可以使用“concat”函数合并列值

from pyspark.sql.types import StructType, StructField, StringType, IntegerType
from pyspark.sql.functions import *
from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
# Define schema
schema = StructType([
    StructField('Col1', StringType(), True),
    StructField('Col2', StringType(), True)
])

# Original data
data = [
    {'Col1': 'Ora', 'Col2': '1234'},
    {'Col1': 'Ora', 'Col2': '0123'},
    {'Col1': 'APP', 'Col2': '0005'},
    {'Col1': 'Ora', 'Col2': '7778'},
    {'Col1': 'APP', 'Col2': '9999'}
]

# Create df from original data
df = spark.createDataFrame(data, schema)

# Add the new column using concat and when
df1 = df.withColumn(
    'NewCol1',
    concat(
        when(df['Col1'] == 'Ora', lit('300|')).
        when(df['Col1'] == 'APP', lit('100|')),
        df['Col2']
    )
)

# Show the contents of the DataFrame
df1.show()

+----+----+--------+
|Col1|Col2| NewCol1|
+----+----+--------+
| Ora|1234|300|1234|
| Ora|0123|300|0123|
| APP|0005|100|0005|
| Ora|7778|300|7778|
| APP|9999|100|9999|
+----+----+--------+