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PERF: Introducing hash tables for complex64 and complex128 #38179

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Dec 30, 2020
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PERF: Introducing hash tables for complex64 and complex128 #38179

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0b70965
remove unnecessary setting of keys kh_put_xxx, already does it!
realead Nov 29, 2020
06f7a07
adding explicit c_type as preparation for complex, for which c_type w…
realead Nov 29, 2020
6fe568e
introducing complex hash tables
realead Nov 27, 2020
fbbf544
ensure const-correctness of input is tested
realead Nov 29, 2020
1fe2d55
const memoryviews of struct dtypes will work only with Cython>=0.29.2…
realead Nov 29, 2020
57e2a72
making count_values and mode accept constand input as well
realead Nov 29, 2020
259deff
activating tests for complex hashtables
realead Nov 29, 2020
22ee6e7
using to_c_type, rather than a switch
realead Nov 30, 2020
5bcd106
getting rid of complex_group/float_group
realead Nov 30, 2020
432f839
fixing style issues
realead Nov 30, 2020
a4903b0
removing commented out code
realead Nov 30, 2020
bb1f3d5
get_labels_groupby is only used with Int64HashTable, thus define it o…
realead Nov 30, 2020
28c2f2d
fixing test case for 32bit build
realead Dec 1, 2020
50d7136
minor style issues
realead Dec 1, 2020
4efdc67
parameterize tests on writeable True/False
realead Dec 2, 2020
9930a55
reshuffle code, so it becomes more obvious which functions are define…
realead Dec 2, 2020
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18 changes: 18 additions & 0 deletions pandas/_libs/hashtable.pxd
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Original file line number Diff line number Diff line change
@@ -1,12 +1,16 @@
from numpy cimport intp_t, ndarray

from pandas._libs.khash cimport (
complex64_t,
complex128_t,
float32_t,
float64_t,
int8_t,
int16_t,
int32_t,
int64_t,
kh_complex64_t,
kh_complex128_t,
kh_float32_t,
kh_float64_t,
kh_int8_t,
Expand All @@ -19,6 +23,8 @@ from pandas._libs.khash cimport (
kh_uint16_t,
kh_uint32_t,
kh_uint64_t,
khcomplex64_t,
khcomplex128_t,
uint8_t,
uint16_t,
uint32_t,
Expand Down Expand Up @@ -90,6 +96,18 @@ cdef class Float32HashTable(HashTable):
cpdef get_item(self, float32_t val)
cpdef set_item(self, float32_t key, Py_ssize_t val)

cdef class Complex64HashTable(HashTable):
cdef kh_complex64_t *table

cpdef get_item(self, complex64_t val)
cpdef set_item(self, complex64_t key, Py_ssize_t val)

cdef class Complex128HashTable(HashTable):
cdef kh_complex128_t *table

cpdef get_item(self, complex128_t val)
cpdef set_item(self, complex128_t key, Py_ssize_t val)

cdef class PyObjectHashTable(HashTable):
cdef kh_pymap_t *table

Expand Down
12 changes: 11 additions & 1 deletion pandas/_libs/hashtable.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,17 @@ cnp.import_array()


from pandas._libs cimport util
from pandas._libs.khash cimport KHASH_TRACE_DOMAIN, kh_str_t, khiter_t
from pandas._libs.khash cimport (
KHASH_TRACE_DOMAIN,
are_equivalent_float32_t,
are_equivalent_float64_t,
are_equivalent_khcomplex64_t,
are_equivalent_khcomplex128_t,
kh_str_t,
khcomplex64_t,
khcomplex128_t,
khiter_t,
)
from pandas._libs.missing cimport checknull


Expand Down
155 changes: 115 additions & 40 deletions pandas/_libs/hashtable_class_helper.pxi.in
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,73 @@ WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
{{py:

# name
cimported_types = ['float32',
complex_types = ['complex64',
'complex128']
}}

{{for name in complex_types}}
cdef kh{{name}}_t to_kh{{name}}_t({{name}}_t val) nogil:
cdef kh{{name}}_t res
res.real = val.real
res.imag = val.imag
return res


cdef {{name}}_t to_{{name}}(kh{{name}}_t val) nogil:
cdef {{name}}_t res
res.real = val.real
res.imag = val.imag
return res

{{endfor}}


{{py:


# name
c_types = ['khcomplex128_t',
'khcomplex64_t',
'float64_t',
'float32_t',
'int64_t',
'int32_t',
'int16_t',
'int8_t',
'uint64_t',
'uint32_t',
'uint16_t',
'uint8_t']
}}

{{for c_type in c_types}}

cdef bint is_nan_{{c_type}}({{c_type}} val) nogil:
{{if c_type in {'khcomplex128_t', 'khcomplex64_t'} }}
return val.real != val.real or val.imag != val.imag
{{elif c_type in {'float64_t', 'float32_t'} }}
return val != val
{{else}}
return False
{{endif}}


{{if c_type in {'khcomplex128_t', 'khcomplex64_t', 'float64_t', 'float32_t'} }}
# are_equivalent_{{c_type}} is cimported via khash.pxd
{{else}}
cdef bint are_equivalent_{{c_type}}({{c_type}} val1, {{c_type}} val2) nogil:
return val1 == val2
{{endif}}

