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fix date_bin overflows scaling extreme Timestamp(Second) source #22315

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Merged
Jefffrey merged 11 commits into from
Jun 4, 2026
Merged

fix date_bin overflows scaling extreme Timestamp(Second) source #22315

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53bfc66
fix date_bin overflows scaling extreme Timestamp(Second) source
xiedeyantu May 17, 2026
346bab4
fmt
xiedeyantu May 17, 2026
5650346
update
xiedeyantu May 18, 2026
964f3a1
fmt
xiedeyantu May 18, 2026
9c55e06
fix
xiedeyantu May 26, 2026
544b70e
fix
xiedeyantu May 26, 2026
b187e97
fmt
xiedeyantu May 26, 2026
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fmt
xiedeyantu May 26, 2026
c16b659
fmt
xiedeyantu May 26, 2026
19435dd
fix
xiedeyantu May 30, 2026
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xiedeyantu May 30, 2026
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145 changes: 91 additions & 54 deletions datafusion/functions/src/datetime/date_bin.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -31,9 +31,12 @@ use arrow::datatypes::{
DataType, Time32MillisecondType, Time32SecondType, Time64MicrosecondType,
Time64NanosecondType, TimeUnit,
};
use arrow::error::ArrowError;
use arrow::temporal_conversions::NANOSECONDS_IN_DAY;
use datafusion_common::cast::as_primitive_array;
use datafusion_common::{Result, ScalarValue, exec_err, not_impl_err, plan_err};
use datafusion_common::{
DataFusionError, Result, ScalarValue, exec_err, not_impl_err, plan_err,
};
use datafusion_expr::TypeSignature::Exact;
use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
use datafusion_expr::{
Expand Down Expand Up @@ -322,7 +325,7 @@ impl Interval {
// return time in nanoseconds that the source timestamp falls into based on the stride and origin
fn date_bin_nanos_interval(stride_nanos: i64, source: i64, origin: i64) -> Result<i64> {
let time_diff = source.checked_sub(origin).ok_or_else(|| {
arrow::error::ArrowError::InvalidArgumentError(format!(
ArrowError::InvalidArgumentError(format!(
"date_bin source timestamp {source} - origin {origin} overflows i64"
))
})?;
Expand All @@ -331,7 +334,7 @@ fn date_bin_nanos_interval(stride_nanos: i64, source: i64, origin: i64) -> Resul
let time_delta = compute_distance(time_diff, stride_nanos)?;

origin.checked_add(time_delta).ok_or_else(|| {
arrow::error::ArrowError::InvalidArgumentError(format!(
ArrowError::InvalidArgumentError(format!(
"date_bin origin {origin} + delta {time_delta} overflows i64"
))
.into()
Expand All @@ -341,20 +344,20 @@ fn date_bin_nanos_interval(stride_nanos: i64, source: i64, origin: i64) -> Resul
// distance from origin to bin
fn compute_distance(time_diff: i64, stride: i64) -> Result<i64> {
let remainder = time_diff.checked_rem(stride).ok_or_else(|| {
arrow::error::ArrowError::InvalidArgumentError(format!(
ArrowError::InvalidArgumentError(format!(
"date_bin compute_distance time_diff {time_diff} % stride {stride} overflows i64"
))
})?;
let time_delta = time_diff.checked_sub(remainder).ok_or_else(|| {
arrow::error::ArrowError::InvalidArgumentError(format!(
ArrowError::InvalidArgumentError(format!(
"date_bin compute_distance time_diff {time_diff} - remainder {remainder} overflows i64"
))
})?;

if time_diff < 0 && stride > 1 && time_delta != time_diff {
// The origin is later than the source timestamp, round down to the previous bin
time_delta.checked_sub(stride).ok_or_else(|| {
arrow::error::ArrowError::InvalidArgumentError(format!(
ArrowError::InvalidArgumentError(format!(
"date_bin compute_distance time_delta {time_delta} - stride {stride} overflows i64"
))
.into()
Expand Down Expand Up @@ -594,53 +597,91 @@ fn date_bin_impl(
return exec_err!("DATE_BIN stride must be non-zero");
}

