In this section, we will introduce the five statements that comprise the DML portion of SQL. The information presented in this section should be enough to allow you to start writing DML statements. As is discussed at the end of the section, however, DML can look deceptively simple, so keep in mind while reading the section that there are many more facets to DML than are discussed here.
The SELECT statement is used to retrieve data from a database. The set of data retrieved via a SELECT statement is referred to as a result set. Like a table, a result set is comprised of rows and columns, making it possible to populate a table using the result set of a SELECT statement. The SELECT statement can be summarized as follows:
SELECT <one or more things> FROM <one or more places> WHERE <zero, one, or more conditions apply>
While the SELECT and FROM clauses are required, the WHERE clause is optional (although you will seldom see it omitted). We will therefore begin with a simple example that retrieves three columns from every row of the customer table:
SELECT cust_nbr, name, region_id FROM customer; CUST_NBR NAME REGION_ID ---------- ------------------------------ ---------- 1 Cooper Industries 5 2 Emblazon Corp. 5 3 Ditech Corp. 5 4 Flowtech Inc. 5 5 Gentech Industries 5 6 Spartan Industries 6 7 Wallace Labs 6 8 Zantech Inc. 6 9 Cardinal Technologies 6 10 Flowrite Corp. 6 11 Glaven Technologies 7 12 Johnson Labs 7 13 Kimball Corp. 7 14 Madden Industries 7 15 Turntech Inc. 7 16 Paulson Labs 8 17 Evans Supply Corp. 8 18 Spalding Medical Inc. 8 19 Kendall-Taylor Corp. 8 20 Malden Labs 8 21 Crimson Medical Inc. 9 22 Nichols Industries 9 23 Owens-Baxter Corp. 9 24 Jackson Medical Inc. 9 25 Worcester Technologies 9 26 Alpha Technologies 10 27 Phillips Labs 10 28 Jaztech Corp. 10 29 Madden-Taylor Inc. 10 30 Wallace Industries 10
Since we neglected to impose any conditions via a WHERE clause, the query returns every row from the customer table. If you want to restrict the set of data returned by the query, you can include a WHERE clause with a single condition:
SELECT cust_nbr, name, region_id FROM customer WHERE region_id = 8; CUST_NBR NAME REGION_ID ---------- ------------------------------ ---------- 16 Paulson Labs 8 17 Evans Supply Corp. 8 18 Spalding Medical Inc. 8 19 Kendall-Taylor Corp. 8 20 Malden Labs 8
The result set now includes only those customers residing in the region with a region_id of 8. But what if you want to specify a region by name instead of region_id? You could query the region table for a particular name and then query the customer table using the retrieved region_id. Instead of issuing two different queries, however, you can produce the same outcome using a single query by introducing a join, as in:
SELECT customer.cust_nbr, customer.name, region.name FROM customer INNER JOIN region ON region.region_id = customer.region_id WHERE region.name = 'New England'; CUST_NBR NAME NAME ---------- ------------------------------ ----------- 1 Cooper Industries New England 2 Emblazon Corp. New England 3 Ditech Corp. New England 4 Flowtech Inc. New England 5 Gentech Industries New England
The FROM clause now contains two tables instead of one and includes a join condition that specifies that the customer and region tables are to be joined using the region_id column found in both tables. Joins and join conditions will be explored in detail in Chapter 3.
Since both the customer and region tables contain a column called name, you must specify which table's name column you are interested in. This is done in the previous example by using dot-notation to append the table name in front of each column name. If you would rather not type full table names, you can assign table aliases to each table in the FROM clause and use those aliases instead of the table names in the SELECT and WHERE clauses, as in:
SELECT c.cust_nbr, c.name, r.name FROM customer c INNER JOIN region r ON r.region_id = c.region_id WHERE r.name = 'New England';
In this example, we assigned the alias c to the customer table and the alias r to the region table. Thus, we can use c. and r. instead of customer. and region. in the SELECT and WHERE clauses.
