Oracle 10g SQL Fundamentals II--Les03

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Manipulating Large Data Sets : 

Manipulating Large Data Sets

Objectives : 

Objectives After completing this lesson, you should be able to do the following: Manipulate data using subqueries Describe the features of multitable inserts Use the following types of multitable inserts Unconditional INSERT Pivoting INSERT Conditional ALL INSERT Conditional FIRST INSERT Merge rows in a table Track the changes to data over a period of time

Using Subqueries to Manipulate Data : 

Using Subqueries to Manipulate Data You can use subqueries in DML statements to: Copy data from one table to another Retrieve data from an inline view Update data in one table based on the values of another table Delete rows from one table based on rows in a another table

Copying Rows from Another Table : 

Copying Rows from Another Table Write your INSERT statement with a subquery. Do not use the VALUES clause. Match the number of columns in the INSERT clause with that in the subquery. INSERT INTO sales_reps(id, name, salary, commission_pct) SELECT employee_id, last_name, salary, commission_pct FROM employees WHERE job_id LIKE '%REP%'; 33 rows created.

Inserting Using a Subquery as a Target : 

Inserting Using a Subquery as a Target INSERT INTO (SELECT employee_id, last_name, email, hire_date, job_id, salary, department_id FROM empl3 WHERE department_id = 50) VALUES (99999, 'Taylor', 'DTAYLOR', TO_DATE('07-JUN-99', 'DD-MON-RR'), 'ST_CLERK', 5000, 50); 1 row created.

Inserting Using a Subquery as a Target : 

Inserting Using a Subquery as a Target Verify the results. SELECT employee_id, last_name, email, hire_date, job_id, salary, department_id FROM employees WHERE department_id = 50; …

Retrieving Data with a Subquery as Source : 

SELECT a.last_name, a.salary, a.department_id, b.salavg FROM employees a, (SELECT department_id, AVG(salary) salavg FROM employees GROUP BY department_id) b WHERE a.department_id = b.department_id AND a.salary > b.salavg; Retrieving Data with a Subquery as Source …

Updating Two Columns with a Subquery : 

UPDATE empl3 SET job_id = (SELECT job_id FROM employees WHERE employee_id = 205), salary = (SELECT salary FROM employees WHERE employee_id = 168) WHERE employee_id = 114; 1 row updated. Updating Two Columns with a Subquery Update the job and salary of employee 114 to match the job of employee 205 and the salary of employee 168.

Updating Rows Based on Another Table : 

UPDATE empl3 SET department_id = (SELECT department_id FROM employees WHERE employee_id = 100) WHERE job_id = (SELECT job_id FROM employees WHERE employee_id = 200); 1 row updated. Updating Rows Based on Another Table Use subqueries in UPDATE statements to update rows in a table based on values from another table.

Deleting Rows Based on Another Table : 

DELETE FROM empl3 WHERE department_id = (SELECT department_id FROM departments WHERE department_name LIKE '%Public%'); 1 row deleted. Deleting Rows Based on Another Table Use subqueries in DELETE statements to remove rows from a table based on values from another table.

Using the WITH CHECK OPTION Keyword on DML Statements : 

Using the WITH CHECK OPTION Keyword on DML Statements A subquery is used to identify the table and columns of the DML statement. The WITH CHECK OPTION keyword prohibits you from changing rows that are not in the subquery. INSERT INTO (SELECT employee_id, last_name, email, hire_date, job_id, salary FROM empl3 WHERE department_id = 50 WITH CHECK OPTION) VALUES (99998, 'Smith', 'JSMITH', TO_DATE('07-JUN-99', 'DD-MON-RR'), 'ST_CLERK', 5000); INSERT INTO * ERROR at line 1: ORA-01402: view WITH CHECK OPTION where-clause violation

Overview of the Explicit Default Feature : 

Overview of the Explicit Default Feature With the explicit default feature, you can use the DEFAULT keyword as a column value where the column default is desired. The addition of this feature is for compliance with the SQL:1999 standard. This allows the user to control where and when the default value should be applied to data. Explicit defaults can be used in INSERT and UPDATE statements.

