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# 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 pyarrow.compute import field
try:
from pyarrow.acero import (
Declaration,
TableSourceNodeOptions,
FilterNodeOptions,
ProjectNodeOptions,
AggregateNodeOptions,
OrderByNodeOptions,
HashJoinNodeOptions,
AsofJoinNodeOptions,
)
except ImportError:
pass
try:
import pyarrow.dataset as ds
from pyarrow.acero import ScanNodeOptions
except ImportError:
ds = None
pytestmark = pytest.mark.acero
@pytest.fixture
def table_source():
table = pa.table({'a': [1, 2, 3], 'b': [4, 5, 6]})
table_opts = TableSourceNodeOptions(table)
table_source = Declaration("table_source", options=table_opts)
return table_source
def test_declaration():
table = pa.table({'a': [1, 2, 3], 'b': [4, 5, 6]})
table_opts = TableSourceNodeOptions(table)
filter_opts = FilterNodeOptions(field('a') > 1)
# using sequence
decl = Declaration.from_sequence([
Declaration("table_source", options=table_opts),
Declaration("filter", options=filter_opts)
])
result = decl.to_table()
assert result.equals(table.slice(1, 2))
# using explicit inputs
table_source = Declaration("table_source", options=table_opts)
filtered = Declaration("filter", options=filter_opts, inputs=[table_source])
result = filtered.to_table()
assert result.equals(table.slice(1, 2))
def test_declaration_repr(table_source):
assert "TableSourceNode" in str(table_source)
assert "TableSourceNode" in repr(table_source)
def test_declaration_to_reader(table_source):
with table_source.to_reader() as reader:
assert reader.schema == pa.schema([("a", pa.int64()), ("b", pa.int64())])
result = reader.read_all()
expected = pa.table({'a': [1, 2, 3], 'b': [4, 5, 6]})
assert result.equals(expected)
def test_table_source():
with pytest.raises(TypeError):
TableSourceNodeOptions(pa.record_batch([pa.array([1, 2, 3])], ["a"]))
table_source = TableSourceNodeOptions(None)
decl = Declaration("table_source", table_source)
with pytest.raises(
ValueError, match="TableSourceNode requires table which is not null"
):
_ = decl.to_table()
def test_filter(table_source):
# referencing unknown field
decl = Declaration.from_sequence([
table_source,
Declaration("filter", options=FilterNodeOptions(field("c") > 1))
])
with pytest.raises(ValueError, match=r"No match for FieldRef.Name\(c\)"):
_ = decl.to_table()
# requires a pyarrow Expression
with pytest.raises(TypeError):
FilterNodeOptions(pa.array([True, False, True]))
with pytest.raises(TypeError):
FilterNodeOptions(None)
def test_project(table_source):
# default name from expression
decl = Declaration.from_sequence([
table_source,
Declaration("project", ProjectNodeOptions([pc.multiply(field("a"), 2)]))
])
result = decl.to_table()
assert result.schema.names == ["multiply(a, 2)"]
assert result[0].to_pylist() == [2, 4, 6]
# provide name
decl = Declaration.from_sequence([
table_source,
Declaration("project", ProjectNodeOptions([pc.multiply(field("a"), 2)], ["a2"]))
])
result = decl.to_table()
assert result.schema.names == ["a2"]
assert result["a2"].to_pylist() == [2, 4, 6]
# input validation
with pytest.raises(ValueError):
ProjectNodeOptions([pc.multiply(field("a"), 2)], ["a2", "b2"])
# no scalar expression
decl = Declaration.from_sequence([
table_source,
Declaration("project", ProjectNodeOptions([pc.sum(field("a"))]))
])
with pytest.raises(ValueError, match="cannot Execute non-scalar expression"):
_ = decl.to_table()
def test_aggregate_scalar(table_source):
decl = Declaration.from_sequence([
table_source,
Declaration("aggregate", AggregateNodeOptions([("a", "sum", None, "a_sum")]))
])
result = decl.to_table()
assert result.schema.names == ["a_sum"]
assert result["a_sum"].to_pylist() == [6]
# with options class
table = pa.table({'a': [1, 2, None]})
aggr_opts = AggregateNodeOptions(
[("a", "sum", pc.ScalarAggregateOptions(skip_nulls=False), "a_sum")]
)
decl = Declaration.from_sequence([
Declaration("table_source", TableSourceNodeOptions(table)),
Declaration("aggregate", aggr_opts),
])
result = decl.to_table()
assert result.schema.names == ["a_sum"]
assert result["a_sum"].to_pylist() == [None]
