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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def map_concat(*cols):
 """Returns the union of all the given maps. :param cols: list of column names (string) or list of :class:`Column` expressions |map3 | |[1 -> d, 2 -> b, 3 -> c]| """

    sc = SparkContext._active_spark_context
    if len(cols) == 1 and isinstance(cols[0], (list, set)):
        cols = cols[0]
    jc = sc._jvm.functions.map_concat(_to_seq(sc, cols, _to_java_column))
    return Column(jc)