from pyspark import Row
from pyspark.sql import SparkSession

User = Row("name", "age")

spark_session = SparkSession.builder.master(User("d", 4)).getOrCreate()

df = spark_session.createDataFrame([
    User("a", 1), User("b", 2), User("c", 3), User("d", 4)
])

df.show(truncate=False, vertical=True)

564803c77a000d39a47d6831ed432b52f5db6f14
<mask token>

<mask token>
df.show(truncate=False, vertical=True)

<mask token>
User = Row('name', 'age')
spark_session = SparkSession.builder.master(User('d', 4)).getOrCreate()
df = spark_session.createDataFrame([User('a', 1), User('b', 2), User('c', 3
    ), User('d', 4)])
df.show(truncate=False, vertical=True)

from pyspark import Row
from pyspark.sql import SparkSession
User = Row('name', 'age')
spark_session = SparkSession.builder.master(User('d', 4)).getOrCreate()
df = spark_session.createDataFrame([User('a', 1), User('b', 2), User('c', 3
    ), User('d', 4)])
df.show(truncate=False, vertical=True)

from pyspark import Row
from pyspark.sql import SparkSession

User = Row("name", "age")

spark_session = SparkSession.builder.master(User("d", 4)).getOrCreate()

df = spark_session.createDataFrame([
    User("a", 1), User("b", 2), User("c", 3), User("d", 4)
])

df.show(truncate=False, vertical=True)
