code: def test_spark_session_dataframe(spark_session):
      test_df = spark_session.createDataFrame(
          [[1, 3], [2, 4]], "a: int, b: int"
      )
  
      assert type(test_df) == pyspark.sql.dataframe.DataFrame
      assert test_df.count() == 2
  
file_path: sk-dist/skdist/tests/test_spark.py
imports: import pytest
  import sys
  import pandas
  import numpy
  from sklearn.datasets import load_breast_cancer, load_digits
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LogisticRegression
  from skdist.distribute.multiclass import DistOneVsRestClassifier
  from skdist.distribute.search import DistGridSearchCV, DistRandomizedSearchCV
  from skdist.distribute.ensemble import DistRandomForestClassifier
  from skdist.distribute.predict import get_prediction_udf
label_desc: Use image node_id 1 for calling a global function with example usage: test_spark_session_dataframe(spark_session) without return types