In the examples thus far, the result sets generated by our queries have contained columns from one or more tables. While most elements in your SELECT clauses will typically be simple column references, a SELECT clause may also include:
Literal values, such as numbers (27) or strings (`abc')
Expressions, such as shape.diameter * 3.1415927
Function calls, such as TO_DATE(`01-JAN-2004',`DD-MON-YYYY')
Pseudocolumns, such as ROWID, ROWNUM, or LEVEL
While the first three items in this list are fairly straightforward, the last item merits further discussion. Oracle makes available several phantom columns, known as pseudocolumns, that do not exist in any tables. Rather, they are values visible during query execution that can be helpful in certain situations.
For example, the pseudocolumn ROWID represents the physical location of a row. This information represents the fastest possible access mechanism. It can be useful if you plan to delete or update a row retrieved via a query. However, you should never store ROWID values in the database, nor should you reference them outside of the transaction in which they are retrieved, since a row's ROWID can change in certain situations, and ROWIDs can be reused after a row has been deleted.
The next example demonstrates each of the different element types from the previous list:
SELECT ROWNUM, cust_nbr, 1 multiplier, 'cust # ' || cust_nbr cust_nbr_str, 'hello' greeting, TO_CHAR(last_order_dt, 'DD-MON-YYYY') last_order FROM customer; ROWNUM CUST_NBR MULTIPLIER CUST_NBR_STR GREETING LAST_ORDER ------ -------- ---------- ------------ -------- ----------- 1 1 1 cust # 1 hello 15-JUN-2000 2 2 1 cust # 2 hello 27-JUN-2000 3 3 1 cust # 3 hello 07-JUL-2000 4 4 1 cust # 4 hello 15-JUL-2000 5 5 1 cust # 5 hello 01-JUN-2000 6 6 1 cust # 6 hello 10-JUN-2000 7 7 1 cust # 7 hello 17-JUN-2000 8 8 1 cust # 8 hello 22-JUN-2000 9 9 1 cust # 9 hello 25-JUN-2000 10 10 1 cust # 10 hello 01-JUN-2000 11 11 1 cust # 11 hello 05-JUN-2000 12 12 1 cust # 12 hello 07-JUN-2000 13 13 1 cust # 13 hello 07-JUN-2000 14 14 1 cust # 14 hello 05-JUN-2000 15 15 1 cust # 15 hello 01-JUN-2000 16 16 1 cust # 16 hello 31-MAY-2000 17 17 1 cust # 17 hello 28-MAY-2000 18 18 1 cust # 18 hello 23-MAY-2000 19 19 1 cust # 19 hello 16-MAY-2000 20 20 1 cust # 20 hello 01-JUN-2000 21 21 1 cust # 21 hello 26-MAY-2000 22 22 1 cust # 22 hello 18-MAY-2000 23 23 1 cust # 23 hello 08-MAY-2000 24 24 1 cust # 24 hello 26-APR-2000 25 25 1 cust # 25 hello 01-JUN-2000 26 26 1 cust # 26 hello 21-MAY-2000 27 27 1 cust # 27 hello 08-MAY-2000 28 28 1 cust # 28 hello 23-APR-2000 29 29 1 cust # 29 hello 06-APR-2000 30 30 1 cust # 30 hello 01-JUN-2000
Interestingly, a SELECT clause is not required to reference columns from any of the tables in the FROM clause. For example, the next query's result set is composed entirely of literals:
SELECT 1 num, 'abc' str FROM customer; NUM STR ---------- --- 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc 1 abc
Since there are 30 rows in the customer table, the query's result set includes 30 identical rows of data.
