)
This branch includes the following new commits:
new ff677c4a8b fix: Fix peak memory display in `EXPLAIN ANALYZE` for multiple operators (#23140)
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(datafusion) 01/01: fix: Fix peak memory display in `EXPLAIN ANALYZE` for multiple operators (#23140)
Posted by gi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
github-merge-queue[bot] pushed a commit to branch gh-readonly-queue/main/pr-23140-32e27acb9f647c40c93e8f208b8805cd7c779ff6
in repository https://gitbox.apache.org/repos/asf/datafusion.git
commit ff677c4a8b6bc098d00fba05a817619b08031809
Author: Yongting You <20...@gmail.com>
AuthorDate: Fri Jun 26 11:44:44 2026 +0800
fix: Fix peak memory display in `EXPLAIN ANALYZE` for multiple operators (#23140)
## Which issue does this PR close?
<!--
We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes #123` indicates that this PR will close issue #123.
-->
- Closes #.
## Rationale for this change
<!--
Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
your changes and offer better suggestions for fixes.
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See reproducer in `datafusion-cli`:
```sh
yongting@Yongtings-MacBook-Pro-2 ~/C/d/datafusion (hj-mem-fix *)> datafusion-cli
DataFusion CLI v54.0.0
> set datafusion.explain.analyze_categories = 'bytes';
0 row(s) fetched.
Elapsed 0.001 seconds.
> explain analyze
select *
from generate_series(100000000) as t1(v1)
join generate_series(100000000) as t2(v1)
on t1.v1=t2.v1;
+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| Plan with Metrics | HashJoinExec: mode=Partitioned, join_type=Inner, on=[(v1@0, v1@0)], metrics=[output_bytes=1526.7 MB, build_mem_used=2.80 B] |
| | RepartitionExec: partitioning=Hash([v1@0], 14), input_partitions=1, maintains_sort_order=true, metrics=[output_bytes=763.4 MB, spilled_bytes=0.0 B] |
| | ProjectionExec: expr=[value@0 as v1], metrics=[output_bytes=763.0 MB] |
| | LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=0, end=100000000, batch_size=8192], metrics=[output_bytes=763.0 MB] |
| | RepartitionExec: partitioning=Hash([v1@0], 14), input_partitions=1, maintains_sort_order=true, metrics=[output_bytes=763.4 MB, spilled_bytes=0.0 B] |
| | ProjectionExec: expr=[value@0 as v1], metrics=[output_bytes=763.0 MB] |
| | LazyMemoryExec: partitions=1, batch_generators=[generate_series: start=0, end=100000000, batch_size=8192], metrics=[output_bytes=763.0 MB] |
| | |
+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row(s) fetched.
Elapsed 1.040 seconds.
```
See `HashJoinExec: ... build_mem_used=2.80 B`, it actually means 2.8
billion bytes, but it looks quite misleading. This PR fixes it:
```sh
+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+-------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------+
| Plan with Metrics | HashJoinExec: mode=Partitioned, join_type=Inner, on=[(v1@0, v1@0)], metrics=[output_bytes=1526.7 MB, build_mem_used=2.6 GB]
```
The reason is those metrics are tracking peak memory usage for a
operator in the query lifecycle, so it's using `Gauge` metrics type, but
how to choose display format become tricky (bytes or count?)
This PR adds a new `Metric` type, that wraps the existing `Gauge`, and
use it to represent 'gauge for memory bytes', this fixes the bytes
display issue.
## What changes are included in this PR?
<!--
There is no need to duplicate the description in the issue here but it
is sometimes worth providing a summary of the individual changes in this
PR.
-->
1. Introduce `MetricValue::PeakMemoryUsage` to address the above issue
2. Use this metric type for applicable metrics
3. Add slts for testing.
## Are these changes tested?
<!--
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1. Prevent the code from being accidentally broken by subsequent changes
4. Serve as another way to document the expected behavior of the code
If tests are not included in your PR, please explain why (for example,
are they covered by existing tests)?
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## Are there any user-facing changes?
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updated before approving the PR.
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change` label.
