PaPER 191-27
Introduction to PROC sql®
Steve First, David Beam
Systems Seminar Consultants, Inc., Madison, WI
ABSTRACT
PROC SQL is a powerful Base SAS7 Procedure that combines the functionality of DATA and PROC steps into a single step.
PROC SQL can sort, summarize, subset, join (merge), and concatenate datasets, create new variables, and print the results or create a new table or view all in one step!
PROC SQL can be used to retrieve, update, and report on information from SAS data sets or other database products. This paper will concentrate on SQL's syntax and how to access information from existing SAS data sets. Some of the topics covered in this brief introduction include:
Write SQL code using various styles of the SELECT statement.
Dynamically create new variables on the SELECT statement.
Use CASE/WHEN clauses for conditionally processing the data.
Joining data from two or more data sets (like a MERGE!).
Concatenating query results together.
Why Learn PROC SQL?
PROC SQL can not only retrieve information without having to learn SAS syntax, but it can often do this with fewer and shorter statements than traditional SAS code. Additionally, SQL often uses fewer resources than conventional DATA and PROC steps. Further, the knowledge learned is transferable to other SQL packages.
An Example of PROC SQL Syntax
Every PROC SQL query must have at least one SELECT statement. The purpose of the SELECT statement is to name the columns that will appear on the report and the order in which they will appear (similar to a VAR statement on PROC PRINT). The FROM clause names the data set from which the information will be extracted from (similar to the SET statement). One advantage nof SQL is that new variables can be dynamically created on the SELECT statement, which is a feature we do not normally associate with a SAS Procedure:
PROC SQL;
SELECT STATE, SALES,
(SALES * .05) AS TAX
FROM USSALES;
QUIT;
(no output shown for this code)
The SELECT Statement Syntax
The purpose of the SELECT statement is to describe how the report will look. It consists of the SELECT clause and several sub-clauses. The sub-clauses name the input dataset, select rows meeting certain conditions (subsetting), group (or aggregate) the data, and order (or sort) the data:
PROC SQL options;
SELECT column(s)
FROM table-name | view-name
WHERE expression
GROUP BY column(s)
HAVING expression
ORDER BY column(s);
QUIT;
A Simple PROC SQL
An asterisk on the SELECT statement will select all columns from the data set. By default a row will wrap when there is too much information to fit across the page. Column headings will be separated from the data with a line and no observation number will appear:
PROC SQL;
SELECT *
FROM USSALES;
QUIT;
(see output #1 for results)
Limiting Information on the SELECT
To specify that only certain variables should appear on the report, the variables are listed and separated on the SELECT statement. The SELECT statement does NOT limit the number of variables read. The NUMBER option will print a column on the report labeled 'ROW' which contains the observation number:
PROC SQL NUMBER;
SELECT STATE, SALES
FROM USSALES;
QUIT;
(see output #2 for results)
Creating New Variables
Variables can be dynamically created in PROC SQL. Dynamically created variables can be given a variable name, label, or neither. If a dynamically created variable is not given a name or a label, it will appear on the report as a column with no column heading. Any of the DATA step functions can be used in an expression to create a new variable except LAG, DIF, and SOUND. Notice the commas separating the columns:
PROC SQL;
SELECT SUBSTR(STORENO,1,3) LABEL='REGION',
SALES, (SALES * .05) AS TAX,
(SALES * .05) * .01
FROM USSALES;
QUIT;
(see output #3 for results)
The CALCULATED Option on the SELECT
Starting with Version 6.07, the CALCULATED component refers to a previously calculated variable so recalculation is not necessary. The CALCULATED component must refer to a variable created within the same SELECT statement:
PROC SQL;
SELECT STATE, (SALES * .05) AS TAX,
(SALES * .05) * .01 AS REBATE
FROM USSALES;
- or -
SELECT STATE, (SALES * .05) AS TAX,
CALCULATED TAX * .01 AS REBATE
FROM USSALES;
QUIT;
(see output #4 for results)
USING LABELs and FORMATs
SAS-defined or user-defined formats can be used to improve the appearance of the body of a report. LABELs give the ability to define longer column headings:
TITLE 'REPORT OF THE U.S. SALES';
FOOTNOTE 'PREPARED BY THE MARKETING DEPT.';
PROC SQL;
SELECT STATE, SALES
FORMAT=DOLLAR10.2
LABEL='AMOUNT OF SALES',
(SALES * .05) AS TAX
FORMAT=DOLLAR7.2
LABEL='5% TAX'
FROM USSALES;
QUIT;
(see output #5 for results)
The CASE Expression on the SELECT
The CASE Expression allows conditional processing within PROC SQL:
PROC SQL;
SELECT STATE,
CASE
WHEN SALES<=10000 THEN 'LOW'
WHEN SALES<=15000 THEN 'AVG'
WHEN SALES<=20000 THEN 'HIGH'
ELSE 'VERY HIGH'
END AS SALESCAT
FROM USSALES;
QUIT;
(see results #6 for results)
The END is required when using the CASE. Coding the WHEN in descending order of probability will improve efficiency because SAS will stop checking the CASE conditions as soon as it finds the first true value.
