Interview Questions and Answers

Database provides a systematic and organized way of storing, managing and retrieving from

collection of logically related information.

Secondly the information has to be persistent, that means even after the application is closed

the information should be persisted.

Finally it should provide an independent way of accessing data and should not be dependent on the application to access the information.

Main difference between a simple file and database that database has independent way (SQL) of accessing information while simple files do not File meets the storing, managing and retrieving part of a database but not the independent way of accessing data. Many experienced programmers think that the main difference is that file can not provide multi-user capabilities which a DBMS provides. But if we look at some old COBOL and C programs where file where the only means of storing data, we can see functionalities like locking, multi-user etc provided very efficiently. So it�s a matter of debate if some interviewers think this as a main difference between files and database accept it� going in to debate is probably loosing a job.

SQL stands for Structured Query Language.SQL is an ANSI (American National Standards

Institute) standard computer language for accessing and manipulating database systems. SQL

statements are used to retrieve and update data in a database.

DBMS provides a systematic and organized way of storing, managing and retrieving from

collection of logically related information. RDBMS also provides what DBMS provides but above that it provides relationship integrity. So in short we can say

RDBMS = DBMS + REFERENTIAL INTEGRITY 

These relations are defined by using �Foreign Keys� in any RDBMS.Many DBMS companies claimed there DBMS product was a RDBMS compliant, but according to industry rules and regulations if the DBMS fulfills the twelve CODD rules it�s truly a RDBMS. Almost all DBMS (SQL SERVER, ORACLE etc) fulfills all the twelve CODD rules and are considered as truly RDBMS.

E-R diagram also termed as Entity-Relationship diagram shows relationship between various

tables in the database.

There are three major relationship models:-

One-to-one

One-to-many

Many-to-many

DML stands for Data Manipulation Statements. They update data values in table. Below are the most important DDL statements:- 

=>SELECT - gets data from a database table 

=> UPDATE - updates data in a table 

=> DELETE - deletes data from a database table 

=> INSERT INTO - inserts new data into a database table

DDL stands for Data definition Language. They change structure of the database objects like table, index etc. Most important DDL statements are as shown below:- 

=>CREATE TABLE - creates a new table in the database. 

=>ALTER TABLE � changes table structure in database. 

=>DROP TABLE - deletes a table from database 

=> CREATE INDEX - creates an index 

=> DROP INDEX - deletes an index

DISTINCT keyword is used to return only distinct values. Below is syntax:- Column age and

Table wbEmp

SELECT DISTINCT age FROM wbEmp

LIKE operator is used to match patterns. A "%" sign is used to define the pattern.

Below SQL statement will return all words with letter "S"

SELECT * FROM pcdsEmployee WHERE EmpName LIKE 'S%'

Below SQL statement will return all words which end with letter "S"

SELECT * FROM pcdsEmployee WHERE EmpName LIKE '%S'

Below SQL statement will return all words having letter "S" in between

SELECT * FROM pcdsEmployee WHERE EmpName LIKE '%S%'

"_" operator (we can read as �Underscore Operator�). �_� operator is the character defined at that point. In the below sample fired a query Select name from pcdsEmployee where name like

'_s%' So all name where second letter is �s� is returned.

Insert statement is used to insert new rows in to table. Update to update existing data in the

table. Delete statement to delete a record from the table. Below code snippet for Insert, Update and Delete :-

INSERT INTO wbEmployee SET name='maxwell',age='22';

UPDATE wbEmployee SET age='22' where name='maxwell';

DELETE FROM wbEmployee WHERE name = 'david';

ORDER BY clause helps to sort the data in either ascending order to descending order.

Ascending order sort query

SELECT name,age FROM pcdsEmployee ORDER BY age ASC

Descending order sort query

SELECT name FROM pcdsEmployee ORDER BY age DESC

SQL IN operator is used to see if the value exists in a group of values. For instance the below

SQL checks if the Name is either 'David' or 'Craig' SELECT * FROM wbEmployee WHERE name IN ('David','Craig') Also you can specify a not clause with the same. SELECT * FROM wbEmployee WHERE age NOT IN (30,25)

Below SQL selects employees born between '01/01/1995' AND '01/01/1978' as per mysql

SELECT * FROM wbEmployee WHERE DOB BETWEEN '1995-01-01' AND '2011-09-28'

UNION SQL syntax is used to select information from two tables. But it selects only distinct

records from both the table, while UNION ALL selects all records from both the tables.

