=schema)
df = df.crossJoin(empty_vector)
df = df.withColumn('feature', F.coalesce('feature', '_empty_vector')
On Thu, Jun 22, 2017 at 11:54 AM, Franklyn D'souza <
franklyn.dso...@shopify.com> wrote:
> We've developed Scala UDFs internally t
to give it more of a first class support in
dataframes by having it work with the lit column expression.
On Wed, Jun 21, 2017 at 9:30 PM, Franklyn D'souza <
franklyn.dso...@shopify.com> wrote:
> From the documentation it states that ` The input columns should be of
> DoubleType or
hon/ml/imputer_example.py
>
> which should at least partially address the problem.
>
> On 06/22/2017 03:03 AM, Franklyn D'souza wrote:
> > I just wanted to highlight some of the rough edges around using
> > vectors in columns in dataframes.
> >
> > If there is a n
I just wanted to highlight some of the rough edges around using vectors in
columns in dataframes.
If there is a null in a dataframe column containing vectors pyspark ml
models like logistic regression will completely fail.
However from what i've read there is no good way to fill in these nulls
wi
-1 https://issues.apache.org/jira/browse/SPARK-18589 hasn't been resolved
by this release and is a blocker in our adoption of spark 2.0. I've updated
the issue with some steps to reproduce the error.
On Mon, Dec 19, 2016 at 4:37 AM, Sean Owen wrote:
> PS, here are the open issues for 2.1.0. Forg
Just wondering where the spark-assembly jar has gone in 2.0. i've been
reading that its been removed but i'm not sure what the new workflow is .
I've built spark-2.0-preview (8f5a04b) with scala-2.10 using the following
>
>
> ./dev/change-version-to-2.10.sh
> ./dev/make-distribution.sh -DskipTests -Dzookeeper.version=3.4.5
> -Dcurator.version=2.4.0 -Dscala-2.10 -Phadoop-2.6 -Pyarn -Phive
and then ran the following code in a pyspark shell
Hi,
I've checked out the 2.0-preview and attempted to build it
with ./dev/make-distribution.sh -Pscala-2.10
However i keep getting
[INFO] --- maven-enforcer-plugin:1.4.1:enforce (enforce-versions) @
spark-parent_2.11 ---
[WARNING] Rule 0: org.apache.maven.plugins.enforcer.BannedDependencies
fail
Just wanted to confirm that this is the expected behaviour.
Basically I'm putting nulls into a non-nullable LongType column and doing a
transformation operation on that column, the result is a column with nulls
converted to 0.
Heres an example
from pyspark.sql import types
from pyspark.sql impor
I'm using the UDT api to work with a custom Money datatype in dataframes.
heres how i have it setup
class StringUDT(UserDefinedType):
@classmethod
def sqlType(self):
return StringType()
@classmethod
def module(cls):
return cls.__module__
@classmethod
def
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