How to optimize query running on hive

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hadoop

big-data

Below is my query which takes around 5k mappers and 1k reducers and time taken is around 2.2 hours to finish. Any scope of optimization in here?

What I have tried:

SELECT
sum(B.item_net_amount) net_amount,
sum(B.item_gross_amount) gross_amount,
sum(B.item_quantity) item_quantity,
(sum(nvl(B.item_gross_amount,0))-sum( nvl(B.total_discount_amount,0)))/100 dollar_sales
from (select item_dim_key from wh_postx_seven11_p1.eal_seven11_it_mstr where category_label in ('34.02 - Products')) A
left outer join
wh_postx_seven11_p2.postx_fact B
on A.item_dim_key = B.src_item_dim_key
WHERE data_supplier_name='SEVEN11'
and retailer_name='SEVEN11'
and tm_dim_key_day between 42598 and 42604 ;

output i got :

258546211.00000000    258550200.00000000    7475811    2585462.1100000

The query used in from statement returns around 1.3 k records. Based on this table the left join is used to main table.

select item_dim_key from wh_postx_seven11_p1.eal_seven11_it_mstr where category_label in ('34.02 - Products')