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---
datafusion/ffi/src/physical_expr/metrics.rs | 22 ++
.../physical-expr-common/src/metrics/builder.rs | 17 ++
datafusion/physical-expr-common/src/metrics/mod.rs | 1 +
.../physical-expr-common/src/metrics/value.rs | 49 ++++-
.../physical-plan/src/aggregates/row_hash.rs | 3 +-
datafusion/physical-plan/src/buffer.rs | 3 +-
datafusion/physical-plan/src/display.rs | 3 +
.../src/joins/sort_merge_join/bitwise_stream.rs | 3 +-
.../src/joins/sort_merge_join/metrics.rs | 5 +-
datafusion/physical-plan/src/joins/utils.rs | 5 +-
.../sqllogictest/test_files/explain_analyze.slt | 231 +++++++++++++++++++++
datafusion/sqllogictest/test_files/joins.slt | 2 +-
12 files changed, 330 insertions(+), 14 deletions(-)
diff --git a/datafusion/ffi/src/physical_expr/metrics.rs b/datafusion/ffi/src/physical_expr/metrics.rs
index ebef728e05..763cc3f079 100644
--- a/datafusion/ffi/src/physical_expr/metrics.rs
+++ b/datafusion/ffi/src/physical_expr/metrics.rs
@@ -128,6 +128,9 @@ pub struct FFI_RatioMetrics {
}
/// FFI-stable mirror of [`MetricValue`].
+///
+/// This is part of the stable ABI and must not be reordered. New variants must be
+/// appended at the end.
#[repr(C, u8)]
#[derive(Debug, Clone)]
pub enum FFI_MetricValue {
@@ -170,6 +173,10 @@ pub enum FFI_MetricValue {
display: SString,
as_usize_value: u64,
},
+ PeakMemoryUsage {
+ name: SString,
+ gauge: u64,
+ },
}
// -----------------------------------------------------------------------------
@@ -425,6 +432,10 @@ impl From<&MetricValue> for FFI_MetricValue {
name: SString::from(name.as_ref()),
gauge: gauge.value() as u64,
},
+ MetricValue::PeakMemoryUsage { name, gauge } => Self::PeakMemoryUsage {
+ name: SString::from(name.as_ref()),
+ gauge: gauge.value() as u64,
+ },
MetricValue::Time { name, time } => Self::Time {
name: SString::from(name.as_ref()),
time_ns: time.value() as u64,
@@ -481,6 +492,10 @@ impl From<FFI_MetricValue> for MetricValue {
name: Cow::Owned(name.into()),
gauge: gauge_from_value(gauge),
},
+ FFI_MetricValue::PeakMemoryUsage { name, gauge } => Self::PeakMemoryUsage {
+ name: Cow::Owned(name.into()),
+ gauge: gauge_from_value(gauge),
+ },
FFI_MetricValue::Time { name, time_ns } => Self::Time {
name: Cow::Owned(name.into()),
time: time_from_nanos(time_ns),
@@ -624,6 +639,13 @@ mod tests {
gauge,
});
+ let peak_memory = Gauge::new();
+ peak_memory.add(44);
+ assert_value_roundtrip(MetricValue::PeakMemoryUsage {
+ name: Cow::Borrowed("peak_mem_used"),
+ gauge: peak_memory,
+ });
+
let time = Time::new();
time.add_duration(std::time::Duration::from_nanos(33));
assert_value_roundtrip(MetricValue::Time {
diff --git a/datafusion/physical-expr-common/src/metrics/builder.rs b/datafusion/physical-expr-common/src/metrics/builder.rs
index de9d1e03d8..7d5a18f535 100644
--- a/datafusion/physical-expr-common/src/metrics/builder.rs
+++ b/datafusion/physical-expr-common/src/metrics/builder.rs
@@ -249,6 +249,23 @@ impl<'a> MetricBuilder<'a> {
gauge
}
+ /// Consumes self and creates a new [`Gauge`] for recording peak memory
+ /// usage in bytes.
