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Merged
luoyuxia merged 4 commits into from
Jan 26, 2026
+507 −48
Merged

test: add it for produce & scan log for all supported datatypes #205

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89d8b57
test: add it for produce & scan log for all supported datatypes
Jan 23, 2026
311888a
support timestamps before the Unix epoch.
Jan 24, 2026
53b32a9
fix get_char
Jan 25, 2026
17d4219
fix build
Jan 26, 2026
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164 changes: 116 additions & 48 deletions crates/fluss/src/row/column.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,11 @@

use crate::row::InternalRow;
use arrow::array::{
Array, AsArray, BinaryArray, Decimal128Array, FixedSizeBinaryArray, Float32Array, Float64Array,
Int8Array, Int16Array, Int32Array, Int64Array, RecordBatch, StringArray,
Array, AsArray, BinaryArray, Date32Array, Decimal128Array, FixedSizeBinaryArray, Float32Array,
Float64Array, Int8Array, Int16Array, Int32Array, Int64Array, RecordBatch, StringArray,
Time32MillisecondArray, Time32SecondArray, Time64MicrosecondArray, Time64NanosecondArray,
TimestampMicrosecondArray, TimestampMillisecondArray, TimestampNanosecondArray,
TimestampSecondArray,
};
use arrow::datatypes::{DataType as ArrowDataType, TimeUnit};
use std::sync::Arc;
Expand Down Expand Up @@ -67,35 +70,110 @@ impl ColumnarRow {
) -> T {
let schema = self.record_batch.schema();
let arrow_field = schema.field(pos);
let value = self.get_long(pos);
let column = self.record_batch.column(pos);

match arrow_field.data_type() {
ArrowDataType::Timestamp(time_unit, _) => {
// Convert based on Arrow TimeUnit
let (millis, nanos) = match time_unit {
TimeUnit::Second => (value * 1000, 0),
TimeUnit::Millisecond => (value, 0),
TimeUnit::Microsecond => {
let millis = value / 1000;
let nanos = ((value % 1000) * 1000) as i32;
(millis, nanos)
}
TimeUnit::Nanosecond => {
let millis = value / 1_000_000;
let nanos = (value % 1_000_000) as i32;
(millis, nanos)
}
};

if nanos == 0 {
construct_compact(millis)
} else {
// nanos is guaranteed to be in valid range [0, 999_999] by arithmetic
construct_with_nanos(millis, nanos)
.expect("nanos in valid range by construction")
// Read value based on the actual Arrow timestamp type
let value = match arrow_field.data_type() {
ArrowDataType::Timestamp(TimeUnit::Second, _) => column
.as_any()
.downcast_ref::<TimestampSecondArray>()
.expect("Expected TimestampSecondArray")
.value(self.row_id),
ArrowDataType::Timestamp(TimeUnit::Millisecond, _) => column
.as_any()
.downcast_ref::<TimestampMillisecondArray>()
.expect("Expected TimestampMillisecondArray")
.value(self.row_id),
ArrowDataType::Timestamp(TimeUnit::Microsecond, _) => column
.as_any()
.downcast_ref::<TimestampMicrosecondArray>()
.expect("Expected TimestampMicrosecondArray")
.value(self.row_id),
ArrowDataType::Timestamp(TimeUnit::Nanosecond, _) => column
.as_any()
.downcast_ref::<TimestampNanosecondArray>()
.expect("Expected TimestampNanosecondArray")
.value(self.row_id),
other => panic!("Expected Timestamp column at position {pos}, got {other:?}"),
};

// Convert based on Arrow TimeUnit
let (millis, nanos) = match arrow_field.data_type() {
ArrowDataType::Timestamp(time_unit, _) => match time_unit {
TimeUnit::Second => (value * 1000, 0),
TimeUnit::Millisecond => (value, 0),
TimeUnit::Microsecond => {
// Use Euclidean division so that nanos is always non-negative,
// even for timestamps before the Unix epoch.
let millis = value.div_euclid(1000);
let nanos = (value.rem_euclid(1000) * 1000) as i32;
(millis, nanos)
}
TimeUnit::Nanosecond => {
// Use Euclidean division so that nanos is always in [0, 999_999].
let millis = value.div_euclid(1_000_000);
let nanos = value.rem_euclid(1_000_000) as i32;
(millis, nanos)
}
},
_ => unreachable!(),
};

if nanos == 0 {
construct_compact(millis)
} else {
// nanos is guaranteed to be in valid range [0, 999_999] by arithmetic
construct_with_nanos(millis, nanos).expect("nanos in valid range by construction")
}
}

