Need to understand why SAS system generate merging in data step as SQL  is already done all those work .. its all about the way we think ...I think we need more enhance processing  we need to do new function and then they created this algorithms .. because any other system can't do what merge is doing here in terms of technical processing  . if they only need to build a Cartesian product they never find the this merge process .. and if there is possible to generate the Cartesian product .. i am also interested to know . But my think is always towards find the efficient and more simple function of processing. ... View more

Thanks and its reduce the slight tie as well but yes in terms of performance if function works well . The stats i get after re-edit the codes . NOTE: There were 15000 observations read from the data set WORK.RAW. NOTE: The data set WORK.IF has 15000 observations and 18 variables. NOTE: DATA statement used (Total process time):       real time           0.03 seconds       user cpu time       0.00 seconds       system cpu time     0.01 seconds       memory              363.84k       OS Memory           6584.00k       Timestamp           01/17/2014 08:47:50 PM NOTE: There were 15000 observations read from the data set WORK.RAW. NOTE: The data set WORK.WHEN has 15000 observations and 21 variables. NOTE: DATA statement used (Total process time):       real time           0.12 seconds       user cpu time       0.03 seconds       system cpu time     0.09 seconds       memory              365.62k       OS Memory           6584.00k       Timestamp           01/17/2014 08:47:50 PM after re-editing the function works great but a major in there real time and  CPU time and this is the only difference I found . ... View more

Can you explain what is time difference in content of this.... ... View more

Just run this and verified is this what you wanna ; proc sql; create table work.one (X num format=1.,A CHAR(1)); insert into work.one values(1,'a') values(4,'d') values(2,'b') ; quit ; proc sql noprint  ; select x into :X1-:X3 from one ; quit ; %put _global_ ; *Look for X1 X2 X3 macro values ; Please confirm . ... View more

Just the way you use both work in similar phase and no need to understand difference because it give you same result . as per your comfort you can either choose if then else or select when statement ; I tried it on same dataset and find out the difference is how much they are used memory . Dataset of 15000 observation and 20 variables is used to analyse . Codes  processed using IF data if  ; set raw ; if Region='Central' then do ; code=1; end ; if Region='East' then do ; code=2; end ; if Region='Wast' then do ; code=3; end ; else code=0 ; run ; *----------------------------------------* NOTE: There were 15000 observations read from the data set WORK.RAW. NOTE: The data set WORK.IF has 15000 observations and 18 variables. NOTE: DATA statement used (Total process time): other is using select when data when ; set raw ; select (Region); when(central)do ; code=1 ; end ; when(East)do ; code=2 ; end ; when(West)do ; code=3 ; end ; otherwise code=0 ; end ; run ; ---------------------------------------------- NOTE: There were 15000 observations read from the data set WORK.RAW. NOTE: The data set WORK.WHEN has 15000 observations and 21 variables. NOTE: DATA statement used (Total process time): Timing used for processing IF       real time           0.03 seconds       user cpu time       0.01 seconds       system cpu time     0.01 seconds       memory              362.75k       OS Memory           6584.00k       Timestamp           01/17/2014 07:48:49 PM Timing used for processing select when ;       real time           0.09 seconds       user cpu time       0.01 seconds       system cpu time     0.09 seconds       memory              367.62k       OS Memory           6584.00k       Timestamp           01/17/2014 07:51:27 PM You find a bit difference in real time and cpu time .. here is start using the way if data will increase to millions which SAS system  actual have to work . the difference can me measured easily . I hope it will help you understand . ... View more