Returns the first argument-based logarithm of the second argument.

    If there is only one argument, then this takes the natural logarithm of the argument.

    >>> df.select(log(10.0, df.age).alias('ten')).rdd.map(lambda l: str(l.ten)[:7]).collect()
    ['0.30102', '0.69897']

    >>> df.select(log(df.age).alias('e')).rdd.map(lambda l: str(l.e)[:7]).collect()
    ['0.69314', '1.60943']

def log(arg1, arg2=None):
    """Returns the first argument-based logarithm of the second argument.

    If there is only one argument, then this takes the natural logarithm of the argument.

    >>> df.select(log(10.0, df.age).alias('ten')).rdd.map(lambda l: str(l.ten)[:7]).collect()
    ['0.30102', '0.69897']

    >>> df.select(log(df.age).alias('e')).rdd.map(lambda l: str(l.e)[:7]).collect()
    ['0.69314', '1.60943']
    """
    sc = SparkContext._active_spark_context
    if arg2 is None:
        jc = sc._jvm.functions.log(_to_java_column(arg1))
    else:
        jc = sc._jvm.functions.log(arg1, _to_java_column(arg2))
    return Column(jc)