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Database Management Systems

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Database Management System (CS403)
VU
Lecture No. 30
Reading Material
"Database Management Systems", 2nd edition, Raghu Ramakrishnan, Johannes Gehrke,
McGraw-Hill
Overview of Lecture
Data Manipulation Language
Functions in SQL
In the previous lecture we have discussed different operators of SQL, which are used
in different commands. By the end of previous lecture we were discussing ORDER
BY clause, which is basically used to bring the output in ascending or descending
order. In this lecture we will see some examples of this clause.
ORDER BY Clause
The ORDER BY clause allows you to sort the records in your result set. The ORDER
BY clause can only be used in SELECT statements. The ORDER BY clause sorts the
result set based on the columns specified. If the ASC or DESC value is omitted, the
system assumed ascending order. We will now see few examples of this clause
SELECT supplier_city
FROM supplier
WHERE supplier_name = 'IBM'
ORDER BY supplier_city;
This would return all records sorted by the supplier_city field in ascending order.
SELECT supplier_city
FROM supplier
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Database Management System (CS403)
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WHERE supplier_name = 'IBM'
ORDER BY supplier_city DESC;
This would return all records sorted by the supplier_city field in descending order.
Functions in SQL
A function is a special type of command. Infact, functions are one-word command
that return a single value. The value of a function can be determined by input
parameters, as with a function that averages a list of database values. But many
functions do not use any type of input parameter, such as the function that returns the
current system time, CURRENT_TIME. There are normally two types of functions.
First is Built in, which are provided by any specific tool or language. Second is user
defined, which are defined by the user. The SQL supports a number of useful
functions.. In addition, each database vendor maintains a long list of their own
internal functions that are outside of the scope of the SQL standard.
Categories of Functions:
These categories of functions are specific to SQL Server. Depending on the
arguments and the return value, functions are categorized as under:
·
Mathematical (ABS, ROUND, SIN, SQRT)
·
String (LOWER, UPPER, SUBSTRING, LEN)
·
Date (DATEDIFF, DATEPART, GETDATE ())
·
System (USER, DATALENGTH, HOST_NAME)
·
Conversion (CAST, CONVERT)
We will now see an example using above-mentioned functions:
SELECT upper (stName), lower (stFName), stAdres, len(convert(char, stAdres)),
FROM student
In this example student name will be displayed in upper case whereas father name
will be displayed in lower case. The third function is of getting the length of student
address. It has got nesting of functions, first address is converted into character and
then its length will be displayed.
Aggregate Functions
These functions operate on a set of rows and return a single value. If used among
many other expressions in the item list of a SELECT statement, the SELECT must
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have a GROUP BY clause. No GROUP BY clause is required if the aggregate
function is the only value retrieved by the SELECT statement. Following are some of
the aggregate functions:
Function
Usage
AVG(expression)
Computes
average value of a column by the
expression
COUNT(expression)
Counts the rows defined by the expression
COUNT(*)
Counts all rows in the specified table or view
MIN(expression)
Finds the minimum value in a column by the
expression
MAX(expression)
Finds the maximum value in a column by the
expression
SUM(expression)
Computes the sum of column values by the expression
SELECT avg(cgpa) as 'Average CGPA', max(cgpa) as 'Maximum CGPA'
from student
GROUP BY Clause
The GROUP BY clause can be used in a SELECT statement to collect data across
multiple records and group the results by one or more columns. It is added to SQL
because aggregate functions (like SUM) return the aggregate of all column values
every time they are called, and without the GROUP BY function it is impossible to
find the sum for each individual group of column values.
The syntax for the GROUP BY clause is:
SELECT column1, column2, ... column_n, aggregate_function
(expression)
FROM tables
WHERE predicates
GROUP BY column1, column2, ... column_n;
Aggregate function can be a function such as SUM, COUNT, MIN or MAX
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Example using the SUM function
For example, the SUM function can be used to return the name of the department and
the total sales (in the associated department).
SELECT department, SUM (sales) as "Total sales"
FROM order_details
GROUP BY department;
In this example we have listed one column in the SELECT statement that is not
encapsulated in the SUM function, so we have used a GROUP BY clause. The
department field must, therefore, be listed in the GROUP BY section.
Example using the COUNT function
We can also use the COUNT function to return the name of the department and the
number of employees (in the associated department) that make over Rs 25,000 / year.
SELECT department, COUNT (*) as "Number of employees"
FROM employees
WHERE salary > 25000
GROUP BY department;
HAVING Clause
The HAVING clause is used in combination with the GROUP BY clause. It can be
used in a SELECT statement to filter the records that a GROUP BY returns. At times
we want to limit the output based on the corresponding sum (or any other aggregate
functions). For example, we might want to see only the stores with sales over Rs
1,500. Instead of using the WHERE clause in the SQL statement, though, we need to
use the HAVING clause, which is reserved for aggregate functions. The HAVING
clause is typically placed near the end of the SQL statement, and a SQL statement
with the HAVING clause may or may not include the GROUP BY clause. The syntax
for the HAVING clause is:
SELECT column1, column2, ... column_n, aggregate_function
(expression)
FROM tables
WHERE predicates
GROUP BY column1, column2, ... column_n
HAVING condition1 ... condition_n;
Aggregate function can be a function such as SUM, MIN or MAX.
We will now see few examples of HAVING Clause.
