Function polars_core::utils::split_ca
source · pub fn split_ca<T>(
ca: &ChunkedArray<T>,
n: usize
) -> PolarsResult<Vec<ChunkedArray<T>>>where
T: PolarsDataType,Examples found in repository?
src/series/mod.rs (line 494)
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pub fn filter_threaded(&self, filter: &BooleanChunked, rechunk: bool) -> PolarsResult<Series> {
// this would fail if there is a broadcasting filter.
// because we cannot split that filter over threads
// besides they are a no-op, so we do the standard filter.
if filter.len() == 1 {
return self.filter(filter);
}
let n_threads = POOL.current_num_threads();
let filters = split_ca(filter, n_threads).unwrap();
let series = split_series(self, n_threads).unwrap();
let series: PolarsResult<Vec<_>> = POOL.install(|| {
filters
.par_iter()
.zip(series)
.map(|(filter, s)| s.filter(filter))
.collect()
});
Ok(self.finish_take_threaded(series?, rechunk))
}More examples
src/frame/mod.rs (line 1545)
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fn filter_vertical(&mut self, mask: &BooleanChunked) -> PolarsResult<Self> {
let n_threads = POOL.current_num_threads();
let masks = split_ca(mask, n_threads).unwrap();
let dfs = split_df(self, n_threads).unwrap();
let dfs: PolarsResult<Vec<_>> = POOL.install(|| {
masks
.par_iter()
.zip(dfs)
.map(|(mask, df)| {
let cols = df
.columns
.iter()
.map(|s| s.filter(mask))
.collect::<PolarsResult<_>>()?;
Ok(DataFrame::new_no_checks(cols))
})
.collect()
});
let mut iter = dfs?.into_iter();
let first = iter.next().unwrap();
Ok(iter.fold(first, |mut acc, df| {
acc.vstack_mut(&df).unwrap();
acc
}))
}
/// Take the `DataFrame` rows by a boolean mask.
///
/// # Example
///
/// ```
/// # use polars_core::prelude::*;
/// fn example(df: &DataFrame) -> PolarsResult<DataFrame> {
/// let mask = df.column("sepal.width")?.is_not_null();
/// df.filter(&mask)
/// }
/// ```
pub fn filter(&self, mask: &BooleanChunked) -> PolarsResult<Self> {
if std::env::var("POLARS_VERT_PAR").is_ok() {
return self.clone().filter_vertical(mask);
}
let new_col = self.try_apply_columns_par(&|s| match s.dtype() {
DataType::Utf8 => s.filter_threaded(mask, true),
_ => s.filter(mask),
})?;
Ok(DataFrame::new_no_checks(new_col))
}
/// Same as `filter` but does not parallelize.
pub fn _filter_seq(&self, mask: &BooleanChunked) -> PolarsResult<Self> {
let new_col = self.try_apply_columns(&|s| s.filter(mask))?;
Ok(DataFrame::new_no_checks(new_col))
}
/// Take `DataFrame` value by indexes from an iterator.
///
/// # Example
///
/// ```
/// # use polars_core::prelude::*;
/// fn example(df: &DataFrame) -> PolarsResult<DataFrame> {
/// let iterator = (0..9).into_iter();
/// df.take_iter(iterator)
/// }
/// ```
pub fn take_iter<I>(&self, iter: I) -> PolarsResult<Self>
where
I: Iterator<Item = usize> + Clone + Sync + TrustedLen,
{
let new_col = self.try_apply_columns_par(&|s| {
let mut i = iter.clone();
s.take_iter(&mut i)
})?;
Ok(DataFrame::new_no_checks(new_col))
}
/// Take `DataFrame` values by indexes from an iterator.
///
/// # Safety
///
/// This doesn't do any bound checking but checks null validity.
