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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
//! Defines partition kernel for `ArrayRef`
use crate::compute::kernels::sort::LexicographicalComparator;
use crate::compute::SortColumn;
use crate::error::{ArrowError, Result};
use std::cmp::Ordering;
use std::iter::Iterator;
use std::ops::Range;
/// Given a list of already sorted columns, find partition ranges that would partition
/// lexicographically equal values across columns.
///
/// Here LexicographicalComparator is used in conjunction with binary
/// search so the columns *MUST* be pre-sorted already.
///
/// The returned vec would be of size k where k is cardinality of the sorted values; Consecutive
/// values will be connected: (a, b) and (b, c), where start = 0 and end = n for the first and last
/// range.
pub fn lexicographical_partition_ranges(
columns: &[SortColumn],
) -> Result<impl Iterator<Item = Range<usize>> + '_> {
LexicographicalPartitionIterator::try_new(columns)
}
struct LexicographicalPartitionIterator<'a> {
comparator: LexicographicalComparator<'a>,
num_rows: usize,
previous_partition_point: usize,
partition_point: usize,
value_indices: Vec<usize>,
}
impl<'a> LexicographicalPartitionIterator<'a> {
fn try_new(columns: &'a [SortColumn]) -> Result<LexicographicalPartitionIterator> {
if columns.is_empty() {
return Err(ArrowError::InvalidArgumentError(
"Sort requires at least one column".to_string(),
));
}
let num_rows = columns[0].values.len();
if columns.iter().any(|item| item.values.len() != num_rows) {
return Err(ArrowError::ComputeError(
"Lexical sort columns have different row counts".to_string(),
));
};
let comparator = LexicographicalComparator::try_new(columns)?;
let value_indices = (0..num_rows).collect::<Vec<usize>>();
Ok(LexicographicalPartitionIterator {
comparator,
num_rows,
previous_partition_point: 0,
partition_point: 0,
value_indices,
})
}
}
impl<'a> Iterator for LexicographicalPartitionIterator<'a> {
type Item = Range<usize>;
fn next(&mut self) -> Option<Self::Item> {
if self.partition_point < self.num_rows {
// invariant:
// value_indices[0..previous_partition_point] all are values <= value_indices[previous_partition_point]
// so in order to save time we can do binary search on the value_indices[previous_partition_point..]
// and find when any value is greater than value_indices[previous_partition_point]; because we are using
// new indices, the new offset is _added_ to the previous_partition_point.
//
// be careful that idx is of type &usize which points to the actual value within value_indices, which itself
// contains usize (0..row_count), providing access to lexicographical_comparator as pointers into the
// original columnar data.
self.partition_point += self.value_indices[self.partition_point..]
.partition_point(|idx| {
self.comparator.compare(idx, &self.partition_point)
!= Ordering::Greater
});
let start = self.previous_partition_point;
let end = self.partition_point;
self.previous_partition_point = self.partition_point;
Some(Range { start, end })
} else {
None
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::array::*;
use crate::compute::SortOptions;
use crate::datatypes::DataType;
use std::sync::Arc;
#[test]
fn test_lexicographical_partition_ranges_empty() {
let input = vec![];
assert!(
lexicographical_partition_ranges(&input).is_err(),
"lexicographical_partition_ranges should reject columns with empty rows"
);
}
#[test]
fn test_lexicographical_partition_ranges_unaligned_rows() {
let input = vec![
SortColumn {
values: Arc::new(Int64Array::from(vec![None, Some(-1)])) as ArrayRef,
options: None,
},
SortColumn {
values: Arc::new(StringArray::from(vec![Some("foo")])) as ArrayRef,
options: None,
},
];
assert!(
lexicographical_partition_ranges(&input).is_err(),
"lexicographical_partition_ranges should reject columns with different row counts"
);
}
#[test]
fn test_lexicographical_partition_single_column() -> Result<()> {
let input = vec![SortColumn {
values: Arc::new(Int64Array::from(vec![1, 2, 2, 2, 2, 2, 2, 2, 9]))
as ArrayRef,
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
}];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(
vec![(0_usize..1_usize), (1_usize..8_usize), (8_usize..9_usize)],
results.collect::<Vec<_>>()
);
}
Ok(())
}
#[test]
fn test_lexicographical_partition_all_equal_values() -> Result<()> {
let input = vec![SortColumn {
values: Arc::new(Int64Array::from_value(1, 1000)) as ArrayRef,
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
}];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(vec![(0_usize..1000_usize)], results.collect::<Vec<_>>());
}
Ok(())
}
#[test]
fn test_lexicographical_partition_all_null_values() -> Result<()> {
let input = vec![
SortColumn {
values: new_null_array(&DataType::Int8, 1000),
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
},
SortColumn {
values: new_null_array(&DataType::UInt16, 1000),
options: Some(SortOptions {
descending: false,
nulls_first: false,
}),
},
];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(vec![(0_usize..1000_usize)], results.collect::<Vec<_>>());
}
Ok(())
}
#[test]
fn test_lexicographical_partition_unique_column_1() -> Result<()> {
let input = vec![
SortColumn {
values: Arc::new(Int64Array::from(vec![None, Some(-1)])) as ArrayRef,
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
},
SortColumn {
values: Arc::new(StringArray::from(vec![Some("foo"), Some("bar")]))
as ArrayRef,
options: Some(SortOptions {
descending: true,
nulls_first: true,
}),
},
];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(
vec![(0_usize..1_usize), (1_usize..2_usize)],
results.collect::<Vec<_>>()
);
}
Ok(())
}
#[test]
fn test_lexicographical_partition_unique_column_2() -> Result<()> {
let input = vec![
SortColumn {
values: Arc::new(Int64Array::from(vec![None, Some(-1), Some(-1)]))
as ArrayRef,
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
},
SortColumn {
values: Arc::new(StringArray::from(vec![
Some("foo"),
Some("bar"),
Some("apple"),
])) as ArrayRef,
options: Some(SortOptions {
descending: true,
nulls_first: true,
}),
},
];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(
vec![(0_usize..1_usize), (1_usize..2_usize), (2_usize..3_usize),],
results.collect::<Vec<_>>()
);
}
Ok(())
}
#[test]
fn test_lexicographical_partition_non_unique_column_1() -> Result<()> {
let input = vec![
SortColumn {
values: Arc::new(Int64Array::from(vec![
None,
Some(-1),
Some(-1),
Some(1),
])) as ArrayRef,
options: Some(SortOptions {
descending: false,
nulls_first: true,
}),
},
SortColumn {
values: Arc::new(StringArray::from(vec![
Some("foo"),
Some("bar"),
Some("bar"),
Some("bar"),
])) as ArrayRef,
options: Some(SortOptions {
descending: true,
nulls_first: true,
}),
},
];
{
let results = lexicographical_partition_ranges(&input)?;
assert_eq!(
vec![(0_usize..1_usize), (1_usize..3_usize), (3_usize..4_usize),],
results.collect::<Vec<_>>()
);
}
Ok(())
}
}