Unpivot in spark-sql/pyspark

Question

I have a problem statement at hand wherein I want to unpivot table in spark-sql/pyspark. I have gone through the documentation and I could see there is support only for pivo

Answer 1

You can use the built in stack function, for example in Scala:

scala> val df = Seq(("G",Some(4),2,None),("H",None,4,Some(5))).toDF("A","X","Y", "Z")
df: org.apache.spark.sql.DataFrame = [A: string, X: int ... 2 more fields]

scala> df.show
+---+----+---+----+
|  A|   X|  Y|   Z|
+---+----+---+----+
|  G|   4|  2|null|
|  H|null|  4|   5|
+---+----+---+----+


scala> df.select($"A", expr("stack(3, 'X', X, 'Y', Y, 'Z', Z) as (B, C)")).where("C is not null").show
+---+---+---+
|  A|  B|  C|
+---+---+---+
|  G|  X|  4|
|  G|  Y|  2|
|  H|  Y|  4|
|  H|  Z|  5|
+---+---+---+

Or in pyspark:

In [1]: df = spark.createDataFrame([("G",4,2,None),("H",None,4,5)],list("AXYZ"))

In [2]: df.show()
+---+----+---+----+
|  A|   X|  Y|   Z|
+---+----+---+----+
|  G|   4|  2|null|
|  H|null|  4|   5|
+---+----+---+----+

In [3]: df.selectExpr("A", "stack(3, 'X', X, 'Y', Y, 'Z', Z) as (B, C)").where("C is not null").show()
+---+---+---+
|  A|  B|  C|
+---+---+---+
|  G|  X|  4|
|  G|  Y|  2|
|  H|  Y|  4|
|  H|  Z|  5|
+---+---+---+