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functions.py
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functions.py
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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.
#
"""
A collections of builtin functions
"""
import inspect
import sys
import functools
import warnings
from typing import (
Any,
cast,
Callable,
Dict,
List,
overload,
Optional,
Tuple,
TYPE_CHECKING,
Union,
ValuesView
)
from pyspark import since, SparkContext
from pyspark.rdd import PythonEvalType
from pyspark.sql.column import ( # type: ignore[attr-defined]
Column,
_to_java_column,
_to_seq,
_create_column_from_literal
)
from pyspark.sql.dataframe import DataFrame
from pyspark.sql.types import ArrayType, DataType, StringType, StructType
# Keep UserDefinedFunction import for backwards compatible import; moved in SPARK-22409
from pyspark.sql.udf import UserDefinedFunction, _create_udf # type: ignore[attr-defined] # noqa: F401
# Keep pandas_udf and PandasUDFType import for backwards compatible import; moved in SPARK-28264
from pyspark.sql.pandas.functions import pandas_udf, PandasUDFType # noqa: F401
from pyspark.sql.utils import to_str
if TYPE_CHECKING:
from pyspark.sql._typing import (
ColumnOrName,
DataTypeOrString,
UserDefinedFunctionLike,
)
# Note to developers: all of PySpark functions here take string as column names whenever possible.
# Namely, if columns are referred as arguments, they can be always both Column or string,
# even though there might be few exceptions for legacy or inevitable reasons.
# If you are fixing other language APIs together, also please note that Scala side is not the case
# since it requires to make every single overridden definition.
def _get_get_jvm_function(name: str, sc: SparkContext) -> Callable:
"""
Retrieves JVM function identified by name from
Java gateway associated with sc.
"""
return getattr(sc._jvm.functions, name) # type: ignore[attr-defined]
def _invoke_function(name: str, *args: Any) -> Column:
"""
Invokes JVM function identified by name with args
and wraps the result with :class:`~pyspark.sql.Column`.
"""
jf = _get_get_jvm_function(
name,
SparkContext._active_spark_context # type: ignore[attr-defined]
)
return Column(jf(*args))
def _invoke_function_over_column(name: str, col: "ColumnOrName") -> Column:
"""
Invokes unary JVM function identified by name
and wraps the result with :class:`~pyspark.sql.Column`.
"""
return _invoke_function(name, _to_java_column(col))
def _invoke_binary_math_function(name: str, col1: Any, col2: Any) -> Column:
"""
Invokes binary JVM math function identified by name
and wraps the result with :class:`~pyspark.sql.Column`.
"""
return _invoke_function(
name,
# For legacy reasons, the arguments here can be implicitly converted into floats,
# if they are not columns or strings.
_to_java_column(col1) if isinstance(col1, (str, Column)) else float(col1),
_to_java_column(col2) if isinstance(col2, (str, Column)) else float(col2)
)
def _options_to_str(options: Optional[Dict[str, Any]] = None) -> Dict[str, Optional[str]]:
if options:
return {key: to_str(value) for (key, value) in options.items()}
return {}
def lit(col: Any) -> Column:
"""
Creates a :class:`~pyspark.sql.Column` of literal value.
.. versionadded:: 1.3.0
Examples
--------
>>> df.select(lit(5).alias('height')).withColumn('spark_user', lit(True)).take(1)
[Row(height=5, spark_user=True)]
"""
return col if isinstance(col, Column) else _invoke_function("lit", col)
@since(1.3)
def col(col: str) -> Column:
"""
Returns a :class:`~pyspark.sql.Column` based on the given column name.'
Examples
--------
>>> col('x')
Column<'x'>
>>> column('x')
Column<'x'>
"""
return _invoke_function("col", col)
column = col
@since(1.3)
def asc(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the ascending order of the given column name.
"""
return (
col.asc() if isinstance(col, Column)
else _invoke_function("asc", col)
)
@since(1.3)
def desc(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the descending order of the given column name.
"""
return (
col.desc() if isinstance(col, Column)
else _invoke_function("desc", col)
)
@since(1.3)
def sqrt(col: "ColumnOrName") -> Column:
"""
Computes the square root of the specified float value.