+ pub fn peak_memory_usage(
+ self,
+ gauge_name: impl Into<Cow<'static, str>>,
+ partition: usize,
+ ) -> Gauge {
+ let gauge = Gauge::new();
+ self.with_category(MetricCategory::Bytes)
+ .with_partition(partition)
+ .build(MetricValue::PeakMemoryUsage {
+ name: gauge_name.into(),
+ gauge: gauge.clone(),
+ });
+ gauge
+ }
+
/// Consume self and create a new Timer for recording the elapsed
/// CPU time spent by an operator
pub fn elapsed_compute(self, partition: usize) -> Time {
diff --git a/datafusion/physical-expr-common/src/metrics/mod.rs b/datafusion/physical-expr-common/src/metrics/mod.rs
index 0a03075b91..d6048a0fcd 100644
--- a/datafusion/physical-expr-common/src/metrics/mod.rs
+++ b/datafusion/physical-expr-common/src/metrics/mod.rs
@@ -309,6 +309,7 @@ impl MetricsSet {
MetricValue::SpilledRows(_) => false,
MetricValue::CurrentMemoryUsage(_) => false,
MetricValue::Gauge { name, .. } => name == metric_name,
+ MetricValue::PeakMemoryUsage { name, .. } => name == metric_name,
MetricValue::StartTimestamp(_) => false,
MetricValue::EndTimestamp(_) => false,
MetricValue::PruningMetrics { name, .. } => name == metric_name,
diff --git a/datafusion/physical-expr-common/src/metrics/value.rs b/datafusion/physical-expr-common/src/metrics/value.rs
index ef0087c20d..232fefcc5f 100644
--- a/datafusion/physical-expr-common/src/metrics/value.rs
+++ b/datafusion/physical-expr-common/src/metrics/value.rs
@@ -672,6 +672,13 @@ pub enum MetricValue {
/// The value of the metric
gauge: Gauge,
},
+ /// Operator defined peak memory usage in bytes.
+ PeakMemoryUsage {
+ /// The provided name of this metric
+ name: Cow<'static, str>,
+ /// The value of the metric
+ gauge: Gauge,
+ },
/// Operator defined time
Time {
/// The provided name of this metric
@@ -744,6 +751,13 @@ impl PartialEq for MetricValue {
name: other_name,
gauge: other_gauge,
},
+ )
+ | (
+ MetricValue::PeakMemoryUsage { name, gauge },
+ MetricValue::PeakMemoryUsage {
+ name: other_name,
+ gauge: other_gauge,
+ },
) => name == other_name && gauge == other_gauge,
(
MetricValue::Time { name, time },
@@ -810,7 +824,9 @@ impl MetricValue {
Self::CurrentMemoryUsage(_) => "mem_used",
Self::ElapsedCompute(_) => "elapsed_compute",
Self::Count { name, .. } => name.borrow(),
- Self::Gauge { name, .. } => name.borrow(),
+ Self::Gauge { name, .. } | Self::PeakMemoryUsage { name, .. } => {
+ name.borrow()
+ }
Self::Time { name, .. } => name.borrow(),
Self::StartTimestamp(_) => "start_timestamp",
Self::EndTimestamp(_) => "end_timestamp",
@@ -833,7 +849,9 @@ impl MetricValue {
Self::CurrentMemoryUsage(used) => used.value(),
Self::ElapsedCompute(time) => time.value(),
Self::Count { count, .. } => count.value(),
- Self::Gauge { gauge, .. } => gauge.value(),
+ Self::Gauge { gauge, .. } | Self::PeakMemoryUsage { gauge, .. } => {
+ gauge.value()
+ }
Self::Time { time, .. } => time.value(),
Self::StartTimestamp(timestamp) => timestamp
.value()
@@ -875,6 +893,10 @@ impl MetricValue {
name: name.clone(),
gauge: Gauge::new(),
},
+ Self::PeakMemoryUsage { name, .. } => Self::PeakMemoryUsage {
+ name: name.clone(),
+ gauge: Gauge::new(),
+ },
Self::Time { name, .. } => Self::Time {
name: name.clone(),
time: Time::new(),
@@ -933,6 +955,12 @@ impl MetricValue {
Self::Gauge {
gauge: other_gauge, ..
},
+ )
+ | (
+ Self::PeakMemoryUsage { gauge, .. },
+ Self::PeakMemoryUsage {
+ gauge: other_gauge, ..
