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SQL Basics Using Proc SQL

written as a valid SQL CREATE TABLE statement. This feature's output can be used to recreate the described table in SAS or another relational database 



Like Learn to Love SAS® Like

pattern-matching and create variables in PROC SQL; and PROC SQL CREATE TABLE LIKE. INTRODUCTION. SAS provides numerous time and angst-saving techniques to 



SAS Certification Handout #10: Adv. Prog. Ch. 5-8 /************ Ch. 5

proc sql; create table work.temp1 as select * from cert.sales10; quit; /* no output but LOG: Table WORK.TEMP1 created



PROC SQL for DATA Step Die-Hards Christianna S. Williams Yale

PROC SQL which is the SAS implementation of PROC SQL;. CREATE TABLE selvar2 AS ... general feature of lists in SQL – lists of tables



139-2010: Exploring Powerful Features in PROC SQL

Views constructed using aggregate and statistical functions tell the SAS System what rows in a table you want summary values for. Joined-Table Views. Views 





268-29: Introduction to PROC SQL

or create a new table or view all in one step! PROC SQL can be used to retrieve update



131-31: Using Data Set Options in PROC SQL

PROC SQL queries require the SELECT statement to specify the variables to be included in create table only_As_1(label='Scores for A Parameters Only') as.



269-29: DATA Step vs. PROC SQL: Whats a Neophyte to Do?

SAS implemented a version of SQL so as to be able to access relational database tables and create SAS data sets as an outcome of such access.



242-31: SQL Set Operators: So Handy Venn You Need Them

source tables; that is characteristic of an OUTER UNION (as distinguished from a Unlike the DATA step PROC SQL does not create even an empty table in ...



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PROC SQL CREATE TABLE LIKE There are several methods of creating an empty data set PROC SQL CREATE TABLE LIKE is one of the most efficient ones when creating a shell from an existing data set as it automatically uses the metadata from the existing SAS data set



268-29: Introduction to PROC SQL - SAS Support

PROC SQL is a powerful Base SAS 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!



How do I create table in SAS? – Bridgitmendlermusiccom

ProcSQL Create Table Basic syntax: proc sql;create table new_SAS_dataset as /* select * for all columns/variables */ select column_1column_2from some_existing_dataset;quit; Although it says create table it is actually creating a SAS dataset PROC SQL terminates with a quit;statement (not run;) WHERE clause



Performing Queries Using PROC SQL - SAS Support

PROC SQL is the SAS implementation of Structured Query Language (SQL) which is a standardized language that is widely used to retrieve and update data in tables and in views that are based on those tables Performing Queries Using PROC SQLHow PROC SQL Is Unique 5



Sometimes SQL Really is Better: A Beginner's Guide to - SAS

Structured Query Language (SQL) in SAS® provides not only a powerful way to manipulate your data it enables users to perform programming tasks in a clean and concise way that would otherwise require multiple DATA steps SORT procedures and other summary statistical procedures Often SAS users use SQL for only specific tasks with which they are



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create table payment1 as select mssql ID mssql Amount mssql prodid from mssql product; create table payment2 as Select myoracle Transaction myoracle Product myoracle PRODID from myoracle sales; Create table final as select * from payment2 as d1 full joinpayment1 as d2 where d1 prodid = d2 prodid; quit; Figure 7

How do I create table in SAS?

    Tools Create Table SAS The Create SAS Table/View window appears. In the Name field, type the name of the table or view. Use a two-level name in the form libref.table-name if you want to store the table or view permanently. Select Table or View. Table creates a SAS data file; View creates a PROC SQL view. Can you add a SAS dataset to a project?

How do I create a table in SQL?

    In SQL, a table can be created using the CREATE keyword. While creating the table, you need to specify its column names, column data types, and the primary key column. The general syntax for doing so is: CREATE TABLE table_name (. column1 datatype.

How to create variables in Proc SQL?