#[must_use]
pub unsafe fn take_iter_unchecked<I>(&self, mut iter: I) -> Self
where
I: Iterator<Item = usize> + Clone + Sync + TrustedLen,
{
if std::env::var("POLARS_VERT_PAR").is_ok() {
let idx_ca: NoNull<IdxCa> = iter.into_iter().map(|idx| idx as IdxSize).collect();
return self.take_unchecked_vectical(&idx_ca.into_inner());
}
let n_chunks = self.n_chunks();
let has_utf8 = self
.columns
.iter()
.any(|s| matches!(s.dtype(), DataType::Utf8));
if (n_chunks == 1 && self.width() > 1) || has_utf8 {
let idx_ca: NoNull<IdxCa> = iter.into_iter().map(|idx| idx as IdxSize).collect();
let idx_ca = idx_ca.into_inner();
return self.take_unchecked(&idx_ca);
}
let new_col = if self.width() == 1 {
self.columns
.iter()
.map(|s| s.take_iter_unchecked(&mut iter))
.collect::<Vec<_>>()
} else {
self.apply_columns_par(&|s| {
let mut i = iter.clone();
s.take_iter_unchecked(&mut i)
})
};
DataFrame::new_no_checks(new_col)
}
/// Take `DataFrame` values by indexes from an iterator that may contain None values.
///
/// # Safety
///
/// This doesn't do any bound checking. Out of bounds may access uninitialized memory.
/// Null validity is checked
#[must_use]
pub unsafe fn take_opt_iter_unchecked<I>(&self, mut iter: I) -> Self
where
I: Iterator<Item = Option<usize>> + Clone + Sync + TrustedLen,
{
if std::env::var("POLARS_VERT_PAR").is_ok() {
let idx_ca: IdxCa = iter
.into_iter()
.map(|opt| opt.map(|v| v as IdxSize))
.collect();
return self.take_unchecked_vectical(&idx_ca);
}
let n_chunks = self.n_chunks();
let has_utf8 = self
.columns
.iter()
.any(|s| matches!(s.dtype(), DataType::Utf8));
if (n_chunks == 1 && self.width() > 1) || has_utf8 {
let idx_ca: IdxCa = iter
.into_iter()
.map(|opt| opt.map(|v| v as IdxSize))
.collect();
return self.take_unchecked(&idx_ca);
}
let new_col = if self.width() == 1 {
self.columns
.iter()
.map(|s| s.take_opt_iter_unchecked(&mut iter))
.collect::<Vec<_>>()
} else {
self.apply_columns_par(&|s| {
let mut i = iter.clone();
s.take_opt_iter_unchecked(&mut i)
})
};
DataFrame::new_no_checks(new_col)
}
/// Take `DataFrame` rows by index values.
///
/// # Example
///
/// ```
/// # use polars_core::prelude::*;
/// fn example(df: &DataFrame) -> PolarsResult<DataFrame> {
/// let idx = IdxCa::new("idx", &[0, 1, 9]);
/// df.take(&idx)
/// }
/// ```
pub fn take(&self, indices: &IdxCa) -> PolarsResult<Self> {
let indices = if indices.chunks.len() > 1 {
Cow::Owned(indices.rechunk())
} else {
Cow::Borrowed(indices)
};
let new_col = POOL.install(|| {
self.try_apply_columns_par(&|s| match s.dtype() {
DataType::Utf8 => s.take_threaded(&indices, true),
_ => s.take(&indices),
})
})?;
Ok(DataFrame::new_no_checks(new_col))
}
pub(crate) unsafe fn take_unchecked(&self, idx: &IdxCa) -> Self {
self.take_unchecked_impl(idx, true)
}
unsafe fn take_unchecked_impl(&self, idx: &IdxCa, allow_threads: bool) -> Self {
let cols = if allow_threads {
POOL.install(|| {
self.apply_columns_par(&|s| match s.dtype() {
DataType::Utf8 => s.take_unchecked_threaded(idx, true).unwrap(),
_ => s.take_unchecked(idx).unwrap(),
})
})
} else {
self.columns
.iter()
.map(|s| s.take_unchecked(idx).unwrap())
.collect()
};
DataFrame::new_no_checks(cols)
}
unsafe fn take_unchecked_vectical(&self, indices: &IdxCa) -> Self {
let n_threads = POOL.current_num_threads();
let idxs = split_ca(indices, n_threads).unwrap();
let dfs: Vec<_> = POOL.install(|| {
