Blocker Description
There seems to be a regression between 1.6.0 and 1.6.1 (snapshot build). By default a scala Seq[Double] is mapped by Spark as an ArrayType with nullable element
|-- valuations: array (nullable = true) | |-- element: double (containsNull = true)
This could be read back to as a Dataset in Spark 1.6.0
val df = sqlContext.table("valuations").as[Valuation]
But with Spark 1.6.1 the same fails with
val df = sqlContext.table("valuations").as[Valuation] org.apache.spark.sql.AnalysisException: cannot resolve 'cast(valuations as array<double>)' due to data type mismatch: cannot cast ArrayType(DoubleType,true) to ArrayType(DoubleType,false);
Here's the classes I am using
case class Valuation(tradeId : String, counterparty: String, nettingAgreement: String, wrongWay: Boolean, valuations : Seq[Double], /* one per scenario */ timeInterval: Int, jobId: String) /* used for hdfs partitioning */ val vals : Seq[Valuation] = Seq() val valsDF = sqlContext.sparkContext.parallelize(vals).toDF valsDF.write.partitionBy("jobId").mode(SaveMode.Overwrite).saveAsTable("valuations")
even the following gives the same result
val valsDF = vals.toDS.toDF
