Neeraj Bhadani NeerajBhadani

## arr_import_lib.scala
import org.apache.spark.sql.functions._

## arr_create_dataframe.scala
val initial_df = Seq(
  ("x", 4, 1),
  ("x", 6, 2),
  ("z", 7, 3),
  ("a", 3, 4),
  ("z", 5, 2),
  ("x", 7, 3),
  ("x", 9, 7),
  ("z", 1, 8),
  ("z", 4, 9),

## arr_check_schema.scala
full_df.printSchema()

## arr_array_contains.scala
val arr_contains_df = df.withColumn("result", array_contains($"array_col2", 3))

arr_contains_df.show()

## arr_array_distinct.scala
val arr_distinct_df = df.withColumn("result", array_distinct($"array_col2"))

arr_distinct_df.show()

## arr_array_except.scala
val arr_except_df = full_df.withColumn("result", array_except($"array_col1", $"array_col2"))

arr_except_df.show()

## arr_array_intersect.scala
val arr_intersect_df = full_df
                       .withColumn("result", array_intersect($"array_col1", $"array_col2"))

arr_intersect_df.show()

## arr_array_join.scala
val arr_join_df = df.withColumn("result", array_join($"array_col2", ","))

arr_join_df.show()

## arr_array_max.scala
val arr_max_df = df.withColumn("result", array_max($"array_col2"))

arr_max_df.show()

## arr_array_min.scala
val arr_min_df = df.withColumn("result", array_min($"array_col2"))

arr_min_df.show()
	val initial_df = Seq(
	("x", 4, 1),
	("x", 6, 2),
	("z", 7, 3),
	("a", 3, 4),
	("z", 5, 2),
	("x", 7, 3),
	("x", 9, 7),
	("z", 1, 8),
	("z", 4, 9),
	val arr_contains_df = df.withColumn("result", array_contains($"array_col2", 3))

	arr_contains_df.show()
	val arr_distinct_df = df.withColumn("result", array_distinct($"array_col2"))

	arr_distinct_df.show()
	val arr_except_df = full_df.withColumn("result", array_except($"array_col1", $"array_col2"))

	arr_except_df.show()
	val arr_intersect_df = full_df
	.withColumn("result", array_intersect($"array_col1", $"array_col2"))

	arr_intersect_df.show()
	val arr_join_df = df.withColumn("result", array_join($"array_col2", ","))

	arr_join_df.show()
	val arr_max_df = df.withColumn("result", array_max($"array_col2"))

	arr_max_df.show()
	val arr_min_df = df.withColumn("result", array_min($"array_col2"))

	arr_min_df.show()