Another CASE
The CASE statement has much of the same functionality as an IF statement. Here is yet another variation on the CASE expression:
PROC SQL;
SELECT STATE,
CASE
WHEN SALES > 20000 AND STORENO
IN ('33281','31983') THEN 'CHECKIT'
ELSE 'OKAY'
END AS SALESCAT
FROM USSALES;
QUIT;
(see output #7 for results)
Additional SELECT Statement Clauses
The GROUP BY clause can be used to summarize or aggregate data. Summary functions (also referred to as aggregate functions) are used on the SELECT statement for each of the analysis variables:
PROC SQL;
SELECT STATE, SUM(SALES) AS TOTSALES
FROM USSALES
GROUP BY STATE;
QUIT;
(see output #8 for results)
Other summary functions available are the AVG/MEAN, COUNT/FREQ/N, MAX, MIN, NMISS, STD, SUM, and VAR.
This capability Is similar to PROC SUMMARY with a CLASS statement.
Remerging
Remerging occurs when a summary function is used without a GROUP BY. The result is a grand total shown on every line:
PROC SQL;
SELECT STATE, SUM(SALES) AS TOTSALES
FROM USSALES;
QUIT;
(see output #9 for results)
Remerging for Totals
Sometimes remerging is good, as in the case when the SELECT statement does not contain any other variables:
PROC SQL;
SELECT SUM(SALES) AS TOTSALES
FROM USSALES;
QUIT;
(see output #10 for results)
Calculating Percentage
Remerging can also be used to calculate percentages:
PROC SQL;
SELECT STATE, SALES,
(SALES/SUM(SALES)) AS PCTSALES
FORMAT=PERCENT7.2
FROM USSALES;
QUIT;
(see output #11 for results)
Check your output carefully when the remerging note appears in your log to determine if the results are what you expect.
Sorting the Data in PROC SQL
The ORDER BY clause will return the data in sorted order: Much like PROC SORT, if the data is already in sorted order, PROC SQL will print a message in the LOG stating the sorting utility was not used. When sorting on an existing column, PROC SQL and PROC SORT are nearly comparable in terms of efficiency. SQL may be more efficient when you need to sort on a dynamically created variable:
PROC SQL;
SELECT STATE, SALES
FROM USSALES
ORDER BY STATE, SALES DESC;
QUIT;
(see output #12 for results)
Sort on new column
On the ORDER BY or GROUP BY clauses, columns can be referred to by their name or by their position on the SELECT cause. The option 'ASC' (ascending) on the ORDER BY clause is the default, it does not need to be specified.
