We finally fix this in 1.5 (next release), see
https://github.com/apache/spark/pull/7301
On Sat, Jul 11, 2015 at 10:32 PM, Jerry Lam wrote:
> Hi guys,
>
> I just hit the same problem. It is very confusing when Row is not the same
> Row type at runtime. The worst thing is that when I use Spark in
Hi guys,
I just hit the same problem. It is very confusing when Row is not the same
Row type at runtime. The worst thing is that when I use Spark in local mode,
the Row is the same Row type! so it passes the test cases but it fails when
I deploy the application.
Can someone suggest a workaround?
Is there some way around this? For example, can Row just be an
implementation of namedtuple throughout?
from collections import namedtuple
class Row(namedtuple):
...
>From a user perspective, it’s confusing that there are 2 different
implementations of the Row class with the same name.
In my
In Row#equals():
while (i < len) {
if (apply(i) != that.apply(i)) {
'!=' should be !apply(i).equals(that.apply(i)) ?
Cheers
On Mon, May 11, 2015 at 1:49 PM, Nicholas Chammas <
nicholas.cham...@gmail.com> wrote:
> This is really strange.
>
> >>> # Spark 1.3.1
> >>> print type(resu
