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#[cfg(feature = "groupby_list")]
use polars_arrow::kernels::list_bytes_iter::numeric_list_bytes_iter;
use polars_arrow::kernels::sort_partition::{create_clean_partitions, partition_to_groups};
use polars_arrow::prelude::*;
use polars_utils::{flatten, HashSingle};
use super::*;
use crate::utils::{_split_offsets, copy_from_slice_unchecked};
pub trait IntoGroupsProxy {
fn group_tuples(&self, _multithreaded: bool, _sorted: bool) -> PolarsResult<GroupsProxy> {
unimplemented!()
}
}
fn group_multithreaded<T: PolarsDataType>(ca: &ChunkedArray<T>) -> bool {
ca.len() > 1000
}
fn num_groups_proxy<T>(ca: &ChunkedArray<T>, multithreaded: bool, sorted: bool) -> GroupsProxy
where
T: PolarsIntegerType,
T::Native: Hash + Eq + Send + AsU64,
Option<T::Native>: AsU64,
{
#[cfg(feature = "dtype-categorical")]
let group_size_hint = if let Some(m) = &ca.categorical_map {
ca.len() / m.len()
} else {
0
};
#[cfg(not(feature = "dtype-categorical"))]
let group_size_hint = 0;
if multithreaded && group_multithreaded(ca) {
let n_partitions = _set_partition_size() as u64;
if ca.chunks.len() == 1 {
if !ca.has_validity() {
let keys = vec![ca.cont_slice().unwrap()];
groupby_threaded_num(keys, group_size_hint, n_partitions, sorted)
} else {
let keys = ca
.downcast_iter()
.map(|arr| arr.into_iter().map(|x| x.copied()).collect::<Vec<_>>())
.collect::<Vec<_>>();
groupby_threaded_num(keys, group_size_hint, n_partitions, sorted)
}
} else if !ca.has_validity() {
let keys = vec![ca.into_no_null_iter().collect::<Vec<_>>()];
groupby_threaded_num(keys, group_size_hint, n_partitions, sorted)
} else {
let keys = vec![ca.into_iter().collect::<Vec<_>>()];
groupby_threaded_num(keys, group_size_hint, n_partitions, sorted)
}
} else if !ca.has_validity() {
groupby(ca.into_no_null_iter(), sorted)
} else {
groupby(ca.into_iter(), sorted)
}
}
impl<T> ChunkedArray<T>
where
T: PolarsNumericType,
T::Native: NumCast,
{
fn create_groups_from_sorted(&self, multithreaded: bool) -> GroupsSlice {
if std::env::var("POLARS_VERBOSE").as_deref().unwrap_or("0") == "1" {
eprintln!("groupby keys are sorted; running sorted key fast path");
}
let arr = self.downcast_iter().next().unwrap();
if arr.is_empty() {
return GroupsSlice::default();
}
let mut values = arr.values().as_slice();
let null_count = arr.null_count();
let mut nulls_first = false;
if null_count > 0 {
nulls_first = arr.get(0).is_none()
}
if nulls_first {
values = &values[null_count..];
} else {
values = &values[..values.len() - null_count];
}
let n_threads = POOL.current_num_threads();
let groups = if multithreaded && n_threads > 1 {
let parts = create_clean_partitions(values, n_threads, self.is_sorted_reverse());
let n_parts = parts.len();
let first_ptr = &values[0] as *const T::Native as usize;
let groups = POOL
.install(|| {
parts.par_iter().enumerate().map(|(i, part)| {
let first_ptr = first_ptr as *const T::Native;
let part_first_ptr = &part[0] as *const T::Native;
let mut offset =
unsafe { part_first_ptr.offset_from(first_ptr) } as IdxSize;
if nulls_first && i == 0 {
partition_to_groups(part, null_count as IdxSize, true, offset)
}
else if !nulls_first && i == n_parts - 1 {
partition_to_groups(part, null_count as IdxSize, false, offset)
}
else {
if nulls_first {
offset += null_count as IdxSize;
};
partition_to_groups(part, 0, false, offset)
}
})
})
.collect::<Vec<_>>();
flatten(&groups, None)
} else {