Using Explicit Default Values : 

Using Explicit Default Values DEFAULT with INSERT: DEFAULT with UPDATE: INSERT INTO deptm3 (department_id, department_name, manager_id) VALUES (300, 'Engineering', DEFAULT); UPDATE deptm3 SET manager_id = DEFAULT WHERE department_id = 10;

Overview of Multitable INSERT Statements : 

Overview of Multitable INSERT Statements INSERT ALL INTO table_a VALUES(…,…,…) INTO table_b VALUES(…,…,…) INTO table_c VALUES(…,…,…) SELECT … FROM sourcetab WHERE …; Table_a Table_b Table_c

Overview of Multitable INSERT Statements : 

Overview of Multitable INSERT Statements The INSERT…SELECT statement can be used to insert rows into multiple tables as part of a single DML statement. Multitable INSERT statements can be used in data warehousing systems to transfer data from one or more operational sources to a set of target tables. They provide significant performance improvement over: Single DML versus multiple INSERT…SELECT statements Single DML versus a procedure to do multiple inserts using IF...THEN syntax

Types of Multitable INSERT Statements : 

Types of Multitable INSERT Statements The different types of multitable INSERT statements are: Unconditional INSERT Conditional ALL INSERT Conditional FIRST INSERT Pivoting INSERT

Multitable INSERT Statements : 

Multitable INSERT Statements Syntax conditional_insert_clause INSERT [ALL] [conditional_insert_clause] [insert_into_clause values_clause] (subquery) [ALL] [FIRST] [WHEN condition THEN] [insert_into_clause values_clause] [ELSE] [insert_into_clause values_clause]

Unconditional INSERT ALL : 

Unconditional INSERT ALL Select the EMPLOYEE_ID, HIRE_DATE, SALARY, and MANAGER_ID values from the EMPLOYEES table for those employees whose EMPLOYEE_ID is greater than 200. Insert these values into the SAL_HISTORY and MGR_HISTORY tables using a multitable INSERT. INSERT ALL INTO sal_history VALUES(EMPID,HIREDATE,SAL) INTO mgr_history VALUES(EMPID,MGR,SAL) SELECT employee_id EMPID, hire_date HIREDATE, salary SAL, manager_id MGR FROM employees WHERE employee_id > 200; 12 rows created.

Conditional INSERT ALL : 

Conditional INSERT ALL Select the EMPLOYEE_ID, HIRE_DATE, SALARY, and MANAGER_ID values from the EMPLOYEES table for those employees whose EMPLOYEE_ID is greater than 200. If the SALARY is greater than $10,000, insert these values into the SAL_HISTORY table using a conditional multitable INSERT statement. If the MANAGER_ID is greater than 200, insert these values into the MGR_HISTORY table using a conditional multitable INSERT statement.

Conditional INSERT ALL : 

Conditional INSERT ALL INSERT ALL WHEN SAL > 10000 THEN INTO sal_history VALUES(EMPID,HIREDATE,SAL) WHEN MGR > 200 THEN INTO mgr_history VALUES(EMPID,MGR,SAL) SELECT employee_id EMPID,hire_date HIREDATE, salary SAL, manager_id MGR FROM employees WHERE employee_id > 200; 4 rows created.

Conditional INSERT FIRST : 

Conditional INSERT FIRST Select the DEPARTMENT_ID, SUM(SALARY), and MAX(HIRE_DATE) from the EMPLOYEES table. If the SUM(SALARY) is greater than $25,000, then insert these values into the SPECIAL_SAL, using a conditional FIRST multitable INSERT. If the first WHEN clause evaluates to true, then the subsequent WHEN clauses for this row should be skipped. For the rows that do not satisfy the first WHEN condition, insert into the HIREDATE_HISTORY_00, HIREDATE_HISTORY_99, or HIREDATE_HISTORY tables, based on the value in the HIRE_DATE column using a conditional multitable INSERT.

Conditional INSERT FIRST : 

Conditional INSERT FIRST INSERT FIRST WHEN SAL > 25000 THEN INTO special_sal VALUES(DEPTID, SAL) WHEN HIREDATE like ('%00%') THEN INTO hiredate_history_00 VALUES(DEPTID,HIREDATE) WHEN HIREDATE like ('%99%') THEN INTO hiredate_history_99 VALUES(DEPTID, HIREDATE) ELSE INTO hiredate_history VALUES(DEPTID, HIREDATE) SELECT department_id DEPTID, SUM(salary) SAL, MAX(hire_date) HIREDATE FROM employees GROUP BY department_id; 12 rows created.