    Create a New Variable with an IF Statement and CASE Statement. You can also create a new variable on a condition with an IF statement (Data Step) or CASE statement (PROC SQL). This means that the value of your variable depends on other variables. Using these conditional statements gives you more flexibility. Below we provide a simple example.

1 BT007

SQL Basics Using Proc SQL Christopher Zogby, Zogby Enterprises, Inc., Alexandria, VA

Abstract:

SQL is an ANSI standard database query language. Its syntax is simple, and its utility is broad in scope. SAS® provides a SQL programming environment via proc SQL. This presentation will elaborate on SQL's major functions, using proc SQL syntax.

Introduction:

SQL, an acronym for Structured Query Language, is an ANSI (American National Standards Institute) standard database programming/query language.

Although its

syntax is relatively compact and simple, it provides a great deal of utility. Its combination of simplicity, power and usefulness has contributed to its ubiquity. With a cursory knowledge of basic SQL syntax, one is able to create, view, combine and manage data stored in variety of database management systems. The purpose of this paper is to present to the uninitiated SQL user, the proc SQL syntax necessary to perform a wide range of basic querying and data management functions. The examples presented herein will demonstrate how to use proc SQL to view data, create and manage SAS data objects, summarize and combine data, plus enhance query performance.

Proc SQL Procedure Basics:

To start the SQL procedure, you must issue the following code: proc sql; Once the procedure has been started, you may submit one or more SQL statements for immediate processing. A SQL statement is a string of SQL code that ends in a semi-colon. A syntactically correct statement, submitted in full (i.e. ending in a semi- colon) is processed immediately. You do not need to submit 'run;' to execute any SQL statements. Data generated or modified by a SQL statement are immediately available to the very next SQL statement. To end the proc SQL instance, submit the following code. quit; All code examples that follow are written as if an instance of proc SQL already exists. If an instance does not exist, one can be started by submitting, 'proc SQL;'.

Viewing SAS Data:

Generally, the SELECT-

FROM SQL statement, on its own,

will write data from the selected columns in the designated table, to the output window or listing. The basic SELECT-

FROM syntax is listed below.

SELECT column-name <,column name>

FROM table-name;

When you select individual columns from a table, you must comma-delimit your SELECT statement's column name list. The shortcut to select all columns from a table is to write an asterisk, following the SELECT statement.

In the example below, all columns from the table

SASHELP.CLASS will be written to the SAS output

window or listing. Note that proc SQL's print option is being activated by a RESET statement. reset print; select * from sashelp.class; Use a WHERE clause to define a filter to restrict which records are processed by your query. In the example below, only girls' names are displayed. The UPCASE function is used to ensure that both lowercase and uppercase values of 'f' pass through the filter. select name from sashelp.class where upcase(sex)='F'; If you wish to include row numbers in your output, prefix your SELECT-FROM code with the following proc SQL option statement. reset number; If you wish to restrict the number of rows proc SQL processes from any single data source, set the INOBS= option to the desired number of rows. The following option setting limits the number of records read from any given source table to 10. reset inobs=10; To remove any restriction set by the INOBS= option, submit the following code. reset inobs=MAX; The INOBS option is useful for trouble shooting queries that produce many records of ouput.

Beginning TutorialsNESUG 16

2 Describing a SAS Table or View:

Proc SQL's DESCRIBE TABLE statement writes, to the SAS log, structural information on the requested table.

The statement's syntax is listed below.

DESCRIBE TABLE table-name;

Note that the DESCRIBE TABLE statement's output is written as a valid SQL CREATE TABLE statement. This feature's output can be used to recreate the described table in SAS or another relational database system. A word of warning: the recreated table would have 0 observations. A SQL view is a stored query whose instructions are processed when the view is executed. A view contains no actual data, however its execution may lead to the creation of data. Proc SQL's DESCRIBE VIEW statement writes to the SAS log the SQL view's definition in the form of a valid SELECT-FROM statement. This feature allows the user to see how the described view was defined. The statement's syntax is listed below.

