Monday, June 11, 2012


SQL : An Overview

The components of SQL are:

Data Manipulation Language

Consists of SQL statements for operating on the data (Inserting, Modifying, Deleting and Retrieving Data) in tables which already exist.

Data Definition Language

Consists of SQL statements for defining the schema (Creating, Modifying and Dropping tables, indexes, views etc.)

Data Control Language

Consists of SQL statements for providing and revoking access permissions to users

Tables used:

Ord # Ord Date Cust#
101 02-08-94 002
102 11-08-94 003
103 21-08-94 003
104 28-08-94 002
105 30-08-94 005
Ord # Item # Qty
101 HW1 100
101 HW3 50
101 SW1 150
102 HW2 10
103 HW3 50
104 HW2 25
104 HW3 100
105 SW1 100

Item # Descr Price
HW1 Power Supply 4000
HW2 101- Keyboard 2000
HW3 Mouse 800
SW1 MS-DOS 6.0 5000
SW2 MS-Word 6.0 8000
Cust # CustName City
001 Shah Bombay
002 Srinivasan Madras
003 Gupta Delhi
004 Banerjee Calcutta
005 Apte Bombay

For additional reference, click here.

2 .DML – SELECT, INSERT, UPDATE and DELETE statements.

The SELECT statement

Retrieves rows from one or more tables according to the conditions provided.

General form:

SELECT [ ALL | DISTINCT ] <attribute (comma)list>
FROM <table (comma)list>
[ WHERE <conditional expression>]
[ ORDER BY [DESC] <attribute list>]
[ GROUP BY <attribute (comma)list>]
[ HAVING <conditional expression>]

Query 1:

Some SELECT statements on the Case Example
SELECT * <-----------------* -denotes all attributes in the table
FROM items;


Query 2

SELECT cust#,custname
FROM customers;


Query 3:

FROM ord_items;


Query 4:
SELECT ord# "Order ", orddate "Ordered On" <---- In the result set the column headings will appear as “Order” and “Ordered On” instead of ord# and orddate.
FROM ord_aug;

Query 5:
SELECT item#, descr
FROM items
WHERE price>2000;

Query 6:
SELECT custname
FROM customers
WHERE city<>'Bombay';


Query 7:
SELECT custname
FROM customers


Query 8:
FROM ord_aug
WHERE orddate > '15-AUG-94'; <-----------

Illustrates the use of 'date' fields. In SQL, a separate datatype (eg: date, datetime etc.) is available to store data of type date.

Query 9:

FROM ord_items
WHERE qty BETWEEN 100 AND 200;


Query 10:
SELECT custname
FROM customers
WHERE city IN ('Bombay', 'Madras'); <-------

The conditional expression evaluates to TRUE for those records for which the value of city field is in the list ('Bombay, 'Madras')

Query 11:
SELECT custname
FROM customers
WHERE custname LIKE 'S%' ; <------------

LIKE 'S%' - 'S' followed by zero or more characters

Query 12:
FROM ord_items
WHERE qty>100 AND item# LIKE 'SW%';


Query 13:

SELECT custname
FROM customers
WHERE city='Bombay' OR city='Madras';


Query 14:
FROM customers
WHERE city='Bombay'
ORDER BY custname; <--------------------

The records in the result set are displayed in the ascending order of custname

Query 15:
FROM ord_items
ORDER BY item#, qty DESC; <-------------

Displays the result set in the ascending order of item#. If there are more than one records with the same item# , they will be displayed in the descending order of qty


Query 16:

SELECT descr, price
FROM items
ORDER BY 2; <----------------------------

ORDER BY the 2nd attribute (price) in the attribute list of the SELECT clause

Query 17:
SELECT ord#, ord_aug.cust#, custname <----------------
FROM ord_aug, customers
WHERE city='Delhi'
AND ord_aug.cust# = customers.cust#; <----------------

SELECT statement implementing JOIN operation.

JOIN condition

Query 18:

SELECT ord#, customers.cust#, city
FROM ord_aug, customers
WHERE ord_aug.cust# = customers.cust#;

Query 19:
SELECT ord#, customers.cust#, city
FROM ord_aug, customers
WHERE ord_aug.cust# = customers.cust# (+); <----------

(+) indicates outer join. Here it is a right outer join as indicated by the (+) after the right side field.


