Thank you for your comments
> You should just Seq(...).toDS
I tried this, however the result is not changed.
>> val ds2 = ds1.map(e => e)
> Why are you e => e (since it's identity) and does nothing?
Yes, e => e does nothing. For the sake of simplicity of an example, I used
the simplest expression in map(). In current Spark, an expression in map()
does not change an schema for its output.
> .as(RowEncoder(new StructType()
> .add("value", ArrayType(IntegerType, false), nullable =
false)))
Sorry, this was my mistake. It did not work for my purpose. It actually
does nothing.
Kazuaki Ishizaki
From: Jacek Laskowski <ja...@japila.pl>
To: Kazuaki Ishizaki/Japan/IBM@IBMJP
Cc: user <user@spark.apache.org>
Date: 2016/08/15 04:56
Subject: Re: Change nullable property in Dataset schema
On Wed, Aug 10, 2016 at 12:04 AM, Kazuaki Ishizaki <ishiz...@jp.ibm.com>
wrote:
> import testImplicits._
> test("test") {
> val ds1 = sparkContext.parallelize(Seq(Array(1, 1), Array(2, 2),
> Array(3, 3)), 1).toDS
You should just Seq(...).toDS
> val ds2 = ds1.map(e => e)
Why are you e => e (since it's identity) and does nothing?
> .as(RowEncoder(new StructType()
> .add("value", ArrayType(IntegerType, false), nullable =
false)))
I didn't know it's possible but looks like it's toDF where you could
replace the schema too (in a less involved way).
I learnt quite a lot from just a single email. Thanks!
Pozdrawiam,
Jacek
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