I have a list of metadata objects from my repository. I've fetched all SASLibrary, PhysicalTable, Jobs objects. Now I need to fetch all their details. Can someone please suggest how can I do that? I am new to SAS DI and need to fetch the details using SAS code.
Thanks
ok, assuming you have a dataset (have) which contains those objects, and that the uri is stored in a variable called uri then the following should suffice:
data associations;
keep assoc assocuri name;
length assoc assocuri name $256;
set have;
rc1=1;n1=1;
do while(rc1>0);
/* Walk through all possible associations of this object. */
rc1=metadata_getnasl(uri,n1,assoc);
rc2=1;n2=1;
do while(rc2>0);
/* Walk through all the associations on this machine object. */
rc2=metadata_getnasn(uri,trim(assoc),n2,assocuri);
if (rc2>0) then do;
rc3=metadata_getattr(assocuri,"Name",name);
output;
end;
call missing(name,assocuri);
put arc= rc2=;
n2+1;
end;
n1+1;
end;
run;
proc sort data=associations;
by assoc name;
run;
proc sql;
create table groupassoc as
select assoc, count(*) as cnt
from associations
group by 1;
data attrprop;
keep type name value;
length type $4 name $256 value $32767;
set have;
rc1=1;n1=1;type='Prop';
do while(rc1>0);
rc1=metadata_getnprp(uri,n1,name,value);
if rc1>0 then output;
n1+1;
end;
rc1=1;n1=1;type='Attr';
do while(rc1>0);
rc1=metadata_getnatr(uri,n1,name,value);
if rc1>0 then output;
n1+1;
end;
run;
proc sort data=attrprop;
by type name;
run;
This information can also be obtained using metabrowse in Base SAS.
for example call this macro for metaobjects intereseting to you. The fullList table will contains all your interesting objects with metaId and object type:
options Metaport=portnumber;
options MetaUser="userid";
options Metapass="password";
options MetaServer="serverName";
options metaprotocol=bridge;
data fullList;
length objName $60 objId $17 objType $50;;
delete;
run;
%macro getMeta(objType);
data temp(keep=objType objName objId);
length uri $256 objName $60 objId $17 objType $50;
uri="";n=1;TableName="";
objType="&objType";
do while(metadata_getnobj("omsobj:&objType?#Id ? '.'",n,uri) >= 0);
rc=metadata_getattr(uri,"Name",objName);
rc=metadata_getattr(uri,"Id",objId);
n=n+1;
output;
end;
run;
proc append base=fullList data=temp;
run;
%mend;
%getMeta(Person);
%getMeta(PhysicalTable);
%getMeta(Job);
%getMeta(JFob);
.
.
. if you want .....
Related
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
I have many datasets for each month with the same name, changing just the end with specific month so for instance my datasets that i am calling with this code:
TEMPCAAD.LIFT_&NOME_MODELO._&VERSAO_MODELO._'!! put(cur_month,yymmn6.));
are called "TEMPCAAD.LIFT_MODEL_V1_202021", "TEMPCAAD.LIFT_MODEL_V1_202022" and so on...
I am trying to append all datasets but some of them doesn't exist, so when i run the following code I get the error
Dataset "TEMPCAAD.LIFT_MODEL_V1_202022" does not exist.
%let currentmonth = &anomes_scores;
%let previousyearmonth = &anomes_x12;
data _null_;
length string $1000;
cur_month = input("&previousyearmonth.01",yymmdd8.);
do until (cur_month > input("¤tmonth.01",yymmdd8.));
string = catx(' ',trim(string),'TEMPCAAD.LIFT_&NOME_MODELO._&VERSAO_MODELO._'!! put(cur_month,yymmn6.));
cur_month = intnx('month',cur_month,1,'b');
end;
call symput('mydatasets',trim(string));
%put &mydatasets;
run;
data WORK.LIFTS_U6M;
set &mydatasets.;
run;
How can I append only existing datasets?
