Thank you Jakob, you were bang on the money. Jorge appologies my snippets
was partial and I hadn't made it equivelent to my failing test.
For reference and for all that pass this way, here is the (a) working
solution with passing tests without inferring a schema, it was the second
test that had been failing prior to Jakobs pointer.
import org.apache.spark.sql.Dataset
import org.scalatest.Matchers
case class Sample(val time:Long , val opt: Option[Long] = None)
class SampleTest extends SparkSimpleContextConfigurator with Matchers{
"A JSON Object" should "Parse Correctly" in {
val jsonStr = """ {"time": 2,
"opt": 1
}
"""
val rdd = sc.parallelize(Seq(jsonStr))
import sqlContext.implicits._
val samples: Dataset[Sample] = sqlContext.read.json(rdd).as[Sample]
val sample: Sample = samples.first()
sample.time should be (2)
sample.opt.isDefined should be (true)
sample.opt.get should be (1)
}
"A Partial JSON Object" should "Parse Correctly" in {
val json = Seq(
""" {"time": 2 }
"""
,
""" {"time": 10,"opt": 10}
"""
)
val rdd = sc.parallelize(json)
import sqlContext.implicits._
val samples: Dataset[Sample] = sqlContext.read.json(rdd).as[Sample]
val sample: Sample = samples.first()
sample.time should be (2)
sample.opt.isDefined should be (false)
}
}
Phone: 087 - 9179799
Quidquid latine dictum sit, altum sonatur
On 23 February 2016 at 00:43, Jakob Odersky <ja...@odersky.com> wrote:
> I think the issue is that the `json.read` function has no idea of the
> underlying schema, in fact the documentation
> (
> http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.DataFrameReader
> )
> says:
>
> > Unless the schema is specified using schema function, this function goes
> through the input once to determine the input schema.
>
> so since your test data does not contain a record with a product_id,
> json.read creates a schema that does not contain it. Only after
> determining the (incorrect) schema, you treat it as a Dataset of
> CustomerEvent which will fail.
> Try creating a schema (StructType) manually for your CustomerEvent
> case class and pass it to the `json.schema` function before calling
> `read`. I.e. something like
>
> val sch = StructType(StructField("customer_id",StringType,false),
> StructField(porduct_id,IntegerType,true)) //there's probably a better
> way to get the schema from a case class
> val customers: Dataset[CustomerEvent] =
> sqlContext.read.schema(sch).json(rdd).as[CustomerEvent]
>
> just a pointer, I haven't tested this.
> regards,
> --Jakob
>
> On Mon, Feb 22, 2016 at 12:17 PM, Jorge Machado <jom...@me.com> wrote:
> > Hi Anthony,
> >
> > I try the code on my self. I think it is on the jsonStr:
> >
> > I do it with : val jsonStr = """{"customer_id":
> > "3ee066ab571e03dd5f3c443a6c34417a","product_id": 3}”""
> >
> > or is it the “,” after your 3 oder the “\n”
> >
> > Regards
> >
> >
> >
> > On 22/02/2016, at 15:42, Anthony Brew <atb...@gmail.com> wrote:
> >
> > Hi,
> > I'm trying to parse JSON data into a case class using the
> > DataFrame.as[] function, nut I am hitting an unusual error and the
> interweb
> > isnt solving my pain so thought I would reach out for help. Ive
> truncated my
> > code a little here to make it readable, but the error is full
> >
> > My case class looks like....
> >
> > case class CustomerEvent(
> > customer_id: String,
> > product_id: Option[Long] = None,
> > )
> >
> >
> > My passing test looks like
> >
> > "A Full CustomerEvent JSON Object" should "Parse Correctly" in {
> > val jsonStr = """ {
> > "customer_id": "3ee066ab571e03dd5f3c443a6c34417a",
> > "product_id": 3,
> > }
> > """
> > // apparently deprecation is not an issue
> > val rdd = sc.parallelize(Seq(jsonStr))
> >
> > import sqlContext.implicits._
> > val customers: Dataset[CustomerEvent] =
> > sqlContext.read.json(rdd).as[CustomerEvent]
> >
> > val ce: CustomerEvent = customers.first()
> > ce.customer_id should be ("3ee066ab571e03dd5f3c443a6c34417a")
> > ce.product_id.get should be (3)
> > }
> >
> > My issue is when the product_id is not part of the json, I get a encoding
> > error
> >
> > ie the following
> >
> > "A Partial CustomerEvent JSON Object" should " should Parse Correctly"
> in
> > {
> > val jsonStr = """ {
> > "customer_id": "3ee066ab571e03dd5f3c443a6c34417a"
> > }
> > """
> > // apparently deprecation is not an issue
> > val rdd = sc.parallelize(Seq(jsonStr))
> >
> > import sqlContext.implicits._
> > val customers: Dataset[CustomerEvent] =
> > sqlContext.read.json(rdd).as[CustomerEvent]
> >
> > val ce: CustomerEvent = customers.first()