Pivoting INSERT : 

Pivoting INSERT Suppose you receive a set of sales records from a nonrelational database table, SALES_SOURCE_DATA, in the following format: EMPLOYEE_ID, WEEK_ID, SALES_MON, SALES_TUE, SALES_WED, SALES_THUR, SALES_FRI You want to store these records in the SALES_INFO table in a more typical relational format: EMPLOYEE_ID, WEEK, SALES Using a pivoting INSERT, convert the set of sales records from the nonrelational database table to relational format.

Pivoting INSERT : 

Pivoting INSERT INSERT ALL INTO sales_info VALUES (employee_id,week_id,sales_MON) INTO sales_info VALUES (employee_id,week_id,sales_TUE) INTO sales_info VALUES (employee_id,week_id,sales_WED) INTO sales_info VALUES (employee_id,week_id,sales_THUR) INTO sales_info VALUES (employee_id,week_id, sales_FRI) SELECT EMPLOYEE_ID, week_id, sales_MON, sales_TUE, sales_WED, sales_THUR,sales_FRI FROM sales_source_data; 5 rows created.

The MERGE Statement : 

The MERGE Statement Provides the ability to conditionally update or insert data into a database table Performs an UPDATE if the row exists, and an INSERT if it is a new row: Avoids separate updates Increases performance and ease of use Is useful in data warehousing applications

The MERGE Statement Syntax : 

The MERGE Statement Syntax You can conditionally insert or update rows in a table by using the MERGE statement. MERGE INTO table_name table_alias USING (table|view|sub_query) alias ON (join condition) WHEN MATCHED THEN UPDATE SET col1 = col_val1, col2 = col2_val WHEN NOT MATCHED THEN INSERT (column_list) VALUES (column_values);

Merging Rows : 

MERGE INTO empl3 c USING employees e ON (c.employee_id = e.employee_id) WHEN MATCHED THEN UPDATE SET c.first_name = e.first_name, c.last_name = e.last_name, ... c.department_id = e.department_id WHEN NOT MATCHED THEN INSERT VALUES(e.employee_id, e.first_name, e.last_name, e.email, e.phone_number, e.hire_date, e.job_id, e.salary, e.commission_pct, e.manager_id, e.department_id); Merging Rows Insert or update rows in the EMPL3 table to match the EMPLOYEES table.

Merging Rows : 

Merging Rows MERGE INTO empl3 c USING employees e ON (c.employee_id = e.employee_id) WHEN MATCHED THEN UPDATE SET ... WHEN NOT MATCHED THEN INSERT VALUES...; TRUNCATE TABLE empl3; SELECT * FROM empl3; no rows selected SELECT * FROM empl3; 107 rows selected.

Tracking Changes in Data : 

Tracking Changes in Data Versions of retrieved rows SELECT …

Example of the Flashback Version Query : 

Example of the Flashback Version Query SELECT salary FROM employees3 WHERE employee_id = 107; UPDATE employees3 SET salary = salary * 1.30 WHERE employee_id = 107; COMMIT; SELECT salary FROM employees3 VERSIONS BETWEEN SCN MINVALUE AND MAXVALUE WHERE employee_id = 107; 1 2 3

Notes Only : 

Notes Only

The VERSIONS BETWEEN Clause : 

The VERSIONS BETWEEN Clause SELECT versions_starttime "START_DATE", versions_endtime "END_DATE", salary FROM employees VERSIONS BETWEEN SCN MINVALUE AND MAXVALUE WHERE last_name = 'Lorentz';

Summary : 

Summary In this lesson, you should have learned how to: Use DML statements and control transactions Describe the features of multitable inserts Use the following types of multitable inserts Unconditional INSERT Pivoting INSERT Conditional ALL INSERT Conditional FIRST INSERT Merge rows in a table Manipulate data using subqueries Track the changes to data over a period of time

Practice 3: Overview : 

Practice 3: Overview This practice covers the following topics: Performing multitable INSERTs Performing MERGE operations Tracking row versions

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