superset/db_engine_specs/redshift.py
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# to you under the Apache License, Version 2.0 (the
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# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
import logging
import re
from re import Pattern
from typing import Any
import pandas as pd
from flask_babel import gettext as __
from sqlalchemy.types import NVARCHAR
from superset.db_engine_specs.base import BasicParametersMixin
from superset.db_engine_specs.postgres import PostgresBaseEngineSpec
from superset.errors import SupersetErrorType
from superset.models.core import Database
from superset.models.sql_lab import Query
from superset.sql_parse import Table
logger = logging.getLogger()
# Regular expressions to catch custom errors
CONNECTION_ACCESS_DENIED_REGEX = re.compile(
'password authentication failed for user "(?P<username>.*?)"'
)
CONNECTION_INVALID_HOSTNAME_REGEX = re.compile(
'could not translate host name "(?P<hostname>.*?)" to address: '
"nodename nor servname provided, or not known"
)
CONNECTION_PORT_CLOSED_REGEX = re.compile(
r"could not connect to server: Connection refused\s+Is the server "
r'running on host "(?P<hostname>.*?)" (\(.*?\) )?and accepting\s+TCP/IP '
r"connections on port (?P<port>.*?)\?"
)
CONNECTION_HOST_DOWN_REGEX = re.compile(
r"could not connect to server: (?P<reason>.*?)\s+Is the server running on "
r'host "(?P<hostname>.*?)" (\(.*?\) )?and accepting\s+TCP/IP '
r"connections on port (?P<port>.*?)\?"
)
CONNECTION_UNKNOWN_DATABASE_REGEX = re.compile(
'database "(?P<database>.*?)" does not exist'
)
class RedshiftEngineSpec(BasicParametersMixin, PostgresBaseEngineSpec):
engine = "redshift"
engine_name = "Amazon Redshift"
max_column_name_length = 127
default_driver = "psycopg2"
sqlalchemy_uri_placeholder = (
"redshift+psycopg2://user:password@host:port/dbname[?key=value&key=value...]"
)
encryption_parameters = {"sslmode": "verify-ca"}
custom_errors: dict[Pattern[str], tuple[str, SupersetErrorType, dict[str, Any]]] = {
CONNECTION_ACCESS_DENIED_REGEX: (
__('Either the username "%(username)s" or the password is incorrect.'),
SupersetErrorType.CONNECTION_ACCESS_DENIED_ERROR,
{"invalid": ["username", "password"]},
),
CONNECTION_INVALID_HOSTNAME_REGEX: (
__('The hostname "%(hostname)s" cannot be resolved.'),
SupersetErrorType.CONNECTION_INVALID_HOSTNAME_ERROR,
{"invalid": ["host"]},
),
CONNECTION_PORT_CLOSED_REGEX: (
__('Port %(port)s on hostname "%(hostname)s" refused the connection.'),
SupersetErrorType.CONNECTION_PORT_CLOSED_ERROR,
{"invalid": ["host", "port"]},
),
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,
{"invalid": ["host", "port"]},
),
CONNECTION_UNKNOWN_DATABASE_REGEX: (
__(
'We were unable to connect to your database named "%(database)s".'
" Please verify your database name and try again."
),
SupersetErrorType.CONNECTION_UNKNOWN_DATABASE_ERROR,
{"invalid": ["database"]},
),
}
@classmethod
def df_to_sql(
cls,
database: Database,
table: Table,
df: pd.DataFrame,
to_sql_kwargs: dict[str, Any],
) -> None:
"""
Upload data from a Pandas DataFrame to a database.
For regular engines this calls the `pandas.DataFrame.to_sql` method.
Overrides the base class to allow for pandas string types to be
used as nvarchar(max) columns, as redshift does not support
text data types.
Note this method does not create metadata for the table.
:param database: The database to upload the data to
:param table: The table to upload the data to
:param df: The dataframe with data to be uploaded
:param to_sql_kwargs: The kwargs to be passed to pandas.DataFrame.to_sql` method
"""
to_sql_kwargs = to_sql_kwargs or {}
to_sql_kwargs["dtype"] = {
# uses the max size for redshift nvarchar(65335)
# the default object and string types create a varchar(256)
col_name: NVARCHAR(length=65535)
for col_name, type in zip(df.columns, df.dtypes)
if isinstance(type, pd.StringDtype)
}
super().df_to_sql(
df=df, database=database, table=table, to_sql_kwargs=to_sql_kwargs
)
@staticmethod
def _mutate_label(label: str) -> str:
"""
Redshift only supports lowercase column names and aliases.
:param label: Expected expression label
:return: Conditionally mutated label
"""
return label.lower()
@classmethod
def get_cancel_query_id(cls, cursor: Any, query: Query) -> str | None:
"""
Get Redshift PID that will be used to cancel all other running
queries in the same session.
:param cursor: Cursor instance in which the query will be executed
:param query: Query instance
:return: Redshift PID
"""
cursor.execute("SELECT pg_backend_pid()")
row = cursor.fetchone()
return row[0]
@classmethod
def cancel_query(cls, cursor: Any, query: Query, cancel_query_id: str) -> bool:
"""
Cancel query in the underlying database.
:param cursor: New cursor instance to the db of the query
:param query: Query instance
:param cancel_query_id: Redshift PID
:return: True if query cancelled successfully, False otherwise
"""
try:
logger.info("Killing Redshift PID:%s", str(cancel_query_id))
cursor.execute(
"SELECT pg_cancel_backend(procpid) "
"FROM pg_stat_activity "
f"WHERE procpid='{cancel_query_id}'"
)
cursor.close()
except Exception: # pylint: disable=broad-except
return False
return True