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Question

We are using SAP HANA 1.0 SPS12.

We have daywise table like below -

select trans_date,article,measure1,measure2 from table_1

Volume of table ~ 5 millions rows

we need to see data like -

select 'day-1',sum(measure1),sum(meaure2) from table1 where trans_date=add_days(current_date,-1) group by 'day-1'
union all
select 'day-2',sum(measure1),sum(meaure2) from table1 where trans_date>=add_days(current_date,-2) group by 'day-2' 
union all
select 'WTD',sum(measure1),sum(meaure2) from table1 where trans_date>=add_days(current_date,-7) group by 'WTD'
union all
select 'WTD-1',sum(measure1),sum(meaure2) from table1 where trans_date>=add_days(current_date,-15) and trans_Date <= add_days(current_date,-7) group by 'WTD-1'

so on and so forth for MTD,MTD-1,MTD-2,YTD.

Performance wise is it better to use WITH CLAUSE and hold data for one year and then split according to timeframe? OR Is it better to use separate aggregation for each timeframe as shown above.

As far as I understand, in RDBMSs like Oracle, WITH CLAUSE materializes results and use it from the memory. SAP HANA is In Memory database itself. Does using WITH CLAUSE in SAP HANA gives distinctive performance edge?

Query using WITH CLAUSE -

WITH t1 as
(
select trans_date,sum(measure1),sum(meaure2) from table1 where trans_date>=add_days(current_date,-365)
)
select 'day-1',sum(measure1),sum(meaure2) from t1 where trans_date=add_days(current_date,-1) group by 'day-1'
union all
select 'day-2',sum(measure1),sum(meaure2) from t1 where trans_date>=add_days(current_date,-2) group by 'day-2' 
union all
select 'WTD',sum(measure1),sum(meaure2) from t1 where trans_date>=add_days(current_date,-7) group by 'WTD'
union all
select 'WTD-1',sum(measure1),sum(meaure2) from t1 where trans_date>=add_days(current_date,-15) 
                                                  and trans_Date <= add_days(current_date,-7) 
                                                  group by 'WTD-1'

Answer 1

If you care about performance, putting the data in a single row should be much better:

select sum(case when trans_date = add_days(current_date, -1) then measure1 end) as measure1_day1,
       sum(case when trans_date = add_days(current_date, -1) then measure2 end) as measure2_day1,
       sum(case when trans_date = add_days(current_date, -2) then measure1 end) as measure1_day2,
       sum(case when trans_date = add_days(current_date, -2) then measure2 end) as measure2_day2,
       . . .       
from table1
where trans_date >= add_days(current_date, -15);

You can unpivot the results afterwards, if you really need the values in separate rows.

Alternatively, you can do:

select days, sum(measure1), sum(measure2)
from (select 1 as days from dummy union all
      select 2 from dummy union all
      select 7 from dummy union all
      select 15 from dummy
     ) d left join
     table1 t
     on t.trans_date = add_days(current_date, - d.days)
group by days
order by days;