Hi,

The point is that I could go full-type with Dataset[String] and wonder
why it's possible with ints.

You're working with DataFrames which are Dataset[Row]. It's too little
to me these days :)

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


On Sat, Aug 13, 2016 at 1:43 PM, Mich Talebzadeh
<mich.talebza...@gmail.com> wrote:
> Would not that be as simple as:
>
> scala> (0 to 9).toDF
> res14: org.apache.spark.sql.DataFrame = [value: int]
>
> scala> (0 to 9).toDF.map(_.toString)
> res13: org.apache.spark.sql.Dataset[String] = [value: string]
>
> with my little knowledge
>
> Dr Mich Talebzadeh
>
>
>
> LinkedIn
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> On 13 August 2016 at 21:17, Jacek Laskowski <ja...@japila.pl> wrote:
>>
>> Hi,
>>
>> Just ran into it and can't explain why it works. Please help me understand
>> it.
>>
>> Q1: Why can I `as[String]` with Ints? Is this type safe?
>>
>> scala> (0 to 9).toDF("num").as[String]
>> res12: org.apache.spark.sql.Dataset[String] = [num: int]
>>
>> Q2: Why can I map over strings even though there are really ints?
>>
>> scala> (0 to 9).toDF("num").as[String].map(_.toUpperCase)
>> res11: org.apache.spark.sql.Dataset[String] = [value: string]
>>
>> Why are the two lines possible?
>>
>> 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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