SQL statements are good for set at a time operation. So it is good at handling set of data. But

there are scenarios where we want to update row depending on certain criteria. we will loop

through all rows and update data accordingly. There�s where cursors come in to picture.

A query nested inside a SELECT statement is known as a subquery and is an alternative to

complex join statements. A subquery combines data from multiple tables and returns results

that are inserted into the WHERE condition of the main query. A subquery is always enclosed within parentheses and returns a column. A subquery can also be referred to as an inner query and the main query as an outer query. JOIN gives better performance than a subquery when you have to check for the existence of records. 

For example, to retrieve all EmployeeID and CustomerID records from the ORDERS table that have the EmployeeID greater than the average of the EmployeeID field, you can create a nested query, as shown:

SELECT DISTINCT EmployeeID, CustomerID FROM ORDERS WHERE EmployeeID > (SELECT AVG(EmployeeID) FROM ORDERS)

A collection of conceptual tools for describing data, data relationships data semantics and constraints.

An entity set may not have sufficient attributes to form a primary key, and its primary key compromises of its partial key and primary key of its parent entity, then it is said to be Weak Entity set. 

It is a 'thing' in the real world with an independent existence.

It is an association among two or more entities.

The domain of attribute must include only atomic (simple, indivisible) values.

A relation schema R is in 2NF if it is in 1NF and every non-prime attribute A in R is fully functionally dependent on primary key.

A foreign key is used to establish relationships among relations in the relational model. Technically, a foreign key is a column (or columns) appearing in one relation that is (are) the primary key of another table. Although there may be exceptions, the values in the foreign key columns usually must correspond to values existing in the set of primary key values. This correspondence requirement is created in a database using a referential integrity constraint on the foreign key.

In 1969 Dr. E. F. Codd laid down some 12 rules which a DBMS should adhere in order to get the logo of a true RDBMS.

"All information in a relational data base is represented explicitly at the logical level and in

exactly one way - by values in tables."

"Each and every datum (atomic value) in a relational data base is guaranteed to be logically

accessible by resorting to a combination of table name, primary key value and column name."

In flat files we have to parse and know exact location of field values. But if a DBMS is truly

RDBMS you can access the value by specifying the table name, field name, for instance

Customers.Fields [�Customer Name�].

"Null values (distinct from the empty character string or a string of blank characters and distinct from zero or any other number) are supported in fully relational DBMS for representing missing information and inapplicable information in a systematic way, independent of data type.". 

"The data base description is represented at the logical level in the same way as ordinary data, so that authorized users can apply the same relational language to its interrogation as they apply to the regular data."The Data Dictionary is held within the RDBMS, thus there is no-need for off-line volumes to tell you the structure of the database.

"A relational system may support several languages and various modes of terminal use (for

example, the fill-in-the-blanks mode). However, there must be at least one language whose

statements are expressible, per some well-defined syntax, as character strings and that is

comprehensive in supporting all the following items.

Inner join shows matches only when they exist in both tables. Example in the below SQL there are two tables Customers and Orders and the inner join in made on Customers. Customerid and Orders.Customerid. So this SQL will only give you result with customers who have orders. If the customer does not have order it will not display that record.

SELECT Customers.*, Orders.* FROM Customers INNER JOIN Orders ON Customers.CustomerID=Orders.CustomerID 

Left join will display all records in left table of the SQL statement. In SQL below customers with or without orders will be displayed. Order data for customers without orders appears as NULL values. For example, you want to determine the amount ordered by each customer and you need to see who has not ordered anything as well. You can also see the LEFT OUTER JOIN as a mirror image of the RIGHT OUTER JOIN (Is covered in the next section) if you switch the side of each table.

SELECT Customers.*, Orders.* FROM Customers LEFT OUTER JOIN Orders ON

Customers.CustomerID =Orders.CustomerID 

Right join will display all records in right table of the SQL statement. In SQL below all orders with or without matching customer records will be displayed. Customer data for orders without customers appears as NULL values. For example, you want to determine if there are any orders in the data with undefined CustomerID values (say, after a conversion or something like it). You can also see the RIGHT OUTER JOIN as a mirror image of the LEFT OUTER JOIN if you switch the side of each table.

