SAS: generate abstractly long and large dataset - sas

Trying to do some performance testing
I can't figure out a macro
%generate(n_rows,n_cols);
that would generate a table with n_rows and n_cols, filled with random numbers/strings
I tried using this link:
http://bi-notes.com/2012/08/benchmark-io-performance/
But I quickly encounter a memory issue
Thanks!

Try this. I added a 2 input parameters. So now you have a number of numerics and a number of characters. Also the ability to define the output dataset name.
%macro generate(n_rows,n_num_cols,n_char_cols,outdata=test,seed=0);
data &outdata;
array nums[&n_num_cols];
array chars[&n_char_cols] $;
temp = "abcdefghijklmnopqrstuvwxyz";
do i=1 to &n_rows;
do j=1 to &n_num_cols;
nums[j] = ranuni(&seed);
end;
do j=1 to &n_char_cols;
chars[j] = substr(temp,ceil(ranuni(&seed)*18),8);
end;
output;
end;
drop i j temp;
run;
%mend;
%generate(10,10,10,outdata=test);

Related

SaS 9.4: How to use different weights on the same variable without datastep or proc sql

I can't find a way to summarize the same variable using different weights.
I try to explain it with an example (of 3 records):
data pippo;
a=10;
wgt1=0.5;
wgt2=1;
wgt3=0;
output;
a=3;
wgt1=0;
wgt2=0;
wgt3=1;
output;
a=8.9;
wgt1=1.2;
wgt2=0.3;
wgt3=0.1;
output;
run;
I tried the following:
proc summary data=pippo missing nway;
var a /weight=wgt1;
var a /weight=wgt2;
var a /weight=wgt3;
output out=pluto (drop=_freq_ _type_) sum()=;
run;
Obviously it gives me a warning because I used the same variable "a" (I can't rename it!).
I've to save a huge amount of data and not so much physical space and I should construct like 120 field (a0-a6,b0-b6 etc) that are the same variables just with fixed weight (wgt0-wgt5).
I want to store a dataset with 20 columns (a,b,c..) and 6 weight (wgt0-wgt5) and, on demand, processing a "summary" without an intermediate datastep that oblige me to create 120 fields.
Due to the huge amount of data (more or less 55Gb every month) I'd like also not to use proc sql statement:
proc sql;
create table pluto
as select sum(db.a * wgt1) as a0, sum(db.a * wgt1) as a1 , etc.
quit;
There is a "Super proc summary" that can summarize the same field with different weights?
Thanks in advance,
Paolo
I think there are a few options. One is the data step view that data_null_ mentions. Another is just running the proc summary however many times you have weights, and either using ods output with the persist=proc or 20 output datasets and then setting them together.
A third option, though, is to roll your own summarization. This is advantageous in that it only sees the data once - so it's faster. It's disadvantageous in that there's a bit of work involved and it's more complicated.
Here's an example of doing this with sashelp.baseball. In your actual case you'll want to use code to generate the array reference for the variables, and possibly for the weights, if they're not easily creatable using a variable list or similar. This assumes you have no CLASS variable, but it's easy to add that into the key if you do have a single (set of) class variable(s) that you want NWAY combinations of only.
data test;
set sashelp.baseball;
array w[5];
do _i = 1 to dim(w);
w[_i] = rand('Uniform')*100+50;
end;
output;
run;
data want;
set test end=eof;
i = .;
length varname $32;
sumval = 0 ;
sum=0;
if _n_ eq 1 then do;
declare hash h_summary(suminc:'sumval',keysum:'sum',ordered:'a');;
h_summary.defineKey('i','varname'); *also would use any CLASS variable in the key;
h_summary.defineData('i','varname'); *also would include any CLASS variable in the key;
h_summary.defineDone();
end;
array w[5]; *if weights are not named in easy fashion like this generate this with code;
array vars[*] nHits nHome nRuns; *generate this with code for the real dataset;
do i = 1 to dim(w);
do j = 1 to dim(vars);
varname = vname(vars[j]);
sumval = vars[j]*w[i];
rc = h_summary.ref();
if i=1 then put varname= sumval= vars[j]= w[i]=;
end;
end;
if eof then do;
rc = h_summary.output(dataset:'summary_output');
end;
run;
One other thing to mention though... if you're doing this because you're doing something like jackknife variance estimation or that sort of thing, or anything that uses replicate weights, consider using PROC SURVEYMEANS which can handle replicate weights for you.
You can SCORE your data set using a customized SCORE data set that you can generate
with a data step.
options center=0;
data pippo;
retain a 10 b 1.75 c 5 d 3 e 32;
run;
data score;
if 0 then set pippo;
array v[*] _numeric_;
retain _TYPE_ 'SCORE';
length _name_ $32;
array wt[3] _temporary_ (.5 1 .333);
do i = 1 to dim(v);
call missing(of v[*]);
do j = 1 to dim(wt);
_name_ = catx('_',vname(v[i]),'WGT',j);
v[i] = wt[j];
output;
end;
end;
drop i j;
run;
proc print;[enter image description here][1]
run;
proc score data=pippo score=score;
id a--e;
var a--e;
run;
proc print;
run;
proc means stackods sum;
ods exclude summary;
ods output summary=summary;
run;
proc print;
run;
enter image description here

