Thanks.
Tried this
scala> val a = df.filter(col("Total") > "").map(p =>
Invoices(p(0).toString,
p(1).toString.TO_DATE(FROM_UNIXTIME(UNIX_TIMESTAMP(p(1),"dd/MM/"),"-MM-dd")),
p(2).toString.substring(1).replace(",", "").toDouble,
p(3).toString.substring(1).replace(",", "").toDouble,
You can invoke exactly the same functions on scala side as well i.e.
http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.functions$
Have you tried them?
On Thu, Mar 24, 2016 at 10:29 PM, Mich Talebzadeh wrote:
>
> Hi,
>
> Read a CSV in with
Hi,
Read a CSV in with the following schema
scala> df.printSchema
root
|-- Invoice Number: string (nullable = true)
|-- Payment date: string (nullable = true)
|-- Net: string (nullable = true)
|-- VAT: string (nullable = true)
|-- Total: string (nullable = true)
I use mapping as below