SELECT Customers.*, Orders.* FROM Customers RIGHT OUTER JOIN Orders ON

Customers.CustomerID =Orders.CustomerID

Following are difference between them: 

�HAVING� clause is used to specify filtering criteria for �GROUP BY�, while �WHERE� clause applies on normal SQL.

Aggregate and Scalar functions are in built function for counting and calculations.

Aggregate functions operate against a group of values but returns only one value.

AVG(column) :- Returns the average value of a column

COUNT(column) :- Returns the number of rows (without a NULL value) of a column

COUNT(*) :- Returns the number of selected rows

MAX(column) :- Returns the highest value of a column

MIN(column) :- Returns the lowest value of a column

Scalar functions operate against a single value and return value on basis of the single value.

UCASE(c) :- Converts a field to upper case

View is a virtual table which is created on the basis of the result set returned by the select

statement.

CREATE VIEW [MyView] AS SELECT * from pcdsEmployee where LastName = 'singh'

In order to query the view.

SELECT * FROM [MyView]

This model is based on collection of objects. An object contains values stored in instance variables with in the object. An object also contains bodies of code that operate on the object. These bodies of code are called methods. Objects that contain same types of values and the same methods are grouped together into classes. 

It is based on concept of full functional dependency. A functional dependency X Y is full functional dependency if removal of any attribute A from X means that the dependency does not hold any more.

A relation schema R is in 3NF if it is in 2NF and for every FD X A either of the following is true 

1. X is a Super-key of R. 

2. A is a prime attribute of R. 

In other words, if every non prime attribute is non-transitively dependent on primary key. 

The phase that identifies an efficient execution plan for evaluating a query that has the least estimated cost is referred to as query optimization.

1. Atomicity: Either all actions are carried out or none are. Users should not have to worry about the effect of incomplete transactions. DBMS ensures this by undoing the actions of incomplete transactions. 

2. Aggregation: A concept which is used to model a relationship between a collection of entities and relationships. It is used when we need to express a relationship among relationships.

No. 

PRODUCT: Concatenation of every row in one relation with every row in another. 

JOIN: Concatenation of rows from one relation and related rows from another.

It is a program module, which is responsible for fetching data from disk storage into main memory and deciding what data to be cache in memory.

It is a program module, which ensures that database, remains in a consistent state despite system failures and concurrent transaction execution proceeds without conflicting.

It is a program module, which manages the allocation of space on disk storage and data structure used to represent information stored on a disk.

There is set of rules that has been established to aid in the design of tables that are meant to be connected through relationships. This set of rules is known as Normalization.

Benefits of Normalizing your database include:

=>Avoiding repetitive entries

=>Reducing required storage space

=>Preventing the need to restructure existing tables to accommodate new data.

=>Increased speed and flexibility of queries, sorts, and summaries.

Following are the three normal forms :-

For a table to be in first normal form, data must be broken up into the smallest un possible.In addition to breaking data up into the smallest meaningful values, tables first normal form should not contain repetitions groups of fields.

The second normal form states that each field in a multiple field primary keytable must be directly related to the entire primary key. Or in other words,each non-key field should be a fact about all the fields in the primary key.

A non-key field should not depend on other Non-key field.

Denormalization is the process of putting one fact in numerous places (its vice-versa of normalization).Only one valid reason exists for denormalizing a relational design - to enhance performance.The sacrifice to performance is that you increase redundancy in database.

In fourth normal form it should not contain two or more independent multi-v about an entity and it should satisfy �Third Normal form�.

Fifth normal form deals with reconstructing information from smaller pieces of information.

These smaller pieces of information can be maintained with less redundancy.

If we want relational system in conjunction with time we use sixth normal form. At this moment

SQL Server does not supports it directly.

