its pretty much impossible to be fully up to date with spark given how fast
it moves!
the book is a very helpful reference
On Wed, Apr 5, 2017 at 11:15 AM, Jacek Laskowski <ja...@japila.pl> wrote:
> Hi,
>
> I'm very sorry for not being up to date with the current style (and
> "promoting" the old style) and am going to review that part soon. I'm very
> close to touch it again since I'm with Optimizer these days.
>
> Jacek
>
> On 5 Apr 2017 6:08 a.m., "Kazuaki Ishizaki" <ishiz...@jp.ibm.com> wrote:
>
>> Hi,
>> The page in the URL explains the old style of physical plan output.
>> The current style adds "*" as a prefix of each operation that the
>> whole-stage codegen can be apply to.
>>
>> So, in your test case, whole-stage codegen has been already enabled!!
>>
>> FYI. I think that it is a good topic for d...@spark.apache.org.
>>
>> Kazuaki Ishizaki
>>
>>
>>
>> From: Koert Kuipers <ko...@tresata.com>
>> To: "user@spark.apache.org" <user@spark.apache.org>
>> Date: 2017/04/05 05:12
>> Subject: how do i force unit test to do whole stage codegen
>> ------------------------------
>>
>>
>>
>> i wrote my own expression with eval and doGenCode, but doGenCode never
>> gets called in tests.
>>
>> also as a test i ran this in a unit test:
>> spark.range(10).select('id as 'asId).where('id === 4).explain
>> according to
>>
>> *https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-sql-whole-stage-codegen.html*
>> <https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-sql-whole-stage-codegen.html>
>> this is supposed to show:
>> == Physical Plan ==
>> WholeStageCodegen
>> : +- Project [id#0L AS asId#3L]
>> : +- Filter (id#0L = 4)
>> : +- Range 0, 1, 8, 10, [id#0L]
>>
>> but it doesn't. instead it shows:
>>
>> == Physical Plan ==
>> *Project [id#12L AS asId#15L]
>> +- *Filter (id#12L = 4)
>> +- *Range (0, 10, step=1, splits=Some(4))
>>
>> so i am again missing the WholeStageCodegen. any idea why?
>>
>> i create spark session for unit tests simply as:
>> val session = SparkSession.builder
>> .master("local[*]")
>> .appName("test")
>> .config("spark.sql.shuffle.partitions", 4)
>> .getOrCreate()
>>
>>
>>