fn stride_map_fn<T: ArrowTimestampType>(
origin: i64,
stride: i64,
stride_fn: BinFunction,
) -> impl Fn(i64) -> Result<i64> {
let scale = match T::UNIT {
fn timestamp_scale<T: ArrowTimestampType>() -> i64 {
match T::UNIT {
Nanosecond => 1,
Microsecond => NANOS_PER_MICRO,
Millisecond => NANOS_PER_MILLI,
Second => NANOSECONDS,
};
move |x: i64| match stride_fn(stride, x * scale, origin) {
Ok(result) => Ok(result / scale),
Err(e) => Err(e),
}
}

fn timestamp_scale_overflow_error(x: i64) -> DataFusionError {
DataFusionError::Execution(format!(
"DATE_BIN source timestamp {x} cannot be represented in nanoseconds"
))
}

Ok(match array {
ColumnarValue::Scalar(ScalarValue::TimestampNanosecond(v, tz_opt)) => {
let apply_stride_fn =
stride_map_fn::<TimestampNanosecondType>(origin, stride, stride_fn);
let scale = timestamp_scale::<TimestampNanosecondType>();
ColumnarValue::Scalar(ScalarValue::TimestampNanosecond(
v.and_then(|val| apply_stride_fn(val).ok()),
match *v {
Some(val) => {
let scaled = val
.checked_mul(scale)
.ok_or_else(|| timestamp_scale_overflow_error(val))?;
match stride_fn(stride, scaled, origin) {
Ok(result) => Some(result / scale),
Err(_) => None,
}
Comment thread
xiedeyantu marked this conversation as resolved.
}
None => None,
},
tz_opt.clone(),
))
}
ColumnarValue::Scalar(ScalarValue::TimestampMicrosecond(v, tz_opt)) => {
let apply_stride_fn =
stride_map_fn::<TimestampMicrosecondType>(origin, stride, stride_fn);
let scale = timestamp_scale::<TimestampMicrosecondType>();
ColumnarValue::Scalar(ScalarValue::TimestampMicrosecond(
v.and_then(|val| apply_stride_fn(val).ok()),
match *v {
Some(val) => {
let scaled = val
.checked_mul(scale)
.ok_or_else(|| timestamp_scale_overflow_error(val))?;
match stride_fn(stride, scaled, origin) {
Ok(result) => Some(result / scale),
Err(_) => None,
}
}
None => None,
},
tz_opt.clone(),
))
}
ColumnarValue::Scalar(ScalarValue::TimestampMillisecond(v, tz_opt)) => {
let apply_stride_fn =
stride_map_fn::<TimestampMillisecondType>(origin, stride, stride_fn);
let scale = timestamp_scale::<TimestampMillisecondType>();
ColumnarValue::Scalar(ScalarValue::TimestampMillisecond(
v.and_then(|val| apply_stride_fn(val).ok()),
match *v {
Some(val) => {
let scaled = val
.checked_mul(scale)
.ok_or_else(|| timestamp_scale_overflow_error(val))?;
match stride_fn(stride, scaled, origin) {
Ok(result) => Some(result / scale),
Err(_) => None,
}
}
None => None,
},
tz_opt.clone(),
))
}
ColumnarValue::Scalar(ScalarValue::TimestampSecond(v, tz_opt)) => {
let apply_stride_fn =
stride_map_fn::<TimestampSecondType>(origin, stride, stride_fn);
let scale = timestamp_scale::<TimestampSecondType>();
ColumnarValue::Scalar(ScalarValue::TimestampSecond(
v.and_then(|val| apply_stride_fn(val).ok()),
match *v {
Some(val) => {
let scaled = val
.checked_mul(scale)
.ok_or_else(|| timestamp_scale_overflow_error(val))?;
match stride_fn(stride, scaled, origin) {
Ok(result) => Some(result / scale),
Err(_) => None,
}
}
None => None,
},
tz_opt.clone(),
))
}
Expand Down Expand Up @@ -710,20 +751,24 @@ fn date_bin_impl(
T: ArrowTimestampType,
{
let array = as_primitive_array::<T>(array)?;
let scale = match T::UNIT {
Nanosecond => 1,
Microsecond => NANOS_PER_MICRO,
Millisecond => NANOS_PER_MILLI,
Second => NANOSECONDS,
};