+ },
) => gauge.add(other_gauge.value()),
(Self::ElapsedCompute(time), Self::ElapsedCompute(other_time))
| (
@@ -1029,6 +1057,7 @@ impl MetricValue {
"page_index_pages_skipped_by_fully_matched" => 8,
_ => 14,
},
+ Self::PeakMemoryUsage { .. } => 13,
Self::Gauge { .. } => 15,
Self::Time { .. } => 16,
Self::Ratio { .. } => 17,
@@ -1064,6 +1093,10 @@ impl Display for MetricValue {
let readable_size = human_readable_size(gauge.value());
write!(f, "{readable_size}")
}
+ Self::PeakMemoryUsage { gauge, .. } => {
+ let readable_size = human_readable_size(gauge.value());
+ write!(f, "{readable_size}")
+ }
Self::Gauge { gauge, .. } => {
// Generic gauge metrics - format with human-readable count
write!(f, "{}", human_readable_count(gauge.value()))
@@ -1525,6 +1558,18 @@ mod tests {
"100.0 MB"
);
+ // Test PeakMemoryUsage formatting (should use size, not count)
+ let peak_mem_gauge = Gauge::new();
+ peak_mem_gauge.add(100 * MB as usize);
+ assert_eq!(
+ MetricValue::PeakMemoryUsage {
+ name: "peak_mem_used".into(),
+ gauge: peak_mem_gauge.clone()
+ }
+ .to_string(),
+ "100.0 MB"
+ );
+
// Test custom Gauge formatting (should use count)
let custom_gauge = Gauge::new();
custom_gauge.add(50_000);
diff --git a/datafusion/physical-plan/src/aggregates/row_hash.rs b/datafusion/physical-plan/src/aggregates/row_hash.rs
index d46faf9acc..5cd7f508af 100644
--- a/datafusion/physical-plan/src/aggregates/row_hash.rs
+++ b/datafusion/physical-plan/src/aggregates/row_hash.rs
@@ -527,8 +527,7 @@ impl GroupedHashAggregateStream {
merging_aggregate_arguments,
merging_group_by: PhysicalGroupBy::new_single(merging_group_by_expr),
peak_mem_used: MetricBuilder::new(&agg.metrics)
- .with_category(MetricCategory::Bytes)
- .gauge("peak_mem_used", partition),
+ .peak_memory_usage("peak_mem_used", partition),
spill_manager,
};
diff --git a/datafusion/physical-plan/src/buffer.rs b/datafusion/physical-plan/src/buffer.rs
index 871d3c4d3f..6d1fb69635 100644
--- a/datafusion/physical-plan/src/buffer.rs
+++ b/datafusion/physical-plan/src/buffer.rs
@@ -194,8 +194,7 @@ impl ExecutionPlan for BufferExec {
let curr_mem_out = Arc::clone(&curr_mem_in);
let mut max_mem_in = 0;
let max_mem = MetricBuilder::new(&self.metrics)
- .with_category(MetricCategory::Bytes)
- .gauge("max_mem_used", partition);
+ .peak_memory_usage("max_mem_used", partition);
let curr_queued_in = Arc::new(AtomicUsize::new(0));
let curr_queued_out = Arc::clone(&curr_queued_in);
diff --git a/datafusion/physical-plan/src/display.rs b/datafusion/physical-plan/src/display.rs
index 164637f760..56b209d921 100644
--- a/datafusion/physical-plan/src/display.rs
+++ b/datafusion/physical-plan/src/display.rs
@@ -775,6 +775,9 @@ impl PgJsonExecutionPlanVisitor<'_> {
}
MetricValue::Count { count, .. } => serde_json::Value::from(count.value()),
MetricValue::Gauge { gauge, .. } => serde_json::Value::from(gauge.value()),
+ MetricValue::PeakMemoryUsage { gauge, .. } => {
+ serde_json::Value::from(gauge.value())
+ }
MetricValue::Time { time, .. } => {
let ms = (time.value() as f64) / 1_000_000.0;
serde_json::Value::from(ms)
diff --git a/datafusion/physical-plan/src/joins/sort_merge_join/bitwise_stream.rs b/datafusion/physical-plan/src/joins/sort_merge_join/bitwise_stream.rs
index 815cc370ca..8de72fd49c 100644
--- a/datafusion/physical-plan/src/joins/sort_merge_join/bitwise_stream.rs
+++ b/datafusion/physical-plan/src/joins/sort_merge_join/bitwise_stream.rs
@@ -360,7 +360,8 @@ impl BitwiseSortMergeJoinStream {
MetricBuilder::new(metrics).counter("input_batches", partition);
