使用AWS Glue实现从Amazon S3到Amazon Redshift的数据转换和加载时，可以通过添加DateTime类型的转换选项来将DateTime类型转换为DATE类型。以下是代码示例：

from awsglue.transforms import ApplyMapping, Filter, SelectFields, ResolveChoice
from awsglue.dynamicframe import DynamicFrame
from awsglue.context import GlueContext
from pyspark.context import SparkContext
from pyspark.sql.functions import to_date

# 初始化上下文
sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)
spark = glueContext.spark_session

# 读取源数据
source_dyf = glueContext.create_dynamic_frame_from_options(
    "s3", {
        "paths": ["s3://my-bucket/my-path/"],
        "recurse": True,
        "groupFiles": True,
        "groupSize": "1048576"
    }
)

# 选择需要处理的字段
source_dyf = SelectFields.apply(source_dyf, ["date_time_column"])

# 将DateTime类型转换为DATE类型
source_dyf = ResolveChoice.apply(source_dyf, specs=[
    ("date_time_column", "cast:string", "date_column"),
    ("date_column", "cast:date", "date_column")
])

# 将处理过的数据写入目标表
target_dyf = DynamicFrame.fromDF(source_dyf.toDF(), glueContext, "target_dyf")
glueContext.write_dynamic_frame.from_options(
    frame=target_dyf,
    connection_type="s3",
    connection_options={
        "path": "s3://my-bucket/my-target-path/",
        "partitionKeys": ["date_column"]
    },
    format="parquet"
)

代码中，首先从Amazon S3读取数据，然后使用SelectFields.apply函数选择需要处理的字段。接着，使用ResolveChoice.apply函数将DateTime类型转换为DATE类型，并将转换后的数据写入目标表来完成数据转换和加载。