peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pyarrow
/tests
/test_exec_plan.py
# 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. | |
import pytest | |
import pyarrow as pa | |
import pyarrow.compute as pc | |
from .test_extension_type import IntegerType | |
try: | |
import pyarrow.dataset as ds | |
except ImportError: | |
pass | |
try: | |
from pyarrow.acero import _perform_join, _filter_table | |
except ImportError: | |
pass | |
pytestmark = pytest.mark.acero | |
def test_joins_corner_cases(): | |
t1 = pa.Table.from_pydict({ | |
"colA": [1, 2, 3, 4, 5, 6], | |
"col2": ["a", "b", "c", "d", "e", "f"] | |
}) | |
t2 = pa.Table.from_pydict({ | |
"colB": [1, 2, 3, 4, 5], | |
"col3": ["A", "B", "C", "D", "E"] | |
}) | |
with pytest.raises(pa.ArrowInvalid): | |
_perform_join("left outer", t1, "", t2, "") | |
with pytest.raises(TypeError): | |
_perform_join("left outer", None, "colA", t2, "colB") | |
with pytest.raises(ValueError): | |
_perform_join("super mario join", t1, "colA", t2, "colB") | |
def test_joins(jointype, expected, use_threads, coalesce_keys, use_datasets): | |
# Allocate table here instead of using parametrize | |
# this prevents having arrow allocated memory forever around. | |
expected = pa.table(expected) | |
t1 = pa.Table.from_pydict({ | |
"colA": [1, 2, 6], | |
"col2": ["a", "b", "f"] | |
}) | |
t2 = pa.Table.from_pydict({ | |
"colB": [99, 2, 1], | |
"col3": ["Z", "B", "A"] | |
}) | |
if use_datasets: | |
t1 = ds.dataset([t1]) | |
t2 = ds.dataset([t2]) | |
r = _perform_join(jointype, t1, "colA", t2, "colB", | |
use_threads=use_threads, coalesce_keys=coalesce_keys) | |
r = r.combine_chunks() | |
if "right" in jointype: | |
r = r.sort_by("colB") | |
else: | |
r = r.sort_by("colA") | |
if coalesce_keys: | |
if jointype in ("inner", "left outer"): | |
expected = expected.drop(["colB"]) | |
elif jointype == "right outer": | |
expected = expected.drop(["colA"]) | |
elif jointype == "full outer": | |
expected = expected.drop(["colB"]).set_column(0, "colA", [[1, 2, 6, 99]]) | |
assert r == expected | |
def test_table_join_collisions(): | |
t1 = pa.table({ | |
"colA": [1, 2, 6], | |
"colB": [10, 20, 60], | |
"colVals": ["a", "b", "f"] | |
}) | |
t2 = pa.table({ | |
"colB": [99, 20, 10], | |
"colVals": ["Z", "B", "A"], | |
"colUniq": [100, 200, 300], | |
"colA": [99, 2, 1], | |
}) | |
result = _perform_join( | |
"full outer", t1, ["colA", "colB"], t2, ["colA", "colB"]) | |
result = result.combine_chunks() | |
result = result.sort_by("colUniq") | |
assert result == pa.table([ | |
[None, 2, 1, 6], | |
[None, 20, 10, 60], | |
[None, "b", "a", "f"], | |
[99, 20, 10, None], | |
["Z", "B", "A", None], | |
[100, 200, 300, None], | |
[99, 2, 1, None], | |
], names=["colA", "colB", "colVals", "colB", "colVals", "colUniq", "colA"]) | |
result = _perform_join("full outer", t1, "colA", | |
t2, "colA", right_suffix="_r", | |
coalesce_keys=False) | |
result = result.combine_chunks() | |
result = result.sort_by("colA") | |
assert result == pa.table({ | |
"colA": [1, 2, 6, None], | |
"colB": [10, 20, 60, None], | |
"colVals": ["a", "b", "f", None], | |
"colB_r": [10, 20, None, 99], | |
"colVals_r": ["A", "B", None, "Z"], | |
"colUniq": [300, 200, None, 100], | |
"colA_r": [1, 2, None, 99], | |
}) | |
result = _perform_join("full outer", t1, "colA", | |
t2, "colA", right_suffix="_r", | |
coalesce_keys=True) | |
result = result.combine_chunks() | |
result = result.sort_by("colA") | |
assert result == pa.table({ | |
"colA": [1, 2, 6, 99], | |
"colB": [10, 20, 60, None], | |
"colVals": ["a", "b", "f", None], | |
"colB_r": [10, 20, None, 99], | |
"colVals_r": ["A", "B", None, "Z"], | |
"colUniq": [300, 200, None, 100] | |
}) | |
def test_table_join_keys_order(): | |
t1 = pa.table({ | |
"colB": [10, 20, 60], | |
"colA": [1, 2, 6], | |
"colVals": ["a", "b", "f"] | |
}) | |
t2 = pa.table({ | |
