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CUSTOMER_CODE
SMUDE
DIVISION_CODE
SMUDE
EVENT_CODE
JAN2016
ASSESSMENT_CODE MIT202_JAN2016
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
13027
QUESTION_TEXT
Explain Relational Database Management System and its components.
SCHEME OF
EVALUATION
Relational Database Management System: A Relational Database
Management System (RDBMS) provides a comprehensive and
integrated approach to information management. A relational model
provides the basis for a relational database. A relational model has three
aspects:
1.Structures: Structures consist of a collection of objects or relations that
store data. An example of relation is a table. You can store information
in a table and use the table to retrieve and modify data.
2.Operations: Operations are used to manipulate data and structures in a
database. When using operations, you must adhere to a predefined set of
integrity rules.
3.Integrity rules: Integrity rules are laws that govern the operations
allowed on data in a database. This ensures data accuracy and
consistency.
(4 Marks)
Relational database components include:
Table
Row
Column
Field
Primary key
Foreign key
A Table is a basic storage structure of an RDBMS and consists of
columns and rows. A table represents an entity. For example, the
S_DEPT table stores information about the departments of an
organization.
A Row is a combination of column values in a table and is identified by
a primary key. Rows are also known as records. For example, a row in
the table S_DEPT contains information about one department.
A Column is a collection of one type of data in a table. Columns
represent the attributes of an object. Each column has a column name
and contains values that are bound by the same type and size. For
example, a column in the table S_DEPT specifies the names of the
departments in the organization.
A Field is an intersection of a row and a column. A field contains one
data value. If there is no data in the field, the field is said to contain a
NULL value.
A Primary key is a column or a combination of columns that is used to
uniquely identify each row in a table. For example, the column
containing department numbers in the S_DEPT table is created as a
primary key and therefore every department number is different. A
primary key must contain a value. It cannot contain a NULL value.
A Foreign key is a column or set of columns that refers to a primary key
in the same table or another table. You use foreign keys to establish
principle connections between, or within, tables. A foreign key must
either match a primary key or else be NULL. Rows are connected
logically when required. The logical connections are based upon
conditions that define a relationship between corresponding values,
typically between a primary key and a matching foreign key. This
relational method of linking provides great flexibility as it is independent
of physical links between records.
(6 Marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
13028
QUESTION_TEXT
Discuss Data Replication in distributed database
SCHEME OF
EVALUATION
The system maintains several identical replicas of the relation. Each
replica is stored in a different site, resulting in data replication. The
alternative to replication is to store only one copy of relation. (2 marks)
If relation r is replicated, a copy of relation r is stored in two or more
sites. In most extreme case, we can have full replication, in which a copy
is stored in every site in the system. In general replication enhances the
performance of read operations and increases the availability of data to
read transactions. (2 marks)
There are number of advantages and disadvantages to replication:
• Availability: If one of the sites containing relation r fails, then the
relation r may be found in another site. Thus, the system may continue to
process queries involving despite the failure of one site.
• Increased parallelism: Where the majority of access to the relation r
results in only the reading of the relation, the several sites can process
queries involving r in parallel. The more replicas of r are there, the
greater the chance that the needed data is found in the site where the
transaction is executing.
• Increase overhead on update: The system must ensure that all
replicas of a relation r are consistent since otherwise erroneous
computations may result. This implies that whenever r is updated, this
update must be propagated to all sites containing replicas, resulting in
increased over head. (2 X3 = 6)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
13030
QUESTION_TEXT
Discuss the advantages of data distribution
SCHEME OF
EVALUATION
Data sharing and Distributed Control: If a number of different sites
are connected to each other, then a user at one site may be able to access
data that is available at another site.. For example, in the distributed
banking system, it is possible for a user in one branch to access data in
another branch. ( 2marks)
The primary advantage to accomplishing data sharing by means of data
distribution is that each site is able to retain a degree of control over data
stored locally.
In distributed system, there is a global database administrator responsible
for the entire system. A part of these responsibilities is delegated to the
local database administrator for each site. ( 2marks)
Reliability and Availability: If one site fails in distributed system, the
remaining sites may be able to continue operating. In particular, if data
are replicated in several sites, transaction needing a particular data item
may find it in several sites. ( 2marks)
The failure of one site must be detected by the system, and appropriate
action may be needed to recover from the failure. Although recovery
from failure is more complex in distributed systems than in a centralized
system, the ability of most of the systems to continue to operate despite
failure of one site, results in increased availability ( 2marks)
Speedup Query Processing: If a query involves data at several sites, it
may be possible to split the query into sub queries that can be executed
in parallel by several sites. Such parallel computation allows for faster
processing of a user’s query. ( 2marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
118838
QUESTION_TEXT
Explain the following statements with example.
a. Insert
b. Update
c. Delete
d. Group by
e.
SCHEME OF
EVALUATION
View
Insert
The insertion facility allows new tuples to be inserted into given relations.
Attributes which are not specified by the insertion statement are given null
values.
1. Add a part with 14, weight 10, coloured red, with the cost and selling
price as 20 and 60 respectively.
