julianpeeters/case-class-generator

Dynamically defines and loads Scala classes at runtime. Useful for turning JSON schemas into Scala case classes on the fly.

case-class-generator's Issues

Not able to Create the case class for following json

{"result":[[{"last24hrs":{"fiat":9050,"vol":500000,"difffiat":"-182835","diffvol":"-10000000"}}],[{"max24Hr":1810000,"diff":"-20000"}],[{"min24Hr":1810000,"diff":"70000"}],[{"lasttrade":[{"ask":[[{"rate":1810000,"volume":500000,"time":1437856586316}]]}]}],{"highestBid":1810000},{"lowestAsk":1850000},{"allaskCoinSum":319800000,"allbidFiatSum":6229412}]}

Please help to figureout

Issues about use generated case class as Encoders.bean

Hi, @julianpeeters
I used this project to generate some case class according to the csv content loaded by spark DataFrame. And I'd like to convert the dataframe to Dataset, which required an Encoder(since the Encoder support basic type and case class ).
However, it always threw some exception like following? Do you have any comments or thoughts about this? Appreciated very much!

java.lang.UnsupportedOperationException: Cannot infer type for class models.Station because it is not bean-compliant
at org.apache.spark.sql.catalyst.JavaTypeInference$.org$apache$spark$sql$catalyst$JavaTypeInference$$serializerFor(JavaTypeInference.scala:416)
at org.apache.spark.sql.catalyst.JavaTypeInference$.serializerFor(JavaTypeInference.scala:327)
at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.javaBean(ExpressionEncoder.scala:82)
at org.apache.spark.sql.Encoders$.bean(Encoders.scala:141)

Attach my code sample as below:

_val hydrologyStationDF = spark.sqlContext.read.format("csv").option("header", true).csv(filePath)
val valueMembers : List[FieldData] = List(FieldData("STCD", typeOf[String]), FieldData("STNM", typeOf[String]),
FieldData("LGTD", typeOf[Double]), FieldData("LTTD", typeOf[Double]))
val classData = new ClassData(ClassNamespace(Some("models")), ClassName("Station"), ClassFieldData(valueMembers))
val dcc = new DynamicCaseClass(classData)
val record1 = dcc.runtimeInstance

type MyRecord = record1.type
import spark.implicits._
val points2 = hydrologyStationPropertyDF.as(Encoders.bean(record1.getClass()))_

Generating Classes with Fields of Type defined by a string

Hi,

I would like to generate case classes and then Map it to Bean. But The fields definition is stored in a database. So the Field names and types as strings:
So I have, for instance, {"name": "String", "age": "Int"}

How can I use your case class generator to create a case class and the map it to bean.

Thanks

sbt 0.13 breakage

After upgrading build.properties file from sbt 0.12.2 to 0.13.2, there is an error. sbt 0.13.7-M3 fixes the issue in sbt run, but now each dynamic class is loaded twice in sbt test.

This issues exists for devs, but not for users (there is no issue when this project is used as a dependency).