partition_to_groups(values, null_count as IdxSize, nulls_first, 0)
};
groups
}
}
impl<T> IntoGroupsProxy for ChunkedArray<T>
where
T: PolarsNumericType,
T::Native: NumCast,
{
fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
if self.is_sorted() || self.is_sorted_reverse() && self.chunks().len() == 1 {
return Ok(GroupsProxy::Slice {
groups: self.create_groups_from_sorted(multithreaded),
rolling: false,
});
}
let out = match self.dtype() {
DataType::UInt64 => {
let ca: &UInt64Chunked = unsafe {
&*(self as *const ChunkedArray<T> as *const ChunkedArray<UInt64Type>)
};
num_groups_proxy(ca, multithreaded, sorted)
}
DataType::UInt32 => {
let ca: &UInt32Chunked = unsafe {
&*(self as *const ChunkedArray<T> as *const ChunkedArray<UInt32Type>)
};
num_groups_proxy(ca, multithreaded, sorted)
}
DataType::Int64 | DataType::Float64 => {
let ca = self.bit_repr_large();
num_groups_proxy(&ca, multithreaded, sorted)
}
DataType::Int32 | DataType::Float32 => {
let ca = self.bit_repr_small();
num_groups_proxy(&ca, multithreaded, sorted)
}
#[cfg(feature = "performant")]
DataType::Int8 => {
let ca: &Int8Chunked =
unsafe { &*(self as *const ChunkedArray<T> as *const ChunkedArray<Int8Type>) };
let ca = ca.reinterpret_unsigned();
num_groups_proxy(&ca, multithreaded, sorted)
}
#[cfg(feature = "performant")]
DataType::UInt8 => {
let ca: &UInt8Chunked =
unsafe { &*(self as *const ChunkedArray<T> as *const ChunkedArray<UInt8Type>) };
num_groups_proxy(ca, multithreaded, sorted)
}
#[cfg(feature = "performant")]
DataType::Int16 => {
let ca: &Int16Chunked =
unsafe { &*(self as *const ChunkedArray<T> as *const ChunkedArray<Int16Type>) };
let ca = ca.reinterpret_unsigned();
num_groups_proxy(&ca, multithreaded, sorted)
}
#[cfg(feature = "performant")]
DataType::UInt16 => {
let ca: &UInt16Chunked = unsafe {
&*(self as *const ChunkedArray<T> as *const ChunkedArray<UInt16Type>)
};
num_groups_proxy(ca, multithreaded, sorted)
}
_ => {
let ca = self.cast_unchecked(&DataType::UInt32).unwrap();
let ca = ca.u32().unwrap();
num_groups_proxy(ca, multithreaded, sorted)
}
};
Ok(out)
}
}
impl IntoGroupsProxy for BooleanChunked {
fn group_tuples(&self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
#[cfg(feature = "performant")]
{
let ca = self.cast(&DataType::UInt8).unwrap();
let ca = ca.u8().unwrap();
ca.group_tuples(multithreaded, sorted)
}
#[cfg(not(feature = "performant"))]
{
let ca = self.cast(&DataType::UInt32).unwrap();
let ca = ca.u32().unwrap();
ca.group_tuples(multithreaded, sorted)
}
}
}
impl IntoGroupsProxy for Utf8Chunked {
#[allow(clippy::needless_lifetimes)]
fn group_tuples<'a>(&'a self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
let hb = RandomState::default();
let null_h = get_null_hash_value(hb.clone());
let out = if multithreaded {
let n_partitions = _set_partition_size();
let split = _split_offsets(self.len(), n_partitions);
let str_hashes = POOL.install(|| {
split
.into_par_iter()
.map(|(offset, len)| {
let ca = self.slice(offset as i64, len);
ca.into_iter()
.map(|opt_s| {
let hash = match opt_s {
Some(s) => hb.hash_single(s),
None => null_h,
};
unsafe {
std::mem::transmute::<BytesHash<'_>, BytesHash<'a>>(
BytesHash::new_from_str(opt_s, hash),
)
}
})
.collect_trusted::<Vec<_>>()
})
.collect::<Vec<_>>()
});
groupby_threaded_num(str_hashes, 0, n_partitions as u64, sorted)
} else {
let str_hashes = self
.into_iter()
.map(|opt_s| {
let hash = match opt_s {
Some(s) => hb.hash_single(s),
