I'm trying to read json into dataset (spark 2.1.1). Unfortunately it doesn't work. And fails with:
Caused by: java.lang.NullPointerException: Null value appeared in non-
nullable field:
- field (class: "scala.Long", name: "age")
Any ideas what am I doing wrong ?
case class Owner(id: String, pets: Seq[Pet])
case class Pet(name: String, age: Long)
val sampleJson = """{"id":"kotek", "pets":[{"name":"miauczek",
"age":18}, {"name":"miauczek2", "age":9}]}"""
val session = SparkSession.builder().master("local").getOrCreate()
import session.implicits._
val rdd = session.sparkContext.parallelize(Seq(sampleJson))
val ds = session.read.json(rdd).as[Owner].collect()
Usually, if some field can be missing use either Option
:
case class Owner(id: String, pets: Seq[Pet])
case class Pet(name: String, age: Option[Long])
or nullable
type:
case class Owner(id: String, pets: Seq[Pet])
case class Pet(name: String, age: java.lang.Long)
But this one indeed looks like a bug. I tested this ins Spark 2.2 and it has been resolved by now. I think that quick workaround is to keep fields sorted by name:
case class Owner(id: String, pets: Seq[Pet])
case class Pet(age: java.lang.Long, name: String)
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