genericity - phuse wiki papers/2011 presentations/ts11... · 28-nov-12 1 genericity new metadata...

1 28-Nov-12

GENERICITY

New Metadata Concepts Applied to SAS Macro Programming

Wolf-Dieter Batz: New Metadata Concepts

2 28-Nov-12


Preface

What it is and what it is not

This paper presents part of my experiences using SAS Macro technology over years with great pleasure and, occasionally, with some success, at least for customer satisfaction.

Starting with an example from an earlier presentation the question is raised, how the positive correlation between program flexibility and number of parameters can be extinguished.

By introducing the term “Reporting Specific Data Structures” one idea is described that allows to make use from metadata already present in the runtime environment.

This paper is NOT about Programming using the SAS Macro Facility.

3 28-Nov-12

Generic Programming


Concept

%MACRO cr_tbl_4_fct; %GLOBAL fct src tbl otb; %LOCAL i_frq n_frq l_frq i_ctl n_ctl l_ctl; %IF %SCAN(&FCT.,1,'_') eq PRR %THEN %DO; /* start PRR main loop */ %LET n_frq = %SCAN(&FCT.,2,'_'); %LET n_ctl = %SCAN(&FCT.,3,'_'); proc sql noprint; select name into :p_key from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum eq 1 ; select name , name into :l_frq separated by ' ' , :l2frq separated by ' * ' from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum gt 1 and varnum le %EVAL(&N_FRQ. + 1) ; insert into header values("PRR values calculated for &L2FRQ."); select name , name into :l_ctl separated by ' , ' , :l2ctl separated by ' * ' from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum gt %EVAL(&N_FRQ. + 1) and varnum le %EVAL(&N_FRQ. + &N_CTL. + 1) ; insert into footer values("Stratification performed by: &L2CTL."); insert into footer select compbl(put(count(*),8.)||" lines processed from %UPCASE(&DB_USR.).&TBL.") from &SRC..&TBL. ; insert into footer select compbl("Frequency tables based on "||put(count(distinct &P_KEY.),8.)||" distinct values from field &P_KEY.") from &SRC..&TBL. ; create table &SRC..c_frq as select distinct %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; , %END; %SCAN(&L_FRQ.,&I_FRQ.,' ') %END; from &SRC..&TBL. where %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; and %END; %SCAN(&L_FRQ.,&I_FRQ.,' ') is not null %END; ; %LET n_c_frq = &SQLOBS.; insert into footer values("&N_C_FRQ. combinations from &L2FRQ. processed"); quit; data _null_; set &SRC..c_frq; %DO i_frq = 1 %TO &N_FRQ.; call symput("%SCAN(&L_FRQ.,&I_FRQ.,' ')"||'_'||trim(left(put(_N_,4.))),trim(left(%SCAN(&L_FRQ.,&I_FRQ.,' ')))); %END; run; %DO i_c_frq = 1 %TO &N_C_FRQ.; /* start FREQ loop */ proc sql; create view WORK.tbl as select distinct &P_KEY. , %DO i_frq = 1 %TO &N_FRQ.; %LET %SCAN(&L_FRQ.,&I_FRQ.,' ') = %QUOTE(&&%SCAN(&L_FRQ.,&I_FRQ.,' ')_&I_C_FRQ.); case when sum( %SCAN(&L_FRQ.,&I_FRQ.,' ') = "&&%SCAN(&L_FRQ.,&I_FRQ.,' ')" ) > 0 then -1 else 0 end as %SCAN(&L_FRQ.,&I_FRQ.,' ')_rnk , %END; &L_CTL. from &SRC..&TBL. group by &P_KEY. ; quit; proc freq noprint data = WORK.tbl; tables &L2CTL. %DO i_frq = 1 %TO &N_FRQ.; %STR(*) %SCAN(&L_FRQ.,&I_FRQ.,' ')_rnk %END; / cmh1 ; output out = WORK.cmh(keep = _mhrrc1_ l_mhrrc1 u_mhrrc1) cmh1; run; proc freq noprint data = WORK.tbl; tables %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; %STR(*) %END; %SCAN(&L_FRQ.,&I_FRQ.,' ')_rnk %END; / cmh1 ; output out = WORK.cmc(keep = l_mhrrc1 u_mhrrc1) cmh1; run; proc freq noprint data = WORK.tbl; tables %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; %STR(*) %END; %SCAN(&L_FRQ.,&I_FRQ.,' ')_rnk %END; / sparse out = WORK.cnt(keep = count) ; run; proc transpose data = WORK.cnt out = WORK.trp; run; data WORK.res; merge WORK.trp WORK.cmh WORK.cmc(rename=(l_mhrrc1=l_mhrrcx u_mhrrc1=u_mhrrcx)); run; proc sql noprint; create table WORK.out as select %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; , %END; "&&%SCAN(&L_FRQ.,&I_FRQ.,' ')" as %SCAN(&L_FRQ.,&I_FRQ.,' ') %END; , col1 as a label = "cell A" , col3 as b label = "cell B" , col2 as c label = "cell C" , col4 as d label = "cell D" , (a/c)*((c+d)/(a+b)) as cmh_crude label = "PRR crude" , l_mhrrcx as cmhlcrude label = "PRR crude lower CL" , u_mhrrcx as cmhucrude label = "PRR crude upper CL" , _mhrrc1_ as cmh_strat label = "PRR stratified" , l_mhrrc1 as cmhlstrat label = "PRR stratified lower CL" , u_mhrrc1 as cmhustrat label = "PRR stratified upper CL" from WORK.res ; %IF &I_C_FRQ. = 1 %THEN %DO; drop table &SRC..&TBL.%SCAN(&FCT.,1,_); %END; create table &SRC..&TBL.%SCAN(&FCT.,1,_) as %IF &I_C_FRQ. > 1 %THEN %DO; select * from &SRC..&TBL.%SCAN(&FCT.,1,_) union %END; select * from out ; quit; %END; /* end FREQ loop */ proc sql; create table &SRC..&TBL.%SCAN(&FCT.,1,_) as %IF %SUBSTR(&RST.,2,1) ne C %THEN %DO; select * from &SRC..&TBL.%SCAN(&FCT.,1,_) as tbl %IF %SUBSTR(&RST.,1,1) ne R %THEN %DO; right %END; join &SRC..&TBL. as fct on %DO i_frq = 1 %TO &N_FRQ.; %IF &I_FRQ. gt 1 %THEN %DO; and %END; fct.%SCAN(&L_FRQ.,&I_FRQ.,' ') = tbl.%SCAN(&L_FRQ.,&I_FRQ.,' ') %END; %END; %ELSE %DO; select * from &SRC..&TBL.%SCAN(&FCT.,1,_) %END; ; quit; %LET otb = &TBL.; %LET tbl = &TBL.%SCAN(&FCT.,1,_); %END; /* end PRR main loop */ %MEND cr_tbl_4_fct;