Nested SELECT statements

SQL allows nesting of SELECT statements. In a nested SELECT statement, the inner SELECT is evaluated first and is replaced by its result to evaluate the outer SELECT statement.

Query 20:
SELECT item#, descr, price <----------------------------------------
FROM items
WHERE price > (SELECT AVG(price) FROM items); <------
Outer SELECT statement

Inner SELECT statement

Query 21:
SELECT cust#, custname <-------------------------
FROM customers
WHERE city = ( SELECT city FROM customers
WHERE custname='Shah');
Here the outer SELECT is evaluated as
SELECT cust#, custname
FROM customers


Arithmetic Expressions
( )

Arithmetic functions are allowed in SELECT and WHERE clauses.

Query 22:
SELECT descr, price, price*0.1 "discount"
FROM items
WHERE price >= 4000


Query 23:
SELECT descr
FROM items, ord_items
WHERE price*qty > 250000
and items.item# = ord_items.item#;


Numeric Functions
Query 24:
SELECT qty, ROUND(qty/2,0) "qty supplied"
FROM ord_items
WHERE item#='HW2';


Query 25:
SELECT qty, TRUNC(qty/2,0) "qty supplied"
FROM ord_items
WHERE item#='HW2';


Examples of Numeric Functions
'm' indicates the number of digits after decimal points in the result.

Date Arithemetic
Date + No. of days
Date - No. of days
Date – Date

Query 26:

SELECT ord#, orddate+15 "Supply by"
FROM ord_aug;

Date Functions
MONTHS_BETWEEN(date1, date2)
ADD_MONTHS(date, no. of months)
Returns system date.

Query 27:
SELECT ord#,
FROM ord_aug;


Query 28:
SELECT TO_CHAR(orddate,' DD/MM/YYYY') <-----
FROM ord_aug;
Converts the value of the date field orddate to character string of the format DD/MM/YYYY

DD - day of month (1-31)
D - day of week (1-7)
DAY - name of day
MM - month (01-12)
MONTH - name of month
MON - abbreviated name of month
HH:MI:SS - hours:minutes:seconds
fm - fill mode : suppress blank padding

Character Expressions & Functions
|| - Concatenate operator

Query 29:

SELECT custname || ' - ' || city
FROM customers;


Examples of Character Functions:
SUBSTR(string,start,no. of characters)
Group Functions
Group functions are functions which act on the entire column of selected rows.

Query 30:
SELECT SUM(qty), AVG(qty) <---------------
FROM ord_items
WHERE item#='SW1';
SUM and AVG are examples of Group Functions. They compute the sum/average of qty values of all rows where item#='SW1'.


Examples of Group Functions:
Query 31:
SELECT item#, SUM(qty)
FROM ord_items
GROUP BY item#; <-------------------------

GROUP BY clause used to group rows according to the value of item# in the result. SUM function acts individually on each group of rows.


Query 32:
SELECT item#, SUM(qty)
FROM ord_items
GROUP BY item#
HAVING SUM(qty)>100; <------------------

HAVING clause used to apply the condition to be applied on the grouped rows and display the final result.


Query 33:
SELECT item#, SUM(qty)
FROM ord_items
GROUP BY item#


The INSERT statement
Inserts one or more tuples in a table.
General forms:
To insert a single tuple
INSERT INTO <table-name> [<attribute (comma)list>]
VALUES <value list>;
To insert multiple tuples
INSERT INTO <table-name> [<attribute (comma)list>]
SELECT [ ALL | DISTINCT ] <attribute (comma)list>
FROM <table (comma)list>*
[ WHERE <conditional expression>];
* - list of existing tables

Sample INSERT statements from the Case Example
Query 34: Insert all values for a new row
INSERT INTO customers <-------------------
VALUES (006, 'Krishnan', 'Madras');
Inserts a single row in Customers Table. Attribute list need not be mentioned if values are given for all attributes in the tuple.

Query 35: Insert values of item# & descr columns for a new row
INSERT INTO items (item#, descr) <----------
VALUES ('HW4', '132-DMPrinter');
Attribute list mentioned since values are not given for all attributes in the tuple. Here Price column for the newly inserted tuple takes NULL value.