"""
return _invoke_function_over_column("sqrt", col)
@since(1.3)
def abs(col: "ColumnOrName") -> Column:
"""
Computes the absolute value.
"""
return _invoke_function_over_column("abs", col)
@since(1.3)
def max(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the maximum value of the expression in a group.
"""
return _invoke_function_over_column("max", col)
@since(1.3)
def min(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the minimum value of the expression in a group.
"""
return _invoke_function_over_column("min", col)
def max_by(col: "ColumnOrName", ord: "ColumnOrName") -> Column:
"""
Returns the value associated with the maximum value of ord.
.. versionadded:: 3.3.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
target column that the value will be returned
ord : :class:`~pyspark.sql.Column` or str
column to be maximized
Returns
-------
:class:`~pyspark.sql.Column`
value associated with the maximum value of ord.
Examples
--------
>>> df = spark.createDataFrame([
... ("Java", 2012, 20000), ("dotNET", 2012, 5000),
... ("dotNET", 2013, 48000), ("Java", 2013, 30000)],
... schema=("course", "year", "earnings"))
>>> df.groupby("course").agg(max_by("year", "earnings")).show()
+------+----------------------+
|course|max_by(year, earnings)|
+------+----------------------+
| Java| 2013|
|dotNET| 2013|
+------+----------------------+
"""
return _invoke_function("max_by", _to_java_column(col), _to_java_column(ord))
def min_by(col: "ColumnOrName", ord: "ColumnOrName") -> Column:
"""
Returns the value associated with the minimum value of ord.
.. versionadded:: 3.3.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
target column that the value will be returned
ord : :class:`~pyspark.sql.Column` or str
column to be minimized
Returns
-------
:class:`~pyspark.sql.Column`
value associated with the minimum value of ord.
Examples
--------
>>> df = spark.createDataFrame([
... ("Java", 2012, 20000), ("dotNET", 2012, 5000),
... ("dotNET", 2013, 48000), ("Java", 2013, 30000)],
... schema=("course", "year", "earnings"))
>>> df.groupby("course").agg(min_by("year", "earnings")).show()
+------+----------------------+
|course|min_by(year, earnings)|
+------+----------------------+
| Java| 2012|
|dotNET| 2012|
+------+----------------------+
"""
return _invoke_function("min_by", _to_java_column(col), _to_java_column(ord))
@since(1.3)
def count(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the number of items in a group.
"""
return _invoke_function_over_column("count", col)
@since(1.3)
def sum(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the sum of all values in the expression.
"""
return _invoke_function_over_column("sum", col)
@since(1.3)
def avg(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the average of the values in a group.
"""
return _invoke_function_over_column("avg", col)
@since(1.3)
def mean(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the average of the values in a group.
"""
return _invoke_function_over_column("mean", col)
@since(1.3)
def sumDistinct(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the sum of distinct values in the expression.
.. deprecated:: 3.2.0
Use :func:`sum_distinct` instead.
"""
warnings.warn("Deprecated in 3.2, use sum_distinct instead.", FutureWarning)
return sum_distinct(col)
@since(3.2)
def sum_distinct(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the sum of distinct values in the expression.
"""
return _invoke_function_over_column("sum_distinct", col)
def product(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the product of the values in a group.
.. versionadded:: 3.2.0
Parameters
----------
col : str, :class:`Column`
column containing values to be multiplied together
Examples
--------
>>> df = spark.range(1, 10).toDF('x').withColumn('mod3', col('x') % 3)
>>> prods = df.groupBy('mod3').agg(product('x').alias('product'))
>>> prods.orderBy('mod3').show()
+----+-------+
|mod3|product|
+----+-------+
| 0| 162.0|
| 1| 28.0|
| 2| 80.0|
+----+-------+
"""
return _invoke_function_over_column("product", col)
def acos(col: "ColumnOrName") -> Column:
"""
Computes inverse cosine of the input column.
.. versionadded:: 1.4.0
Returns
-------
:class:`~pyspark.sql.Column`
inverse cosine of `col`, as if computed by `java.lang.Math.acos()`
"""
return _invoke_function_over_column("acos", col)
def acosh(col: "ColumnOrName") -> Column:
"""
Computes inverse hyperbolic cosine of the input column.