idxs.par_iter()
.map(|idx| {
let cols = self
.columns
.iter()
.map(|s| s.take_unchecked(idx).unwrap())
.collect();
DataFrame::new_no_checks(cols)
})
.collect()
});
let mut iter = dfs.into_iter();
let first = iter.next().unwrap();
iter.fold(first, |mut acc, df| {
acc.vstack_mut(&df).unwrap();
acc
})
}src/frame/hash_join/single_keys_dispatch.rs (line 173)
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fn num_group_join_inner<T>(
left: &ChunkedArray<T>,
right: &ChunkedArray<T>,
) -> ((Vec<IdxSize>, Vec<IdxSize>), bool)
where
T: PolarsIntegerType,
T::Native: Hash + Eq + Send + AsU64 + Copy,
Option<T::Native>: AsU64,
{
let n_threads = POOL.current_num_threads();
let (a, b, swap) = det_hash_prone_order!(left, right);
let splitted_a = split_ca(a, n_threads).unwrap();
let splitted_b = split_ca(b, n_threads).unwrap();
match (
left.null_count() == 0,
right.null_count() == 0,
left.chunks.len(),
right.chunks.len(),
) {
(true, true, 1, 1) => {
let keys_a = splitted_to_slice(&splitted_a);
let keys_b = splitted_to_slice(&splitted_b);
(hash_join_tuples_inner(keys_a, keys_b, swap), !swap)
}
(true, true, _, _) => {
let keys_a = splitted_by_chunks(&splitted_a);
let keys_b = splitted_by_chunks(&splitted_b);
(hash_join_tuples_inner(keys_a, keys_b, swap), !swap)
}
_ => {
let keys_a = splitted_to_opt_vec(&splitted_a);
let keys_b = splitted_to_opt_vec(&splitted_b);
(hash_join_tuples_inner(keys_a, keys_b, swap), !swap)
}
}
}
#[cfg(feature = "chunked_ids")]
fn create_mappings(
chunks_left: &[ArrayRef],
chunks_right: &[ArrayRef],
left_len: usize,
right_len: usize,
) -> (Option<Vec<ChunkId>>, Option<Vec<ChunkId>>) {
let mapping_left = || {
if chunks_left.len() > 1 {
Some(create_chunked_index_mapping(chunks_left, left_len))
} else {
None
}
};
let mapping_right = || {
if chunks_right.len() > 1 {
Some(create_chunked_index_mapping(chunks_right, right_len))
} else {
None
}
};
POOL.join(mapping_left, mapping_right)
}
#[cfg(not(feature = "chunked_ids"))]
fn create_mappings(
_chunks_left: &[ArrayRef],
_chunks_right: &[ArrayRef],
_left_len: usize,
_right_len: usize,
) -> (Option<Vec<ChunkId>>, Option<Vec<ChunkId>>) {
(None, None)
}
fn num_group_join_left<T>(left: &ChunkedArray<T>, right: &ChunkedArray<T>) -> LeftJoinIds
where
T: PolarsIntegerType,
T::Native: Hash + Eq + Send + AsU64,
Option<T::Native>: AsU64,
{
let n_threads = POOL.current_num_threads();
let splitted_a = split_ca(left, n_threads).unwrap();
let splitted_b = split_ca(right, n_threads).unwrap();
match (
left.null_count(),
right.null_count(),
left.chunks.len(),
right.chunks.len(),
) {
(0, 0, 1, 1) => {
let keys_a = splitted_to_slice(&splitted_a);
let keys_b = splitted_to_slice(&splitted_b);
hash_join_tuples_left(keys_a, keys_b, None, None)
}
(0, 0, _, _) => {
let keys_a = splitted_by_chunks(&splitted_a);
let keys_b = splitted_by_chunks(&splitted_b);
let (mapping_left, mapping_right) =
create_mappings(left.chunks(), right.chunks(), left.len(), right.len());
hash_join_tuples_left(
keys_a,
keys_b,
mapping_left.as_deref(),
mapping_right.as_deref(),
)
}
_ => {
let keys_a = splitted_to_opt_vec(&splitted_a);
let keys_b = splitted_to_opt_vec(&splitted_b);
let (mapping_left, mapping_right) =
create_mappings(left.chunks(), right.chunks(), left.len(), right.len());
hash_join_tuples_left(
keys_a,
keys_b,
mapping_left.as_deref(),
mapping_right.as_deref(),
)