None => null_h,
};
BytesHash::new_from_str(opt_s, hash)
})
.collect_trusted::<Vec<_>>();
groupby(str_hashes.iter(), sorted)
};
Ok(out)
}
}
#[cfg(feature = "dtype-binary")]
impl IntoGroupsProxy for BinaryChunked {
#[allow(clippy::needless_lifetimes)]
fn group_tuples<'a>(&'a self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
let hb = RandomState::default();
let null_h = get_null_hash_value(hb.clone());
let out = if multithreaded {
let n_partitions = _set_partition_size();
let split = _split_offsets(self.len(), n_partitions);
let byte_hashes = POOL.install(|| {
split
.into_par_iter()
.map(|(offset, len)| {
let ca = self.slice(offset as i64, len);
ca.into_iter()
.map(|opt_b| {
let hash = match opt_b {
Some(s) => hb.hash_single(s),
None => null_h,
};
unsafe {
std::mem::transmute::<BytesHash<'_>, BytesHash<'a>>(
BytesHash::new(opt_b, hash),
)
}
})
.collect_trusted::<Vec<_>>()
})
.collect::<Vec<_>>()
});
groupby_threaded_num(byte_hashes, 0, n_partitions as u64, sorted)
} else {
let byte_hashes = self
.into_iter()
.map(|opt_b| {
let hash = match opt_b {
Some(s) => hb.hash_single(s),
None => null_h,
};
BytesHash::new(opt_b, hash)
})
.collect_trusted::<Vec<_>>();
groupby(byte_hashes.iter(), sorted)
};
Ok(out)
}
}
impl IntoGroupsProxy for ListChunked {
#[allow(clippy::needless_lifetimes)]
#[allow(unused_variables)]
fn group_tuples<'a>(&'a self, multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
#[cfg(feature = "groupby_list")]
{
if !self.inner_dtype().to_physical().is_numeric() {
return Err(PolarsError::ComputeError(
"Grouping on List type is only allowed if the inner type is numeric".into(),
));
}
let hb = RandomState::default();
let null_h = get_null_hash_value(hb.clone());
let arr_to_hashes = |ca: &ListChunked| {
let mut out = Vec::with_capacity(ca.len());
for arr in ca.downcast_iter() {
out.extend(numeric_list_bytes_iter(arr)?.map(|opt_bytes| {
let hash = match opt_bytes {
Some(s) => hb.hash_single(s),
None => null_h,
};
unsafe {
std::mem::transmute::<BytesHash<'_>, BytesHash<'a>>(BytesHash::new(
opt_bytes, hash,
))
}
}))
}
Ok(out)
};
if multithreaded {
let n_partitions = _set_partition_size();
let split = _split_offsets(self.len(), n_partitions);
let groups: PolarsResult<_> = POOL.install(|| {
let bytes_hashes = split
.into_par_iter()
.map(|(offset, len)| {
let ca = self.slice(offset as i64, len);
arr_to_hashes(&ca)
})
.collect::<PolarsResult<Vec<_>>>()?;
Ok(groupby_threaded_num(
bytes_hashes,
0,
n_partitions as u64,
sorted,
))
});
groups
} else {
let hashes = arr_to_hashes(self)?;
Ok(groupby(hashes.iter(), sorted))
}
}
#[cfg(not(feature = "groupby_list"))]
{
panic!("activate 'groupby_list' feature")
}
}
}
#[cfg(feature = "object")]
impl<T> IntoGroupsProxy for ObjectChunked<T>
where
T: PolarsObject,
{
fn group_tuples(&self, _multithreaded: bool, sorted: bool) -> PolarsResult<GroupsProxy> {
Ok(groupby(self.into_iter(), sorted))
}
}
#[inline]
pub(super) fn pack_u32_tuples(opt_l: Option<u32>, opt_r: Option<u32>) -> [u8; 9] {
let mut val = [0u8; 9];
let s = &mut val;
match (opt_l, opt_r) {
(Some(l), Some(r)) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..4]) }
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[4..8]) }
}
(Some(l), None) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..4]) }
s[8] = 1;
}
(None, Some(r)) => {
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[4..8]) }
s[8] = 1 << 1;
}
(None, None) => {
