I am able to filter a Spark dataframe (in PySpark) based on particular value existence within an array column by doing the following:

from pyspark.sql.functions import array_contains
spark_df.filter(array_contains(spark_df.array_column_name, "value that I want")) 

But is there a way to get the index of where in the array the item was found?

I am using spark 2.3 version, so I tried this using udf.

df = spark.createDataFrame([(["c", "b", "a","e","f"],)], ['arraydata'])
+---------------+
|      arraydata|
+---------------+
|[c, b, a, e, f]|
+---------------+

user_func = udf (lambda x,y: [i for i, e in enumerate(x) if e==y ])

checking index position for item 'b':

newdf = df.withColumn('item_position',user_func(df.arraydata,lit('b')))

>>> newdf.show();
+---------------+-------------+
|      arraydata|item_position|
+---------------+-------------+
|[c, b, a, e, f]|          [1]|
+---------------+-------------+

checking index position for item 'e':

newdf = df.withColumn('item_position',user_func(df.arraydata,lit('e')))

>>> newdf.show();
+---------------+-------------+
|      arraydata|item_position|
+---------------+-------------+
|[c, b, a, e, f]|          [3]|
+---------------+-------------+