Usually using broadcast join could boost the performance when you have
enough memory,
You should decrease it or even disable it when there is no enough memory.
On Thu, Oct 27, 2016 at 1:22 PM, Pietro Pugni wrote:
> Thank you Davies,
> this worked! But what are the
Thank you Davies,
this worked! But what are the consequences of setting
spark.sql.autoBroadcastJoinThreshold=0?
Will it degrade or boost performance?
Thank you again
Pietro
> Il giorno 27 ott 2016, alle ore 18:54, Davies Liu ha
> scritto:
>
> I think this is caused by
I think this is caused by BroadcastHashJoin try to use more memory
than the amount driver have, could you decrease the
spark.sql.autoBroadcastJoinThreshold (-1 or 0 means disable it)?
On Thu, Oct 27, 2016 at 9:19 AM, Pietro Pugni wrote:
> I’m sorry, here’s the formatted
I’m sorry, here’s the formatted message text:
I'm running an ETL process that joins table1 with other tables (CSV files), one
table at time (for example table1 with table2, table1 with table3, and so on).
The join is written inside a PostgreSQL istance using JDBC.
The entire process runs