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[branch-51]: Add timezone to date_trunc fast path (#18596) #18629

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merged 1 commit into from
Nov 12, 2025
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[branch-51]: Add timezone to date_trunc fast path (#18596) #18629

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177 changes: 176 additions & 1 deletion datafusion/functions/src/datetime/date_trunc.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -276,6 +276,7 @@ impl ScalarUDFImpl for DateTruncFunc {
T::UNIT,
array,
granularity,
tz_opt.clone(),
)?;
return Ok(ColumnarValue::Array(result));
}
Expand Down Expand Up @@ -522,6 +523,7 @@ fn general_date_trunc_array_fine_granularity<T: ArrowTimestampType>(
tu: TimeUnit,
array: &PrimitiveArray<T>,
granularity: DateTruncGranularity,
tz_opt: Option<Arc<str>>,
) -> Result<ArrayRef> {
let unit = match (tu, granularity) {
(Second, DateTruncGranularity::Minute) => NonZeroI64::new(60),
Expand Down Expand Up @@ -556,7 +558,8 @@ fn general_date_trunc_array_fine_granularity<T: ArrowTimestampType>(
.iter()
.map(|v| *v - i64::rem_euclid(*v, unit)),
array.nulls().cloned(),
);
)
.with_timezone_opt(tz_opt);
Ok(Arc::new(array))
} else {
// truncate to the same or smaller unit
Expand Down Expand Up @@ -1094,4 +1097,176 @@ mod tests {
}
});
}

#[test]
fn test_date_trunc_fine_granularity_timezones() {
let cases = [
// Test "second" granularity
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:42:30.500000Z",
"2020-09-08T13:42:31.999999Z",
],
Some("+00".into()),
"second",
vec![
"2020-09-08T13:42:29.000000Z",
"2020-09-08T13:42:30.000000Z",
"2020-09-08T13:42:31.000000Z",
],
),
(
vec![
"2020-09-08T13:42:29.190855+05",
"2020-09-08T13:42:30.500000+05",
"2020-09-08T13:42:31.999999+05",
],
Some("+05".into()),
"second",
vec![
"2020-09-08T13:42:29.000000+05",
"2020-09-08T13:42:30.000000+05",
"2020-09-08T13:42:31.000000+05",
],
),
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:42:30.500000Z",
"2020-09-08T13:42:31.999999Z",
],
Some("Europe/Berlin".into()),
"second",
vec![
"2020-09-08T13:42:29.000000Z",
"2020-09-08T13:42:30.000000Z",
"2020-09-08T13:42:31.000000Z",
],
),
// Test "minute" granularity
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:43:30.500000Z",
"2020-09-08T13:44:31.999999Z",
],
Some("+00".into()),
"minute",
vec![
"2020-09-08T13:42:00.000000Z",
"2020-09-08T13:43:00.000000Z",
"2020-09-08T13:44:00.000000Z",
],
),
(
vec![
"2020-09-08T13:42:29.190855+08",
"2020-09-08T13:43:30.500000+08",
"2020-09-08T13:44:31.999999+08",
],
Some("+08".into()),
"minute",
vec![
"2020-09-08T13:42:00.000000+08",
"2020-09-08T13:43:00.000000+08",
"2020-09-08T13:44:00.000000+08",
],
),
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:43:30.500000Z",
"2020-09-08T13:44:31.999999Z",
],
Some("America/Sao_Paulo".into()),
"minute",
vec![
"2020-09-08T13:42:00.000000Z",
"2020-09-08T13:43:00.000000Z",
"2020-09-08T13:44:00.000000Z",
],
),
// Test with None (no timezone)
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:43:30.500000Z",
"2020-09-08T13:44:31.999999Z",
],
None,
"minute",
vec![
"2020-09-08T13:42:00.000000Z",
"2020-09-08T13:43:00.000000Z",
"2020-09-08T13:44:00.000000Z",
],
),
// Test millisecond granularity
(
vec![
"2020-09-08T13:42:29.190855Z",
"2020-09-08T13:42:29.191999Z",
"2020-09-08T13:42:29.192500Z",
],
Some("Asia/Kolkata".into()),
"millisecond",
vec![
"2020-09-08T19:12:29.190000+05:30",
"2020-09-08T19:12:29.191000+05:30",
"2020-09-08T19:12:29.192000+05:30",
],
),
];