Matching SAS character variables to a list

So I have a vector of search terms, and my main data set. My goal is to create an indicator for each observation in my main data set where variable1 includes at least one of the search terms. Both the search terms and variable1 are character variables.
Currently, I am trying to use a macro to iterate through the search terms, and for each search term, indicate if it is in the variable1. I do not care which search term triggered the match, I just care that there was a match (hence I only need 1 indicator variable at the end).
I am a novice when it comes to using SAS macros and loops, but have tried searching and piecing together code from some online sites, unfortunately, when I run it, it does nothing, not even give me an error.
I have put the code I am trying to run below.
*for example, I am just testing on one of the SASHELP data sets;
*I take the first five team names to create a search list;
data terms; set sashelp.baseball (obs=5);
search_term = substr(team,1,3);
keep search_term;;
run;
*I will be searching through the baseball data set;
data test; set sashelp.baseball;
run;
%macro search;
%local i name_list next_name;
proc SQL;
select distinct search_term into : name_list separated by ' ' from work.terms;
quit;
%let i=1;
%do %while (%scan(&name_list, &i) ne );
%let next_name = %scan(&name_list, &i);
*I think one of my issues is here. I try to loop through the list, and use the find command to find the next_name and if it is in the variable, then I should get a non-zero value returned;
data test; set test;
indicator = index(team,&next_name);
run;
%let i = %eval(&i + 1);
%end;
%mend;
Thanks
Here's the temporary array solution which is fully data driven.
Store the number of terms in a macro variable to assign the length of arrays
Load terms to search into a temporary array
Loop through for each word and search the terms
Exit loop if you find the term to help speed up the process
/*1*/
proc sql noprint;
select count(*) into :num_search_terms from terms;
quit;
%put &num_search_terms.;
data flagged;
*declare array;
array _search(&num_search_terms.) $ _temporary_;
/*2*/
*load array into memory;
if _n_ = 1 then do j=1 to &num_search_terms.;
set terms;
_search(j) = search_term;
end;
set test;
*set flag to 0 for initial start;
flag = 0;
/*3*/
*loop through and craete flag;
do i=1 to &num_search_terms. while(flag=0); /*4*/
if find(team, _search(i), 'it')>0 then flag=1;
end;
drop i j search_term ;
run;
Not sure I totally understand what you are trying to do but if you want to add a new binary variable that indicates if any of the substrings are found just use code like:
data want;
set have;
indicator = index(term,'string1') or index(term,'string2')
... or index(term,'string27') ;
run;
Not sure what a "vector" would be but if you had the list of terms in a dataset you could easily generate that code from the data. And then use %include to add it to your program.
filename code temp;
data _null_;
set term_list end=eof;
file code ;
if _n_ =1 then put 'indicator=' # ;
else put ' or ' #;
put 'index(term,' string :$quote. ')' #;
if eof then put ';' ;
run;
data want;
set have;
%include code / source2;
run;
If you did want to think about creating a macro to generate code like that then the parameters to the macro might be the two input dataset names, the two input variable names and the output variable name.