PROC SQL;
SELECT SUBSTR(STORENO,1,3)
LABEL='REGION',
(SALES * .05) AS TAX
FROM USSALES
ORDER BY 1 ASC, TAX DESC;
QUIT;
(see output #13 for results)
Subsetting Using the WHERE
The WHERE statement will process a subset of data rows before they are processed:
PROC SQL;
SELECT *
FROM USSALES
WHERE STATE IN
('OH','IN','IL');
SELECT *
FROM USSALES
WHERE NSTATE IN (10,20,30);
SELECT *
FROM USSALES
WHERE STATE IN
('OH','IN','IL')
AND SALES > 500;
QUIT;
(no output shown for this example)
Incorrect WHERE clause
Be careful of the WHERE clause, it cannot reference a computed variable:
PROC SQL;
SELECT STATE, SALES,
(SALES * .05) AS TAX
FROM USSALES
WHERE STATE IN
('OH','IN','IL')
AND TAX > 10 ;
QUIT;
(see output #14 for results)
WHERE on computed column
To use computed variables on the WHERE clause they must be recomputed:
PROC SQL;
SELECT STATE, SALES,
(SALES * .05) AS TAX
FROM USSALES
WHERE STATE IN
('OH','IL','IN')
AND (SALES * .05) > 10;
QUIT;
(see output #15 for results)
Selection on GROUP column
The WHERE clause cannot be used with the GROUP BY:
PROC SQL;
SELECT STATE, STORE,
SUM(SALES) AS TOTSALES
FROM USSALES
GROUP BY STATE, STORE
WHERE TOTSALES > 500;
QUIT;
(see output #16 for results)
Use HAVING clause
In order to subset data when grouping is in effect, the HAVING clause must be used:
PROC SQL;
SELECT STATE, STORENO,
SUM(SALES) AS TOTSALES
FROM USSALES
GROUP BY STATE, STORENO
HAVING SUM(SALES) > 500;
QUIT;
(see output #17 for results)
HAVING without a computed column
The HAVING clause is needed even if it is not referring to a computed variable:
PROC SQL;
SELECT STATE,
SUM(SALES) AS TOTSALES
FROM USSALES
GROUP BY STATE
HAVING STATE IN ('IL','WI');
QUIT;
(see output #18 for results)
Creating new tables or views
The CREATE statement provides the ability to create a new data set as output in lieu of a report (which is what happens when a SELECT is present without a CREATE statement). The CREATE statement can either build a TABLE (a traditional SAS dataset, like what is built on a SAS DATA statement) or a VIEW (not covered in this paper):
PROC SQL;
CREATE TABLE TESTA AS
SELECT STATE, SALES
FROM USSALES
WHERE STATE IN ('IL','OH');
SELECT * FROM TESTA;
QUIT;
(see output #19 for results)
The name given on the create statement can either be temporary or permanent. Only one table or view can be created by a CREATE statement. The second SELECT statement (without a CREATE) is used to generate the report.
Joining Datasets Using Proc SQL
A join is used to combine information from multiple files. One advantage of using PROC SQL to join files is that it does not require sorting the datasets prior to joining as is required with a DATA step merge.
A Cartesian Join combines all rows from one file with all rows from another file. This type of join is difficult to perform using traditional SAS code.
PROC SQL;
SELECT *
FROM JANSALES, FEBSALES;
QUIT;
(see output #20 for results)
Inner Join
A Conventional or Inner Join combines datasets only if an observation is in both datasets. This type of join is similar to a DATA step merge using the IN Data Set Option and IF logic requiring that the observation is on both data sets (IF ONA AND ONB).
PROC SQL;
SELECT U.STORENO, U.STATE,
F.SALES AS FEBSALES
FROM USSALES U, FEBSALES F
WHERE U.STORENO=F.STORENO;
QUIT;
(see output #21 for results)
Joining three or more tables
An Associative Join combines information from three or more tables. Performing this operation using traditional SAS code would require several PROC SORTs and several DATA step merges. The same result can be achieved with one PROC SQL:
PROC SQL;
SELECT B.FNAME, B.LNAME, CLAIMS,
E.STORENO, STATE
FROM BENEFITS B, EMPLOYEE E,
FEBSALES F
WHERE B.FNAME=E.FNAME AND
B.LNAME=E.LNAME AND
E.STORENO=F.STORENO AND
CLAIMS > 1000;
QUIT;
(see output #22 for dataset list and results)
CONCATENATING QUERY RESULTS
Query results can be concatenated with the UNION operator.