DESCRIBE VIEW view-name;

Creating a SAS Table or View:

There are three ways in which you can create a table using proc SQL, all of which use the CREATE TABLE statement. The first method creates a blank table with columns and their assigned data types as they are explicitly defined. This method's syntax, shown below, is the same returned by DESCRIBE TABLE.

CREATE TABLE table-name (column-

specification <, column-specification> ...<, constraint-specification> ...); The code below creates a blank table in the WORK library called CLASS.

CREATE WORK.TABLE CLASS ( name char(8) not null, sex char(1), age num, height num, weight num, constraint sex_MF check(sex in('M','F')) );

The newly created table, WORK.CLASS, has 5 columns. The columns NAME and SEX are character type and have lengths of 8 and 1 byte, respectively. The remaining three columns, AGE, HEIGHT and WEIGHT are numeric type and by default store 8 bytes each. Integrity constraints

have been defined for the columns NAME and SEX. Both methods for defining an integrity constraint, written in

italicized text, have been used. Because of these integrity constraints, no row of data can be inserted if the NAME field is null, or the SEX field contains any value other than 'M' or 'F'. Other integrity constraints have been available since the release of SAS V8, and it's recommended that you explore further this relatively new (to SAS), but highly useful feature. You can create a blank clone of another table by using the

CREATE TABLE statement with the LIKE clause.

CREATE TABLE table-name LIKE

table-name; Finally, you can create a table via a query expression.

CREATE TABLE table-name AS

query-expression ...>; The result of your query expression is written to a SAS table, specified in table-name. In the following example, a table WORK.MALES is created by selecting all columns from SASHELP.CLASS, and only those records where the column, SEX, has the value 'M'. The resulting table is sorted in descending order by weight. In the ORDER BY statement, the keyword DESC, causes the sort to be in descending order for the column(s) after which it immediately follows. By default the ORDER BY statement sorts data in ascending order. create table males as select * from sashelp.class where sex='M' order by weight desc;

SAS SQL views can only be created via a query

expression.

CREATE VIEW view-name AS

query-expression ...>;

Based on the following example, the view,

TALLEST_FEM, when executed, will produce a single row containing the greatest value of HEIGHT for those records whose column SEX = 'F'. Note that we are using the MAX() function to determine what value of HEIGHT is the greatest from among all the rows that have the column SEX = 'F'. Also note that we are storing the result of our summary function into a new column called

MAX_F_HEIGHT.

Beginning TutorialsNESUG 16

3 create view tallest_fem as

select max(height) as max_f_height from sashelp.class where sex='F';

Dropping SAS Tables and Views:

You can use proc SQL to delete or drop tables and views. The syntax for dropping tables and views is listed below.

DROP TABLE table-name <,table-name>

DROP VIEW viewname <,viewname> ...;

The following proc SQL statement deletes the tables

TEMP1 and TEMP2 from the WORK library:

drop table temp1, temp2;

Summarizing Data:

Stratification for data summarization is defined in SQL's GROUP BY statement. Proc SQL can produce a table or listing that contains summary level information for each unique value within a column or combination of values across columns listed in its GROUP BY statement. For instance, the following query lists, as SAS output, totals for the number of boys and girls in the table

SASHELP.CLASS:

select sex, count(*) as count from sashelp.class group by sex order by count desc; Because SEX appears in the GROUP BY statement, the summary function, COUNT(*), produces a total count for each unique value of SEX (in our example, assume the column SEX contains only two possible values: 'M' and 'F'). This query will yield two columns, with two records: one record containing the total number of boys and another with the total number of girls. The most common sex will be listed first, because the ORDER BY statement sorts our results in descending order by the calculated field, COUNT. Generally, only those fields listed in the GROUP BY statement, plus any summarized fields are listed in the SELECT statement. For some SQL (DB2 & Oracle) this is a rule, however SAS's proc SQL does not impose the said restriction. It's recommended that you follow this rule, until you become more familiar with how SQL summarizes data. SQL allows you to filter your summarized results via the HAVING clause. The HAVING clause works in the same

fashion as a SQL WHERE clause except that, instead of restricting which rows are processed, it restricts which

post-summarized data are returned. In the example below, the SASHELP.CLASS table is summarized by SEX and AGE, producing a single record for each age within each sex type that has an average height greater than 60. The resulting records will be written to the table

