1 files changed, 40 insertions, 0 deletions
diff --git a/nixpkgs/nixos/tests/spark/spark_sample.py b/nixpkgs/nixos/tests/spark/spark_sample.py
new file mode 100644
index 000000000000..c4939451eae0
--- /dev/null
+++ b/nixpkgs/nixos/tests/spark/spark_sample.py
@@ -0,0 +1,40 @@
+from pyspark.sql import Row, SparkSession
+from pyspark.sql import functions as F
+from pyspark.sql.functions import udf
+from pyspark.sql.types import *
+from pyspark.sql.functions import explode
+
+def explode_col(weight):
+    return int(weight//10) * [10.0] + ([] if weight%10==0 else [weight%10])
+
+spark = SparkSession.builder.getOrCreate()
+
+dataSchema = [
+    StructField("feature_1", FloatType()),
+    StructField("feature_2", FloatType()),
+    StructField("bias_weight", FloatType())
+]
+
+data = [
+    Row(0.1, 0.2, 10.32),
+    Row(0.32, 1.43, 12.8),
+    Row(1.28, 1.12, 0.23)
+]
+
+df = spark.createDataFrame(spark.sparkContext.parallelize(data), StructType(dataSchema))
+
+normalizing_constant = 100
+sum_bias_weight = df.select(F.sum('bias_weight')).collect()[0][0]
+normalizing_factor = normalizing_constant / sum_bias_weight
+df = df.withColumn('normalized_bias_weight', df.bias_weight * normalizing_factor)
+df = df.drop('bias_weight')
+df = df.withColumnRenamed('normalized_bias_weight', 'bias_weight')
+
+my_udf = udf(lambda x: explode_col(x), ArrayType(FloatType()))
+df1 = df.withColumn('explode_val', my_udf(df.bias_weight))
+df1 = df1.withColumn("explode_val_1", explode(df1.explode_val)).drop("explode_val")
+df1 = df1.drop('bias_weight').withColumnRenamed('explode_val_1', 'bias_weight')
+
+df1.show()
+
+assert(df1.count() == 12)