Mixing macro-DO-loops with data step DO-loops

Some context:
I have a string of digits (not ordered, but with known range 1 - 78) and I want to extract the digits to create specific variables with it, so I have
"64,2,3" => var_64 = 1; var_02 = 2; var_03 = 1; (the rest, like var_01 are all set to missing)
I basically came up with two solutions, one is using a macro DO loop and the other one a data step DO loop. The non-macro solution was to fist initialize all variables var_01 - var_78 (via a macro), then to put them into an array and then to gradually set the values of this array while looping through the string, word-by-word.
I then realized that it would be way easier to use the loop iterator as a macro variable and I came up with this MWE:
%macro fast(w,l);
do p = 1 to &l.;
%do j = 1 %to 9;
if &j. = scan(&w.,p,",") then var_0&j. = 1 ;
%end;
%do j = 10 %to 78;
if &j. = scan(&w.,p,",") then var_&j. = 1 ;
%end;
end;
%mend;
data want;
string = "2,4,64,54,1,4,7";
l = countw(string,",");
%fast(string,l);
run;
It works (no errors, no warnings, expected result) but I am unsure about mixing macro-DO-loops and non-macro-DO-loops. Could this lead to any inconsistencies or should I just stay with the non-macro solution?
Your current code is comparing numbers like 1 to strings like "1".
&j. = scan(&w.,p,",")
It will work as long as the strings can be converted into numbers, but it is not a good practice. It would be better to explicitly convert the strings into numbers.
input(scan(&w.,p,","),32.)
You can do what you want with an array. Use the number generated from the next item in the list as the index into the array.
data want;
string = "2,4,64,54,1,4,7";
array var_ var_01-var_78 ;
do index=1 to countw(string,",");
var_[input(scan(string,index,","),32.)]=1;
end;
drop index;
run;

