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#
# 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.
#
from pyspark.errors import PySparkValueError, PySparkTypeError
from pyspark.sql.connect.utils import check_dependencies
check_dependencies(__name__)
from typing import Any, Dict, Optional, Union, cast
import warnings
from pyspark import _NoValue
from pyspark._globals import _NoValueType
from pyspark.sql.conf import RuntimeConfig as PySparkRuntimeConfig
from pyspark.sql.connect import proto
from pyspark.sql.connect.client import SparkConnectClient
class RuntimeConf:
def __init__(self, client: SparkConnectClient) -> None:
"""Create a new RuntimeConfig."""
self._client = client
__init__.__doc__ = PySparkRuntimeConfig.__init__.__doc__
def set(self, key: str, value: Union[str, int, bool]) -> None:
if isinstance(value, bool):
value = "true" if value else "false"
elif isinstance(value, int):
value = str(value)
op_set = proto.ConfigRequest.Set(pairs=[proto.KeyValue(key=key, value=value)])
operation = proto.ConfigRequest.Operation(set=op_set)
result = self._client.config(operation)
for warn in result.warnings:
warnings.warn(warn)
set.__doc__ = PySparkRuntimeConfig.set.__doc__
def _set_all(self, configs: Dict[str, Union[str, int, bool]], silent: bool) -> None:
conf_list = []
for key, value in configs.items():
if isinstance(value, bool):
value = "true" if value else "false"
elif isinstance(value, int):
value = str(value)
conf_list.append(proto.KeyValue(key=key, value=value))
op_set = proto.ConfigRequest.Set(pairs=conf_list, silent=silent)
operation = proto.ConfigRequest.Operation(set=op_set)
result = self._client.config(operation)
for warn in result.warnings:
warnings.warn(warn)
def get(
self, key: str, default: Union[Optional[str], _NoValueType] = _NoValue
) -> Optional[str]:
self._checkType(key, "key")
if default is _NoValue:
op_get = proto.ConfigRequest.Get(keys=[key])
operation = proto.ConfigRequest.Operation(get=op_get)
else:
if default is not None:
self._checkType(default, "default")
op_get_with_default = proto.ConfigRequest.GetWithDefault(
pairs=[proto.KeyValue(key=key, value=cast(Optional[str], default))]
)
operation = proto.ConfigRequest.Operation(get_with_default=op_get_with_default)
result = self._client.config(operation)
return result.pairs[0][1]
get.__doc__ = PySparkRuntimeConfig.get.__doc__
@property
def getAll(self) -> Dict[str, str]:
op_get_all = proto.ConfigRequest.GetAll()
operation = proto.ConfigRequest.Operation(get_all=op_get_all)
result = self._client.config(operation)
confs: Dict[str, str] = dict()
for key, value in result.pairs:
assert value is not None
confs[key] = value
return confs
getAll.__doc__ = PySparkRuntimeConfig.getAll.__doc__
def unset(self, key: str) -> None:
op_unset = proto.ConfigRequest.Unset(keys=[key])
operation = proto.ConfigRequest.Operation(unset=op_unset)
result = self._client.config(operation)
for warn in result.warnings:
warnings.warn(warn)
unset.__doc__ = PySparkRuntimeConfig.unset.__doc__
def isModifiable(self, key: str) -> bool:
op_is_modifiable = proto.ConfigRequest.IsModifiable(keys=[key])
operation = proto.ConfigRequest.Operation(is_modifiable=op_is_modifiable)
result = self._client.config(operation).pairs[0][1]
if result == "true":
return True
elif result == "false":
return False
else:
raise PySparkValueError(
errorClass="VALUE_NOT_ALLOWED",
messageParameters={"arg_name": "result", "allowed_values": "'true' or 'false'"},
)
isModifiable.__doc__ = PySparkRuntimeConfig.isModifiable.__doc__
def _checkType(self, obj: Any, identifier: str) -> None:
"""Assert that an object is of type str."""
if not isinstance(obj, str):
raise PySparkTypeError(
errorClass="NOT_STR",
messageParameters={
"arg_name": identifier,
"arg_type": type(obj).__name__,
},
)
RuntimeConf.__doc__ = PySparkRuntimeConfig.__doc__
def _test() -> None:
import os
import sys
import doctest
from pyspark.sql import SparkSession as PySparkSession
import pyspark.sql.connect.conf
globs = pyspark.sql.connect.conf.__dict__.copy()
globs["spark"] = (
PySparkSession.builder.appName("sql.connect.conf tests")
.remote(os.environ.get("SPARK_CONNECT_TESTING_REMOTE", "local[4]"))
.getOrCreate()
)
(failure_count, test_count) = doctest.testmod(
pyspark.sql.connect.conf,
globs=globs,
optionflags=doctest.ELLIPSIS
| doctest.NORMALIZE_WHITESPACE
| doctest.IGNORE_EXCEPTION_DETAIL,
)
globs["spark"].stop()
if failure_count:
sys.exit(-1)
if __name__ == "__main__":
_test()