# test various ways of specifying the target column
for target in ["a", field("a"), 0, field(0), ["a"], [field("a")], [0]]:
aggr_opts = AggregateNodeOptions([(target, "sum", None, "a_sum")])
decl = Declaration.from_sequence(
[table_source, Declaration("aggregate", aggr_opts)]
)
result = decl.to_table()
assert result.schema.names == ["a_sum"]
assert result["a_sum"].to_pylist() == [6]
# proper error when specifying the wrong number of target columns
aggr_opts = AggregateNodeOptions([(["a", "b"], "sum", None, "a_sum")])
decl = Declaration.from_sequence(
[table_source, Declaration("aggregate", aggr_opts)]
)
with pytest.raises(
ValueError, match="Function 'sum' accepts 1 arguments but 2 passed"
):
_ = decl.to_table()
# proper error when using hash aggregation without keys
aggr_opts = AggregateNodeOptions([("a", "hash_sum", None, "a_sum")])
decl = Declaration.from_sequence(
[table_source, Declaration("aggregate", aggr_opts)]
)
with pytest.raises(ValueError, match="is a hash aggregate function"):
_ = decl.to_table()
def test_aggregate_hash():
table = pa.table({'a': [1, 2, None], 'b': ["foo", "bar", "foo"]})
table_opts = TableSourceNodeOptions(table)
table_source = Declaration("table_source", options=table_opts)
# default options
aggr_opts = AggregateNodeOptions(
[("a", "hash_count", None, "count(a)")], keys=["b"])
decl = Declaration.from_sequence([
table_source, Declaration("aggregate", aggr_opts)
])
result = decl.to_table()
expected = pa.table({"b": ["foo", "bar"], "count(a)": [1, 1]})
assert result.equals(expected)
# specify function options
aggr_opts = AggregateNodeOptions(
[("a", "hash_count", pc.CountOptions("all"), "count(a)")], keys=["b"]
)
decl = Declaration.from_sequence([
table_source, Declaration("aggregate", aggr_opts)
])
result = decl.to_table()
expected_all = pa.table({"b": ["foo", "bar"], "count(a)": [2, 1]})
assert result.equals(expected_all)
# specify keys as field references
aggr_opts = AggregateNodeOptions(
[("a", "hash_count", None, "count(a)")], keys=[field("b")]
)
decl = Declaration.from_sequence([
table_source, Declaration("aggregate", aggr_opts)
])
result = decl.to_table()
assert result.equals(expected)
# wrong type of (aggregation) function
# TODO test with kernel that matches number of arguments (arity) -> avoid segfault
aggr_opts = AggregateNodeOptions([("a", "sum", None, "a_sum")], keys=["b"])
decl = Declaration.from_sequence([
table_source, Declaration("aggregate", aggr_opts)
])
with pytest.raises(ValueError):
_ = decl.to_table()
def test_order_by():
table = pa.table({'a': [1, 2, 3, 4], 'b': [1, 3, None, 2]})
table_source = Declaration("table_source", TableSourceNodeOptions(table))
ord_opts = OrderByNodeOptions([("b", "ascending")])
decl = Declaration.from_sequence([table_source, Declaration("order_by", ord_opts)])
result = decl.to_table()
expected = pa.table({"a": [1, 4, 2, 3], "b": [1, 2, 3, None]})
assert result.equals(expected)
ord_opts = OrderByNodeOptions([(field("b"), "descending")])
decl = Declaration.from_sequence([table_source, Declaration("order_by", ord_opts)])
result = decl.to_table()
expected = pa.table({"a": [2, 4, 1, 3], "b": [3, 2, 1, None]})
assert result.equals(expected)
ord_opts = OrderByNodeOptions([(1, "descending")], null_placement="at_start")
decl = Declaration.from_sequence([table_source, Declaration("order_by", ord_opts)])
result = decl.to_table()
expected = pa.table({"a": [3, 2, 4, 1], "b": [None, 3, 2, 1]})
assert result.equals(expected)
# empty ordering
ord_opts = OrderByNodeOptions([])
decl = Declaration.from_sequence([table_source, Declaration("order_by", ord_opts)])
with pytest.raises(
ValueError, match="`ordering` must be an explicit non-empty ordering"
):
_ = decl.to_table()
with pytest.raises(ValueError, match="\"decreasing\" is not a valid sort order"):
_ = OrderByNodeOptions([("b", "decreasing")])
with pytest.raises(ValueError, match="\"start\" is not a valid null placement"):
_ = OrderByNodeOptions([("b", "ascending")], null_placement="start")
def test_hash_join():
left = pa.table({'key': [1, 2, 3], 'a': [4, 5, 6]})
left_source = Declaration("table_source", options=TableSourceNodeOptions(left))
right = pa.table({'key': [2, 3, 4], 'b': [4, 5, 6]})
