You probably have to increase jvm/jdk memory size
https://stackoverflow.com/questions/1565388/increase-heap-size-in-java
On Mon, Jul 29, 2024 at 9:36 PM mike Jadoo wrote:
> Thanks. I just downloaded the corretto but I got this error message,
> which was the same as before. [It was shared wi
Can you try disabling broadcast join and see what happens?
On Mon, Jul 8, 2024 at 12:03 PM Sudharshan V
wrote:
> Hi all,
>
> Been facing a weird issue lately.
> In our production code base , we have an explicit broadcast for a small
> table.
> It is just a look up table that is around 1gb in siz
What exactly is the error? Is it erroring out while reading the data from
db? How are you partitioning the data?
How much memory currently do you have? What is the network time out?
Regards,
Meena
On Mon, May 27, 2024 at 4:22 PM Perez wrote:
> Hi Team,
>
> I want to extract the data from DB a
Mitch, you are right these days the attention span is getting shorter.
Christian could work on a completely new thing for 3 hours and is proud to
explain. It is amazing.
Thanks for sharing.
On Sat, Apr 27, 2024 at 9:40 PM Farshid Ashouri
wrote:
> Mich, this is absolutely amazing.
>
> Thanks f
.* from rev
>> inner join customer c
>> on rev.custumer_id =c.id
>> inner join product p
>> on rev.sys = p.sys
>> and rev.prin = p.prin
>> and rev.scode= p.bcode
>>
>> left join item I
>> on rev.sys = I.sys
>> and rev.custumer_id = I.cust
Hello all:
I am using spark sql to join two tables. To my surprise I am
getting redundant rows. What could be the cause.
select rev.* from rev
inner join customer c
on rev.custumer_id =c.id
inner join product p
rev.sys = p.sys
rev.prin = p.prin
rev.scode= p.bcode
left join item I
on rev.sys = i