WORK.HEIGHT_SUM. Note that the HAVING clause

evaluates a summarized value, avg(height), against a constant, 60. The summary function, which returns an average value for height, does so for each combination of values listed in the GROUP BY statement (i.e. SEX and AGE). If, for instance, the average height for girls who are

13 years old is greater than 60, then that record's

summarized height values as listed in the SELECT statement are written to WORK.HEIGHT_SUM. create table height_sum as select sex, age, count(*) as count, avg(height) as avg_height, min(height) as min_height, max(height) as max_height, std(height) as std_height from sashelp.class group by sex, age having avg(height) > 60;

Combining Data:

There are many ways to combine data from two or more data sources. This paper will demonstrate how to control how data sources are combined using various SQL joins. There are two principle types of joins: inner and outer (full, right and left). An inner join produces a result set that contain records from all source tables that share common key column(s) values. The syntax to perform an inner join is listed below.

select a.index, a.field1, b.field2 from one a inner join two b on a.index=b.index;

Notice that between the source table names ONE and TWO, the join type, INNER JOIN, is listed. The join

criterion, which defines which key columns proc SQL will compare, is listed in the ON statement. Also note that the letters 'a' and 'b', that immediately follow the table names in the FROM statement, are used as shorthand table references to distinguish between commonly named fields

that exist on more than one table.

Beginning TutorialsNESUG 16

4 The results set will contain all records from WORK.ONE

and WORK.TWO that have matching key column values stored in the fields INDEX. When proc SQL finds a match between INDEX from WORK.ONE and INDEX from WORK.TWO, FIELD1 from WORK.ONE is combined on

the same result set record with FIELD2 from WORK.TWO.

An outer join writes as output, in addition to those records that match on key columns, records that do not have key column(s) matches. A full outer join returns all matching records, plus all records from all source tables that do not have key column(s) matches. A left outer join, will return

all records from the table on the left hand side of the join type definition, and only those matching records from the

table immediately to the right of the join type definition. A right outer join returns matching records from the table on the left hand side of the join type definition, and all records

from the table immediately to the right of the join type definition. In the sample SQL code below, we perform a left join between WORK.MASTER_LIST and WORK.DEATH_LIST

on common values of social security number (SSN). SSN, LAST_PAY and LAST_PAY_DT for all rows of WORK.MASTER_LIST and DEATH_DT from any matching records on WORK.DEATH_LIST are returned.

select a.ssn, a.last_pay, a.last_pay_dt, b.death_dt from master_list a left join death_list b on a.ssn = b.ssn;

Creating/Dropping Indexes:

An index is an object associated with a specific table that stores information on where in the said table the values of the indexed column or columns are stored. An index acts as a virtual sort, without affecting the physical order of

data within its associated table. An index can greatly

improve query performance, however its efficacy can vary due to a number of factors. Improving query performance is a complex subject matter, and is beyond the scope of

this paper. I encourage the user to explore further how to improve query performance using indexes.

You can create multiple simple (single column) and composite indexes (two or more columns) for a given table. The syntax to create an index is listed below.

CREATE INDEX indexname ON

table-name (column <,column> ...); The optional UNIQUE keyword applies a constraint on the

table, preventing any indexed columns from having duplicate values. You can not create a unique index on a column or columns that contain duplicate values.

The code below creates a simple index on the column SEX, and a unique composite index SEX_NAME on the columns SEX and NAME on the table SASHELP.CLASS.

create index sex on sashelp.class; create unique index sex_name on sashelp.class(sex, name);

To drop an index, use the following SQL syntax.

DROP INDEX indexname <,indexname> ...

FROM table-name;

The code below drops the composite index SEX_NAME from SASHELP.CLASS. drop index sex_name from sashelp.class;

Conclusions:

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