}
}
}
impl<T> ChunkedArray<T>
where
T: PolarsIntegerType + Sync,
T::Native: Eq + Hash + num::NumCast,
{
fn hash_join_outer(&self, other: &ChunkedArray<T>) -> Vec<(Option<IdxSize>, Option<IdxSize>)> {
let (a, b, swap) = det_hash_prone_order!(self, other);
let n_partitions = _set_partition_size();
let splitted_a = split_ca(a, n_partitions).unwrap();
let splitted_b = split_ca(b, n_partitions).unwrap();
match (a.null_count(), b.null_count()) {
(0, 0) => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
_ => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
}
}
}
pub(crate) fn prepare_strs<'a>(
been_split: &'a [Utf8Chunked],
hb: &RandomState,
) -> Vec<Vec<BytesHash<'a>>> {
POOL.install(|| {
been_split
.par_iter()
.map(|ca| {
ca.into_iter()
.map(|opt_s| {
let mut state = hb.build_hasher();
opt_s.hash(&mut state);
let hash = state.finish();
BytesHash::new_from_str(opt_s, hash)
})
.collect::<Vec<_>>()
})
.collect()
})
}
impl Utf8Chunked {
fn prepare(
&self,
other: &Utf8Chunked,
swapped: bool,
) -> (Vec<Self>, Vec<Self>, bool, RandomState) {
let n_threads = POOL.current_num_threads();
let (a, b, swap) = if swapped {
det_hash_prone_order!(self, other)
} else {
(self, other, false)
};
let hb = RandomState::default();
let splitted_a = split_ca(a, n_threads).unwrap();
let splitted_b = split_ca(b, n_threads).unwrap();
(splitted_a, splitted_b, swap, hb)
}
// returns the join tuples and whether or not the lhs tuples are sorted
fn hash_join_inner(&self, other: &Utf8Chunked) -> ((Vec<IdxSize>, Vec<IdxSize>), bool) {
let (splitted_a, splitted_b, swap, hb) = self.prepare(other, true);
let str_hashes_a = prepare_strs(&splitted_a, &hb);
let str_hashes_b = prepare_strs(&splitted_b, &hb);
(
hash_join_tuples_inner(str_hashes_a, str_hashes_b, swap),
!swap,
)
}
fn hash_join_left(&self, other: &Utf8Chunked) -> LeftJoinIds {
let (splitted_a, splitted_b, _, hb) = self.prepare(other, false);
let str_hashes_a = prepare_strs(&splitted_a, &hb);
let str_hashes_b = prepare_strs(&splitted_b, &hb);
let (mapping_left, mapping_right) =
create_mappings(self.chunks(), other.chunks(), self.len(), other.len());
hash_join_tuples_left(
str_hashes_a,
str_hashes_b,
mapping_left.as_deref(),
mapping_right.as_deref(),
)
}
#[cfg(feature = "semi_anti_join")]
fn hash_join_semi_anti(&self, other: &Utf8Chunked, anti: bool) -> Vec<IdxSize> {
let (splitted_a, splitted_b, _, hb) = self.prepare(other, false);
let str_hashes_a = prepare_strs(&splitted_a, &hb);
let str_hashes_b = prepare_strs(&splitted_b, &hb);
if anti {
hash_join_tuples_left_anti(str_hashes_a, str_hashes_b)
} else {
hash_join_tuples_left_semi(str_hashes_a, str_hashes_b)
}
}
fn hash_join_outer(&self, other: &Utf8Chunked) -> Vec<(Option<IdxSize>, Option<IdxSize>)> {
let (a, b, swap) = det_hash_prone_order!(self, other);
let n_partitions = _set_partition_size();
let splitted_a = split_ca(a, n_partitions).unwrap();
let splitted_b = split_ca(b, n_partitions).unwrap();
match (a.has_validity(), b.has_validity()) {
(false, false) => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
_ => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
}
}
}
#[cfg(feature = "dtype-binary")]
pub(crate) fn prepare_bytes<'a>(
been_split: &'a [BinaryChunked],
hb: &RandomState,
) -> Vec<Vec<BytesHash<'a>>> {
POOL.install(|| {
been_split
.par_iter()
.map(|ca| {
ca.into_iter()
.map(|opt_b| {