.. versionadded:: 3.1.0
Returns
-------
:class:`~pyspark.sql.Column`
"""
return _invoke_function_over_column("acosh", col)
def asin(col: "ColumnOrName") -> Column:
"""
Computes inverse sine of the input column.
.. versionadded:: 1.3.0
Returns
-------
:class:`~pyspark.sql.Column`
inverse sine of `col`, as if computed by `java.lang.Math.asin()`
"""
return _invoke_function_over_column("asin", col)
def asinh(col: "ColumnOrName") -> Column:
"""
Computes inverse hyperbolic sine of the input column.
.. versionadded:: 3.1.0
Returns
-------
:class:`~pyspark.sql.Column`
"""
return _invoke_function_over_column("asinh", col)
def atan(col: "ColumnOrName") -> Column:
"""
Compute inverse tangent of the input column.
.. versionadded:: 1.4.0
Returns
-------
:class:`~pyspark.sql.Column`
inverse tangent of `col`, as if computed by `java.lang.Math.atan()`
"""
return _invoke_function_over_column("atan", col)
def atanh(col: "ColumnOrName") -> Column:
"""
Computes inverse hyperbolic tangent of the input column.
.. versionadded:: 3.1.0
Returns
-------
:class:`~pyspark.sql.Column`
"""
return _invoke_function_over_column("atanh", col)
@since(1.4)
def cbrt(col: "ColumnOrName") -> Column:
"""
Computes the cube-root of the given value.
"""
return _invoke_function_over_column("cbrt", col)
@since(1.4)
def ceil(col: "ColumnOrName") -> Column:
"""
Computes the ceiling of the given value.
"""
return _invoke_function_over_column("ceil", col)
def cos(col: "ColumnOrName") -> Column:
"""
Computes cosine of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
cosine of the angle, as if computed by `java.lang.Math.cos()`.
"""
return _invoke_function_over_column("cos", col)
def cosh(col: "ColumnOrName") -> Column:
"""
Computes hyperbolic cosine of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
hyperbolic angle
Returns
-------
:class:`~pyspark.sql.Column`
hyperbolic cosine of the angle, as if computed by `java.lang.Math.cosh()`
"""
return _invoke_function_over_column("cosh", col)
def cot(col: "ColumnOrName") -> Column:
"""
Computes cotangent of the input column.
.. versionadded:: 3.3.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
Angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
Cotangent of the angle.
"""
return _invoke_function_over_column("cot", col)
def csc(col: "ColumnOrName") -> Column:
"""
Computes cosecant of the input column.
.. versionadded:: 3.3.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
Angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
Cosecant of the angle.
"""
return _invoke_function_over_column("csc", col)
@since(1.4)
def exp(col: "ColumnOrName") -> Column:
"""
Computes the exponential of the given value.
"""
return _invoke_function_over_column("exp", col)
@since(1.4)
def expm1(col: "ColumnOrName") -> Column:
"""
Computes the exponential of the given value minus one.
"""
return _invoke_function_over_column("expm1", col)
@since(1.4)
def floor(col: "ColumnOrName") -> Column:
"""
Computes the floor of the given value.
"""
return _invoke_function_over_column("floor", col)
@since(1.4)
def log(col: "ColumnOrName") -> Column:
"""
Computes the natural logarithm of the given value.
"""
return _invoke_function_over_column("log", col)
@since(1.4)
def log10(col: "ColumnOrName") -> Column:
"""
Computes the logarithm of the given value in Base 10.
"""
return _invoke_function_over_column("log10", col)
@since(1.4)
def log1p(col: "ColumnOrName") -> Column:
"""
Computes the natural logarithm of the given value plus one.
"""
return _invoke_function_over_column("log1p", col)
@since(1.4)
def rint(col: "ColumnOrName") -> Column:
"""
Returns the double value that is closest in value to the argument and
is equal to a mathematical integer.
"""
return _invoke_function_over_column("rint", col)
def sec(col: "ColumnOrName") -> Column:
"""
Computes secant of the input column.
.. versionadded:: 3.3.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
Angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
Secant of the angle.
