blob: 8e16e2e94a6637c5ed4d1b3b307565d6378719fa [file]
#
# 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 Any, Dict, Optional
import uuid
from pyspark.errors import (
PySparkTypeError,
PySparkValueError,
IllegalArgumentException,
PySparkAssertionError,
)
from pyspark.sql.column import Column
from pyspark.sql.connect.dataframe import DataFrame
from pyspark.sql.observation import Observation as PySparkObservation
import pyspark.sql.connect.plan as plan
__all__ = ["Observation"]
class Observation:
def __init__(self, name: Optional[str] = None) -> None:
if name is not None:
if not isinstance(name, str):
raise PySparkTypeError(
errorClass="NOT_EXPECTED_TYPE",
messageParameters={
"arg_name": "name",
"expected_type": "str",
"arg_type": type(name).__name__,
},
)
if name == "":
raise PySparkValueError(
errorClass="VALUE_NOT_NON_EMPTY_STR",
messageParameters={"arg_name": "name", "arg_value": name},
)
self._name = name
self._result: Optional[Dict[str, Any]] = None
self._error: Optional[BaseException] = None
__init__.__doc__ = PySparkObservation.__init__.__doc__
def _set_error(self, exc: BaseException) -> None:
"""Set the error that occurred while collecting observed metrics (used by the client)."""
self._error = exc
def _on(self, df: DataFrame, *exprs: Column) -> DataFrame:
if self._result is not None:
raise PySparkAssertionError(errorClass="REUSE_OBSERVATION", messageParameters={})
if self._name is None:
self._name = str(uuid.uuid4())
if df.isStreaming:
raise IllegalArgumentException(
errorClass="UNSUPPORTED_OPERATION",
messageParameters={"operation": "Streaming DataFrame with Observation"},
)
self._result = {}
return DataFrame(plan.CollectMetrics(df._plan, self, list(exprs)), df._session)
_on.__doc__ = PySparkObservation._on.__doc__
@property
def get(self) -> Dict[str, Any]:
if self._error is not None:
raise self._error
if self._result is None:
raise PySparkAssertionError(errorClass="NO_OBSERVE_BEFORE_GET", messageParameters={})
return self._result
get.__doc__ = PySparkObservation.get.__doc__
Observation.__doc__ = PySparkObservation.__doc__
def _test() -> None:
import os
import sys
import doctest
from pyspark.sql import SparkSession as PySparkSession
import pyspark.sql.connect.observation
globs = pyspark.sql.connect.observation.__dict__.copy()
globs["spark"] = (
PySparkSession.builder.appName("sql.connect.observation tests")
.remote(os.environ.get("SPARK_CONNECT_TESTING_REMOTE", "local[4]"))
.getOrCreate()
)
failure_count, test_count = doctest.testmod(
pyspark.sql.connect.observation,
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()