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feat: extend interval analysis support for temporal types #21520

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9c50e6d
feat: extend interval analysis support for temporal types (Date32, Da…
buraksenn Apr 9, 2026
26bc9ee
Merge branch 'main' into extend-interval-analysis-temporal
buraksenn Apr 9, 2026
3a328aa
fix partition statistics tests in optimizer
buraksenn Apr 9, 2026
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55 changes: 53 additions & 2 deletions datafusion/common/src/scalar/mod.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -2526,6 +2526,23 @@ impl ScalarValue {
(Self::Float64(Some(l)), Self::Float64(Some(r))) => {
Some((l - r).abs().round() as _)
}
(Self::Date32(Some(l)), Self::Date32(Some(r))) => Some(l.abs_diff(*r) as _),
(Self::Date64(Some(l)), Self::Date64(Some(r))) => Some(l.abs_diff(*r) as _),
(Self::TimestampSecond(Some(l), _), Self::TimestampSecond(Some(r), _)) => {
Some(l.abs_diff(*r) as _)
}
(
Self::TimestampMillisecond(Some(l), _),
Self::TimestampMillisecond(Some(r), _),
) => Some(l.abs_diff(*r) as _),
(
Self::TimestampMicrosecond(Some(l), _),
Self::TimestampMicrosecond(Some(r), _),
) => Some(l.abs_diff(*r) as _),
(
Self::TimestampNanosecond(Some(l), _),
Self::TimestampNanosecond(Some(r), _),
) => Some(l.abs_diff(*r) as _),
(
Self::Decimal128(Some(l), lprecision, lscale),
Self::Decimal128(Some(r), rprecision, rscale),
Expand Down Expand Up @@ -8766,6 +8783,42 @@ mod tests {
ScalarValue::Decimal256(Some(10.into()), 1, 0),
5,
),
// Temporal types
(
ScalarValue::Date32(Some(0)),
ScalarValue::Date32(Some(10)),
10,
),
(
ScalarValue::Date32(Some(10)),
ScalarValue::Date32(Some(0)),
10,
),
(
ScalarValue::Date64(Some(1000)),
ScalarValue::Date64(Some(5000)),
4000,
),
(
ScalarValue::TimestampSecond(Some(100), None),
ScalarValue::TimestampSecond(Some(200), None),
100,
),
(
ScalarValue::TimestampMillisecond(Some(1000), None),
ScalarValue::TimestampMillisecond(Some(5000), None),
4000,
),
(
ScalarValue::TimestampMicrosecond(Some(0), None),
ScalarValue::TimestampMicrosecond(Some(1_000_000), None),
1_000_000,
),
(
ScalarValue::TimestampNanosecond(Some(1_000_000_000), None),
ScalarValue::TimestampNanosecond(Some(2_000_000_000), None),
1_000_000_000,
),
];
for (lhs, rhs, expected) in cases.iter() {
let distance = lhs.distance(rhs).unwrap();
Expand Down Expand Up @@ -8828,8 +8881,6 @@ mod tests {
ScalarValue::Boolean(Some(true)),
ScalarValue::Boolean(Some(false)),
),
(ScalarValue::Date32(Some(0)), ScalarValue::Date32(Some(1))),
(ScalarValue::Date64(Some(0)), ScalarValue::Date64(Some(1))),
(
ScalarValue::Decimal128(Some(123), 5, 5),
ScalarValue::Decimal128(Some(120), 5, 3),
Expand Down
32 changes: 16 additions & 16 deletions datafusion/core/tests/physical_optimizer/partition_statistics.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -154,15 +154,16 @@ mod test {
// - null_count = 0 (partition values from paths are never null)
// - min/max are the merged partition values across files in the group
// - byte_size = num_rows * 4 (Date32 is 4 bytes per row)
// - distinct_count = Inexact(1) per partition file (single partition value per file),
// preserved via max() when merging stats across partitions
// - distinct_count = Inexact(max_date - min_date + 1), derived from the
// date range via interval analysis for temporal types
let date32_byte_size = num_rows * 4;
let distinct_dates = (max_date - min_date + 1) as usize;
column_stats.push(ColumnStatistics {
null_count: Precision::Exact(0),
max_value: Precision::Exact(ScalarValue::Date32(Some(max_date))),
min_value: Precision::Exact(ScalarValue::Date32(Some(min_date))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(distinct_dates),
byte_size: Precision::Exact(date32_byte_size),
});
}
Expand Down Expand Up @@ -583,7 +584,7 @@ mod test {
max_value: Precision::Exact(ScalarValue::Date32(Some(20151))),
min_value: Precision::Exact(ScalarValue::Date32(Some(20148))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(4),
byte_size: Precision::Absent,
},
// column 2: right.id (Int32, file column from t2) - right partition 0: ids [3,4]
Expand Down Expand Up @@ -617,7 +618,7 @@ mod test {
max_value: Precision::Exact(ScalarValue::Date32(Some(20151))),
min_value: Precision::Exact(ScalarValue::Date32(Some(20148))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(4),
byte_size: Precision::Absent,
},
// column 2: right.id (Int32, file column from t2) - right partition 1: ids [1,2]
Expand Down Expand Up @@ -1256,7 +1257,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(2),
byte_size: Precision::Exact(8),
},
ColumnStatistics::new_unknown(), // window column
Expand Down Expand Up @@ -1284,7 +1285,7 @@ mod test {
DATE_2025_03_03,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(2),
byte_size: Precision::Exact(8),
},
ColumnStatistics::new_unknown(), // window column
Expand Down Expand Up @@ -1421,8 +1422,7 @@ mod test {
byte_size: Precision::Exact(16),
},
// Left date column: all partitions (2025-03-01..2025-03-04)
// NDV is Inexact(1) because each Hive partition has exactly 1 distinct date value,
// and merging takes max as a conservative lower bound
// NDV is Inexact(4) derived from the date range via interval analysis
ColumnStatistics {
null_count: Precision::Exact(0),
max_value: Precision::Exact(ScalarValue::Date32(Some(
Expand All @@ -1432,7 +1432,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(4),
byte_size: Precision::Exact(16),
},
// Right id column: partition 0 only (id 3..4)
Expand All @@ -1445,7 +1445,7 @@ mod test {
byte_size: Precision::Exact(8),
},
// Right date column: partition 0 only (2025-03-01..2025-03-02)
// NDV is Inexact(1) from the single Hive partition's date value
// NDV is Inexact(2) derived from the date range via interval analysis
ColumnStatistics {
null_count: Precision::Exact(0),
max_value: Precision::Exact(ScalarValue::Date32(Some(
Expand All @@ -1455,7 +1455,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(2),
byte_size: Precision::Exact(8),
},
],
Expand Down Expand Up @@ -1507,7 +1507,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(2),
byte_size: Precision::Exact(8),
},
// Right id column: partition 0 only (id 3..4)
Expand All @@ -1529,7 +1529,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(2),
byte_size: Precision::Exact(8),
},
],
Expand Down Expand Up @@ -1581,7 +1581,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(4),
byte_size: Precision::Exact(16),
},
// Right id column: all partitions (id 1..4)
Expand All @@ -1603,7 +1603,7 @@ mod test {
DATE_2025_03_01,
))),
sum_value: Precision::Absent,
distinct_count: Precision::Inexact(1),
distinct_count: Precision::Inexact(4),
byte_size: Precision::Exact(16),
},
],
Expand Down
27 changes: 26 additions & 1 deletion datafusion/expr-common/src/interval_arithmetic.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -929,7 +929,7 @@ impl Interval {
/// when the calculated cardinality does not fit in an `u64`.
pub fn cardinality(&self) -> Option<u64> {
let data_type = self.data_type();
if data_type.is_integer() {
if data_type.is_integer() || data_type.is_temporal() {
self.upper.distance(&self.lower).map(|diff| diff as u64)
} else if data_type.is_floating() {
// Negative numbers are sorted in the reverse order. To
Expand Down Expand Up @@ -3958,6 +3958,31 @@ mod tests {
)?;
assert_eq!(interval.cardinality().unwrap(), 2);