Query 36
: Inserts a new row which includes a date field
VALUES(106, '31-AUG-94', 005);

Query 37: Inserts a new row with the date field being specified in non DD-MON-YY format
VALUES (106, TO_DATE('310894','DDMMYY'), 005);
The UPDATE statement
Updates values of one or more attributes of one or more tuples in a table.
General form:
UPDATE <table-name>
SET <attribute-1 = value-1[, attribute-2 = value-2,...attribute-n = value-n]
[ WHERE <conditional expression>];
Sample UPDATE statements from the Case Example
Query 38: Changes price of item SW1 to 6000
UPDATE items
SET price = 6000
WHERE item# ='SW1';

Query 39:
 Changes a wrongly entered item# from HW2 to SW2
UPDATE ord_items
SET item# = 'SW2'
WHERE ord#=104 AND item# = 'HW2';
The DELETE statement
Deletes one or more tuples in a table according to given conditions
General form:
DELETE FROM <table-name>
[ WHERE <conditional expression>];
Sample DELETE statements from the Case Example

Query 40:
 Deletes Customer record with Customer Number 004
DELETE FROM customers
WHERE cust# = 004;
DELETE FROM Ord_Items; <---------------------------------------

Deletes all rows in Ord_Items Table. The table remains empty after the DELETE operation.

3. DDL – CREATE, ALTER, and DROP statements.

DDL statements are those which are used to create, modify and drop the definitions or structures of various tables, views, indexes and other elements of the DBMS.
The CREATE TABLE statement
Creates a new table.
General form:
CREATE TABLE <table-name>
(<table-element (comma)list>*);
* - table element may be attribute with its data-type and size or any integrity constraint on attributes.
Some CREATE TABLE statements on the Case Example

CREATE TABLE customers
( cust# NUMBER(6) NOT NULL,
custname CHAR(30) ,
city CHAR(20));

- This query Creates a table CUSTOMERS with 3 fields - cust#, custname and city. Cust# cannot be null

CREATE TABLE ord_sep <--------------

AS SELECT * from ord_aug;
Creates a new table ord_sep, which has the same structure of ord_aug. The data in ord_aug is copied to the new table ord_sep.

- This query Creates table ORD_SEP as a cpy of ORD-AUG. Copies structure as well as data.

CREATE TABLE ord_sep <-------------

AS SELECT * from ord_aug
WHERE 1 = 2;
Creates a new table ord_sep, which has the same structure of ord_aug. No data in ord_aug is copied to the new table since there is no row which satisfies the 'always false' condition 1 = 2.

- This query Creates table ORD_SEP as a copy of ORD_AUG, but does not copy any data as the WHERE clause is never satisfied.
The ALTER TABLE statement
Alters the structure of an existing table.
General form:
ALTER TABLE <table-name>
ADD | MODIFY (<table-element (comma)list);
Examples of ALTER TABLE statement.

ALTER TABLE customers
MODIFY custname CHAR(35); <--------

Modifies the data type/size of an attribute in the table
- This query changes the custname field to a character field of length 35. Used for modifying field lengths and attributes.

ALTER TABLE customers
ADD (phone number(8), <-----------------------
credit_rating char(1));
Adds two new attributes to the Customers table. Here, for existing tuples (if any), the new attribute will take NULL values since no DEFAULT value is mentioned for the attribute.
- This query adds two new fields - phone & credit_rating to the customers table.

The DROP TABLE statement
DROPS an existing table.
General form:
DROP TABLE <table-name>;

DROP TABLE ord_sep;
- The above query drops table ORD_SEP from the database
Creating & Dropping Views
A view is a virtual relation created with attributes from one or more base tables.
SELECT * FROM myview1; at any given time will evaluate the view-defining query in the CREATE VIEW statement and display the result.


ord#, orddate, ord_aug.cust#, custname
FROM ord_aug, customers
WHERE ord_aug.cust# = customers.cust#;
- This query defines a view consisting of ord#, cust#, and custname using a join of ORD_AUG and CUSTOMERS tables.

CREATE VIEW myview2 (ItemNo, Quantity)
AS SELECT item#, qty
FROM ord_items;
- This query defines a view with columns item# and qty from the ORD_ITEMS table, and renames these columns as ItemNo. and Quantity respectively.

AS SELECT item#, descr, price
FROM items
WHERE price < 1000
WITH CHECK OPTION; <-------------------

WITH CHECK OPTION in a CREATE VIEW statement indicates that INSERTs or UPDATEs on the view will be rejected if they violate any integrity constraint implied by the view-defining query.
- This query defines the view as defined. WITH CHECK OPTION ensures that if this view is used for updation, the updated values do not cause the row to fall outside the view.


