I'm loading json into spark to create a schemaRDD (sqlContext.jsonRDD(..)).
I'd like some of the json fields to be in a MapType rather than a sub
StructType, as the keys will be very sparse.
For example:
> val sqlContext = new org.apache.spark.sql.SQLContext(sc)
> import sqlContext.createSchemaRDD
> val jsonRdd = sc.parallelize(Seq("""{"key": "1234", "attributes":
> {"gender": "m"}}""",
"""{"key": "4321",
"attributes": {"location": "nyc"}}"""))
> val schemaRdd = sqlContext.jsonRDD(jsonRdd)
> schemaRdd.printSchema
root
|-- attributes: struct (nullable = true)
| |-- gender: string (nullable = true)
| |-- location: string (nullable = true)
|-- key: string (nullable = true)
> schemaRdd.collect
res1: Array[org.apache.spark.sql.Row] = Array([[m,null],1234],
[[null,nyc],4321])
However this isn't what I want. So I created my own StructType to pass to
the jsonRDD call:
> import org.apache.spark.sql._
> val st = StructType(Seq(StructField("key", StringType, false),
StructField("attributes",
MapType(StringType, StringType, false))))
> val jsonRddSt = sc.parallelize(Seq("""{"key": "1234", "attributes":
> {"gender": "m"}}""",
"""{"key": "4321",
"attributes": {"location": "nyc"}}"""))
> val schemaRddSt = sqlContext.jsonRDD(jsonRddSt, st)
> schemaRddSt.printSchema
root
|-- key: string (nullable = false)
|-- attributes: map (nullable = true)
| |-- key: string
| |-- value: string (valueContainsNull = false)
> schemaRddSt.collect
*** Failure ***
scala.MatchError: MapType(StringType,StringType,false) (of class
org.apache.spark.sql.catalyst.types.MapType)
at
org.apache.spark.sql.json.JsonRDD$.enforceCorrectType(JsonRDD.scala:397)
...
The schema of the schemaRDD is correct. But it seems that the json cannot
be coerced to a MapType. I can see at the line in the stack trace that
there is no case statement for MapType. Is there something I'm missing? Is
this a bug or decision to not support MapType with json?
Thanks,
Brian
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