"""
return _invoke_function_over_column("sec", col)
@since(1.4)
def signum(col: "ColumnOrName") -> Column:
"""
Computes the signum of the given value.
"""
return _invoke_function_over_column("signum", col)
def sin(col: "ColumnOrName") -> Column:
"""
Computes sine of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
Returns
-------
:class:`~pyspark.sql.Column`
sine of the angle, as if computed by `java.lang.Math.sin()`
"""
return _invoke_function_over_column("sin", col)
def sinh(col: "ColumnOrName") -> Column:
"""
Computes hyperbolic sine of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
hyperbolic angle
Returns
-------
:class:`~pyspark.sql.Column`
hyperbolic sine of the given value,
as if computed by `java.lang.Math.sinh()`
"""
return _invoke_function_over_column("sinh", col)
def tan(col: "ColumnOrName") -> Column:
"""
Computes tangent of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
tangent of the given value, as if computed by `java.lang.Math.tan()`
"""
return _invoke_function_over_column("tan", col)
def tanh(col: "ColumnOrName") -> Column:
"""
Computes hyperbolic tangent of the input column.
.. versionadded:: 1.4.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
hyperbolic angle
Returns
-------
:class:`~pyspark.sql.Column`
hyperbolic tangent of the given value
as if computed by `java.lang.Math.tanh()`
"""
return _invoke_function_over_column("tanh", col)
@since(1.4)
def toDegrees(col: "ColumnOrName") -> Column:
"""
.. deprecated:: 2.1.0
Use :func:`degrees` instead.
"""
warnings.warn("Deprecated in 2.1, use degrees instead.", FutureWarning)
return degrees(col)
@since(1.4)
def toRadians(col: "ColumnOrName") -> Column:
"""
.. deprecated:: 2.1.0
Use :func:`radians` instead.
"""
warnings.warn("Deprecated in 2.1, use radians instead.", FutureWarning)
return radians(col)
@since(1.4)
def bitwiseNOT(col: "ColumnOrName") -> Column:
"""
Computes bitwise not.
.. deprecated:: 3.2.0
Use :func:`bitwise_not` instead.
"""
warnings.warn("Deprecated in 3.2, use bitwise_not instead.", FutureWarning)
return bitwise_not(col)
@since(3.2)
def bitwise_not(col: "ColumnOrName") -> Column:
"""
Computes bitwise not.
"""
return _invoke_function_over_column("bitwise_not", col)
@since(2.4)
def asc_nulls_first(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the ascending order of the given
column name, and null values return before non-null values.
"""
return (
col.asc_nulls_first() if isinstance(col, Column)
else _invoke_function("asc_nulls_first", col)
)
@since(2.4)
def asc_nulls_last(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the ascending order of the given
column name, and null values appear after non-null values.
"""
return (
col.asc_nulls_last() if isinstance(col, Column)
else _invoke_function("asc_nulls_last", col)
)
@since(2.4)
def desc_nulls_first(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the descending order of the given
column name, and null values appear before non-null values.
"""
return (
col.desc_nulls_first() if isinstance(col, Column)
else _invoke_function("desc_nulls_first", col)
)
@since(2.4)
def desc_nulls_last(col: "ColumnOrName") -> Column:
"""
Returns a sort expression based on the descending order of the given
column name, and null values appear after non-null values.
"""
return (
col.desc_nulls_last() if isinstance(col, Column)
else _invoke_function("desc_nulls_last", col)
)
@since(1.6)
def stddev(col: "ColumnOrName") -> Column:
"""
Aggregate function: alias for stddev_samp.
"""
return _invoke_function_over_column("stddev", col)
@since(1.6)
def stddev_samp(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the unbiased sample standard deviation of
the expression in a group.
"""
return _invoke_function_over_column("stddev_samp", col)
@since(1.6)
def stddev_pop(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns population standard deviation of
the expression in a group.
"""
return _invoke_function_over_column("stddev_pop", col)
@since(1.6)
def variance(col: "ColumnOrName") -> Column:
"""
Aggregate function: alias for var_samp
"""
return _invoke_function_over_column("variance", col)
@since(1.6)
def var_samp(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the unbiased sample variance of
the values in a group.
"""
return _invoke_function_over_column("var_samp", col)
@since(1.6)
def var_pop(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the population variance of the values in a group.
