In Spark SQL, transform JSON key name into value - json

Question

It seems like there should be a function for this in Spark SQL similar to pivoting, but I haven't found any solution to transforming a JSON key into a a value. Suppose I have a badly formed JSON (the format of which I cannot change):
{"A long string containing serverA": {"x": 1, "y": 2}}
how can I process it to
{"server": "A", "x": 1, "y": 2}
?
I read the JSONs into an an sql.dataframe and would then like to process them as described above:
val cs = spark.read.json("sample.json")
.???

Answer 1

If we want to use only spark functions and no UDFs, you could use from_json to parse the json into a map (we need to specify a schema). Then you just need to extract the information with spark functions.
One way to do it is as follows:
val schema = MapType(
StringType,
StructType(Array(
StructField("x", IntegerType),
StructField("y", IntegerType)
))
)
spark.read.text("...")
.withColumn("json", from_json('value, schema))
.withColumn("key", map_keys('json).getItem(0))
.withColumn("value", map_values('json).getItem(0))
.withColumn("server",
// Extracting the server name with a regex
regexp_replace(regexp_extract('key, "server[^ ]*", 0), "server", ""))
.select("server", "value.*")
.show(false)
which yields:
+------+---+---+
|server|x |y |
+------+---+---+
|A |1 |2 |
+------+---+---+