/// Read date value from Arrow Date32Array
fn read_date_from_arrow(&self, pos: usize) -> i32 {
self.record_batch
.column(pos)
.as_any()
.downcast_ref::<Date32Array>()
.expect("Expected Date32Array")
.value(self.row_id)
}

/// Read time value from Arrow Time32/Time64 arrays, converting to milliseconds
fn read_time_from_arrow(&self, pos: usize) -> i32 {
let schema = self.record_batch.schema();
let arrow_field = schema.field(pos);
let column = self.record_batch.column(pos);

match arrow_field.data_type() {
ArrowDataType::Time32(TimeUnit::Second) => {
let value = column
.as_any()
.downcast_ref::<Time32SecondArray>()
.expect("Expected Time32SecondArray")
.value(self.row_id);
value * 1000 // Convert seconds to milliseconds
}
other => panic!("Expected Timestamp column at position {pos}, got {other:?}"),
ArrowDataType::Time32(TimeUnit::Millisecond) => column
.as_any()
.downcast_ref::<Time32MillisecondArray>()
.expect("Expected Time32MillisecondArray")
.value(self.row_id),
ArrowDataType::Time64(TimeUnit::Microsecond) => {
let value = column
.as_any()
.downcast_ref::<Time64MicrosecondArray>()
.expect("Expected Time64MicrosecondArray")
.value(self.row_id);
(value / 1000) as i32 // Convert microseconds to milliseconds
}
ArrowDataType::Time64(TimeUnit::Nanosecond) => {
let value = column
.as_any()
.downcast_ref::<Time64NanosecondArray>()
.expect("Expected Time64NanosecondArray")
.value(self.row_id);
(value / 1_000_000) as i32 // Convert nanoseconds to milliseconds
}
other => panic!("Expected Time column at position {pos}, got {other:?}"),
}
}
}
Expand Down Expand Up @@ -220,11 +298,11 @@ impl InternalRow for ColumnarRow {
}

fn get_date(&self, pos: usize) -> crate::row::datum::Date {
crate::row::datum::Date::new(self.get_int(pos))
crate::row::datum::Date::new(self.read_date_from_arrow(pos))
}

fn get_time(&self, pos: usize) -> crate::row::datum::Time {
crate::row::datum::Time::new(self.get_int(pos))
crate::row::datum::Time::new(self.read_time_from_arrow(pos))
}

fn get_timestamp_ntz(&self, pos: usize, precision: u32) -> crate::row::datum::TimestampNtz {
Expand All @@ -250,16 +328,12 @@ impl InternalRow for ColumnarRow {
}

fn get_char(&self, pos: usize, _length: usize) -> &str {
let array = self
.record_batch
self.record_batch
.column(pos)
.as_any()
.downcast_ref::<FixedSizeBinaryArray>()
.expect("Expected fixed-size binary array for char type");

let bytes = array.value(self.row_id);
// don't check length, following java client
std::str::from_utf8(bytes).expect("Invalid UTF-8 in char field")
.downcast_ref::<StringArray>()
.expect("Expected String array for char type")
.value(self.row_id)
}

fn get_string(&self, pos: usize) -> &str {
Expand Down Expand Up @@ -294,8 +368,8 @@ impl InternalRow for ColumnarRow {
mod tests {
use super::*;
use arrow::array::{
BinaryArray, BooleanArray, FixedSizeBinaryArray, Float32Array, Float64Array, Int8Array,
Int16Array, Int32Array, Int64Array, StringArray,
BinaryArray, BooleanArray, Float32Array, Float64Array, Int8Array, Int16Array, Int32Array,
Int64Array, StringArray,
};
use arrow::datatypes::{DataType, Field, Schema};

Expand All @@ -311,7 +385,7 @@ mod tests {
Field::new("f64", DataType::Float64, false),
Field::new("s", DataType::Utf8, false),
Field::new("bin", DataType::Binary, false),
Field::new("char", DataType::FixedSizeBinary(2), false),
Field::new("char", DataType::Utf8, false),
]));

let batch = RecordBatch::try_new(
Expand All @@ -326,13 +400,7 @@ mod tests {
Arc::new(Float64Array::from(vec![2.5])),
Arc::new(StringArray::from(vec!["hello"])),
Arc::new(BinaryArray::from(vec![b"data".as_slice()])),
Arc::new(
FixedSizeBinaryArray::try_from_sparse_iter_with_size(
vec![Some(b"ab".as_slice())].into_iter(),
2,
)
.expect("fixed array"),
),
Arc::new(StringArray::from(vec!["ab"])),
],
)
.expect("record batch");
Expand Down
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