let mut state = hb.build_hasher();
opt_b.hash(&mut state);
let hash = state.finish();
BytesHash::new(opt_b, hash)
})
.collect::<Vec<_>>()
})
.collect()
})
}
#[cfg(feature = "dtype-binary")]
impl BinaryChunked {
fn prepare(
&self,
other: &BinaryChunked,
swapped: bool,
) -> (Vec<Self>, Vec<Self>, bool, RandomState) {
let n_threads = POOL.current_num_threads();
let (a, b, swap) = if swapped {
det_hash_prone_order!(self, other)
} else {
(self, other, false)
};
let hb = RandomState::default();
let splitted_a = split_ca(a, n_threads).unwrap();
let splitted_b = split_ca(b, n_threads).unwrap();
(splitted_a, splitted_b, swap, hb)
}
// returns the join tuples and whether or not the lhs tuples are sorted
fn hash_join_inner(&self, other: &BinaryChunked) -> ((Vec<IdxSize>, Vec<IdxSize>), bool) {
let (splitted_a, splitted_b, swap, hb) = self.prepare(other, true);
let str_hashes_a = prepare_bytes(&splitted_a, &hb);
let str_hashes_b = prepare_bytes(&splitted_b, &hb);
(
hash_join_tuples_inner(str_hashes_a, str_hashes_b, swap),
!swap,
)
}
fn hash_join_left(&self, other: &BinaryChunked) -> LeftJoinIds {
let (splitted_a, splitted_b, _, hb) = self.prepare(other, false);
let str_hashes_a = prepare_bytes(&splitted_a, &hb);
let str_hashes_b = prepare_bytes(&splitted_b, &hb);
let (mapping_left, mapping_right) =
create_mappings(self.chunks(), other.chunks(), self.len(), other.len());
hash_join_tuples_left(
str_hashes_a,
str_hashes_b,
mapping_left.as_deref(),
mapping_right.as_deref(),
)
}
#[cfg(feature = "semi_anti_join")]
fn hash_join_semi_anti(&self, other: &BinaryChunked, anti: bool) -> Vec<IdxSize> {
let (splitted_a, splitted_b, _, hb) = self.prepare(other, false);
let str_hashes_a = prepare_bytes(&splitted_a, &hb);
let str_hashes_b = prepare_bytes(&splitted_b, &hb);
if anti {
hash_join_tuples_left_anti(str_hashes_a, str_hashes_b)
} else {
hash_join_tuples_left_semi(str_hashes_a, str_hashes_b)
}
}
fn hash_join_outer(&self, other: &BinaryChunked) -> Vec<(Option<IdxSize>, Option<IdxSize>)> {
let (a, b, swap) = det_hash_prone_order!(self, other);
let n_partitions = _set_partition_size();
let splitted_a = split_ca(a, n_partitions).unwrap();
let splitted_b = split_ca(b, n_partitions).unwrap();
match (a.has_validity(), b.has_validity()) {
(false, false) => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_no_null_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
_ => {
let iters_a = splitted_a
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
let iters_b = splitted_b
.iter()
.map(|ca| ca.into_iter())
.collect::<Vec<_>>();
hash_join_tuples_outer(iters_a, iters_b, swap)
}
}
}
}
#[cfg(feature = "semi_anti_join")]
fn num_group_join_anti_semi<T>(
left: &ChunkedArray<T>,
right: &ChunkedArray<T>,
anti: bool,
) -> Vec<IdxSize>
where
T: PolarsIntegerType,
T::Native: Hash + Eq + Send + AsU64,
Option<T::Native>: AsU64,
{
let n_threads = POOL.current_num_threads();
let splitted_a = split_ca(left, n_threads).unwrap();
let splitted_b = split_ca(right, n_threads).unwrap();
match (
left.null_count(),
right.null_count(),
left.chunks.len(),
right.chunks.len(),
) {
(0, 0, 1, 1) => {
let keys_a = splitted_to_slice(&splitted_a);
let keys_b = splitted_to_slice(&splitted_b);
if anti {
hash_join_tuples_left_anti(keys_a, keys_b)
} else {
hash_join_tuples_left_semi(keys_a, keys_b)
}
}
(0, 0, _, _) => {
let keys_a = splitted_by_chunks(&splitted_a);
