# 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()