{{endfor}}


{{py:

# name
cimported_types = ['complex64',
'complex128',
'float32',
'float64',
'int8',
'int16',
Expand All @@ -32,6 +98,7 @@ from pandas._libs.khash cimport (
kh_put_{{name}},
kh_resize_{{name}},
)

{{endfor}}

# ----------------------------------------------------------------------
Expand All @@ -48,7 +115,9 @@ from pandas._libs.missing cimport C_NA
# but is included for completeness (rather ObjectVector is used
# for uniques in hashtables)

dtypes = [('Float64', 'float64', 'float64_t'),
dtypes = [('Complex128', 'complex128', 'khcomplex128_t'),
('Complex64', 'complex64', 'khcomplex64_t'),
('Float64', 'float64', 'float64_t'),
('Float32', 'float32', 'float32_t'),
('Int64', 'int64', 'int64_t'),
('Int32', 'int32', 'int32_t'),
Expand Down Expand Up @@ -94,6 +163,8 @@ ctypedef fused vector_data:
UInt8VectorData
Float64VectorData
Float32VectorData
Complex128VectorData
Complex64VectorData
StringVectorData

cdef inline bint needs_resize(vector_data *data) nogil:
Expand All @@ -106,7 +177,9 @@ cdef inline bint needs_resize(vector_data *data) nogil:
{{py:

# name, dtype, c_type
dtypes = [('Float64', 'float64', 'float64_t'),
dtypes = [('Complex128', 'complex128', 'khcomplex128_t'),
('Complex64', 'complex64', 'khcomplex64_t'),
('Float64', 'float64', 'float64_t'),
('UInt64', 'uint64', 'uint64_t'),
('Int64', 'int64', 'int64_t'),
('Float32', 'float32', 'float32_t'),
Expand Down Expand Up @@ -303,22 +376,24 @@ cdef class HashTable:

{{py:

# name, dtype, float_group
dtypes = [('Float64', 'float64', True),
('UInt64', 'uint64', False),
('Int64', 'int64', False),
('Float32', 'float32', True),
('UInt32', 'uint32', False),
('Int32', 'int32', False),
('UInt16', 'uint16', False),
('Int16', 'int16', False),
('UInt8', 'uint8', False),
('Int8', 'int8', False)]
# name, dtype, c_type, to_c_type
dtypes = [('Complex128', 'complex128', 'khcomplex128_t', 'to_khcomplex128_t'),
('Float64', 'float64', 'float64_t', ''),
('UInt64', 'uint64', 'uint64_t', ''),
('Int64', 'int64', 'int64_t', ''),
('Complex64', 'complex64', 'khcomplex64_t', 'to_khcomplex64_t'),
('Float32', 'float32', 'float32_t', ''),
('UInt32', 'uint32', 'uint32_t', ''),
('Int32', 'int32', 'int32_t', ''),
('UInt16', 'uint16', 'uint16_t', ''),
('Int16', 'int16', 'int16_t', ''),
('UInt8', 'uint8', 'uint8_t', ''),
('Int8', 'int8', 'int8_t', '')]

}}


{{for name, dtype, float_group in dtypes}}
{{for name, dtype, c_type, to_c_type in dtypes}}

cdef class {{name}}HashTable(HashTable):

Expand All @@ -339,7 +414,9 @@ cdef class {{name}}HashTable(HashTable):
def __contains__(self, object key):
cdef:
khiter_t k
k = kh_get_{{dtype}}(self.table, key)
{{c_type}} ckey
ckey = {{to_c_type}}(key)
k = kh_get_{{dtype}}(self.table, ckey)
return k != self.table.n_buckets

def sizeof(self, deep=False):
Expand All @@ -353,7 +430,9 @@ cdef class {{name}}HashTable(HashTable):
cpdef get_item(self, {{dtype}}_t val):
cdef:
khiter_t k
k = kh_get_{{dtype}}(self.table, val)
{{c_type}} cval
cval = {{to_c_type}}(val)
k = kh_get_{{dtype}}(self.table, cval)
if k != self.table.n_buckets:
return self.table.vals[k]
else:
Expand All @@ -363,9 +442,9 @@ cdef class {{name}}HashTable(HashTable):
cdef:
khiter_t k
int ret = 0

k = kh_put_{{dtype}}(self.table, key, &ret)
self.table.keys[k] = key
{{c_type}} ckey
ckey = {{to_c_type}}(key)
k = kh_put_{{dtype}}(self.table, ckey, &ret)
if kh_exist_{{dtype}}(self.table, k):
self.table.vals[k] = val
else:
Expand All @@ -376,12 +455,12 @@ cdef class {{name}}HashTable(HashTable):
cdef:
Py_ssize_t i, n = len(values)
int ret = 0
{{dtype}}_t key
{{c_type}} key
khiter_t k

with nogil:
for i in range(n):
key = keys[i]
key = {{to_c_type}}(keys[i])
k = kh_put_{{dtype}}(self.table, key, &ret)
self.table.vals[k] = <Py_ssize_t>values[i]