In general, there is no guarantee that the result set generated by your query will be in any particular order. If you want your results to be sorted by one or more columns, you can add an ORDER BY clause after the WHERE clause. The following example sorts the results from the New England query by customer name:
SELECT c.cust_nbr, c.name, r.name FROM customer c INNER JOIN region r ON r.region_id = c.region_id WHERE r.name = 'New England' ORDER BY c.name; CUST_NBR NAME NAME -------- ------------------------------ ----------- 1 Cooper Industries New England 3 Ditech Corp. New England 2 Emblazon Corp. New England 4 Flowtech Inc. New England 5 Gentech Industries New England
You may also designate the sort column(s) by their position in the SELECT clause. To sort the previous query by customer number, which is the first column in the SELECT clause, you could issue the following statement:
SELECT c.cust_nbr, c.name, r.name FROM customer c INNER JOIN region r ON r.region_id = c.region_id WHERE r.name = 'New England' ORDER BY 1; CUST_NBR NAME NAME ---------- ------------------------------ ----------- 1 Cooper Industries New England 2 Emblazon Corp. New England 3 Ditech Corp. New England 4 Flowtech Inc. New England 5 Gentech Industries New England
Specifying sort keys by position will certainly save you some typing, but it can often lead to errors if you later change the order of the columns in your SELECT clause.
In some cases, your result set may contain duplicate data. For example, if you are compiling a list of parts that were included in last month's orders, the same part number would appear multiple times if more than one order included that part. If you want duplicates removed from your result set, you can include the DISTINCT keyword in your SELECT clause, as in:
SELECT DISTINCT li.part_nbr FROM cust_order co INNER JOIN line_item li ON co.order_nbr = li.order_nbr WHERE co.order_dt >= TO_DATE('01-JUL-2001','DD-MON-YYYY') AND co.order_dt < TO_DATE('01-AUG-2001','DD-MON-YYYY');
This query returns the distinct set of parts ordered during July 2001. Without the DISTINCT keyword, the result set would contain one row for every line-item of every order, and the same part would appear multiple times if it was included in multiple orders. When deciding whether to include DISTINCT in your SELECT clause, keep in mind that finding and removing duplicates necessitates a sort operation, which can greatly increase the execution time of your query.
The INSERT statement is the mechanism for loading data into your database. This section will introduce the traditional single-table INSERT statement, as well as the new multitable INSERT ALL statement introduced in Oracle 9i.
With the traditional INSERT statement, data can be inserted into only one table at a time, although the data being loaded into the table can be pulled from one or more additional tables. When inserting data into a table, you do not need to provide values for every column in the table; however, you need to be aware of the columns that require non-NULL values and the ones that do not. Here's the definition of the employee table:
 NULL indicates the absence of a value. The use of NULL is covered in Chapter 2.
describe employee Name Null? Type ----------------------------------------- -------- ------------ EMP_ID NOT NULL NUMBER(5) FNAME VARCHAR2(20) LNAME VARCHAR2(20) DEPT_ID NOT NULL NUMBER(5) MANAGER_EMP_ID NUMBER(5) SALARY NUMBER(5) HIRE_DATE DATE JOB_ID NUMBER(3)
The NOT NULL designation for the emp_id and dept_id columns indicates that values are required for these two columns. Therefore, you must be sure to provide values for at least these two columns in your INSERT statements, as demonstrated by the following:
INSERT INTO employee (emp_id, dept_id) VALUES (101, 20);
Any inserts into employee may optionally include any or all of the remaining six columns, which are described as nullable since they may be left undefined. Thus, you could decide to add the employee's last name to the previous statement:
INSERT INTO employee (emp_id, lname, dept_id) VALUES (101, 'Smith', 20);
The VALUES clause must contain the same number of elements as the column list, and the data types must match the column definitions. In this example, emp_id and dept_id hold numeric values while lname holds character data, so the INSERT statement will execute without error. Oracle always tries to convert data from one type to another automatically, however, so the following statement will also run without error:
INSERT INTO employee (emp_id, lname, dept_id) VALUES ('101', 'Smith', '20');
Sometimes, the data to be inserted needs to be retrieved from one or more tables. Since the SELECT statement generates a result set consisting of rows and columns of data, you can feed the result set from a SELECT statement directly into an INSERT statement, as in:
INSERT INTO employee (emp_id, fname, lname, dept_id, hire_date) SELECT 101, 'Dave', 'Smith', d.dept_id, SYSDATE FROM department d WHERE d.name = 'ACCOUNTING';
In this example, the purpose of the SELECT statement is to retrieve the department ID for the Accounting department. The other four columns in the SELECT clause are either literals (101, 'Dave', 'Smith') or function calls (SYSDATE).
