Java spark dataframe join column containing array

Question

I have 2 dataframes df1 and df2. df1 has 1 column key of type String

df1.show()

key
----
k1
k2
k3

df2 has 2 columns
df2.show()
topic | keys
-------------
 t1  | [k1, k2]
 t2  | [pk1, pk2]

I want to join the 2 dataframes when df1.key is present in df2.keys. I saw previous examples posted here Spark: Join dataframe column with an array

However, I am looking for a whole word match. Contains method is joining rows that have a partial match. What I mean is in the above example, I don't want k2 to be joined with [pk1, pk2] because array does not contain key k2, it contains pk2.

Can someone suggest how to join in this case ? Please provide example in JAVA.

Answer 1

Function "array_contains" can be used:

val df1 = List("k1", "k2", "k3").toDF("key")
val df2 = List(
  ("t1", Array("k1", "k2")),
  ("t2", Array("pk1", "pk2"))
).toDF("topic", "keys")
val result = df1.join(df2, expr("array_contains(keys,key)"))
result.show(false)

Output:

+---+-----+--------+
|key|topic|keys    |
+---+-----+--------+
|k1 |t1   |[k1, k2]|
|k2 |t1   |[k1, k2]|
+---+-----+--------+

Answer 2

What you can do is explode your array and get one line per key like that :

df2 = df2.withColumn("key", explode(df2.col("keys")))
df2.show()

+-----+----------+---+
|topic|      keys|key|
+-----+----------+---+
|   t1|  [k1, k2]| k1|
|   t1|  [k1, k2]| k2|
|   t2|[pk1, pk2]|pk1|
|   t2|[pk1, pk2]|pk2|
+-----+----------+---+

Then you can join on this new column :

Dataset<Row> result = df2.join(key, df2.col("key").equalTo(df1.col("key")), "inner")
result.show()

+-----+--------+---+---+
|topic|    keys|key|key|
+-----+--------+---+---+
|   t1|[k1, k2]| k1| k1|
|   t1|[k1, k2]| k2| k2|
+-----+--------+---+---+

Note that it is not very efficient because it duplicates the data.