Instead of looping on every file to see whether it exist or not, why don't you just extract all the dataset names from dictionary.tables?
libname TEMPCAAD "/home/kermit/TEMPCAAD";
data tempcaad.lift_model_v1_202110 tempcaad.lift_model_v1_202111 tempcaad.lift_model_v1_202112;
id = 1;
output tempcaad.lift_model_v1_202110;
id = 2;
output tempcaad.lift_model_v1_202111;
id = 3;
output tempcaad.lift_model_v1_202112;
run;
%let nome_modelo = MODEL;
%let versao_modelo = V1;
proc sql;
select strip("TEMPCAAD."||memname) into :dataset separated by " "
from dictionary.tables
where libname="TEMPCAAD" and memname like "LIFT_&NOME_MODELO._&VERSAO_MODELO.%";
quit;
data want;
set &dataset.;
run;
You can easily tweak the where statement to only extract the data that you wish to append. Just remember to put double quotes if you specify a macro-variable in it.
I have a work table in SAS and I want to move the last row of the table to 2nd last row. Is it possible doing this programmatically? If so, how?
Thanks in advance
Use the SET option POINT= to read from specific rows based on a serial position.
data have;
do row = 1 to 10;
output;
end;
run;
data want;
do row_index = 1 to row_count-2, row_count, row_count-1;
set have nobs=row_count point=row_index;
output;
end;
STOP;
run;
I think this is what you want
data class;
set sashelp.class nobs=n;
if _N_ = n-1 then delete;
run;
If you don't have an id variable in your dataset, you may create one first. In the following case your dataset is called have:
data temp;
set have;
id + 1;
run;
Then, you may just subtract one from the id variable when it is equal to the max(id) and add one when it is equal to the max(id) minus one. Finally, you order your new dataset by id. This will switch the positions of the two last rows.
proc sql;
create table want as
select
case when id=max(id) then id-1
when id=max(id)-1 then id+1
else id end as id,
*
from temp
order by id;
quit;
If your original dataset already has a variable called id, just replace all id in the code above for the name of a new variable, and it will do what you want.
One more using MODIFY.
data class;
_obs_+1;
set sashelp.class;
run;
data class;
do point=nobs-2;
modify class point=point nobs=nobs;
remove;
output;
end;
stop;
run;
proc print;
run;
Suppose I have these data read into SAS:
I would like to list each unique name and the number of months it appeared in the data above to give a data set like this:
I have looked into PROC FREQ, but I think I need to do this in a DATA step, because I would like to be able to create other variables within the new data set and otherwise be able to manipulate the new data.
Data step:
proc sort data=have;
by name month;
run;
data want;
set have;
by name month;
m=month(lag(month));
if first.id then months=1;
else if month(date)^=m then months+1;
if last.id then output;
keep name months;
run;
Pro Sql:
proc sql;
select distinct name,count(distinct(month(month))) as months from have group by name;
quit;
While it's possible to do this in a data step, you wouldn't; you'd use proc freq or similar. Almost every PROC can give you an output dataset (rather than just print to the screen).
PROC FREQ data=sashelp.class;
tables age/out=age_counts noprint;
run;
Then you can use this output dataset (age_counts) as a SET input to another data step to perform your further calculations.
You can also use proc sql to group the variable and count how many are in that group. It might be faster than proc freq depending on how large your data is.
proc sql noprint;
create table counts as
select AGE, count(*) as AGE_CT from sashelp.class
group by AGE;
quit;
If you want to do it in a data step, you can use a Hash Object to hold the counted values:
data have;
do i=1 to 100;
do V = 'a', 'b', 'c';
output;
end;
end;
run;
data _null_;
set have end=last;
if _n_ = 1 then do;
declare hash cnt();
rc = cnt.definekey('v');
rc = cnt.definedata('v','v_cnt');
rc = cnt.definedone();
call missing(v_cnt);
end;
rc = cnt.find();
if rc then do;
v_cnt = 1;
cnt.add();
end;
else do;
v_cnt = v_cnt + 1;
cnt.replace();
end;
if last then
rc = cnt.output(dataset: "want");
run;
This is very efficient as it is a single loop over the data. The WANT data set contains the key and count values.
I have the following problem:
I want to fill missing values with proc expand be simply taking the value from the next data row.
My data looks like this:
date;index;
29.Jun09;-1693
30.Jun09;-1692
01.Jul09;-1691
02.Jul09;-1690
03.Jul09;-1689
04.Jul09;.
05.Jul09;.
06.Jul09;-1688
07.Jul09;-1687
08.Jul09;-1686
09.Jul09;-1685
10.Jul09;-1684
11.Jul09;.