"""
return _invoke_function_over_column("var_pop", col)
@since(1.6)
def skewness(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the skewness of the values in a group.
"""
return _invoke_function_over_column("skewness", col)
@since(1.6)
def kurtosis(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns the kurtosis of the values in a group.
"""
return _invoke_function_over_column("kurtosis", col)
def collect_list(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns a list of objects with duplicates.
.. versionadded:: 1.6.0
Notes
-----
The function is non-deterministic because the order of collected results depends
on the order of the rows which may be non-deterministic after a shuffle.
Examples
--------
>>> df2 = spark.createDataFrame([(2,), (5,), (5,)], ('age',))
>>> df2.agg(collect_list('age')).collect()
[Row(collect_list(age)=[2, 5, 5])]
"""
return _invoke_function_over_column("collect_list", col)
def collect_set(col: "ColumnOrName") -> Column:
"""
Aggregate function: returns a set of objects with duplicate elements eliminated.
.. versionadded:: 1.6.0
Notes
-----
The function is non-deterministic because the order of collected results depends
on the order of the rows which may be non-deterministic after a shuffle.
Examples
--------
>>> df2 = spark.createDataFrame([(2,), (5,), (5,)], ('age',))
>>> df2.agg(array_sort(collect_set('age')).alias('c')).collect()
[Row(c=[2, 5])]
"""
return _invoke_function_over_column("collect_set", col)
def degrees(col: "ColumnOrName") -> Column:
"""
Converts an angle measured in radians to an approximately equivalent angle
measured in degrees.
.. versionadded:: 2.1.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
angle in radians
Returns
-------
:class:`~pyspark.sql.Column`
angle in degrees, as if computed by `java.lang.Math.toDegrees()`
"""
return _invoke_function_over_column("degrees", col)
def radians(col: "ColumnOrName") -> Column:
"""
Converts an angle measured in degrees to an approximately equivalent angle
measured in radians.
.. versionadded:: 2.1.0
Parameters
----------
col : :class:`~pyspark.sql.Column` or str
angle in degrees
Returns
-------
:class:`~pyspark.sql.Column`
angle in radians, as if computed by `java.lang.Math.toRadians()`
"""
return _invoke_function_over_column("radians", col)
@overload
def atan2(col1: "ColumnOrName", col2: "ColumnOrName") -> Column:
...
@overload
def atan2(col1: float, col2: "ColumnOrName") -> Column:
...
@overload
def atan2(col1: "ColumnOrName", col2: float) -> Column:
...
def atan2(col1: Union["ColumnOrName", float], col2: Union["ColumnOrName", float]) -> Column:
"""
.. versionadded:: 1.4.0
Parameters
----------
col1 : str, :class:`~pyspark.sql.Column` or float
coordinate on y-axis
col2 : str, :class:`~pyspark.sql.Column` or float
coordinate on x-axis
Returns
-------
:class:`~pyspark.sql.Column`
the `theta` component of the point
(`r`, `theta`)
in polar coordinates that corresponds to the point
(`x`, `y`) in Cartesian coordinates,
as if computed by `java.lang.Math.atan2()`
"""
return _invoke_binary_math_function("atan2", col1, col2)
@overload
def hypot(col1: "ColumnOrName", col2: "ColumnOrName") -> Column:
...
@overload
def hypot(col1: float, col2: "ColumnOrName") -> Column:
...
@overload
def hypot(col1: "ColumnOrName", col2: float) -> Column:
...
@since(1.4)
def hypot(col1: Union["ColumnOrName", float], col2: Union["ColumnOrName", float]) -> Column:
"""
Computes ``sqrt(a^2 + b^2)`` without intermediate overflow or underflow.
"""
return _invoke_binary_math_function("hypot", col1, col2)
@overload
def pow(col1: "ColumnOrName", col2: "ColumnOrName") -> Column:
...
@overload
def pow(col1: float, col2: "ColumnOrName") -> Column:
...
@overload
def pow(col1: "ColumnOrName", col2: float) -> Column:
...
@since(1.4)
def pow(col1: Union["ColumnOrName", float], col2: Union["ColumnOrName", float]) -> Column: