code: def pyspark_hello_world(
      dataset_url="file:///tmp/hello_world_dataset",
  ):
      spark = SparkSession.builder.master("local[1]").getOrCreate()
  
      # dataset_as_rdd creates an rdd of named tuples.
      rdd = dataset_as_rdd(
          dataset_url,
          spark,
          [HelloWorldSchema.id, HelloWorldSchema.image1],
      )
      print("An id in the dataset: ", rdd.first().id)
  
      # Create a dataframe object from a parquet file
      dataframe = spark.read.parquet(dataset_url)
  
      # Show a schema
      dataframe.printSchema()
  
      # Count all
      dataframe.count()
  
      # Show just some columns
      dataframe.select("id").show()
  
      # This is how you can use a standard SQL to query a dataset. Note that the data is not decoded in this case.
      number_of_rows = spark.sql(
          "SELECT count(id) " "from parquet.`{}` ".format(dataset_url)
      ).collect()
      print(
          "Number of rows in the dataset: {}".format(
              number_of_rows[0][0]
          )
      )
  
imports: from __future__ import print_function
  from pyspark.sql import SparkSession
  from examples.hello_world.petastorm_dataset.generate_petastorm_dataset import HelloWorldSchema
  from petastorm.spark_utils import dataset_as_rdd
label_desc: Use image node_id 1 for calling a global function with example usage: pyspark_hello_world(dataset_url) without return types