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# Licensed to the Apache Software Foundation (ASF) under one
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# 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 logging
import re
from datetime import datetime
from re import Pattern
from typing import Any, Optional
from flask_babel import gettext as __
from sqlalchemy import types
from sqlalchemy.dialects.mssql.base import SMALLDATETIME
from superset.constants import TimeGrain
from superset.db_engine_specs.base import BaseEngineSpec, LimitMethod
from superset.errors import SupersetErrorType
from superset.utils.core import GenericDataType
logger = logging.getLogger(__name__)
# Regular expressions to catch custom errors
CONNECTION_ACCESS_DENIED_REGEX = re.compile("Adaptive Server connection failed")
CONNECTION_INVALID_HOSTNAME_REGEX = re.compile(
r"Adaptive Server is unavailable or does not exist \((?P<hostname>.*?)\)"
"(?!.*Net-Lib error).*$"
)
CONNECTION_PORT_CLOSED_REGEX = re.compile(
r"Net-Lib error during Connection refused \(61\)"
)
CONNECTION_HOST_DOWN_REGEX = re.compile(
r"Net-Lib error during Operation timed out \(60\)"
)
class MssqlEngineSpec(BaseEngineSpec):
engine = "mssql"
engine_name = "Microsoft SQL Server"
limit_method = LimitMethod.WRAP_SQL
max_column_name_length = 128
allows_cte_in_subquery = False
allow_limit_clause = False
_time_grain_expressions = {
None: "{col}",
TimeGrain.SECOND: "DATEADD(SECOND, \
DATEDIFF(SECOND, '2000-01-01', {col}), '2000-01-01')",
TimeGrain.MINUTE: "DATEADD(MINUTE, DATEDIFF(MINUTE, 0, {col}), 0)",
TimeGrain.FIVE_MINUTES: "DATEADD(MINUTE, \
DATEDIFF(MINUTE, 0, {col}) / 5 * 5, 0)",
TimeGrain.TEN_MINUTES: "DATEADD(MINUTE, \
DATEDIFF(MINUTE, 0, {col}) / 10 * 10, 0)",
TimeGrain.FIFTEEN_MINUTES: "DATEADD(MINUTE, \
DATEDIFF(MINUTE, 0, {col}) / 15 * 15, 0)",
TimeGrain.THIRTY_MINUTES: "DATEADD(MINUTE, \
DATEDIFF(MINUTE, 0, {col}) / 30 * 30, 0)",
TimeGrain.HOUR: "DATEADD(HOUR, DATEDIFF(HOUR, 0, {col}), 0)",
TimeGrain.DAY: "DATEADD(DAY, DATEDIFF(DAY, 0, {col}), 0)",
TimeGrain.WEEK: "DATEADD(DAY, 1 - DATEPART(WEEKDAY, {col}),"
" DATEADD(DAY, DATEDIFF(DAY, 0, {col}), 0))",
TimeGrain.MONTH: "DATEADD(MONTH, DATEDIFF(MONTH, 0, {col}), 0)",
TimeGrain.QUARTER: "DATEADD(QUARTER, DATEDIFF(QUARTER, 0, {col}), 0)",
TimeGrain.YEAR: "DATEADD(YEAR, DATEDIFF(YEAR, 0, {col}), 0)",
TimeGrain.WEEK_STARTING_SUNDAY: "DATEADD(DAY, -1,"
" DATEADD(WEEK, DATEDIFF(WEEK, 0, {col}), 0))",
TimeGrain.WEEK_STARTING_MONDAY: "DATEADD(WEEK,"
" DATEDIFF(WEEK, 0, DATEADD(DAY, -1, {col})), 0)",
}
column_type_mappings = (
(
re.compile(r"^smalldatetime.*", re.IGNORECASE),
SMALLDATETIME(),
GenericDataType.TEMPORAL,
),
)
custom_errors: dict[Pattern[str], tuple[str, SupersetErrorType, dict[str, Any]]] = {
CONNECTION_ACCESS_DENIED_REGEX: (
__(
'Either the username "%(username)s", password, '
'or database name "%(database)s" is incorrect.'
),
SupersetErrorType.CONNECTION_ACCESS_DENIED_ERROR,
{},
),
CONNECTION_INVALID_HOSTNAME_REGEX: (
__('The hostname "%(hostname)s" cannot be resolved.'),
SupersetErrorType.CONNECTION_INVALID_HOSTNAME_ERROR,
{},
),
CONNECTION_PORT_CLOSED_REGEX: (
__('Port %(port)s on hostname "%(hostname)s" refused the connection.'),
SupersetErrorType.CONNECTION_PORT_CLOSED_ERROR,
{},
),
CONNECTION_HOST_DOWN_REGEX: (
__(
'The host "%(hostname)s" might be down, and can\'t be '
"reached on port %(port)s."
),
SupersetErrorType.CONNECTION_HOST_DOWN_ERROR,
{},
),
}
@classmethod
def epoch_to_dttm(cls) -> str:
return "dateadd(S, {col}, '1970-01-01')"
@classmethod
def convert_dttm(
cls, target_type: str, dttm: datetime, db_extra: Optional[dict[str, Any]] = None
) -> Optional[str]:
sqla_type = cls.get_sqla_column_type(target_type)
if isinstance(sqla_type, types.Date):
return f"CONVERT(DATE, '{dttm.date().isoformat()}', 23)"
if isinstance(sqla_type, SMALLDATETIME):
datetime_formatted = dttm.isoformat(sep=" ", timespec="seconds")
return f"""CONVERT(SMALLDATETIME, '{datetime_formatted}', 20)"""
if isinstance(sqla_type, types.DateTime):
datetime_formatted = dttm.isoformat(timespec="milliseconds")
return f"""CONVERT(DATETIME, '{datetime_formatted}', 126)"""
return None
@classmethod
def fetch_data(
cls, cursor: Any, limit: Optional[int] = None
) -> list[tuple[Any, ...]]:
data = super().fetch_data(cursor, limit)
# Lists of `pyodbc.Row` need to be unpacked further
return cls.pyodbc_rows_to_tuples(data)
@classmethod
def extract_error_message(cls, ex: Exception) -> str:
if str(ex).startswith("(8155,"):
return (
f"{cls.engine} error: All your SQL functions need to "
"have an alias on MSSQL. For example: SELECT COUNT(*) AS C1 FROM TABLE1"
)
return f"{cls.engine} error: {cls._extract_error_message(ex)}"
class AzureSynapseSpec(MssqlEngineSpec):
engine = "mssql"
engine_name = "Azure Synapse"
default_driver = "pyodbc"