While inserting data into a single table is the norm, there are situations where data from a single source must be inserted either into multiple tables or into the same table multiple times. Such tasks would normally be handled programatically using PL/SQL, but Oracle9i introduced the concept of a multitable insert to allow complex data insertion via a single INSERT statement. For example, let's say that one of Mary Turner's customers wants to set up a recurring order on the last day of each month for the next six months. The following statement adds six rows to the cust_order table using a SELECT statement that returns exactly one row:
INSERT ALL INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr, cust_nbr, emp_id, ord_dt, ord_dt + 7, status) INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr + 1, cust_nbr, emp_id, add_months(ord_dt, 1), add_months(ord_dt, 1) + 7, status) INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr + 2, cust_nbr, emp_id, add_months(ord_dt, 2), add_months(ord_dt, 2) + 7, status) INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr + 3, cust_nbr, emp_id, add_months(ord_dt, 3), add_months(ord_dt, 3) + 7, status) INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr + 4, cust_nbr, emp_id, add_months(ord_dt, 4), add_months(ord_dt, 4) + 7, status) INTO cust_order (order_nbr, cust_nbr, sales_emp_id, order_dt, expected_ship_dt, status) VALUES (ord_nbr + 5, cust_nbr, emp_id, add_months(ord_dt, 5), add_months(ord_dt, 5) + 7, status) SELECT 99990 ord_nbr, c.cust_nbr cust_nbr, e.emp_id emp_id, last_day(SYSDATE) ord_dt, 'PENDING' status FROM customer c CROSS JOIN employee e WHERE e.fname = 'MARY' and e.lname = 'TURNER' and c.name = 'Gentech Industries';
The SELECT statement returns the data necessary for this month's order, and the INSERT statement modifies the order_nbr, order_dt, and expected_ship_dt columns for the next five months' orders. You are not obligated to insert all rows into the same table, nor must your SELECT statement return only one row, making the multitable insert statement quite flexible and powerful. The next example shows how data about a new salesperson can be entered into both the employee and salesperson tables:
INSERT ALL INTO employee (emp_id, fname, lname, dept_id, hire_date) VALUES (eid, fnm, lnm, did, TRUNC(SYSDATE)) INTO salesperson (salesperson_id, name, primary_region_id) VALUES (eid, fnm || ' ' || lnm, rid) SELECT 1001 eid, 'JAMES' fnm, 'GOULD' lnm, d.dept_id did, r.region_id rid FROM department d, region r WHERE d.name = 'SALES' and r.name = 'Southeast US';
So far, you have seen how multiple rows can be inserted into the same table and how the same rows can be inserted into multiple tables. The next, and final, example of multitable inserts demonstrates how a conditional clause can be used to direct each row of data generated by the SELECT statement into zero, one, or many tables:
INSERT FIRST WHEN order_dt < TO_DATE('2001-01-01', 'YYYY-MM-DD') THEN INTO cust_order_2000 (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) VALUES (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) WHEN order_dt < TO_DATE('2002-01-01', 'YYYY-MM-DD') THEN INTO cust_order_2001 (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) VALUES (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) WHEN order_dt < TO_DATE('2003-01-01', 'YYYY-MM-DD') THEN INTO cust_order_2002 (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) VALUES (order_nbr, cust_nbr, sales_emp_id, sale_price, order_dt) SELECT co.order_nbr, co.cust_nbr, co.sales_emp_id, co.sale_price, co.order_dt FROM cust_order co WHERE co.cancelled_dt IS NULL AND co.ship_dt IS NOT NULL;
This statement copies all customer orders prior to January 1, 2003, to one of three tables depending on the value of the order_dt column. The keyword FIRST specifies that once one of the conditions evaluates to TRUE, the statement should skip the remaining conditions and move on to the next row. If you specify ALL instead of FIRST, all conditions will be evaluated, and each row might be inserted into multiple tables if more than one condition evaluates to TRUE.