Example using the SUM function
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We can use the SUM function to return the name of the department and the total sales
(in the associated department). The HAVING clause will filter the results so that only
departments with sales greater than Rs 1000 will be returned.
SELECT department, SUM (sales) as "Total sales"
FROM order_details
GROUP BY department
HAVING SUM (sales) > 1000;
Example using the COUNT function
For example, you could use the COUNT function to return the name of the
department and the number of employees (in the associated department) that make
over $25,000 / year. The HAVING clause will filter the results so that only
departments with at least 25 employees will be returned.
SELECT department, COUNT (*) as "Number of employees"
FROM employees
WHERE salary > 25000
GROUP BY department
HAVING COUNT (*) > 10;
Accessing Multiple Tables:
Until now we have been accessing data through one table only. But there can be
occasions where we have to access the data from different tables. So depending
upon different requirements data can be accessed from different tables.
Referential integrity constraint plays an important role in gathering data from
multiple tables. Following are the methods of accessing data from different
tables:
Cartesian Product
·  Inner join
·
Outer Join
·
Full outer join
·
Semi Join
·
Natural JoinWe will now discuss them one by one.
Cartesian product:
A Cartesian join gives a Cartesian product. A Cartesian join is when you join every
row of one table to every row of another table. You can also get one by joining every
row of a table to every row of itself. No specific command is used just Select is used
to join two tables. Simply the names of the tables involved are given and Cartesian
product is produced. It produces m x n rows in the resulting table. We will now see
few examples of Cartesian product.
Select * from program, course
Now in this example all the attributes of program and course are selected and the total
number of rows would be number of rows of program x number of rows of course.In
Cartesian product certain columns can be selected, same column name needs to be
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qualified. Similarly it can be applied to more than one table, and even can be applied
on the same table .For Example
SELECT * from Student, class, program
Summary
In today's lecture we have seen certain important functions of SQL, which are more
specific to SQL Server. We studied some mathematical, string and conversion
functions, which are used in SQL Commands. We also studied Aggregate functions,
which are applied on a entire table or a set of rows and return one value. We also
studied Group By clause which is used in conjunction with aggregate functions. In the
end we saw how to extract data from different tables and in that we studied Cartesian
product. We will see rest of the methods in our coming lectures.
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Table of Contents:
  1. Introduction to Databases and Traditional File Processing Systems
  2. Advantages, Cost, Importance, Levels, Users of Database Systems
  3. Database Architecture: Level, Schema, Model, Conceptual or Logical View:
  4. Internal or Physical View of Schema, Data Independence, Funct ions of DBMS
  5. Database Development Process, Tools, Data Flow Diagrams, Types of DFD
  6. Data Flow Diagram, Data Dictionary, Database Design, Data Model
  7. Entity-Relationship Data Model, Classification of entity types, Attributes
  8. Attributes, The Keys
  9. Relationships:Types of Relationships in databases
  10. Dependencies, Enhancements in E-R Data Model. Super-type and Subtypes
  11. Inheritance Is, Super types and Subtypes, Constraints, Completeness Constraint, Disjointness Constraint, Subtype Discriminator
  12. Steps in the Study of system
  13. Conceptual, Logical Database Design, Relationships and Cardinalities in between Entities
  14. Relational Data Model, Mathematical Relations, Database Relations
  15. Database and Math Relations, Degree of a Relation
  16. Mapping Relationships, Binary, Unary Relationship, Data Manipulation Languages, Relational Algebra
  17. The Project Operator
  18. Types of Joins: Theta Join, Equi–Join, Natural Join, Outer Join, Semi Join
  19. Functional Dependency, Inference Rules, Normal Forms
  20. Second, Third Normal Form, Boyce - Codd Normal Form, Higher Normal Forms
  21. Normalization Summary, Example, Physical Database Design
  22. Physical Database Design: DESIGNING FIELDS, CODING AND COMPRESSION TECHNIQUES
  23. Physical Record and De-normalization, Partitioning
  24. Vertical Partitioning, Replication, MS SQL Server
  25. Rules of SQL Format, Data Types in SQL Server
  26. Categories of SQL Commands,
  27. Alter Table Statement
  28. Select Statement, Attribute Allias
  29. Data Manipulation Language
  30. ORDER BY Clause, Functions in SQL, GROUP BY Clause, HAVING Clause, Cartesian Product
  31. Inner Join, Outer Join, Semi Join, Self Join, Subquery,
  32. Application Programs, User Interface, Forms, Tips for User Friendly Interface
  33. Designing Input Form, Arranging Form, Adding Command Buttons
  34. Data Storage Concepts, Physical Storage Media, Memory Hierarchy
  35. File Organizations: Hashing Algorithm, Collision Handling
  36. Hashing, Hash Functions, Hashed Access Characteristics, Mapping functions, Open addressing
  37. Index Classification
  38. Ordered, Dense, Sparse, Multi-Level Indices, Clustered, Non-clustered Indexes
  39. Views, Data Independence, Security, Vertical and Horizontal Subset of a Table
  40. Materialized View, Simple Views, Complex View, Dynamic Views
  41. Updating Multiple Tables, Transaction Management
  42. Transactions and Schedules, Concurrent Execution, Serializability, Lock-Based Concurrency Control, Deadlocks
  43. Incremental Log with Deferred, Immediate Updates, Concurrency Control
  44. Serial Execution, Serializability, Locking, Inconsistent Analysis
  45. Locking Idea, DeadLock Handling, Deadlock Resolution, Timestamping rules