let input_rows = MetricBuilder::new(metrics).counter("input_rows", partition);
let baseline_metrics = BaselineMetrics::new(metrics, partition);
- let peak_mem_used = MetricBuilder::new(metrics).gauge("peak_mem_used", partition);
+ let peak_mem_used =
+ MetricBuilder::new(metrics).peak_memory_usage("peak_mem_used", partition);
Ok(Self {
join_type,
diff --git a/datafusion/physical-plan/src/joins/sort_merge_join/metrics.rs b/datafusion/physical-plan/src/joins/sort_merge_join/metrics.rs
index 62efb77f87..6f52a2234b 100644
--- a/datafusion/physical-plan/src/joins/sort_merge_join/metrics.rs
+++ b/datafusion/physical-plan/src/joins/sort_merge_join/metrics.rs
@@ -46,9 +46,8 @@ impl SortMergeJoinMetrics {
let input_rows = MetricBuilder::new(metrics)
.with_category(MetricCategory::Rows)
.counter("input_rows", partition);
- let peak_mem_used = MetricBuilder::new(metrics)
- .with_category(MetricCategory::Bytes)
- .gauge("peak_mem_used", partition);
+ let peak_mem_used =
+ MetricBuilder::new(metrics).peak_memory_usage("peak_mem_used", partition);
let baseline_metrics = BaselineMetrics::new(metrics, partition);
diff --git a/datafusion/physical-plan/src/joins/utils.rs b/datafusion/physical-plan/src/joins/utils.rs
index 7ecace6b0e..39a4c178ca 100644
--- a/datafusion/physical-plan/src/joins/utils.rs
+++ b/datafusion/physical-plan/src/joins/utils.rs
@@ -1798,9 +1798,8 @@ impl BuildProbeJoinMetrics {
.with_category(MetricCategory::Rows)
.counter("build_input_rows", partition);
- let build_mem_used = MetricBuilder::new(metrics)
- .with_category(MetricCategory::Bytes)
- .gauge("build_mem_used", partition);
+ let build_mem_used =
+ MetricBuilder::new(metrics).peak_memory_usage("build_mem_used", partition);
let input_batches = MetricBuilder::new(metrics)
.with_category(MetricCategory::Rows)
diff --git a/datafusion/sqllogictest/test_files/explain_analyze.slt b/datafusion/sqllogictest/test_files/explain_analyze.slt
index 623580fce9..665c8d7f44 100644
--- a/datafusion/sqllogictest/test_files/explain_analyze.slt
+++ b/datafusion/sqllogictest/test_files/explain_analyze.slt
@@ -300,6 +300,237 @@ reset datafusion.explain.analyze_categories;
statement ok
reset datafusion.explain.analyze_level;
+# ------------------------------------------------
+# Test memory metrics display.
+# ------------------------------------------------
+
+statement ok
+set datafusion.explain.analyze_level = dev;
+
+statement ok
+set datafusion.explain.analyze_categories = 'bytes';
+
+statement ok
+set datafusion.execution.target_partitions = 1;
+
+statement ok
+set datafusion.optimizer.repartition_joins = false;
+
+statement ok
+set datafusion.optimizer.prefer_hash_join = true;
+
+statement ok
+set datafusion.optimizer.enable_piecewise_merge_join = false;
+
+statement ok
+set datafusion.optimizer.hash_join_inlist_pushdown_max_size = 0;
+
+statement ok
+set datafusion.optimizer.hash_join_inlist_pushdown_max_distinct_values = 0;
+
+query TT
+EXPLAIN ANALYZE
+WITH t1 (k) AS (
+ VALUES (1), (2), (3)
+), t2 (k) AS (
+ VALUES (1), (2), (3)
+)
+SELECT *
+FROM t1
+JOIN t2 ON t1.k = t2.k;
+----
+Plan with Metrics
+01)HashJoinExec: mode=CollectLeft, join_type=Inner, on=[(k@0, k@0)], metrics=[output_bytes=128.0 KB, build_mem_used=44.0 B]
+02)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+05)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+set datafusion.execution.hash_join_buffering_capacity = 1024;
+
+query TT
+EXPLAIN ANALYZE
+WITH t1 (k) AS (
+ VALUES (1), (2), (3)
+), t2 (k) AS (