The UNION operator keeps only unique observations. To keep all observations, the UNION ALL operator can be used. Traditional SAS syntax would require the creation of multiple tables and then either a SET concatenation or a PROC APPEND. Again, the results can be achieved with one PROC SQL:
PROC SQL;
CREATE TABLE YTDSALES AS
SELECT TRANCODE, STORENO, SALES
FROM JANSALES
UNION
SELECT TRANCODE, STORENO,
SALES * .99
FROM FEBSALES;
QUIT;
(no output shown for this example)
CHANGES IN VERSION 8
1. Some PROC SQL views are now updateable. The view must be based on a single DBMS table or SAS data file and must not contain a join, an ORDER BY clause, or a subquery.
2. Whenever possible, PROC SQL passes joins to the DBMS rather than doing the joins itself. This enhances performance.
3. You can now store DBMS connection information in a view with the USING LIBNAME clause.
4. A new option, DQUOTE=ANSI, enables you to non-SAS names in PROC-SQL.
5. A PROC SQL query can now reference up to 32 views or tables. PROC SQL can perform joins on up to 32 tables.
6. PROC SQL can now create and update tables that contain integrity constraints.
In Summary
PROC SQL is a powerful data analysis tool. It can perform many of the same operations as found in traditional SAS code, but can often be more efficient because of its dense language structure.
PROC SQL can be an effective tool for joining data, particularly when doing associative, or three-way joins. For more information regarding SQL joins, reference the papers noted in the bibliography.
Trademark Notice
SAS and PROC SQL are registered trademarks of the SAS Institute Inc., Cary, NC, USA and other countries.
Useful Publications
SAS Institute Inc., Getting Started with the SQL Procedure, Version 6, First Edition
SAS Institute Inc., SAS7 Guide to the SQL Procedure: Usage and Reference, Version 6, First Edition
Kolbe Ritzow, Kim, "Joining Data with SQL", Proceedings of the 6th Annual MidWest SAS7 Users Group Conference
Contact Information
Any questions or comments regarding the paper may be directed to:
Katie M Ronk
Steve First
Systems Seminar Consultant, Inc.
2997 Yarmouth Greenway Drive
Madison, WI 53711
Phone: (608) 278-9964
Fax: (608) 278-0065
Email: train@sys-seminar.com
Output #1 (partial):
STATE SALES STORENO
COMMENT
STORENAM
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
WI 10103.23 32331
SALES WERE SLOW BECAUSE OF COMPETITORS SALE
RON'S VALUE RITE STORE
WI 9103.23 32320
SALES SLOWER THAN NORMAL BECAUSE OF BAD WEATHER
PRICED SMART GROCERS
WI 15032.11 32311
AVERAGE SALES ACTIVITY REPORTED
VALUE CITY
Output #2 (partial):
ROW STATE SALES ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑-‑ 1 WI 10103.23 2 WI 9103.23 3 WI 15032.11
Output #3 (partial):
REGION SALES TAX ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ 323 10103.23 505.1615 5.051615 323 9103.23 455.1615 4.551615 323 15032.11 751.6055 7.516055 332 33209.23 1660.462 16.60461
Output #4 (partial):
STATE TAX REBATE ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ WI 505.1615 5.051615 WI 455.1615 4.551615 WI 751.6055 7.516055 MI 1660.462 16.60461
Output #5 (partial):
REPORT OF THE U.S. SALES
AMOUNT OF
STATE SALES 5% TAX
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
WI $10,103.23 $505.16
WI $9,103.23 $455.16
WI $15,032.11 $751.61
MI $33,209.23 1660.46
PREPARED BY THE MARKETING DEPT.
Output #6 (partial):
STATE SALESCAT ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ WI AVG WI LOW WI HIGH MI VERY HIGH
Output #7 (partial):
STATE SALESCAT
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
WI OKAY
WI OKAY
WI OKAY
MI CHECKIT
Output #8:
STATE TOTSALES ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ IL 84976.57 MI 53341.66 WI 34238.57
Output #9 (partial):
STATE TOTSALES
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
WI 172556.8
WI 172556.8
WI 172556.8
MI 172556.8
Output #10:
TOTSALES
‑‑‑‑‑‑‑‑
172556.8
Output #11 (partial):
(log message shown) STATE SALES PCTSALES
________________________
WI 10103.23 5.86%
WI 9103.23 5.28%
WI 15032.11 8.71%
MI 33209.23 19.2%
NOTE: The query requires remerging summary
Statistics back with the original data.