s[8] = 3;
}
}
val
}
#[inline]
pub(super) fn pack_u64_tuples(opt_l: Option<u64>, opt_r: Option<u64>) -> [u8; 17] {
let mut val = [0u8; 17];
let s = &mut val;
match (opt_l, opt_r) {
(Some(l), Some(r)) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..8]) }
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[8..16]) }
}
(Some(l), None) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..8]) }
s[16] = 1;
}
(None, Some(r)) => {
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[8..16]) }
s[16] = 1 << 1;
}
(None, None) => {
s[16] = 3;
}
}
val
}
#[inline]
pub(super) fn pack_u32_u64_tuples(opt_l: Option<u32>, opt_r: Option<u64>) -> [u8; 13] {
let mut val = [0u8; 13];
let s = &mut val;
match (opt_l, opt_r) {
(Some(l), Some(r)) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..4]) }
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[4..12]) }
}
(Some(l), None) => {
unsafe { copy_from_slice_unchecked(&l.to_ne_bytes(), &mut s[..4]) }
s[12] = 1;
}
(None, Some(r)) => {
unsafe { copy_from_slice_unchecked(&r.to_ne_bytes(), &mut s[4..12]) }
s[12] = 1 << 1;
}
(None, None) => {
s[12] = 3;
}
}
val
}
pub(super) fn pack_utf8_columns(
lhs: &Utf8Chunked,
rhs: &Utf8Chunked,
n_partitions: usize,
sorted: bool,
) -> GroupsProxy {
let splits = _split_offsets(lhs.len(), n_partitions);
let hb = RandomState::default();
let null_h = get_null_hash_value(hb.clone());
let (hashes, _backing_bytes): (Vec<_>, Vec<_>) = splits
.into_par_iter()
.map(|(offset, len)| {
let lhs = lhs.slice(offset as i64, len);
let rhs = rhs.slice(offset as i64, len);
let size = lhs.get_values_size() + rhs.get_values_size() + lhs.len() * 3 + 1;
let mut values = Vec::with_capacity(size);
let ptr = values.as_ptr() as usize;
let mut str_hashes = Vec::with_capacity(lhs.len());
lhs.into_iter().zip(rhs.into_iter()).for_each(|(lhs, rhs)| {
match (lhs, rhs) {
(Some(lhs), Some(rhs)) => {
let start = values.len();
values.extend_from_slice("11".as_bytes());
values.extend_from_slice(lhs.as_bytes());
values.push(b'_');
values.extend_from_slice(rhs.as_bytes());
debug_assert_eq!(ptr, values.as_ptr() as usize);
let end = values.len();
let str_val: &'static str = unsafe {
std::mem::transmute(std::str::from_utf8_unchecked(
values.get_unchecked(start..end),
))
};
let hash = hb.hash_single(str_val);
str_hashes.push(BytesHash::new(Some(str_val.as_bytes()), hash))
}
(None, Some(rhs)) => {
let start = values.len();
values.extend_from_slice("01".as_bytes());
values.push(b'_');
values.extend_from_slice(rhs.as_bytes());
debug_assert_eq!(ptr, values.as_ptr() as usize);
let end = values.len();
let str_val: &'static str = unsafe {
std::mem::transmute(std::str::from_utf8_unchecked(
values.get_unchecked(start..end),
))
};
let hash = hb.hash_single(str_val);
str_hashes.push(BytesHash::new(Some(str_val.as_bytes()), hash))
}
(Some(lhs), None) => {
let start = values.len();
values.extend_from_slice("10".as_bytes());
values.extend_from_slice(lhs.as_bytes());
values.push(b'_');
debug_assert_eq!(ptr, values.as_ptr() as usize);
let end = values.len();
let str_val: &'static str = unsafe {
std::mem::transmute(std::str::from_utf8_unchecked(
values.get_unchecked(start..end),
))
};
let hash = hb.hash_single(str_val);
str_hashes.push(BytesHash::new(Some(str_val.as_bytes()), hash))
}
(None, None) => str_hashes.push(BytesHash::new(None, null_h)),
}
});
(str_hashes, values)
})
.unzip();
groupby_threaded_num(hashes, 0, n_partitions as u64, sorted)
}