> remove that requirement.
>
> On Wed, Aug 19, 2020 at 3:21 AM Jatin Puri wrote:
> >
> > Hello,
> >
> > This is wrt
> https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala#L244
> >
> > require(vocab.
Hello,
This is wrt
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala#L244
require(vocab.length > 0, "The vocabulary size should be > 0. Lower minDF
as necessary.")
Currently, if `CountVectorizer` is trained on an empty dataset resu
>From this
>(http://apache-spark-developers-list.1001551.n3.nabble.com/DISCUSS-Spark-2-5-release-td27963.html#a27966),
> looks like there is no confirmation yet if at all Spark 2.5 would have JDK 11
>support.
Spark 3 would most likely be out soon (tentatively this quarter as per mailing
list).
and tried a few. But they didnt seem
to work. I am using spark 2.3.1
Thanks.
On Sun, Sep 23, 2018 at 6:00 PM Michael Artz wrote:
> Are you using the scheduler in fair mode instead of fifo mode?
>
> Sent from my iPhone
>
> > On Sep 22, 2018, at 12:58 AM, Jatin Puri
Hi.
What tactics can I apply for such a scenario.
I have a pipeline of 10 stages. Simple text processing. I train the data
with the pipeline and for the fitted data, do some modelling and store the
results.
I also have a web-server, where I receive requests. For each request
(dataframe of single
Hello.
I am wondering, if there is any new update on Spark upgrade to Scala 2.12.
https://issues.apache.org/jira/browse/SPARK-14220. Especially given that
Scala 2.13 is near the vicinity of a release.
This is because, there is no recent update on the Jira and related ticket.
May be someone is act
