GroupBy and concat array columns pyspark

Question

I have this data frame

df = sc.parallelize([(1, [1, 2, 3]), (1, [4, 5, 6]) , (2,[2]),(2,[3])]).toDF([\"store\", \"values\"])

+-----+---------+
|store|   values|         


        

Answer 1

Now, it is possible to use the flatten function and things become a lot easier. You just have to flatten the collected array after the groupby.

# 1. Create the DF

    df = sc.parallelize([(1, [1, 2, 3]), (1, [4, 5, 6]) , (2,[2]),(2,[3])]).toDF(["store","values"])

+-----+---------+
|store|   values|
+-----+---------+
|    1|[1, 2, 3]|
|    1|[4, 5, 6]|
|    2|      [2]|
|    2|      [3]|
+-----+---------+

# 2. Group by store

    df = df.groupBy("store").agg(F.collect_list("values"))

+-----+--------------------+
|store|collect_list(values)|
+-----+--------------------+
|    1|[[1, 2, 3], [4, 5...|
|    2|          [[2], [3]]|
+-----+--------------------+

# 3. finally.... flat the array

    df = df.withColumn("flatten_array", F.flatten("collect_list(values)"))

+-----+--------------------+------------------+
|store|collect_list(values)|     flatten_array|
+-----+--------------------+------------------+
|    1|[[1, 2, 3], [4, 5...|[1, 2, 3, 4, 5, 6]|
|    2|          [[2], [3]]|            [2, 3]|
+-----+--------------------+------------------+