let keys_b = splitted_by_chunks(&splitted_b);
if anti {
hash_join_tuples_left_anti(keys_a, keys_b)
} else {
hash_join_tuples_left_semi(keys_a, keys_b)
}
}
_ => {
let keys_a = splitted_to_opt_vec(&splitted_a);
let keys_b = splitted_to_opt_vec(&splitted_b);
if anti {
hash_join_tuples_left_anti(keys_a, keys_b)
} else {
hash_join_tuples_left_semi(keys_a, keys_b)
}
}
}
}src/frame/asof_join/groups.rs (line 248)
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fn asof_join_by_numeric<T, S>(
by_left: &ChunkedArray<S>,
by_right: &ChunkedArray<S>,
left_asof: &ChunkedArray<T>,
right_asof: &ChunkedArray<T>,
tolerance: Option<AnyValue<'static>>,
strategy: AsofStrategy,
) -> PolarsResult<Vec<Option<IdxSize>>>
where
T: PolarsNumericType,
S: PolarsNumericType,
S::Native: Hash + Eq + AsU64,
{
#[allow(clippy::type_complexity)]
let (join_asof_fn, tolerance, forward): (
unsafe fn(T::Native, &[T::Native], &[IdxSize], T::Native) -> (Option<IdxSize>, usize),
_,
_,
) = match (tolerance, strategy) {
(Some(tolerance), AsofStrategy::Backward) => {
let tol = tolerance.extract::<T::Native>().unwrap();
(
join_asof_backward_with_indirection_and_tolerance,
tol,
false,
)
}
(None, AsofStrategy::Backward) => (
join_asof_backward_with_indirection,
T::Native::zero(),
false,
),
(Some(tolerance), AsofStrategy::Forward) => {
let tol = tolerance.extract::<T::Native>().unwrap();
(join_asof_forward_with_indirection_and_tolerance, tol, true)
}
(None, AsofStrategy::Forward) => {
(join_asof_forward_with_indirection, T::Native::zero(), true)
}
};
let left_asof = left_asof.rechunk();
let err = |_: PolarsError| {
PolarsError::ComputeError("Keys are not allowed to have null values in asof join.".into())
};
let left_asof = left_asof.cont_slice().map_err(err)?;
let right_asof = right_asof.rechunk();
let right_asof = right_asof.cont_slice().map_err(err)?;
let n_threads = POOL.current_num_threads();
let splitted_left = split_ca(by_left, n_threads).unwrap();
let splitted_right = split_ca(by_right, n_threads).unwrap();
let vals_left = splitted_left
.iter()
.map(|ca| ca.cont_slice().unwrap())
.collect::<Vec<_>>();
let vals_right = splitted_right
.iter()
.map(|ca| ca.cont_slice().unwrap())
.collect::<Vec<_>>();
let hash_tbls = create_probe_table(vals_right);
// we determine the offset so that we later know which index to store in the join tuples
let offsets = vals_left
.iter()
.map(|ph| ph.len())
.scan(0, |state, val| {
let out = *state;
*state += val;
Some(out)
})
.collect::<Vec<_>>();
let n_tables = hash_tbls.len() as u64;
debug_assert!(n_tables.is_power_of_two());
// next we probe the right relation
Ok(POOL.install(|| {
vals_left
.into_par_iter()
.zip(offsets)
// probes_hashes: Vec<u64> processed by this thread
// offset: offset index
.map(|(vals_left, offset)| {
// local reference
let hash_tbls = &hash_tbls;
// assume the result tuples equal length of the no. of hashes processed by this thread.
let mut results = Vec::with_capacity(vals_left.len());
let mut right_tbl_offsets = PlHashMap::with_capacity(HASHMAP_INIT_SIZE);
vals_left.iter().enumerate().for_each(|(idx_a, k)| {
let idx_a = (idx_a + offset) as IdxSize;
// probe table that contains the hashed value
let current_probe_table = unsafe {
get_hash_tbl_threaded_join_partitioned(k.as_u64(), hash_tbls, n_tables)
};
// we already hashed, so we don't have to hash again.