DROP VIEW myview1; <---- To drop a view

- this query drops the view MYVIEW1

Creating & Dropping Indexes

CREATE INDEX i_city <----------------
ON customers (city);
Creates a new index named i_city. The new index file(table) will have the values of city column of Customers table
CREATE UNIQUE INDEX i_custname <---
ON customers (custname);
Creates an index which allows only unique values for custnames
CREATE INDEX i_city_custname <---------
ON customers (city, custname);
Creates an index based on two fields : city and custname

DROP INDEX i_city; <--------------------

4 DCL – GRANT and REVOKE statements.

DCL statements are those which are used to control access permissions on the tables, indexes, views and other elements of the DBMS.
GRANT ALL <------------------------
ON customers
TO ashraf;
Grants all permissions on the table customers to the user who logs in as 'ashraf'.

GRANT SELECT <------------------
ON customers
TO sunil;
Grants SELECT permission on the table customers to the user 'sunil'. User 'sunil' does not have permission to insert, update, delete or perform any other operation on customers table.
ON customers
TO sunil
WITH GRANT OPTION; <--------------------

Enables user 'sunil' to give SELECT permission on customers table to other users.

REVOKE DELETE <-------------------------
ON customers
FROM ashraf;

5. Recovery and Concurrency
ry DBMS, Recovery and Concurrency are part of the general topic of transaction management. We shall now discuss the fundamental notion of a transaction.

5.1 Transaction

A transaction is a logical unit of work.

Consider the example below:

The following is the procedure to transfer an amount of Rs. 100/- from the account of one customer to another:

Here, please note that the single operation "amount transfer" involves two database updates - updating the record of from_cust and updating the record of to_cust. Between the two updates, the database would be in an inconsistent (incorrect; in this example) state. i.e., if only one of the updates is performed, you cannot look at the database contents and ascertain whether the amount transfer operation has been completed. Hence to guarantee the database consistency, it needs to be ensured that either both updates are performed or none are performed. If any problem; like a system crash, an overflow error or a violation of an integrity constraint occurs after one update and before the next update, then the first update also needs to be undone.

This is the case with all transactions. Any transaction would take the database from one consistent state to another. However, it might not necessarily preserve the consistency of the database at all intermediate points. Hence, it is important to ensure that either a transaction executes in its entirety or is totally cancelled. The set of programs which handles this is the transaction manager in the DBMS. The transaction manager uses COMMIT and ROLLBACK operations for ensuring the atomicity of transactions.

COMMIT - The COMMIT operation indicates successful completion of a transaction which means that the database is in a consistent state and all updates made by the transaction can now be made permanent. If a transaction successfully commits, then the system will guarantee that its updates will be permanently installed in the database even if the system crashes immediately after the COMMIT.

ROLLBACK - The ROLLBACK operation indicates that the transaction has been unsuccessful which means that all updates done by the transaction till then need to be undone to bring the database back to a consistent state. To help to undo the updates that have been done once, a system log or journal is maintained by the transaction manager. The before- and after-images of the updated tuples are recorded in the log.

The basic properties of transactions could be summarised using the ACID mnemonic- ACID: Atomicity, Consistency, Isolation and Durability.

Every transaction is atomic. This means that either all the operations in the transaction have to be performed or none should be performed.

Transactions preserve database consistency. This means that a transaction helps to transform one consistent state of the database into another without necessarily preserving the consistency at all intermediate points.

Transactions are isolated from one another. In other words, the updates to one transaction are concealed from all other transactions until it commits (or rolls back).

Once a transaction commits, its updates survive in the database even if there is a subsequent system crash.
To read more about transactions, click here.

5.2 Recovery from System Failures

System failures (also called soft crashes) are those failures like power outage which affect all transactions in progress, but do not physically damage the database.

During a system failure, the contents of the main memory are lost. Thus the contents of the database buffers which contain the updates of transactions are lost. (Note: Transactions do not directly write on to the database. The updates are written to database buffers and, at regular intervals, transferred to the database.) At restart, the system has to ensure that the ACID properties of transactions are maintained and the database remains in a consistent state. To attain this, the strategy to be followed for recovery at restart is as follows:
Transactions which were in progress at the time of failure have to be undone at the time of restart. This is needed because the precise state of such a transaction which was active at the time of failure is no longer known and hence cannot be successfully completed.
Transactions which had completed prior to the crash but could not get all their updates transferred from the database buffers to the physical database have to redone at the time of restart.

