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join.pyx
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join.pyx
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# cython: profile=False
cimport cython
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (ndarray,
int8_t, int16_t, int32_t, int64_t, uint8_t, uint16_t,
uint32_t, uint64_t, float32_t, float64_t)
cnp.import_array()
cdef double NaN = <double> np.NaN
cdef double nan = NaN
from pandas._libs.algos import groupsort_indexer, ensure_platform_int
from pandas.core.algorithms import take_nd
include "join_func_helper.pxi"
def inner_join(ndarray[int64_t] left, ndarray[int64_t] right,
Py_ssize_t max_groups):
cdef:
Py_ssize_t i, j, k, count = 0
ndarray[int64_t] left_count, right_count, left_sorter, right_sorter
ndarray[int64_t] left_indexer, right_indexer
int64_t lc, rc
# NA group in location 0
left_sorter, left_count = groupsort_indexer(left, max_groups)
right_sorter, right_count = groupsort_indexer(right, max_groups)
# First pass, determine size of result set, do not use the NA group
for i in range(1, max_groups + 1):
lc = left_count[i]
rc = right_count[i]
if rc > 0 and lc > 0:
count += lc * rc
# group 0 is the NA group
cdef:
Py_ssize_t loc, left_pos = 0, right_pos = 0, position = 0
Py_ssize_t offset
# exclude the NA group
left_pos = left_count[0]
right_pos = right_count[0]
left_indexer = np.empty(count, dtype=np.int64)
right_indexer = np.empty(count, dtype=np.int64)
for i in range(1, max_groups + 1):
lc = left_count[i]
rc = right_count[i]
if rc > 0 and lc > 0:
for j in range(lc):
offset = position + j * rc
for k in range(rc):
left_indexer[offset + k] = left_pos + j
right_indexer[offset + k] = right_pos + k
position += lc * rc
left_pos += lc
right_pos += rc
return (_get_result_indexer(left_sorter, left_indexer),
_get_result_indexer(right_sorter, right_indexer))
def left_outer_join(ndarray[int64_t] left, ndarray[int64_t] right,
Py_ssize_t max_groups, sort=True):
cdef:
Py_ssize_t i, j, k, count = 0
ndarray[int64_t] left_count, right_count
ndarray left_sorter, right_sorter, rev
ndarray[int64_t] left_indexer, right_indexer
int64_t lc, rc
# NA group in location 0
left_sorter, left_count = groupsort_indexer(left, max_groups)
right_sorter, right_count = groupsort_indexer(right, max_groups)
# First pass, determine size of result set, do not use the NA group
for i in range(1, max_groups + 1):
if right_count[i] > 0:
count += left_count[i] * right_count[i]
else:
count += left_count[i]
# group 0 is the NA group
cdef:
Py_ssize_t loc, left_pos = 0, right_pos = 0, position = 0
Py_ssize_t offset
# exclude the NA group
left_pos = left_count[0]
right_pos = right_count[0]
left_indexer = np.empty(count, dtype=np.int64)
right_indexer = np.empty(count, dtype=np.int64)
for i in range(1, max_groups + 1):
lc = left_count[i]
rc = right_count[i]
if rc == 0:
for j in range(lc):
left_indexer[position + j] = left_pos + j
right_indexer[position + j] = -1
position += lc
else:
for j in range(lc):
offset = position + j * rc
for k in range(rc):
left_indexer[offset + k] = left_pos + j
right_indexer[offset + k] = right_pos + k
position += lc * rc
left_pos += lc
right_pos += rc
left_indexer = _get_result_indexer(left_sorter, left_indexer)
right_indexer = _get_result_indexer(right_sorter, right_indexer)
if not sort: # if not asked to sort, revert to original order
if len(left) == len(left_indexer):
# no multiple matches for any row on the left
# this is a short-cut to avoid groupsort_indexer
# otherwise, the `else` path also works in this case
left_sorter = ensure_platform_int(left_sorter)
rev = np.empty(len(left), dtype=np.intp)
rev.put(left_sorter, np.arange(len(left)))
else:
rev, _ = groupsort_indexer(left_indexer, len(left))
rev = ensure_platform_int(rev)
right_indexer = right_indexer.take(rev)
left_indexer = left_indexer.take(rev)
return left_indexer, right_indexer
def full_outer_join(ndarray[int64_t] left, ndarray[int64_t] right,
Py_ssize_t max_groups):
cdef:
Py_ssize_t i, j, k, count = 0
ndarray[int64_t] left_count, right_count, left_sorter, right_sorter
ndarray[int64_t] left_indexer, right_indexer
int64_t lc, rc
# NA group in location 0
left_sorter, left_count = groupsort_indexer(left, max_groups)
right_sorter, right_count = groupsort_indexer(right, max_groups)
# First pass, determine size of result set, do not use the NA group
for i in range(1, max_groups + 1):
lc = left_count[i]
rc = right_count[i]
if rc > 0 and lc > 0:
count += lc * rc
else:
count += lc + rc
# group 0 is the NA group
cdef:
int64_t left_pos = 0, right_pos = 0
Py_ssize_t offset, position = 0
# exclude the NA group
left_pos = left_count[0]
right_pos = right_count[0]
left_indexer = np.empty(count, dtype=np.int64)
right_indexer = np.empty(count, dtype=np.int64)
for i in range(1, max_groups + 1):
lc = left_count[i]
rc = right_count[i]
if rc == 0:
for j in range(lc):
left_indexer[position + j] = left_pos + j
right_indexer[position + j] = -1
position += lc
elif lc == 0:
for j in range(rc):
left_indexer[position + j] = -1
right_indexer[position + j] = right_pos + j
position += rc
else:
for j in range(lc):
offset = position + j * rc
for k in range(rc):
left_indexer[offset + k] = left_pos + j
right_indexer[offset + k] = right_pos + k
position += lc * rc
left_pos += lc
right_pos += rc
return (_get_result_indexer(left_sorter, left_indexer),
_get_result_indexer(right_sorter, right_indexer))
def _get_result_indexer(sorter, indexer):
if len(sorter) > 0:
res = take_nd(sorter, indexer, fill_value=-1)
else:
# length-0 case
res = np.empty(len(indexer), dtype=np.int64)
res.fill(-1)
return res
def ffill_indexer(ndarray[int64_t] indexer):
cdef:
Py_ssize_t i, n = len(indexer)
ndarray[int64_t] result
int64_t val, last_obs
result = np.empty(n, dtype=np.int64)
last_obs = -1
for i in range(n):
val = indexer[i]
if val == -1:
result[i] = last_obs
else:
result[i] = val
last_obs = val
return result
include "join_helper.pxi"