/
test_arrow.py
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/
test_arrow.py
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# Copyright 2021 Google LLC
#
# Licensed 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
#
# https://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.
"""System tests for Arrow connector."""
from typing import Optional
import pytest
from google.cloud import bigquery
from google.cloud.bigquery import enums
pyarrow = pytest.importorskip(
"pyarrow", minversion="3.0.0"
) # Needs decimal256 for BIGNUMERIC columns.
@pytest.mark.parametrize(
("max_results", "scalars_table_name"),
(
(None, "scalars_table"), # Use BQ Storage API.
(10, "scalars_table"), # Use REST API.
(None, "scalars_extreme_table"), # Use BQ Storage API.
(10, "scalars_extreme_table"), # Use REST API.
),
)
def test_list_rows_nullable_scalars_dtypes(
bigquery_client: bigquery.Client,
scalars_table: str,
scalars_extreme_table: str,
max_results: Optional[int],
scalars_table_name: str,
):
table_id = scalars_table
if scalars_table_name == "scalars_extreme_table":
table_id = scalars_extreme_table
# TODO(GH#836): Avoid INTERVAL columns until they are supported by the
# BigQuery Storage API and pyarrow.
schema = [
bigquery.SchemaField("bool_col", enums.SqlTypeNames.BOOLEAN),
bigquery.SchemaField("bignumeric_col", enums.SqlTypeNames.BIGNUMERIC),
bigquery.SchemaField("bytes_col", enums.SqlTypeNames.BYTES),
bigquery.SchemaField("date_col", enums.SqlTypeNames.DATE),
bigquery.SchemaField("datetime_col", enums.SqlTypeNames.DATETIME),
bigquery.SchemaField("float64_col", enums.SqlTypeNames.FLOAT64),
bigquery.SchemaField("geography_col", enums.SqlTypeNames.GEOGRAPHY),
bigquery.SchemaField("int64_col", enums.SqlTypeNames.INT64),
bigquery.SchemaField("numeric_col", enums.SqlTypeNames.NUMERIC),
bigquery.SchemaField("string_col", enums.SqlTypeNames.STRING),
bigquery.SchemaField("time_col", enums.SqlTypeNames.TIME),
bigquery.SchemaField("timestamp_col", enums.SqlTypeNames.TIMESTAMP),
]
arrow_table = bigquery_client.list_rows(
table_id, max_results=max_results, selected_fields=schema,
).to_arrow()
schema = arrow_table.schema
bignumeric_type = schema.field("bignumeric_col").type
# 77th digit is partial.
# https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#decimal_types
assert bignumeric_type.precision in {76, 77}
assert bignumeric_type.scale == 38
bool_type = schema.field("bool_col").type
assert bool_type.equals(pyarrow.bool_())
bytes_type = schema.field("bytes_col").type
assert bytes_type.equals(pyarrow.binary())
date_type = schema.field("date_col").type
assert date_type.equals(pyarrow.date32())
datetime_type = schema.field("datetime_col").type
assert datetime_type.unit == "us"
assert datetime_type.tz is None
float64_type = schema.field("float64_col").type
assert float64_type.equals(pyarrow.float64())
geography_type = schema.field("geography_col").type
assert geography_type.equals(pyarrow.string())
int64_type = schema.field("int64_col").type
assert int64_type.equals(pyarrow.int64())
numeric_type = schema.field("numeric_col").type
assert numeric_type.precision == 38
assert numeric_type.scale == 9
string_type = schema.field("string_col").type
assert string_type.equals(pyarrow.string())
time_type = schema.field("time_col").type
assert time_type.equals(pyarrow.time64("us"))
timestamp_type = schema.field("timestamp_col").type
assert timestamp_type.unit == "us"
assert timestamp_type.tz is not None
@pytest.mark.parametrize("do_insert", [True, False])
def test_arrow_extension_types_same_for_storage_and_REST_APIs_894(
dataset_client, test_table_name, do_insert
):
types = dict(
astring=("STRING", "'x'"),
astring9=("STRING(9)", "'x'"),
abytes=("BYTES", "b'x'"),
abytes9=("BYTES(9)", "b'x'"),
anumeric=("NUMERIC", "42"),
anumeric9=("NUMERIC(9)", "42"),
anumeric92=("NUMERIC(9,2)", "42"),
abignumeric=("BIGNUMERIC", "42e30"),
abignumeric49=("BIGNUMERIC(37)", "42e30"),
abignumeric492=("BIGNUMERIC(37,2)", "42e30"),
abool=("BOOL", "true"),
adate=("DATE", "'2021-09-06'"),
adatetime=("DATETIME", "'2021-09-06T09:57:26'"),
ageography=("GEOGRAPHY", "ST_GEOGFROMTEXT('point(0 0)')"),
# Can't get arrow data for interval :(
# ainterval=('INTERVAL', "make_interval(1, 2, 3, 4, 5, 6)"),
aint64=("INT64", "42"),
afloat64=("FLOAT64", "42.0"),
astruct=("STRUCT<v int64>", "struct(42)"),
atime=("TIME", "'1:2:3'"),
atimestamp=("TIMESTAMP", "'2021-09-06T09:57:26'"),
)
columns = ", ".join(f"{k} {t[0]}" for k, t in types.items())
dataset_client.query(f"create table {test_table_name} ({columns})").result()
if do_insert:
names = list(types)
values = ", ".join(types[name][1] for name in names)
names = ", ".join(names)
dataset_client.query(
f"insert into {test_table_name} ({names}) values ({values})"
).result()
at = dataset_client.query(f"select * from {test_table_name}").result().to_arrow()
storage_api_metadata = {
at.field(i).name: at.field(i).metadata for i in range(at.num_columns)
}
at = (
dataset_client.query(f"select * from {test_table_name}")
.result()
.to_arrow(create_bqstorage_client=False)
)
rest_api_metadata = {
at.field(i).name: at.field(i).metadata for i in range(at.num_columns)
}
assert rest_api_metadata == storage_api_metadata
assert rest_api_metadata["adatetime"] == {
b"ARROW:extension:name": b"google:sqlType:datetime"
}
assert rest_api_metadata["ageography"] == {
b"ARROW:extension:name": b"google:sqlType:geography",
b"ARROW:extension:metadata": b'{"encoding": "WKT"}',
}