Output #12 (partial):
STATE SALES
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
IL 32083.22
IL 22223.12
IL 20338.12
IL 10332.11
MI 33209.23
Output #13 (partial):
REGION TAX
‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑
312 516.6055
313 1604.161
313 1111.156
319 1016.906
Output #14 (The resulting SAS LOG- partial):
27 PROC SQL;
28 SELECT STATE,SALES, (SALES * .05) AS TAX
29 FROM USSALES
30 WHERE STATE IN ('OH','IN','IL') AND TAX > 10;
ERROR: THE FOLLOWING COLUMNS WERE NOT FOUND IN THE
CONTRIBUTING TABLES: TAX.
NOTE: The SAS System stopped processing this step because
of errors.
Output #15 (partial):
STATE SALES TAX ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ WI 10103.23 505.1615 WI 9103.23 455.1615 WI 15032.11 751.6055 IL 20338.12 1016.906
Output #16 (The resulting SAS LOG- partial):
167 GROUP BY STATE, STORE
168 WHERE TOTSALES > 500;
-----
22
202
ERROR 22-322: Expecting one of the following: (, **, *, /, +, -,
!!, ||, <, <=, <>, =, >, >=, EQ, GE, GT, LE, LT,
NE, ^=, ~=, &, AND, !, OR, |, ',', HAVING, ORDER.
The statement is being ignored.
ERROR 202-322: The option or parameter is not recognized.
Output #17 (partial):
STATE STORENO TOTSALES ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ IL 31212 10332.11 IL 31373 22223.12 IL 31381 32083.22 IL 31983 20338.12 MI 33281 33209.23
Output #18:
STATE TOTSALES ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ IL 84976.57 WI 34238.57
Output #19:
STATE SALES ‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑ IL 20338.12 IL 10332.11 IL 32083.22 IL 22223.12
Output #20(pARTIAL):
STATE SALES STORENO NUMEMP STATE SALES STORENO
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
WI 9103.23 32320 10 IL 30083.22 31381
WI 9103.23 32320 10 IL 30083.22 31381
WI 15032.11 32311 13 IL 30083.22 31381
MI 33209.23 33281 25 IL 30083.22 31381
MI 20132.43 33312 20 IL 30083.22 31381
IL 20338.12 31983 21 IL 30083.22 31381
IL 10332.11 31212 18 IL 30083.22 31381
IL 32083.22 31381 31 IL 30083.22 31381
IL 22223.12 31373 28 IL 30083.22 31381
WI 9103.23 32320 10 IL 26223.12 31373
WI 9103.23 32320 10 IL 26223.12 31373
WI 15032.11 32311 13 IL 26223.12 31373
MI 33209.23 33281 25 IL 26223.12 31373
Output #21 (PARTIAL):
STORENO STATE FEBSALES
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
32320 WI 9103.23
32331 WI 8103.23
32320 WI 10103.23
32311 WI 13032.11
33281 MI 31209.23
33312 MI 15132.43
31983 IL 25338.12
31212 IL 8332.11
Output #22:
EMPLOYEE FEBSALES BENEFITS
OBS FNAME LNAME STORENO OBS STATE SALES STORENO OBS FNAME LNAME CLAIMS
1 ANN BECKER 33281 1 MI 31209.23 33281 1 ANN BECKER 2003
2 CHRIS DOBSON 33281 2 MI 15132.43 33312 2 CHRIS DOBSON 100
3 EARL FISHER 33281 3 IL 25338.12 31983 3 ALLEN PARK 10392
4 ALLEN PARK 31373 4 IL 26223.12 31373 4 BETTY JOHNSON 3832
5 BETTY JOHNSON 31373
6 KAREN ADAMS 31373
FNAME LNAME CLAIMS STORENO STATE
---------------------------------------------
ANN BECKER 2003 33281 MI
ALLEN PARK 10392 31373 IL
BETTY JOHNSON 3832 31373 IL