# # 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 overload from typing import Any, Iterable, List, Optional, Tuple, TypeVar, Union from py4j.java_gateway import JavaObject # type: ignore[import] from pyspark.sql._typing import DateTimeLiteral, LiteralType, DecimalLiteral, RowLike from pyspark.sql.pandas._typing import DataFrameLike from pyspark.conf import SparkConf from pyspark.context import SparkContext from pyspark.rdd import RDD from pyspark.sql.catalog import Catalog from pyspark.sql.conf import RuntimeConfig from pyspark.sql.dataframe import DataFrame from pyspark.sql.pandas.conversion import SparkConversionMixin from pyspark.sql.types import AtomicType, StructType from pyspark.sql.readwriter import DataFrameReader from pyspark.sql.streaming import DataStreamReader, StreamingQueryManager from pyspark.sql.udf import UDFRegistration T = TypeVar("T") class SparkSession(SparkConversionMixin): class Builder: @overload def config(self, *, conf: SparkConf) -> SparkSession.Builder: ... @overload def config(self, key: str, value: Any) -> SparkSession.Builder: ... def master(self, master: str) -> SparkSession.Builder: ... def appName(self, name: str) -> SparkSession.Builder: ... def enableHiveSupport(self) -> SparkSession.Builder: ... def getOrCreate(self) -> SparkSession: ... builder: SparkSession.Builder def __init__( self, sparkContext: SparkContext, jsparkSession: Optional[JavaObject] = ... ) -> None: ... def newSession(self) -> SparkSession: ... @classmethod def getActiveSession(cls) -> SparkSession: ... @property def sparkContext(self) -> SparkContext: ... @property def version(self) -> str: ... @property def conf(self) -> RuntimeConfig: ... @property def catalog(self) -> Catalog: ... @property def udf(self) -> UDFRegistration: ... def range( self, start: int, end: Optional[int] = ..., step: int = ..., numPartitions: Optional[int] = ..., ) -> DataFrame: ... @overload def createDataFrame( self, data: Union[RDD[RowLike], Iterable[RowLike]], samplingRatio: Optional[float] = ..., ) -> DataFrame: ... @overload def createDataFrame( self, data: Union[RDD[RowLike], Iterable[RowLike]], schema: Union[List[str], Tuple[str, ...]] = ..., verifySchema: bool = ..., ) -> DataFrame: ... @overload def createDataFrame( self, data: Union[ RDD[Union[DateTimeLiteral, LiteralType, DecimalLiteral]], Iterable[Union[DateTimeLiteral, LiteralType, DecimalLiteral]], ], schema: Union[AtomicType, str], verifySchema: bool = ..., ) -> DataFrame: ... @overload def createDataFrame( self, data: Union[RDD[RowLike], Iterable[RowLike]], schema: Union[StructType, str], verifySchema: bool = ..., ) -> DataFrame: ... @overload def createDataFrame( self, data: DataFrameLike, samplingRatio: Optional[float] = ... ) -> DataFrame: ... @overload def createDataFrame( self, data: DataFrameLike, schema: Union[StructType, str], verifySchema: bool = ..., ) -> DataFrame: ... def sql(self, sqlQuery: str) -> DataFrame: ... def table(self, tableName: str) -> DataFrame: ... @property def read(self) -> DataFrameReader: ... @property def readStream(self) -> DataStreamReader: ... @property def streams(self) -> StreamingQueryManager: ... def stop(self) -> None: ... def __enter__(self) -> SparkSession: ... def __exit__(self, exc_type, exc_val, exc_tb) -> None: ...