File size: 3,687 Bytes
1856027 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | # Copyright 2020 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
#
# 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 typing
from typing import Dict, Optional
if typing.TYPE_CHECKING:
from google.cloud import bigquery
def create_materialized_view(
override_values: Optional[Dict[str, str]] = None
) -> "bigquery.Table":
if override_values is None:
override_values = {}
# [START bigquery_create_materialized_view]
from google.cloud import bigquery
bigquery_client = bigquery.Client()
view_id = "my-project.my_dataset.my_materialized_view"
base_table_id = "my-project.my_dataset.my_base_table"
# [END bigquery_create_materialized_view]
# To facilitate testing, we replace values with alternatives
# provided by the testing harness.
view_id = override_values.get("view_id", view_id)
base_table_id = override_values.get("base_table_id", base_table_id)
# [START bigquery_create_materialized_view]
view = bigquery.Table(view_id)
view.mview_query = f"""
SELECT product_id, SUM(clicks) AS sum_clicks
FROM `{base_table_id}`
GROUP BY 1
"""
# Make an API request to create the materialized view.
view = bigquery_client.create_table(view)
print(f"Created {view.table_type}: {str(view.reference)}")
# [END bigquery_create_materialized_view]
return view
def update_materialized_view(
override_values: Optional[Dict[str, str]] = None
) -> "bigquery.Table":
if override_values is None:
override_values = {}
# [START bigquery_update_materialized_view]
import datetime
from google.cloud import bigquery
bigquery_client = bigquery.Client()
view_id = "my-project.my_dataset.my_materialized_view"
# [END bigquery_update_materialized_view]
# To facilitate testing, we replace values with alternatives
# provided by the testing harness.
view_id = override_values.get("view_id", view_id)
# [START bigquery_update_materialized_view]
view = bigquery.Table(view_id)
view.mview_enable_refresh = True
view.mview_refresh_interval = datetime.timedelta(hours=1)
# Make an API request to update the materialized view.
view = bigquery_client.update_table(
view,
# Pass in a list of any fields you need to modify.
["mview_enable_refresh", "mview_refresh_interval"],
)
print(f"Updated {view.table_type}: {str(view.reference)}")
# [END bigquery_update_materialized_view]
return view
def delete_materialized_view(override_values: Optional[Dict[str, str]] = None) -> None:
if override_values is None:
override_values = {}
# [START bigquery_delete_materialized_view]
from google.cloud import bigquery
bigquery_client = bigquery.Client()
view_id = "my-project.my_dataset.my_materialized_view"
# [END bigquery_delete_materialized_view]
# To facilitate testing, we replace values with alternatives
# provided by the testing harness.
view_id = override_values.get("view_id", view_id)
# [START bigquery_delete_materialized_view]
# Make an API request to delete the materialized view.
bigquery_client.delete_table(view_id)
# [END bigquery_delete_materialized_view]
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