On Thu, Aug 4, 2016 at 11:56 PM, luismattor <luismat...@gmail.com> wrote:
> import java.sql.Timestamp
> case class MyProduct(t: Timestamp, a: Float)
> val rdd = sc.parallelize(List(MyProduct(new Timestamp(0), 10))).toDF()
> rdd.printSchema()
>
> The output is:
> root
> |-- t: timestamp (nullable = true)
> |-- a: float (nullable = false)
>
> How can I set the timestamp column to be NOT nullable?
Gotcha! :)
scala> import java.sql.Timestamp
import java.sql.Timestamp
scala> case class MyProduct(t: java.sql.Timestamp, a: Float)
defined class MyProduct
scala> import org.apache.spark.sql._
import org.apache.spark.sql._
scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._
scala> import org.apache.spark.sql.catalyst.encoders._
import org.apache.spark.sql.catalyst.encoders._
scala> implicit def myEncoder: Encoder[MyProduct] =
ExpressionEncoder[MyProduct].copy(schema = new StructType().add("t",
"timestamp", false).add("a", "float", false))
myEncoder: org.apache.spark.sql.Encoder[MyProduct]
scala> spark.createDataset(Seq(MyProduct(new Timestamp(0), 10))).printSchema
root
|-- t: timestamp (nullable = false)
|-- a: float (nullable = false)
Pozdrawiam,
Jacek Laskowski
----
https://medium.com/@jaceklaskowski/
Mastering Apache Spark 2.0 http://bit.ly/mastering-apache-spark
Follow me at https://twitter.com/jaceklaskowski
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