// Temporal types
let interval = Interval::try_new(
ScalarValue::Date32(Some(0)),
ScalarValue::Date32(Some(10)),
)?;
assert_eq!(interval.cardinality().unwrap(), 11);

let interval = Interval::try_new(
ScalarValue::Date64(Some(1000)),
ScalarValue::Date64(Some(5000)),
)?;
assert_eq!(interval.cardinality().unwrap(), 4001);

let interval = Interval::try_new(
ScalarValue::TimestampSecond(Some(100), None),
ScalarValue::TimestampSecond(Some(200), None),
)?;
assert_eq!(interval.cardinality().unwrap(), 101);

let interval = Interval::try_new(
ScalarValue::TimestampNanosecond(Some(1_000_000_000), None),
ScalarValue::TimestampNanosecond(Some(2_000_000_000), None),
)?;
assert_eq!(interval.cardinality().unwrap(), 1_000_000_001);

Ok(())
}

Expand Down
3 changes: 3 additions & 0 deletions datafusion/physical-expr/src/intervals/utils.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -104,6 +104,9 @@ pub fn is_datatype_supported(data_type: &DataType) -> bool {
| &DataType::UInt8
| &DataType::Float64
| &DataType::Float32
| &DataType::Date32
| &DataType::Date64
| &DataType::Timestamp(_, _)
)
}

Expand Down
46 changes: 46 additions & 0 deletions datafusion/physical-plan/src/filter.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -2577,6 +2577,52 @@ mod tests {
Ok(())
}

#[tokio::test]
async fn test_filter_statistics_equality_timestamp_ndv() -> Result<()> {
// ts: min=1_000_000_000, max=2_000_000_000, ndv=500
let schema = Schema::new(vec![Field::new(
"ts",
DataType::Timestamp(arrow::datatypes::TimeUnit::Nanosecond, None),
false,
)]);
let input = Arc::new(StatisticsExec::new(
Statistics {
num_rows: Precision::Inexact(1000),
total_byte_size: Precision::Inexact(8000),
column_statistics: vec![ColumnStatistics {
min_value: Precision::Inexact(ScalarValue::TimestampNanosecond(
Some(1_000_000_000),
None,
)),
max_value: Precision::Inexact(ScalarValue::TimestampNanosecond(
Some(2_000_000_000),
None,
)),
distinct_count: Precision::Inexact(500),
..Default::default()
}],
},
schema.clone(),
));

let predicate = Arc::new(BinaryExpr::new(
Arc::new(Column::new("ts", 0)),
Operator::Eq,
Arc::new(Literal::new(ScalarValue::TimestampNanosecond(
Some(1_500_000_000),
None,
))),
));
let filter: Arc<dyn ExecutionPlan> =
Arc::new(FilterExec::try_new(predicate, input)?);
let statistics = filter.partition_statistics(None)?;
assert_eq!(
statistics.column_statistics[0].distinct_count,
Precision::Exact(1)
);
Ok(())
}

/// Regression test: ProjectionExec on top of a FilterExec that already has
/// an explicit projection must not panic when `try_swapping_with_projection`
/// attempts to swap the two nodes.
Expand Down
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