cases
.iter()
.for_each(|(original, tz_opt, granularity, expected)| {
let input = original
.iter()
.map(|s| Some(string_to_timestamp_nanos(s).unwrap()))
.collect::<TimestampNanosecondArray>()
.with_timezone_opt(tz_opt.clone());
let right = expected
.iter()
.map(|s| Some(string_to_timestamp_nanos(s).unwrap()))
.collect::<TimestampNanosecondArray>()
.with_timezone_opt(tz_opt.clone());
let batch_len = input.len();
let arg_fields = vec![
Field::new("a", DataType::Utf8, false).into(),
Field::new("b", input.data_type().clone(), false).into(),
];
let args = datafusion_expr::ScalarFunctionArgs {
args: vec![
ColumnarValue::Scalar(ScalarValue::from(*granularity)),
ColumnarValue::Array(Arc::new(input)),
],
arg_fields,
number_rows: batch_len,
return_field: Field::new(
"f",
DataType::Timestamp(TimeUnit::Nanosecond, tz_opt.clone()),
true,
)
.into(),
config_options: Arc::new(ConfigOptions::default()),
};
let result = DateTruncFunc::new().invoke_with_args(args).unwrap();
if let ColumnarValue::Array(result) = result {
assert_eq!(
result.data_type(),
&DataType::Timestamp(TimeUnit::Nanosecond, tz_opt.clone()),
"Failed for granularity: {granularity}, timezone: {tz_opt:?}"
);
let left = as_primitive_array::<TimestampNanosecondType>(&result);
assert_eq!(
left, &right,
"Failed for granularity: {granularity}, timezone: {tz_opt:?}"
);
} else {
panic!("unexpected column type");
}
});
}
}
55 changes: 34 additions & 21 deletions datafusion/sqllogictest/test_files/timestamps.slt
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Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,9 @@ create table ts_data_millis as select arrow_cast(ts / 1000000, 'Timestamp(Millis
statement ok
create table ts_data_secs as select arrow_cast(ts / 1000000000, 'Timestamp(Second, None)') as ts, value from ts_data;

statement ok
create table ts_data_micros_kolkata as select arrow_cast(ts / 1000, 'Timestamp(Microsecond, Some("Asia/Kolkata"))') as ts, value from ts_data;


##########
## Current date Tests
Expand Down Expand Up @@ -1873,27 +1876,6 @@ true false true true



##########
## Common timestamp data
##########

statement ok
drop table ts_data

statement ok
drop table ts_data_nanos

statement ok
drop table ts_data_micros

statement ok
drop table ts_data_millis

statement ok
drop table ts_data_secs



##########
## Timezone impact on scalar functions
#
Expand Down Expand Up @@ -3703,3 +3685,34 @@ SELECT
FROM (SELECT CAST('2005-09-10 13:31:00 +02:00' AS timestamp with time zone) AS a)
----
Timestamp(ns, "+00") 2005-09-10T11:31:00Z 2005-09-10T11:31:00Z 2005-09-10T11:31:00Z 2005-09-10T11:31:00Z

query P
SELECT
date_trunc('millisecond', ts)
FROM ts_data_micros_kolkata
----
2020-09-08T19:12:29.190+05:30
2020-09-08T18:12:29.190+05:30
2020-09-08T17:12:29.190+05:30

##########
## Common timestamp data
##########

statement ok
drop table ts_data

statement ok
drop table ts_data_nanos

statement ok
drop table ts_data_micros

statement ok
drop table ts_data_millis

statement ok
drop table ts_data_secs

statement ok
drop table ts_data_micros_kolkata
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