let value = current_probe_table.get(k);
match value {
// left and right matches
Some(indexes_b) => {
process_group(
*k,
idx_a,
tolerance,
indexes_b,
&mut right_tbl_offsets,
join_asof_fn,
left_asof,
right_asof,
&mut results,
forward,
);
}
// only left values, right = null
None => results.push(None),
}
});
results
})
.flatten()
.collect()
}))
}
fn asof_join_by_utf8<T>(
by_left: &Utf8Chunked,
by_right: &Utf8Chunked,
left_asof: &ChunkedArray<T>,
right_asof: &ChunkedArray<T>,
tolerance: Option<AnyValue<'static>>,
strategy: AsofStrategy,
) -> Vec<Option<IdxSize>>
where
T: PolarsNumericType,
{
#[allow(clippy::type_complexity)]
let (join_asof_fn, tolerance, forward): (
unsafe fn(T::Native, &[T::Native], &[IdxSize], T::Native) -> (Option<IdxSize>, usize),
_,
_,
) = match (tolerance, strategy) {
(Some(tolerance), AsofStrategy::Backward) => {
let tol = tolerance.extract::<T::Native>().unwrap();
(
join_asof_backward_with_indirection_and_tolerance,
tol,
false,
)
}
(None, AsofStrategy::Backward) => (
join_asof_backward_with_indirection,
T::Native::zero(),
false,
),
(Some(tolerance), AsofStrategy::Forward) => {
let tol = tolerance.extract::<T::Native>().unwrap();
(join_asof_forward_with_indirection_and_tolerance, tol, true)
}
(None, AsofStrategy::Forward) => {
(join_asof_forward_with_indirection, T::Native::zero(), true)
}
};
let left_asof = left_asof.rechunk();
let left_asof = left_asof.cont_slice().unwrap();
let right_asof = right_asof.rechunk();
let right_asof = right_asof.cont_slice().unwrap();
let n_threads = POOL.current_num_threads();
let splitted_by_left = split_ca(by_left, n_threads).unwrap();
let splitted_right = split_ca(by_right, n_threads).unwrap();
let hb = RandomState::default();
let vals_left = prepare_strs(&splitted_by_left, &hb);
let vals_right = prepare_strs(&splitted_right, &hb);
let hash_tbls = create_probe_table(vals_right);
// we determine the offset so that we later know which index to store in the join tuples
let offsets = vals_left
.iter()
.map(|ph| ph.len())
.scan(0, |state, val| {
let out = *state;
*state += val;
Some(out)
})
.collect::<Vec<_>>();
let n_tables = hash_tbls.len() as u64;
debug_assert!(n_tables.is_power_of_two());
// next we probe the right relation
POOL.install(|| {
vals_left
.into_par_iter()
.zip(offsets)
// probes_hashes: Vec<u64> processed by this thread
// offset: offset index
.map(|(vals_left, offset)| {
// local reference
let hash_tbls = &hash_tbls;
// assume the result tuples equal length of the no. of hashes processed by this thread.
let mut results = Vec::with_capacity(vals_left.len());
let mut right_tbl_offsets = PlHashMap::with_capacity(HASHMAP_INIT_SIZE);
vals_left.iter().enumerate().for_each(|(idx_a, k)| {
let idx_a = (idx_a + offset) as IdxSize;
// probe table that contains the hashed value
let current_probe_table = unsafe {
get_hash_tbl_threaded_join_partitioned(k.as_u64(), hash_tbls, n_tables)
};
// we already hashed, so we don't have to hash again.
let value = current_probe_table.get(k);
match value {
// left and right matches
Some(indexes_b) => {
process_group(
*k,
idx_a,
tolerance,
indexes_b,
&mut right_tbl_offsets,
join_asof_fn,
left_asof,
right_asof,
&mut results,
forward,
);
}
// only left values, right = null
None => results.push(None),
}
});
results
})
.flatten()
.collect()
})
}