Expand All @@ -390,12 +469,12 @@ cdef class {{name}}HashTable(HashTable):
cdef:
Py_ssize_t i, n = len(values)
int ret = 0
{{dtype}}_t val
{{c_type}} val
khiter_t k

with nogil:
for i in range(n):
val = values[i]
val= {{to_c_type}}(values[i])
k = kh_put_{{dtype}}(self.table, val, &ret)
self.table.vals[k] = i

Expand All @@ -404,13 +483,13 @@ cdef class {{name}}HashTable(HashTable):
cdef:
Py_ssize_t i, n = len(values)
int ret = 0
{{dtype}}_t val
{{c_type}} val
khiter_t k
intp_t[:] locs = np.empty(n, dtype=np.intp)

with nogil:
for i in range(n):
val = values[i]
val = {{to_c_type}}(values[i])
k = kh_get_{{dtype}}(self.table, val)
if k != self.table.n_buckets:
locs[i] = self.table.vals[k]
Expand Down Expand Up @@ -466,7 +545,7 @@ cdef class {{name}}HashTable(HashTable):
Py_ssize_t i, idx, count = count_prior, n = len(values)
int64_t[:] labels
int ret = 0
{{dtype}}_t val, na_value2
{{c_type}} val, na_value2
khiter_t k
{{name}}VectorData *ud
bint use_na_value, use_mask
Expand All @@ -487,23 +566,21 @@ cdef class {{name}}HashTable(HashTable):
# We use None, to make it optional, which requires `object` type
# for the parameter. To please the compiler, we use na_value2,
# which is only used if it's *specified*.
na_value2 = <{{dtype}}_t>na_value
na_value2 = {{to_c_type}}(na_value)
else:
na_value2 = 0
na_value2 = {{to_c_type}}(0)

with nogil:
for i in range(n):
val = values[i]
val = {{to_c_type}}(values[i])

if ignore_na and use_mask:
if mask_values[i]:
labels[i] = na_sentinel
continue
elif ignore_na and (
{{if not name.lower().startswith(("uint", "int"))}}
val != val or
{{endif}}
(use_na_value and val == na_value2)
is_nan_{{c_type}}(val) or
(use_na_value and are_equivalent_{{c_type}}(val, na_value2))
):
# if missing values do not count as unique values (i.e. if
# ignore_na is True), skip the hashtable entry for them,
Expand Down Expand Up @@ -606,14 +683,15 @@ cdef class {{name}}HashTable(HashTable):
ignore_na=True, return_inverse=True)
return labels

{{if dtype == 'int64'}}
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why adding this only for int64?

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This function is used just in int64-version:

pandas/pandas/core/sorting.py

Lines 598 to 603 in aad85ad

table = hashtable.Int64HashTable(size_hint)
group_index = ensure_int64(group_index)
# note, group labels come out ascending (ie, 1,2,3 etc)
comp_ids, obs_group_ids = table.get_labels_groupby(group_index)

The logic in this function:

pandas/pandas/_libs/hashtable_class_helper.pxi.in

Lines 628 to 633 in 1fc5efd

# specific for groupby
{{if dtype != 'uint64'}}
if val < 0:
labels[i] = -1
continue
{{endif}}

IIUC, negative numbers are special and should be skipped, but this is only a convention for the meaning of values group_index. For other types there is no such convention. Instead of inventing something, I've decided to delete unused functions/versions.

@cython.boundscheck(False)
def get_labels_groupby(self, const {{dtype}}_t[:] values):
cdef:
Py_ssize_t i, n = len(values)
intp_t[:] labels
Py_ssize_t idx, count = 0
int ret = 0
{{dtype}}_t val
{{c_type}} val
khiter_t k
{{name}}Vector uniques = {{name}}Vector()
{{name}}VectorData *ud
Expand All @@ -623,14 +701,12 @@ cdef class {{name}}HashTable(HashTable):

with nogil:
for i in range(n):
val = values[i]
val = {{to_c_type}}(values[i])

# specific for groupby
{{if dtype != 'uint64'}}
if val < 0:
labels[i] = -1
continue
{{endif}}

k = kh_get_{{dtype}}(self.table, val)
if k != self.table.n_buckets:
Expand All @@ -650,6 +726,7 @@ cdef class {{name}}HashTable(HashTable):
arr_uniques = uniques.to_array()

return np.asarray(labels), arr_uniques
{{endif}}

{{endfor}}

Expand Down Expand Up @@ -698,7 +775,6 @@ cdef class StringHashTable(HashTable):
v = get_c_string(key)

k = kh_put_str(self.table, v, &ret)
self.table.keys[k] = v
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if kh_exist_str(self.table, k):
self.table.vals[k] = val
else:
Expand Down Expand Up @@ -1022,7 +1098,6 @@ cdef class PyObjectHashTable(HashTable):
hash(key)

k = kh_put_pymap(self.table, <PyObject*>key, &ret)
# self.table.keys[k] = key
if kh_exist_pymap(self.table, k):
self.table.vals[k] = val
else:
Expand Down
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