livy result shows dataframe.schema contains data types

livyResultForSchema.json

{
    "code": "import org.apache.spark.sql._\nvar d = sqlContext.sql(\"SELECT tbl10.`venueid`, tbl10.`venuename`, tbl10.`venuecity`, tbl10.`venuestate`, tbl10.`venueseats`, tbl10.`processing_dttm` AS `venues_processing_dttm` FROM `concerts`.`venues` tbl10\")\nd.schema\n",
    "id": 5,
    "output": {
        "data": {
            "text/plain": "import org.apache.spark.sql._\nd: org.apache.spark.sql.DataFrame = [venueid: int, venuename: string, venuecity: string, venuestate: string, venueseats: int, venues_processing_dttm: string]\nres2: org.apache.spark.sql.types.StructType = StructType(StructField(venueid,IntegerType,true), StructField(venuename,StringType,true), StructField(venuecity,StringType,true), StructField(venuestate,StringType,true), StructField(venueseats,IntegerType,true), StructField(venues_processing_dttm,StringType,true))\n"
        },
        "execution_count": 5,
        "status": "ok"
    },
    "progress": 1.0,
    "state": "available"
}