"colVals": ["Z", "B", "A"], | |
"colX": [99, 2, 1], | |
}) | |
result = _perform_join("full outer", t1, "colA", t2, "colX", | |
left_suffix="_l", right_suffix="_r", | |
coalesce_keys=True) | |
result = result.combine_chunks() | |
result = result.sort_by("colA") | |
assert result == pa.table({ | |
"colB": [10, 20, 60, None], | |
"colA": [1, 2, 6, 99], | |
"colVals_l": ["a", "b", "f", None], | |
"colVals_r": ["A", "B", None, "Z"], | |
}) | |
def test_filter_table_errors(): | |
t = pa.table({ | |
"a": [1, 2, 3, 4, 5], | |
"b": [10, 20, 30, 40, 50] | |
}) | |
with pytest.raises(pa.ArrowTypeError): | |
_filter_table(t, pc.divide(pc.field("a"), pc.scalar(2))) | |
with pytest.raises(pa.ArrowInvalid): | |
_filter_table(t, (pc.field("Z") <= pc.scalar(2))) | |
def test_filter_table(): | |
t = pa.table({ | |
"a": [1, 2, 3, 4, 5], | |
"b": [10, 20, 30, 40, 50] | |
}) | |
result = _filter_table( | |
t, (pc.field("a") <= pc.scalar(3)) & (pc.field("b") == pc.scalar(20)), | |
) | |
assert result == pa.table({ | |
"a": [2], | |
"b": [20] | |
}) | |
result = _filter_table(t, pc.field("b") > pc.scalar(30)) | |
assert result == pa.table({ | |
"a": [4, 5], | |
"b": [40, 50] | |
}) | |
def test_filter_table_ordering(): | |
table1 = pa.table({'a': [1, 2, 3, 4], 'b': ['a'] * 4}) | |
table2 = pa.table({'a': [1, 2, 3, 4], 'b': ['b'] * 4}) | |
table = pa.concat_tables([table1, table2]) | |
for _ in range(20): | |
# 20 seems to consistently cause errors when order is not preserved. | |
# If the order problem is reintroduced this test will become flaky | |
# which is still a signal that the order is not preserved. | |
r = _filter_table(table, pc.field('a') == 1) | |
assert r["b"] == pa.chunked_array([["a"], ["b"]]) | |
def test_complex_filter_table(): | |
t = pa.table({ | |
"a": [1, 2, 3, 4, 5, 6, 6], | |
"b": [10, 20, 30, 40, 50, 60, 61] | |
}) | |
result = _filter_table( | |
t, ((pc.bit_wise_and(pc.field("a"), pc.scalar(1)) == pc.scalar(0)) & | |
(pc.multiply(pc.field("a"), pc.scalar(10)) == pc.field("b"))) | |
) | |
assert result == pa.table({ | |
"a": [2, 4, 6], # second six must be omitted because 6*10 != 61 | |
"b": [20, 40, 60] | |
}) | |
def test_join_extension_array_column(): | |
storage = pa.array([1, 2, 3], type=pa.int64()) | |
ty = IntegerType() | |
ext_array = pa.ExtensionArray.from_storage(ty, storage) | |
dict_array = pa.DictionaryArray.from_arrays( | |
pa.array([0, 2, 1]), pa.array(['a', 'b', 'c'])) | |
t1 = pa.table({ | |
"colA": [1, 2, 6], | |
"colB": ext_array, | |
"colVals": ext_array, | |
}) | |
t2 = pa.table({ | |
"colA": [99, 2, 1], | |
"colC": ext_array, | |
}) | |
t3 = pa.table({ | |
"colA": [99, 2, 1], | |
"colC": ext_array, | |
"colD": dict_array, | |
}) | |
result = _perform_join( | |
"left outer", t1, ["colA"], t2, ["colA"]) | |
assert result["colVals"] == pa.chunked_array(ext_array) | |
result = _perform_join( | |
"left outer", t1, ["colB"], t2, ["colC"]) | |
assert result["colB"] == pa.chunked_array(ext_array) | |
result = _perform_join( | |
"left outer", t1, ["colA"], t3, ["colA"]) | |
assert result["colVals"] == pa.chunked_array(ext_array) | |
result = _perform_join( | |
"left outer", t1, ["colB"], t3, ["colC"]) | |
assert result["colB"] == pa.chunked_array(ext_array) | |
def test_group_by_ordering(): | |
# GH-36709 - preserve ordering in groupby by setting use_threads=False | |
table1 = pa.table({'a': [1, 2, 3, 4], 'b': ['a'] * 4}) | |
table2 = pa.table({'a': [1, 2, 3, 4], 'b': ['b'] * 4}) | |
table = pa.concat_tables([table1, table2]) | |
for _ in range(50): | |
# 50 seems to consistently cause errors when order is not preserved. | |
# If the order problem is reintroduced this test will become flaky | |
# which is still a signal that the order is not preserved. | |
result = table.group_by("b", use_threads=False).aggregate([]) | |
assert result["b"] == pa.chunked_array([["a"], ["b"]]) | |