Metadata

+

4 28-Nov-12

“A problem well stated is a problem half solved“

Charles Kettering (1876-1958) Founder of the General Motors Research Corporation

Never forget


5 28-Nov-12

Np = f(F)


Flexibility

Num

ber o

f Par

amet

ers

6 28-Nov-12


Intro

When producing reports You might end up with

-  One appropriately sized program per report

-  One somehow macroized program per report type

-  One Macro System for reporting domains

7 28-Nov-12


Start

For example:

8 28-Nov-12

Total subjects treated 2821 ( 100) 2823 ( 100) Start of study medication within 24 hrs after randomization Yes 2751 (97.5) 2775 (98.3) No 66 ( 2.3) 47 ( 1.7) Surgery delayed 59 ( 2.1) 41 ( 1.5) Other 13 ( 0.5) 13 ( 0.5) Missing - ( - ) - ( - ) Missing 4 ( 0.1) 1 ( 0.0) Study medication only from kit allocated Yes 2821 ( 100) 2823 ( 100) Missing - ( - ) - ( - ) Number of subjects who did not receive full loading 26 ( 0.9) 12 ( 0.4) dose Reason: Adverse event 3 ( 0.1) 3 ( 0.1) Technical failure / dosing error 17 ( 0.6) 8 ( 0.3) Missing 6 ( 0.2) 1 ( 0.0) At least 75% of loading dose administered Yes 2808 (99.5) 2819 (99.9) No 8 ( 0.3) 4 ( 0.1) Missing 5 ( 0.2) - ( - ) Number of subjects with maintenance dose 86 ( 3.0) 101 ( 3.6) interruptions longer than 1 hour Number of maintenance dose interruptions 1 79 ( 2.8) 98 ( 3.5) 2 4 ( 0.1) 4 ( 0.1)

This Quest


9 28-Nov-12


Macro System

generated by a single macro system

10 28-Nov-12


System Architecture

Core Modules Perform input

transformation, calculations and

output transformation

User Modules Generate datasets carrying subtables controlled by user-

supplied parms

Service Modules Provide frequently

requested tasks in a standard format with limited parameter set

Info Modules Provide information about datasets and variables for correct

processing

11 28-Nov-12


Program Controlling

Required already a few parameters

12 28-Nov-12


full parameter set – user modules

%TWO_BOBO() – Build super row (=block) from boolean selections nested in boolean selection

dsn input dataset name

row, row2 categorial variable name, 2=list of nested_var#true_value

rev Y/N (output decodes of &ROW in reverse order)

use, use2 select decode from &ROW, 2=decode from &ROW used as nesting context

weight Y/N (multiply percentages for &ROW and &ROW2)

col categorial variable name used for columns

total T/I/B/O/N/TC/IC/BC/OC/NC

head, head2 Y/N (block header, 2=nested variable)

indent, indinc n (number of indent columns and increment for nested variable)

num n (sequence number of output)

stat Y/N (column with statistics names)

space 1/2/3 (blank line before or after output and between nesting levels)

struct, struct2 name of reference dataset used for full decode structure, 2=nested variable

condense var#value (non-distinct variable and true value for &ROW)

misslin2 Y/N (force missing line for nested variable)

13 28-Nov-12


user parameters - common

DSN: Name of input dataset or view. This may be any valid SAS dataset name (one-level or two-level) not accompanied by dataset options or other SAS syntax components.

