PySpark で DataFrame にリテラルで列を追加しようとすると "col should be Column" と怒られる

事象

PySpark で DataFrame にリテラルで列を追加しようとすると "col should be Column" と怒られる。

コード

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql import SQLContext
from pyspark.sql.functions import year, month, date_format

sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init('addYearColumn')
datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "ssbgz", table_name = "gz_customer", transformation_ctx = "datasource0")
df = datasource0.toDF()
df.cache()
yearAddedDf = df.withColumn("yyyy", "1001")

エラーメッセージ

col should be Column
Traceback (most recent call last):
  File "/mnt/yarn/usercache/livy/appcache/application_1568634099044_0001/container_1568634099044_0001_01_000001/pyspark.zip/pyspark/sql/dataframe.py", line 1619, in withColumn
    assert isinstance(col, Column), "col should be Column"
AssertionError: col should be Column

解決策

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql import SQLContext
from pyspark.sql.functions import year, month, date_format
from pyspark.sql.functions import lit # ★ literal を import

sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init('addYearColumn')
datasource0 = glueContext.create_dynamic_frame.from_catalog(database = "ssbgz", table_name = "gz_customer", transformation_ctx = "datasource0")
df = datasource0.toDF()
df.cache()
yearAddedDf = df.withColumn("yyyy", lit('1001')) # ★ literal で囲む