+ VALUES (1), (2), (3)
+)
+SELECT *
+FROM t1
+JOIN t2 ON t1.k = t2.k;
+----
+Plan with Metrics
+01)HashJoinExec: mode=CollectLeft, join_type=Inner, on=[(k@0, k@0)], metrics=[output_bytes=128.0 KB, build_mem_used=44.0 B]
+02)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--BufferExec: capacity=1024, metrics=[max_mem_used=128.0 B]
+05)----ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+06)------DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+reset datafusion.execution.hash_join_buffering_capacity;
+
+query TT
+EXPLAIN ANALYZE
+WITH t1 (k) AS (
+ VALUES (1), (2)
+), t2 (k) AS (
+ VALUES (10), (20)
+)
+SELECT *
+FROM t1
+CROSS JOIN t2;
+----
+Plan with Metrics
+01)CrossJoinExec, metrics=[output_bytes=96.0 B, build_mem_used=128.0 B]
+02)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+05)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+query TT
+EXPLAIN ANALYZE
+WITH t1 (k) AS (
+ VALUES (1), (2)
+), t2 (k) AS (
+ VALUES (2), (3)
+)
+SELECT *
+FROM t1
+JOIN t2 ON t1.k < t2.k;
+----
+Plan with Metrics
+01)NestedLoopJoinExec: join_type=Inner, filter=k@0 < k@1, metrics=[output_bytes=128.0 KB, spilled_bytes=0.0 B, build_mem_used=128.0 B]
+02)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+05)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+set datafusion.optimizer.enable_piecewise_merge_join = true;
+
+query TT
+EXPLAIN ANALYZE
+WITH t1 (k) AS (
+ VALUES (3), (4)
+), t2 (k) AS (
+ VALUES (1), (2)
+)
+SELECT *
+FROM t1
+JOIN t2 ON t1.k > t2.k;
+----
+Plan with Metrics
+01)PiecewiseMergeJoin: operator=Gt, join_type=Inner, on=(k > k), metrics=[output_bytes=0.0 B, build_mem_used=144.0 B]
+02)--SortExec: expr=[k@0 ASC], preserve_partitioning=[false], metrics=[output_bytes=0.0 B, spilled_bytes=0.0 B]
+03)----ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+04)------DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+05)--ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+06)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+set datafusion.optimizer.enable_piecewise_merge_join = false;
+
+statement ok
+set datafusion.execution.target_partitions = 2;
+
+statement ok
+set datafusion.optimizer.repartition_joins = true;
+
+statement ok
+set datafusion.optimizer.prefer_hash_join = false;
+
+statement ok
+CREATE TABLE ea_smj_t1(a text, b int) AS VALUES ('Alice', 50), ('Alice', 100), ('Bob', 1);
+
+statement ok
+CREATE TABLE ea_smj_t2(a text, b int) AS VALUES ('Alice', 2), ('Alice', 1);
+
+query TT
+EXPLAIN ANALYZE
+SELECT ea_smj_t1.a, ea_smj_t1.b, ea_smj_t2.a, ea_smj_t2.b
+FROM ea_smj_t1
+JOIN ea_smj_t2 ON ea_smj_t1.a = ea_smj_t2.a
+ AND ea_smj_t2.b * 50 <= ea_smj_t1.b;
+----
+Plan with Metrics
+01)SortMergeJoinExec: join_type=Inner, on=[(a@0, a@0)], filter=CAST(b@1 AS Int64) * 50 <= CAST(b@0 AS Int64), metrics=[output_bytes=320.0 KB, spilled_bytes=0.0 B, peak_mem_used=432.0 B]
+02)--SortExec: expr=[a@0 ASC], preserve_partitioning=[false], metrics=[output_bytes=0.0 B, spilled_bytes=0.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--SortExec: expr=[a@0 ASC], preserve_partitioning=[false], metrics=[output_bytes=0.0 B, spilled_bytes=0.0 B]
+05)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+query TT
+EXPLAIN ANALYZE
+SELECT ea_smj_t1.a, ea_smj_t1.b
+FROM ea_smj_t1
+LEFT SEMI JOIN ea_smj_t2 ON ea_smj_t1.a = ea_smj_t2.a;
+----
+Plan with Metrics
+01)SortMergeJoinExec: join_type=LeftSemi, on=[(a@0, a@0)], metrics=[output_bytes=160.0 KB, spilled_bytes=0.0 B, peak_mem_used=0.0 B]
