fdolce commented on code in PR #29088:
URL: https://github.com/apache/flink/pull/29088#discussion_r3958521326
##########
flink-python/pyflink/dataframe/context.py:
##########
@@ -95,9 +105,14 @@ def get_or_create_table_environment() -> TableEnvironment:
global _global_table_environment
if _global_table_environment is None:
+ from pyflink.dataframe._config import config
from pyflink.datastream import StreamExecutionEnvironment
- stream_environment =
StreamExecutionEnvironment.get_execution_environment()
- _global_table_environment =
StreamTableEnvironment.create(stream_environment)
+ stream_environment =
StreamExecutionEnvironment.get_execution_environment(
+ config._to_configuration()
+ )
+ t_env = StreamTableEnvironment.create(stream_environment)
Review Comment:
Oh, nice, this looks way better. Still getting learning the pyflink api, so
sometimes I miss things. Fixing this, and yes, we shouldn't need the apply_to
at this point
##########
flink-python/pyflink/dataframe/_config.py:
##########
@@ -0,0 +1,151 @@
+################################################################################
+# 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 typing import Dict, Optional
+
+from pyflink.common import Configuration
+from pyflink.table import TableEnvironment
+from pyflink.util.api_stability_decorators import PublicEvolving
+
+__all__ = [
+ "DataFrameConfig",
+ "config",
+]
+
+
+@PublicEvolving()
+class DataFrameConfig:
+ """
+ A unified entry point for Flink configuration in the DataFrame API.
+
+ Accepts any Flink configuration key and buffers the value, so
configuration can be set
+ at any time -- even before an environment exists. Buffered values are used
when
+ :func:`get_or_create_table_environment` creates the underlying
+ :class:`~pyflink.table.TableEnvironment`, so options that can only be
chosen at creation
+ time, such as ``execution.runtime-mode``, take effect. An environment
injected via
+ :func:`set_table_environment` receives the buffered values for every key
it does not
+ already set explicitly. While an environment is active, values are also
written through
+ to its configuration immediately.
+
+ Use the module-level singleton :data:`config` instead of instantiating
this class.
+
+ Example::
+
+ >>> import pyflink.dataframe as pf
+ >>> _ = pf.config.set("parallelism.default", "4")
+ >>> pf.config.get("parallelism.default")
+ '4'
+
+ .. versionadded:: 2.4.0
+ """
+
+ def __init__(self: "DataFrameConfig"):
+ self._buffered: Dict[str, str] = {}
+
+ def set(self, key: str, value: str) -> "DataFrameConfig":
+ """
+ Sets a string-based value for the given string-based key.
+
+ The value is buffered and applied to the underlying environment once
it is created
+ or injected; when an environment is already active, the value is
applied to its
+ configuration immediately as well. A value the active environment
rejects is not
+ buffered.
+
+ :param key: The configuration key.
+ :param value: The configuration value. It will be parsed by the
framework on access.
+ :return: This object, to allow chaining of calls.
+ :raises TypeError: If ``key`` or ``value`` is not a string.
+
+ Example::
+
+ >>> import pyflink.dataframe as pf
+ >>> _ = pf.config.set("parallelism.default", "4") \\
+ ... .set("execution.runtime-mode", "batch")
+
+ .. versionadded:: 2.4.0
+ """
+ if not isinstance(key, str):
+ raise TypeError("key must be a string")
+ if not isinstance(value, str):
+ raise TypeError("value must be a string")
+
+ from pyflink.dataframe.context import get_table_environment
+
+ t_env = get_table_environment()
+ if t_env is not None:
Review Comment:
Yes, this was one of my main doubts about the design. Making the
DataFrameConfig incompatible with a global environment and failing fast sounds
a lot better to me, and also requiring the config to be set before the
environment is created makes things easier, so yep, I'm going to change this.
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