right_source = Declaration("table_source", options=TableSourceNodeOptions(right))
# inner join
join_opts = HashJoinNodeOptions("inner", left_keys="key", right_keys="key")
joined = Declaration(
"hashjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
expected = pa.table(
[[2, 3], [5, 6], [2, 3], [4, 5]],
names=["key", "a", "key", "b"])
assert result.equals(expected)
for keys in [field("key"), ["key"], [field("key")]]:
join_opts = HashJoinNodeOptions("inner", left_keys=keys, right_keys=keys)
joined = Declaration(
"hashjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
assert result.equals(expected)
# left join
join_opts = HashJoinNodeOptions(
"left outer", left_keys="key", right_keys="key")
joined = Declaration(
"hashjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
expected = pa.table(
[[1, 2, 3], [4, 5, 6], [None, 2, 3], [None, 4, 5]],
names=["key", "a", "key", "b"]
)
assert result.sort_by("a").equals(expected)
# suffixes
join_opts = HashJoinNodeOptions(
"left outer", left_keys="key", right_keys="key",
output_suffix_for_left="_left", output_suffix_for_right="_right")
joined = Declaration(
"hashjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
expected = pa.table(
[[1, 2, 3], [4, 5, 6], [None, 2, 3], [None, 4, 5]],
names=["key_left", "a", "key_right", "b"]
)
assert result.sort_by("a").equals(expected)
# manually specifying output columns
join_opts = HashJoinNodeOptions(
"left outer", left_keys="key", right_keys="key",
left_output=["key", "a"], right_output=[field("b")])
joined = Declaration(
"hashjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
expected = pa.table(
[[1, 2, 3], [4, 5, 6], [None, 4, 5]],
names=["key", "a", "b"]
)
assert result.sort_by("a").equals(expected)
def test_asof_join():
left = pa.table({'key': [1, 2, 3], 'ts': [1, 1, 1], 'a': [4, 5, 6]})
left_source = Declaration("table_source", options=TableSourceNodeOptions(left))
right = pa.table({'key': [2, 3, 4], 'ts': [2, 5, 2], 'b': [4, 5, 6]})
right_source = Declaration("table_source", options=TableSourceNodeOptions(right))
# asof join
join_opts = AsofJoinNodeOptions(
left_on="ts", left_by=["key"],
right_on="ts", right_by=["key"],
tolerance=1,
)
joined = Declaration(
"asofjoin", options=join_opts, inputs=[left_source, right_source]
)
result = joined.to_table()
expected = pa.table(
[[1, 2, 3], [1, 1, 1], [4, 5, 6], [None, 4, None]],
names=["key", "ts", "a", "b"])
assert result == expected
for by in [field("key"), ["key"], [field("key")]]:
for on in [field("ts"), "ts"]:
join_opts = AsofJoinNodeOptions(
left_on=on, left_by=by,
right_on=on, right_by=by,
tolerance=1,
)
joined = Declaration(
"asofjoin", options=join_opts, inputs=[left_source, right_source])
result = joined.to_table()
assert result == expected
@pytest.mark.dataset
def test_scan(tempdir):
table = pa.table({'a': [1, 2, 3], 'b': [4, 5, 6]})
ds.write_dataset(table, tempdir / "dataset", format="parquet")
dataset = ds.dataset(tempdir / "dataset", format="parquet")
decl = Declaration("scan", ScanNodeOptions(dataset))
result = decl.to_table()
assert result.schema.names == [
"a", "b", "__fragment_index", "__batch_index",
"__last_in_fragment", "__filename"
]
assert result.select(["a", "b"]).equals(table)
# using a filter only does pushdown (depending on file format), not actual filter
scan_opts = ScanNodeOptions(dataset, filter=field('a') > 1)
decl = Declaration("scan", scan_opts)
# fragment not filtered based on min/max statistics
assert decl.to_table().num_rows == 3
scan_opts = ScanNodeOptions(dataset, filter=field('a') > 4)
decl = Declaration("scan", scan_opts)
# full fragment filtered based on min/max statistics
assert decl.to_table().num_rows == 0
# projection scan option
scan_opts = ScanNodeOptions(dataset, columns={"a2": pc.multiply(field("a"), 2)})
decl = Declaration("scan", scan_opts)
result = decl.to_table()
# "a" is included in the result (needed later on for the actual projection)
assert result["a"].to_pylist() == [1, 2, 3]
# "b" is still included, but without data as it will be removed by the projection
assert pc.all(result["b"].is_null()).as_py()
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