+02)--SortExec: expr=[a@0 ASC], preserve_partitioning=[false], metrics=[output_bytes=0.0 B, spilled_bytes=0.0 B]
+03)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+04)--SortExec: expr=[a@0 ASC], preserve_partitioning=[false], metrics=[output_bytes=0.0 B, spilled_bytes=0.0 B]
+05)----DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+DROP TABLE ea_smj_t1;
+
+statement ok
+DROP TABLE ea_smj_t2;
+
+statement ok
+set datafusion.execution.target_partitions = 1;
+
+statement ok
+set datafusion.optimizer.repartition_joins = false;
+
+statement ok
+set datafusion.execution.enable_migration_aggregate = false;
+
+query TT
+EXPLAIN ANALYZE
+WITH t (k) AS (
+ VALUES (1), (2), (1), (3)
+)
+SELECT k, count(*)
+FROM t
+GROUP BY k;
+----
+Plan with Metrics
+01)ProjectionExec: expr=[k@0 as k, count(Int64(1))@1 as count(*)], metrics=[output_bytes=1056.0 B]
+02)--AggregateExec: mode=Single, gby=[k@0 as k], aggr=[count(Int64(1))], metrics=[output_bytes=1056.0 B, spilled_bytes=0.0 B, peak_mem_used=9.2 KB]
+03)----ProjectionExec: expr=[column1@0 as k], metrics=[output_bytes=32.0 B]
+04)------DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
+
+statement ok
+reset datafusion.execution.enable_migration_aggregate;
+
+statement ok
+reset datafusion.optimizer.prefer_hash_join;
+
+statement ok
+reset datafusion.optimizer.hash_join_inlist_pushdown_max_size;
+
+statement ok
+reset datafusion.optimizer.hash_join_inlist_pushdown_max_distinct_values;
+
+statement ok
+reset datafusion.optimizer.repartition_joins;
+
+statement ok
+reset datafusion.optimizer.enable_piecewise_merge_join;
+
+statement ok
+set datafusion.execution.target_partitions = 4;
+
+statement ok
+reset datafusion.explain.analyze_categories;
+
+statement ok
+reset datafusion.explain.analyze_level;
+
# ------------------------------------------------------------------
# Same category/level filtering, but via the Postgres-style
# `EXPLAIN (ANALYZE, METRICS ..., LEVEL ...)` statement option list.
diff --git a/datafusion/sqllogictest/test_files/joins.slt b/datafusion/sqllogictest/test_files/joins.slt
index 082b101672..1101ad6d2b 100644
--- a/datafusion/sqllogictest/test_files/joins.slt
+++ b/datafusion/sqllogictest/test_files/joins.slt
@@ -5185,7 +5185,7 @@ LEFT ANTI JOIN (
) t2 ON t1.k = t2.k;
----
Plan with Metrics
-01)HashJoinExec: mode=CollectLeft, join_type=RightAnti, on=[(k@0, k@0)], metrics=[output_rows=2, elapsed_compute=<slt:ignore>, output_bytes=<slt:ignore>, output_batches=1, array_map_created_count=0, build_input_batches=0, build_input_rows=0, input_batches=1, input_rows=2, build_mem_used=<slt:ignore>, build_time=<slt:ignore>, join_time=<slt:ignore>, avg_fanout=N/A (0/0), probe_hit_rate=0% (0/2)]
+01)HashJoinExec: mode=CollectLeft, join_type=RightAnti, on=[(k@0, k@0)], metrics=[output_rows=2, elapsed_compute=<slt:ignore>, output_bytes=<slt:ignore>, output_batches=1, build_mem_used=<slt:ignore>, array_map_created_count=0, build_input_batches=0, build_input_rows=0, input_batches=1, input_rows=2, build_time=<slt:ignore>, join_time=<slt:ignore>, avg_fanout=N/A (0/0), probe_hit_rate=0% (0/2)]
02)--ProjectionExec: expr=[column1@0 as k], metrics=[output_rows=0, elapsed_compute=<slt:ignore>, output_bytes=<slt:ignore>, output_batches=0, expr_0_eval_time=<slt:ignore>]
03)----FilterExec: column1@0 != 1, metrics=[output_rows=0, elapsed_compute=<slt:ignore>, output_bytes=<slt:ignore>, output_batches=0, selectivity=0% (0/1)]
04)------DataSourceExec: partitions=1, partition_sizes=[1], metrics=[]
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