SAS - repeating a data step to solve for a value

Is it possible to repeat a data step a number of times (like you might in a %do-%while loop) where the number of repetitions depends on the result of the data step?
I have a data set with numeric variables A. I calculate a new variable result = min(1, A). I would like the average value of result to equal a target and I can get there by scaling variable A by a constant k. That is solve for k where target = average(min(1,A*k)) - where k and target are constants and A is a list.
Here is what I have so far:
filename f0 'C:\Data\numbers.csv';
filename f1 'C:\Data\target.csv';
data myDataSet;
infile f0 dsd dlm=',' missover firstobs=2;
input A;
init_A = A; /* store the initial value of A */
run;
/* read in the target value (1 observation) */
data targets;
infile f1 dsd dlm=',' missover firstobs=2;
input target;
K = 1; * initialise the constant K;
run;
%macro iteration; /* I need to repeat this macro a number of times */
data myDataSet;
retain key 1;
set myDataSet;
set targets point=key;
A = INIT_A * K; /* update the value of A /*
result = min(1, A);
run;
/* calculate average result */
proc sql;
create table estimate as
select avg(result) as estimate0
from myDataSet;
quit;
/* compare estimate0 to target and update K */
data targets;
set targets;
set estimate;
K = K * (target / estimate0);
run;
%mend iteration;
I can get the desired answer by running %iteration a few times, but Ideally I would like to run the iteration until (target - estimate0 < 0.01). Is such a thing possible?
Thanks!
I had a similar problem to this just the other day. The below approach is what I used, you will need to change the loop structure from a for loop to a do while loop (or whatever suits your purposes):
First perform an initial scan of the table to figure out your loop termination conditions and get the number of rows in the table:
data read_once;
set sashelp.class end=eof;
if eof then do;
call symput('number_of_obs', cats(_n_) );
call symput('number_of_times_to_loop', cats(3) );
end;
run;
Make sure results are as expected:
%put &=number_of_obs;
%put &=number_of_times_to_loop;
Loop over the source table again multiple times:
data final;
do loop=1 to &number_of_times_to_loop;
do row=1 to &number_of_obs;
set sashelp.class point=row;
output;
end;
end;
stop; * REQUIRED BECAUSE WE ARE USING POINT=;
run;
Two part answer.
First, it's certainly possible to do what you say. There are some examples of code that works like this available online, if you want a working, useful-code example of iterative macros; for example, David Izrael's seminal Rakinge macro, which performs a rimweighting procedure by iterating over a relatively simple process (proc freqs, basically). This is pretty similar to what you're doing. In the process it looks in the datastep at the various termination criteria, and outputs a macro variable that is the total number of criteria met (as each stratification variable separately needs to meet the termination criterion). It then checks %if that criterion is met, and terminates if so.
The core of this is two things. First, you should have a fixed maximum number of iterations, unless you like infinite loops. That number should be larger than the largest reasonable number you should ever need, often by around a factor of two. Second, you need convergence criteria such that you can terminate the loop if they're met.
For example:
data have;
x=5;
run;
%macro reduce(data=, var=, amount=, target=, iter=20);
data want;
set have;
run;
%let calc=.;
%let _i=0;
%do %until (&calc.=&target. or &_i.=&iter.);
%let _i = %eval(&_i.+1);
data want;
set want;
&var. = &var. - &amount.;
call symputx('calc',&var.);
run;
%end;
%if &calc.=&target. %then %do;
%put &var. reduced to &target. in &_i. iterations.;
%end;
%else %do;
%put &var. not reduced to &target. in &iter. iterations. Try a larger number.;
%end;
%mend reduce;
%reduce(data=have,var=x,amount=1,target=0);
That is a very simple example, but it has all of the same elements. I prefer to use do-until and increment on my own but you can do the opposite also (as %rakinge does). Sadly the macro language doesn't allow for do-by-until like the data step language does. Oh well.
Secondly, you can often do things like this inside a single data step. Even in older versions (9.2 etc.), you can do all of what you ask above in a single data step, though it might look a little clunky. In 9.3+, and particularly 9.4, there are ways to run that proc sql inside the data step and get the result back without waiting for another data step, using RUN_MACRO or DOSUBL and/or the FCMP language. Even something simple, like this:
data have;
initial_a=0.3;
a=0.3;
target=0.5;
output;
initial_a=0.6;
a=0.6;
output;
initial_a=0.8;
a=0.8;
output;
run;
data want;
k=1;
do iter=1 to 20 until (abs(target-estimate0) < 0.001);
do _n_ = 1 to nobs;
if _n_=1 then result_tot=0;
set have nobs=nobs point=_n_;
a=initial_a*k;
result=min(1,a);
result_tot+result;
end;
estimate0 = result_tot/nobs;
k = k * (target/estimate0);
end;
output;
stop;
run;
That does it all in one data step. I'm cheating a bit because I'm writing my own data step iterator, but that's fairly common in this sort of thing, and it is very fast. Macros iterating multiple data steps and proc sql steps will be much slower typically as there is some overhead from each one.

Randomize n unique number

No idea why, but I'm really struggling with this one.
I'm trying to get n unique numbers.
On this example, I want it to be 15 number;
%let maximum_draws = 15;
Whatever I tried (and I'm on this for couple of hours, I get duplicates).
Could someone please explain why?
data test;
array game(&maximum_draws);
game(1) = int(ranuni(0)*15+1);
do i = 2 to &maximum_draws;
rand = int(ranuni(0)*15+1);
do j = 1 to i-1;
if rand eq game(j) then do while (rand eq game(j));
rand = int(ranuni(0)*15+1);
end;
end;
game(i) = rand;
end;
run;
You can do a more efficient test to check whether the number has already been picked, using the not in operator:
data test;
array game(&maximum_draws);
do i = 1 to &maximum_draws;
do while (game(i) = .);
rand = int(ranuni(0)*15+1);
if rand not in game then game(i) = rand;
end;
end;
run;
Another option if you're sure you have a relatively small (ie, not billions or something) is to explicitly create the values and then pick from them.
%let maximum_draws=15;
%let draws=10;
data population;
do game = 1 to &maximum_Draws.;
output;
end;
run;
proc surveyselect data=population out=games n=&draws;
run;
SAS does the work for you this way.