COL: Name of variable used to construct columns. The variable is checked for number of levels and an appropriate number of columns are generated.

ROW: Name of variable to construct rows, superrows, and subtables. Modules capable of processing more than one variable accept a list here.

HEAD: Optionally specify “N” to suppress output of the header line for the row variable generated from their label. In categorial processing the header is an additional 1st line whereas in continuous processing the header text is written left-hand to the 1st stats line output. Default is “Y”.

STAT: Optionally select “Y” to generate an output column which contains the names of statistics generated. Default is “N”.

INDENT: Optionally select a positive integer to indent the rows generated as one block. Default is “0”.

SPACE: Optionally select spacing mode for one-level subtables: 0=no blank lines; 1=1st output line is blank; 2=last output line is blank. Default is “2”. For two-level subtables: 2=insert additional blank line between upper and lower level output; 3=only last output line is a blank line. Default is “3”.

NUM: Assigns a unique number to the output generated. Only one digit is allowed here.

14 28-Nov-12


Not amused

This appears quite complicated Isn’t there another way

-  To have limited source code

-  With a high level of flexibility

-  And not to drown in parameter flood

Let’s have a closer look…

15 28-Nov-12


Talk to me

When running macro programs You may influence results on several levels

-  Parameter passing (“feed”)

-  Controlling (“feed and prevent”)

-  Communication (“feed, prevent and search”)

16 28-Nov-12


Search

Make your Macro a curious Communicator

Implement a search mechanism that

-  makes it follow a set of rules

-  provides or

-  generates knowledge on metadata in reach

-  is fault-tolerant

17 28-Nov-12


Search

Of course, this should be a Macro because you want to

-  do it once

-  do it generic

-  use it forever

18 28-Nov-12


Metadata

Metadata are all around -  Simple variable lists: “-NUMERIC-”

-  Libref “dictionary”: tables, columns, etc.

-  User defined repositories of any kind

19 28-Nov-12


Report Specific Data Structures

Let’s focus on one One of the frequently neglected or simply overseen

information bits from dictionary.columns is VARNUM.

This may result from historical reasons, since the SAS dataset structure was learned as more or less fixed.

Reordering a dataset’s variables was not supported very well by the SAS System and hence, not used.

Since concepts emerge from programming habits…

20 28-Nov-12



SQL Views Today, since 1990, it is very easy to reorder the “virtual

physical” sequence of variables in a dataset.

The SAS System treats the properties of an SQL view equally to those of an old-fashioned somewhat “clumsy” SAS Dataset.

This is good News!

21 28-Nov-12


Let’s try a small example:


22 28-Nov-12

data testdsn; label a=Variable A in SAS Dataset b=Variable B in SAS Dataset ; a=22; b=190; run; proc sql; create view testsql as select b as a label="Variable B from SAS Dataset" , a as b label="Variable A from SAS Dataset" from testdsn ; select memname , name , label

, varnum from dictionary.columns where memname like 'TEST___' ; quit;



23 28-Nov-12

Member Name Column Name Column Label Column Number in Table

TESTDSN a Variable A in SAS Dataset 1

TESTDSN b Variable B in SAS Dataset 2

TESTSQL a Variable B from SAS Dataset 1

TESTSQL b Variable A from SAS Dataset 2



24 28-Nov-12



Access Layer Obviously, utilizing the select clause in an SQL view adds a high amount of information to the data structure. This is not surprising, in case you

-  are a physicist

-  can count from zero to 1023 using ten fingers

25 28-Nov-12


Information Gain by Ordering

Source: http://courses.geoplanet.ca/ice3m/image/binary_hand_1-7.gif

26 28-Nov-12


Now let’s have a look a real life:


27 28-Nov-12



28 28-Nov-12



29 28-Nov-12


Resulting Output

30 28-Nov-12



%LET n_frq = %SCAN(&FCT.,2,'_'); %LET n_ctl = %SCAN(&FCT.,3,'_');

Howto

31 28-Nov-12



select name into :p_key from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum eq 1 ;

Howto

32 28-Nov-12



select name , name into :l_frq separated by ' ' , :l2frq separated by ' * ' from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum gt 1 and varnum le %EVAL(&N_FRQ. + 1) ;

Howto

33 28-Nov-12



select name , name into :l_ctl separated by ' , ' , :l2ctl separated by ' * ' from dictionary.columns where libname = %UPCASE("&SRC.") and memname = %UPCASE("&TBL.") and varnum gt %EVAL(&N_FRQ. + 1) and varnum le %EVAL(&N_FRQ. + &N_CTL. + 1) ;

Howto

34 28-Nov-12


Questions welcome

35 28-Nov-12


THANK YOU

genericity - phuse wiki papers/2011 presentations/ts11... · 28-nov-12 1 genericity new metadata...

Documents