> > ce.customer_id should be ("3ee066ab571e03dd5f3c443a6c34417a")
> > ce.product_id.isDefined should be (false)
> >
> > }
> >
> >
> >
> > My error looks like
> >
> > Error while decoding: java.lang.UnsupportedOperationException: Cannot
> > evaluate expression: upcast('product_id,DoubleType,- field (class:
> > "scala.Option", name: "product_id"),- root class: "data.CustomerEvent")
> > newinstance(class data.CustomerEvent,invoke(input[3,
> > StringType],toString,ObjectType(class java.lang.String)),input[0,
> > LongType],input[9, LongType],invoke(input[5,
> > StringType],toString,ObjectType(class java.lang.String)),invoke(input[6,
> > StringType],toString,ObjectType(class java.lang.String)),input[7,
> > LongType],invoke(input[1, StringType],toString,ObjectType(class
> > java.lang.String)),wrapoption(input[8,
> > LongType]),wrapoption(upcast('product_id,DoubleType,- field (class:
> > "scala.Option", name: "product_id"),- root class:
> > "data.CustomerEvent")),wrapoption(input[4,
> > DoubleType]),wrapoption(invoke(input[2,
> > StringType],toString,ObjectType(class
> > java.lang.String))),false,ObjectType(class data.CustomerEvent),None)
> > :- invoke(input[3, StringType],toString,ObjectType(class
> java.lang.String))
> > : +- input[3, StringType]
> > :- input[0, LongType]
> > :- input[9, LongType]
> > :- invoke(input[5, StringType],toString,ObjectType(class
> java.lang.String))
> > : +- input[5, StringType]
> > :- invoke(input[6, StringType],toString,ObjectType(class
> java.lang.String))
> > : +- input[6, StringType]
> > :- input[7, LongType]
> > :- invoke(input[1, StringType],toString,ObjectType(class
> java.lang.String))
> > : +- input[1, StringType]
> > :- wrapoption(input[8, LongType])
> > : +- input[8, LongType]
> > :- wrapoption(upcast('product_id,DoubleType,- field (class:
> "scala.Option",
> > name: "product_id"),- root class: "data.CustomerEvent"))
> > : +- upcast('product_id,DoubleType,- field (class: "scala.Option", name:
> > "product_id"),- root class: "data.CustomerEvent")
> > : +- 'product_id
> > :- wrapoption(input[4, DoubleType])
> > : +- input[4, DoubleType]
> > +- wrapoption(invoke(input[2, StringType],toString,ObjectType(class
> > java.lang.String)))
> > +- invoke(input[2, StringType],toString,ObjectType(class
> > java.lang.String))
> > +- input[2, StringType]
> >
> >
> > at
> >
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.fromRow(ExpressionEncoder.scala:224)
> > at
> > org.apache.spark.sql.Dataset$$anonfun$collect$2.apply(Dataset.scala:668)
> > at
> > org.apache.spark.sql.Dataset$$anonfun$collect$2.apply(Dataset.scala:668)
> > at
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> > at
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> > at
> >
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> > at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
> > at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> > at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
> > at org.apache.spark.sql.Dataset.collect(Dataset.scala:668)
> > at org.apache.spark.sql.Dataset.take(Dataset.scala:689)
> > at org.apache.spark.sql.Dataset.first(Dataset.scala:654)
> > at
> >
> data.TestLoadingCustomerEventFromJSON$$anonfun$2.apply$mcV$sp(TestLoadingCustomerEventFromJSON.scala:70)
> > at
> >
> data.TestLoadingCustomerEventFromJSON$$anonfun$2.apply(TestLoadingCustomerEventFromJSON.scala:50)
> > at
> >
> data.TestLoadingCustomerEventFromJSON$$anonfun$2.apply(TestLoadingCustomerEventFromJSON.scala:50)
> > at
> >
> org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
> > at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
> > at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
> > at org.scalatest.Transformer.apply(Transformer.scala:22)
> > at org.scalatest.Transformer.apply(Transformer.scala:20)
> > at org.scalatest.FlatSpecLike$$anon$1.apply(FlatSpecLike.scala:1647)
> > at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
> > at org.scalatest.FlatSpec.withFixture(FlatSpec.scala:1683)
> > at
> >
> org.scalatest.FlatSpecLike$class.invokeWithFixture$1(FlatSpecLike.scala:1644)
> > at
> >
> org.scalatest.FlatSpecLike$$anonfun$runTest$1.apply(FlatSpecLike.scala:1656)
> > at
> >
> org.scalatest.FlatSpecLike$$anonfun$runTest$1.apply(FlatSpecLike.scala:1656)
> > at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
> > at org.scalatest.FlatSpecLike$class.runTest(FlatSpecLike.scala:1656)
> >
> >
> >
> > Any pointers on what I am doing wrong would be gratefully accepted!
> >
> > Thanks a Million,
> > Anthony
> >
> >
>