let result: PrimitiveArray<T> = array.try_unary(|val| {
stride_fn(stride, val * scale, origin)
.map(|binned| binned / scale)
.map_err(|e| {
arrow::error::ArrowError::ComputeError(e.to_string())
})
})?;
let scale = timestamp_scale::<T>();

let values = array
.iter()
.map(|val| match val {
Some(val) => {
let scaled = val
.checked_mul(scale)
.ok_or_else(|| timestamp_scale_overflow_error(val))?;
Ok(stride_fn(stride, scaled, origin)
.ok()

@Jefffrey Jefffrey May 30, 2026

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cc @kumarUjjawal I think this will overlap with your PR

@kumarUjjawal kumarUjjawal May 31, 2026

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Thanks @Jefffrey I will wait for this to get merged as I am doing some cleanup too.

.map(|binned| binned / scale))
}
None => Ok(None),
})
.collect::<Result<Vec<_>>>()?;

let result = PrimitiveArray::<T>::from_iter(values);

let array = result.with_timezone_opt(tz_opt.clone());
Ok(ColumnarValue::Array(Arc::new(array)))
Expand Down Expand Up @@ -764,9 +809,7 @@ fn date_bin_impl(
let nanos = binned_nanos % (NANOSECONDS_IN_DAY);
(nanos / NANOS_PER_MILLI) as i32
})
.map_err(|e| {
arrow::error::ArrowError::ComputeError(e.to_string())
})
.map_err(|e| ArrowError::ComputeError(e.to_string()))
})?;
ColumnarValue::Array(Arc::new(result))
}
Expand All @@ -784,9 +827,7 @@ fn date_bin_impl(
let nanos = binned_nanos % (NANOSECONDS_IN_DAY);
(nanos / NANOS_PER_SEC) as i32
})
.map_err(|e| {
arrow::error::ArrowError::ComputeError(e.to_string())
})
.map_err(|e| ArrowError::ComputeError(e.to_string()))
})?;
ColumnarValue::Array(Arc::new(result))
}
Expand All @@ -804,9 +845,7 @@ fn date_bin_impl(
let nanos = binned_nanos % (NANOSECONDS_IN_DAY);
nanos / NANOS_PER_MICRO
})
.map_err(|e| {
arrow::error::ArrowError::ComputeError(e.to_string())
})
.map_err(|e| ArrowError::ComputeError(e.to_string()))
})?;
ColumnarValue::Array(Arc::new(result))
}
Expand All @@ -821,9 +860,7 @@ fn date_bin_impl(
array.try_unary(|x| {
stride_fn(stride, x, origin)
.map(|binned_nanos| binned_nanos % (NANOSECONDS_IN_DAY))
.map_err(|e| {
arrow::error::ArrowError::ComputeError(e.to_string())
})
.map_err(|e| ArrowError::ComputeError(e.to_string()))
})?;
ColumnarValue::Array(Arc::new(result))
}
Expand Down
21 changes: 20 additions & 1 deletion datafusion/sqllogictest/test_files/date_bin_errors.slt
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Original file line number Diff line number Diff line change
Expand Up @@ -77,4 +77,23 @@ select date_bin(
arrow_cast(-9223372036854775808, 'Timestamp(Nanosecond, None)')
);
----
NULL
NULL

# Source timestamp scaling to nanoseconds overflows: should return an error, not panic
query error DataFusion error: Execution error: DATE_BIN source timestamp 9223372036854775807 cannot be represented in nanoseconds
select date_bin(
interval '1 nanosecond',
arrow_cast(9223372036854775807, 'Timestamp(Second, None)'),
timestamp '1970-01-01 00:00:00'
);

# Source timestamp scaling to nanoseconds overflows in array path: should return an error, not panic
query error DataFusion error: Execution error: DATE_BIN source timestamp 9223372036854775807 cannot be represented in nanoseconds
select date_bin(
interval '1 nanosecond',
ts,
timestamp '1970-01-01 00:00:00'
)
from (
values (arrow_cast(9223372036854775807, 'Timestamp(Second, None)'))
) as t(ts);
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