The DELETE statement facilitates the removal of data from the database. Like the SELECT statement, the DELETE statement contains a WHERE clause that specifies the conditions used to identify rows to be deleted. If you neglect to add a WHERE clause to your DELETE statement, all rows will be deleted from the target table. The following statement will delete all employees with the last name of Hooper from the employee table:
DELETE FROM employee WHERE lname = 'HOOPER';
In some cases, the values needed for one or more of the conditions in your WHERE clause exist in another table. For example, your company may decide to outsource its accounting functions, thereby necessitating the removal of all accounting personnel from the employee table:
DELETE FROM employee WHERE dept_id = (SELECT dept_id FROM department WHERE name = 'ACCOUNTING');
The use of the SELECT statement in this example is known as a subquery and will be studied in detail in Chapter 5.
In certain cases, you may want to restrict the number of rows that are to be deleted from a table. For example, you may want to remove all data from a table, but you want to limit your transactions to no more than 100,000 rows. If the cust_order table contained 527,365 records, you would need to find a way to restrict your DELETE statement to 100,000 rows and then run the statement six times until all the data has been purged. The following example demonstrates how the ROWNUM pseudocolumn may be used in a DELETE statement to achieve the desired effect:
DELETE FROM cust_order WHERE ROWNUM <= 100000; COMMIT;
Modifications to existing data are handled by the UPDATE statement. Like the DELETE statement, the UPDATE statement includes a WHERE clause to specify which rows should be targeted. The following example shows how you might give a 10% raise to everyone making less than $40,000:
UPDATE employee SET salary = salary * 1.1 WHERE salary < 40000;
If you want to modify more than one column in the table, you have two choices: provide a set of column/value pairs separated by commas, or provide a set of columns and a subquery. The following two UPDATE statements modify the inactive_dt and inactive_ind columns in the customer table for any customer who hasn't placed an order in the past year:
UPDATE customer SET inactive_dt = SYSDATE, inactive_ind = 'Y' WHERE last_order_dt < SYSDATE -- 365; UPDATE customer SET (inactive_dt, inactive_ind) = (SELECT SYSDATE, 'Y' FROM dual) WHERE last_order_dt < SYSDATE -- 365;
The subquery in the second example is a bit forced, since it uses a query against the dual table to build a result set containing two literals, but it should give you an idea of how you would use a subquery in an UPDATE statement. In later chapters, you will see far more interesting uses for subqueries.
There are certain situations, especially within Data Warehouse applications, where you may want to either insert a new row into a table or update an existing row depending on whether or not the data already exists in the table. For example, you may receive a nightly feed of parts data that contains both parts that are known to the system along with parts just introduced by your suppliers. If a part number exists in the part table, you will need to update the unit_cost and status columns; otherwise, you will need to insert a new row.
While you could write code that reads each record from the feed, determines whether or not the part number exists in the part table, and issues either an INSERT or UPDATE statement, you could instead issue a single MERGE statement. Assuming that your data feed has been loaded into the part_stg staging table, your MERGE statement would look something like the following:
 MERGE was introduced in Oracle9i.
MERGE INTO part p_dest USING part_stg p_src ON (p_dest.part_nbr = p_src.part_nbr) WHEN MATCHED THEN UPDATE SET p_dest.unit_cost = p_src.unit_cost, p_dest.status = p_src.status WHEN NOT MATCHED THEN INSERT (p_dest.part_nbr, p_dest.name, p_dest.supplier_id, p_dest.status, p_dest.inventory_qty, p_dest.unit_cost, p_dest.resupply_date) VALUES (p_src.part_nbr, p_src.name, p_src.supplier_id, p_src.status, 0, p_src.unit_cost, null);
This statement looks fairly complex, so here is a description of what it is doing:
For each row in the part_stg table, see if the part_nbr column exists in the part table.
If it does, then update the matching row in the part table using data from the part_stg table.
Otherwise, insert a new row into the part table using the data from the part_stg table.