This recovery procedure is carried out with the help of:
An online logfile or journal: The logfile maintains the before- and after-images of the tuples updated during a transaction. This helps in carrying out the UNDO and REDO operations as required. Typical entries made in the logfile are :

Start of Transaction Marker
Transaction Identifier
Record Identifier
Operations Performed
Previous Values of Modified Data (Before-image or Undo Log)
Updated Values of Modified Records (After-image or Redo Log)
Commit / Rollback Transaction Marker

Taking a checkpoint at specific intervals - This involves the following two operations:

Physically writing the contents of the database buffers out to the physical database. Thus during a checkpoint the updates of all transactions, including both active and committed transactions, will be written to the physical database.
Physically writing a special checkpoint record to the physical log. The checkpoint record has a list of all active transactions at the time of taking the checkpoint.

For additional reference, click here.

5.3 Recovery : An Example

At the time of restart, T3 and T5 must be undone and T2 and T4 must be redone.
T1 does not enter the recovery procedure at all since it updates were all written to the database at time tc as part of the checkpoint proces

5.4 Concurrency

Concurrency refers to multiple transactions accessing the same database at the same time. In a system that allows concurrency, there has to be some control mechanism in place to ensure that concurrent transactions do not interfere with each other.

Three typical problems that can occur due to concurrency are explained here.

Lost Update Problem:

(To understand the Lost Update Problem, assume that

there is a record R, with a field, say Amt, having value 1000 before time t1.

Both transactions A & B fetch this value at t1 and t2 respectively.
Transaction A updates the Amt field in R to 800 at time t3.
Transaction B updates the Amt field in R to 1200 at time t4.

Thus after time t4, the Amt value in record R has value 1200. Update by Transaction A at time t3 is over-written by the Transaction B at time t4.)

2. Uncommitted Dependency Problem:
(To understand the above situation, assume that

there is a record R, with a field, say Amt, having value 1000 before time t1.

Transaction B fetches this value and updates it to 800 at time t1.
Transaction A fetches R with Amt field value 800 at time t2.
Transaction B rolls back and its update is undone at time t3. The Amt field takes the initial value 1000 during rollback.

Transaction A continues processing with Amt field value 800 without knowing about B's rollback.)

3. Inconsistent Analysis Problem:

For additional reference, click here.

5.5 Locking

Locking is a solution to problems arising due to concurrency.

Locking of records can be used as a concurrency control technique to prevent the above mentioned problems. A transaction acquires a lock on a record if it does not want the record values to be changed by some other transaction during a period of time. The transaction releases the lock after this time.

Locks are of two types:
shared (S lock)
2. and exclusive (X Lock)

A transaction acquires a shared (read) lock on a record when it wishes to retrieve or fetch the record.
An exclusive (write) lock is acquired on a record when a transaction wishes to update the record. (Here update means INSERT, UPDATE or DELETE.)

The following figure shows the Lock Compatibility matrix:

Normally, locks are implicit. A FETCH request is an implicit request for a shared lock whereas an UPDATE request is an implicit request for an exclusive lock.
Explicit lock requests need to be issued if a different kind of lock is required during an operation. For example, if an X lock is to acquired before a FETCH it has to be explicitly requested for.

6. Query Optimization

6.1 Overview

When compared to other database systems, query optimization is a strength of the relational systems. It can be said so since relational systems by themselves do optimization to a large extent unlike the other systems which leave optimization to the programmer. Automatic optimization done by the relational systems will be much more efficient than manual optimization due to several reasons like :
Uniformity in optimization across programs irrespective of the programmer's expertise in optimizing the programs.
System's ability to make use of the knowledge of internal conditions (eg: volume of data at the time of querying) for optimization. For the same query, such conditions may be different at different times of querying. (In a manual system, this knowledge can be utilised only if the query is re-written each time, which is not practically possible.)
System's ability to evaluate large number of alternatives to find the most efficient query evaluation method.

In this chapter we shall look into the process of automatic query optimization done by the relational systems.

Takes away DELETE permission on customers table from user 'ashraf'.
Drops index i_city

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