12.Jul09;.
13.Jul09;-1683
As you can see for some dates the index is missing. I want to achieve the following:
date;index;
29.Jun09;-1693
30.Jun09;-1692
01.Jul09;-1691
02.Jul09;-1690
03.Jul09;-1689
04.Jul09;-1688
05.Jul09;-1688
06.Jul09;-1688
07.Jul09;-1687
08.Jul09;-1686
09.Jul09;-1685
10.Jul09;-1684
11.Jul09;-1683
12.Jul09;-1683
13.Jul09;-1683
As you can see the values for the missing data where taken from the next row (11.Jul09 and 12Jul09 got the value from 13Jul09)
So proc expand seems to be the right approach and i started using this code:
PROC EXPAND DATA=DUMMY
OUT=WORK.DUMMY_TS
FROM = DAY
ALIGN = BEGINNING
METHOD = STEP
OBSERVED = (BEGINNING, BEGINNING);
ID date;
CONVERT index /;
RUN;
QUIT;
This filled the gaps but from the previous row and whatever I set for ALIGN, OBSERVED or even sorting the data descending I do not achieve the behavior I want.
If you know how to make it right it would be great if you could give me a hint. Good papers on proc expand are apprechiated as well.
Thanks for your help and kind regards
Stephan
I don't know about proc expand. But apparently this can be done with a few steps.
Read the dataset and create a new variable that will get the value of n.
data have;
set have;
pos = _n_;
run;
Sort this dataset by this new variable, in descending order.
proc sort data=have;
by descending pos;
run;
Use Lag or retain to fill the missing values from the "next" row (After sorting, the order will be reversed).
data want;
set have (rename=(index=index_old));
retain index;
if not missing(index_old) then index = index_old;
run;
Sort back if needed.
proc sort data=want;
by pos;
run;
I'm no PROC EXPAND expert but this is what I came up with. Create LEADS for the maximum gap run (2) then coalesce them into INDEX.
data index;
infile cards dsd dlm=';';
input date:date11. index;
format date date11.;
cards4;
29.Jun09;-1693
30.Jun09;-1692
01.Jul09;-1691
02.Jul09;-1690
03.Jul09;-1689
04.Jul09;.
05.Jul09;.
06.Jul09;-1688
07.Jul09;-1687
08.Jul09;-1686
09.Jul09;-1685
10.Jul09;-1684
11.Jul09;.
12.Jul09;.
13.Jul09;-1683
;;;;
run;
proc print;
run;
PROC EXPAND DATA=index OUT=index2 method=none;
ID date;
convert index=lead1 / transform=(lead 1);
CONVERT index=lead2 / transform=(lead 2);
RUN;
QUIT;
proc print;
run;
data index3;
set index2;
pocb = coalesce(index,lead1,lead2);
run;
proc print;
run;
Modified to work for any reasonable gap size.
data index;
infile cards dsd dlm=';';
input date:date11. index;
format date date11.;
cards4;
27.Jun09;
28.Jun09;
29.Jun09;-1693
30.Jun09;-1692
01.Jul09;-1691
02.Jul09;-1690
03.Jul09;-1689
04.Jul09;.
05.Jul09;.
06.Jul09;-1688
07.Jul09;-1687
08.Jul09;-1686
09.Jul09;-1685
10.Jul09;-1684
11.Jul09;.
12.Jul09;.
13.Jul09;-1683
14.Jul09;
15.Jul09;
16.Jul09;
17.Jul09;-1694
;;;;
run;
proc print;
run;
/* find the largest gap */
data gapsize(keep=n);
set index;
by index notsorted;
if missing(index) then do;
if first.index then n=0;
n+1;
if last.index then output;
end;
run;
proc summary data=gapsize;
output out=maxgap(drop=_:) max(n)=maxgap;
run;
/* Gen the convert statement for LEADs */
filename FT67F001 temp;
data _null_;
file FT67F001;
set maxgap;
do i = 1 to maxgap;
put 'Convert index=lead' i ' / transform=(lead ' i ');';
end;
stop;
run;
proc expand data=index out=index2 method=none;
id date;
%inc ft67f001;
run;
quit;
data index3;
set index2;
pocb = coalesce(index,of lead:);
drop lead:;
run;
proc print;
run;