Insert into P <14,10, ‘red’, 20, 60>
Update
When the columns are to be modified, set clause is used. This clause
specifies the update to be
made to selected tuples
Ex: update S set city=’Bangalore’ turnover=turnover+20 where S#=13
Delete
The deletion removes specified tuples from the database
Delete S where S#=13
Group by
This feature allows one to partition the result into a number of groups such
that all rows of the group have the same value in some specified column
Select P#, sum(qty), from SP group by P#
View
A very important aspect of data definition is the ability to define alternative
views of data. The process of specifying an alternative view is very similar to
that of framing a query
Define view D50 AS select empno, name, job from emp where DNO=50
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
118841
QUESTION_TEXT
Explain different categories of SQL commands.
SCHEME OF
EVALUATION
•
SQL commands can be roughly divided into 3 major
categories with regard to their functionality.
a.
Data Definition Statements: (04 marks)
•
Used to create and maintain the database structure.
•
2 major DDL statements CREATE and DROP.
•
CREATE DATABASE to create a database.
•
DROP DATABASE to remove a database.
•
CREATE TABLE create table.
•
DROP TABLE to drop a table.
•
CREATE INDEX to create an index on a column.
•
DROP INDEX to drop index.
•
CREATE VIEW to create view.
•
DROP VIEW drop a view.
b.
Data Manipulation Statements: (02 marks)
To manipulate data in tables directly or through views 4
standard DML statements: SELECT DELETE INSERT UPDATE
c.
Data Control: (04 marks)
3 issues
a.
Recovery and concurrency:
•
Manner in which multiple users operate upon the data base
•
Reflect updates of a transaction by using the COMMIT.
•
Cancel all updates using ROLLBACK.
b.
Security: 2 aspects
•
GRANT-this shall grant one or more access rights to perform
the data manipulative operations on the relations.
•
VIEW mechanism it can be created which hides the sensitive
information and defines only that part of a relation which should be
visible.
•
A user can then be allowed to access this view
•
Ex: CREATE VIEW LOCAL AS
SELECT * FROM SUPPLIER
WHERE SUPPLIER.CITY=’Delhi’
c.
Integrity constraints: ex: one can specify that an attribute of
a relation will not take on null values.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
118846
Explain Heuristics in Query Optimization in brief.
QUESTION_TEXT
SCHEME OF
EVALUATION
Heuristics in Query Optimization
Heuristic rule is applied for Query Optimization by modifying the
internal representation of query. This form of query is generally in the
form of query tree or a query graph data structure. Although some
optimization technique were based on query graph, nowadays, this
technique is not applied because query graph cannot show the order of
operation which is needed by query optimizer for query execution. So
this unit will deal mainly with the Heuristic Optimization of query tree.
A heuristic rule is applied to the initial query expression and produces
the heuristically transformed equivalent query expressions. This is
performed by transforming an initial expression (tree) into an equivalent
expression (tree) which is made more efficient for execution. This rule
works well in most cases but not always guaranteed.
An execution of the query tree consists of executing an internal node
operation whenever its operands are available and then replacing that
internal node by the relation that results from executing the operation.
Query trees and query graphs
The query tree is a tree data structure that represents the relational
algebra expression in the query optimization process. The leaf nodes in
the query tree correspond to the input relations of the query. The internal
nodes represent the relational algebra operations. The system will
execute an internal node operation whenever its operands are available
and then the internal node is replaced by the relation which is obtained
from executing the operation. The execution is terminated when the root
node is executed and produces the result relation for the query.
Query can also be represented by a query graph. In this case the relations
in the query are represented by relational nodes and are represented by
single circles. Constant nodes are used to represent constant values and
are displayed as double circles or ovals. Selection and join conditions are
represented by the graph edges. And finally the attributes to be retrieved
from each relation are displayed in square brackets above each relation.
The graph query representation does not give an order of performing the
operations because there is only a single graph corresponding to each
query.
Hence query trees are better than query graphs because query optimizer
needs to show the order of operations for query execution which is not
possible in query graphs.
Heuristic optimization of query trees:
Two relational algebra expressions are said to be equivalent if the two
expressions generate two relation of the same set of attributes and
contain the same set of tuples although their attributes may be ordered
differently.
Hence while doing Heuristic Optimization on Query Trees, generally,
many different relational algebra expressions can be found out which can
be equivalent to correspond to the same query. And for every relational
algebra expressions a query tree can be drawn. And hence there can be
many different query trees to correspond to the same query.
The query parser generates a standard initial query tree to correspond to
SQL query without optimizing. When the simple standard form of query
tree is found out then the heuristic query optimizer transforms this initial
query tree into a final query tree that is efficient to execute.
General outline of a Heuristic Algebraic Optimization Algorithm
Heuristic rule are generally applied as per the following steps:
First of all SELECT operations are broken up with conjunctive
operations into a cascade of SELECT operations.
Then SELECT operations are moved down far to the query tree as is
permitted by the attributes involved in the select condition.
Leaf nodes of the tree are rearranged by :
positioning the leaf node relation with the most restrictive SELECT
operations so they are executed first in the query representation,
and making sure that the ordering of leaf nodes does not cause
CARTESIAN PRODUCT operation.
CARTESIAN PRODUCT operations are combined with a subsequent
SELECT operation in the tree into a JOIN operation, if the condition
represents a join condition.
Lists of projection attributes are broken down and moved down the tree
as far as possible by creating new PROJECT operations as needed.
And lastly subtrees are identified that represent groups of operations that
can be executed by a single algorithm.
These steps are applied using general transformation rules for relational
algebra operations into equivalent ones. While transforming, the
meaning of the operations and the resulting relations should not
mismatch.
(2.5 marks each)