Below Sql Query find the second highest salary:

SELECT * FROM wbEmployeeSalary a WHERE (2=(SELECT COUNT(DISTINCT(b.salary)) FROM wbEmployeeSalary b WHERE b.salary>=a.salary))

�CROSS JOIN� or �CARTESIAN PRODUCT� combines all rows from both tables. Number of rows will be product of the number of rows in each table. In real life scenario I can not imagine where we will want to use a Cartesian product. But there are scenarios where we would like permutation and combination probably Cartesian would be the easiest way to achieve it.

SELECT INTO statement is used mostly to create backups. The below SQL backsup the

Employee table in to the EmployeeBackUp table. One point to be noted is that the structure of

wbEmployeeBackup and wbEmployee table should be same. SELECT * INTO

wbEmployeeBackup FROM wbEmployee

It is a Form of attack on a database-driven Web site in which the attacker executes

unauthorized SQL commands by taking advantage of insecure code on a system connected to the Internet, bypassing the firewall. SQL injection attacks are used to steal information from a database from which the data would normally not be available and/or to gain access to an organization�s host computers through the computer that is hosting the database.

SQL injection attacks typically are easy to avoid by ensuring that a system has strong input

validation.

As name suggest we inject SQL which can be relatively dangerous for the database. Example this is a simple SQL

SELECT email, passwd, login_id, full_name FROM members WHERE email = 'x'

Now somebody does not put �x� as the input but puts �x ; DROP TABLE members;�.

So the actual SQL which will execute is :-

SELECT email, passwd, login_id, full_name FROM members WHERE email = 'x' ; DROP TABLE

members;

Think what will happen to your database.

Data independence means that "the application is independent of the storage structure and access strategy of data". In other words, The ability to modify the schema definition in one level should not affect the schema definition in the next higher level. 

Two types of Data Independence: 

1. Physical Data Independence: Modification in physical level should not affect the logical level.

2. Logical Data Independence: Modification in logical level should affect the view level.

A Functional dependency is denoted by X Y between two sets of attributes X and Y that are subsets of R specifies a constraint on the possible tuple that can form a relation state r of R. The constraint is for any two tuples t1 and t2 in r if t1[X] = t2[X] then they have t1[Y] = t2[Y]. This means the value of X component of a tuple uniquely determines the value of component Y. 

A relation schema R is in BCNF if it is in 3NF and satisfies an additional constraint that for every FD X A, X must be a candidate key.

A relation schema R is said to be in 4NF if for every Multivalued dependency X Y that holds over R, one of following is true. 

1.) X is subset or equal to (or) XY = R. 

2.) X is a super key. 

A Relation schema R is said to be 5NF if for every join dependency {R1, R2, ..., Rn} that holds R, one the following is true 

1) Ri = R for some i. 

2) The join dependency is implied by the set of FD, over R in which the left side is key of R.

A relation is said to be in DKNF if all constraints and dependencies that should hold on the the constraint can be enforced by simply enforcing the domain constraint and key constraint on the relation.

1. Partial Key: It is a set of attributes that can uniquely identify weak entities and that are related to same owner entity. It is sometime called as Discriminator. 

2. Alternate Key: All Candidate Keys excluding the Primary Key are known as Alternate Keys.

Indexing is a technique for determining how quickly specific data can be found. 

Types: 

1. Binary search style indexing 

2. B-Tree indexing 

3. Inverted list indexing 

4. Memory resident table 

5. Table indexing 

A RDBMS maintains a description of all the data that it contains, information about every relation and index that it contains. This information is stored in a collection of relations maintained by the system called metadata. It is also called data dictionary.

Once the DBMS informs the user that a transaction has successfully completed, its effects should persist even if the system crashes before all its changes are reflected on disk. This property is called durability.

In distributed deadlock detection, the delay in propagating local information might cause the deadlock detection algorithms to identify deadlocks that do not really exist. Such situations are called phantom deadlocks and they lead to unnecessary aborts.

A Checkpoint is like a snapshot of the DBMS state. By taking checkpoints, the DBMS can reduce the amount of work to be done during restart in the event of subsequent crashes.

Two important pieces of RDBMS architecture are the kernel, which is the software, and the data dictionary, which consists of the system-level data structures used by the kernel to manage the database You might think of an RDBMS as an operating system (or set of subsystems), designed specifically for controlling data access; its primary functions are storing, retrieving, and securing data. An RDBMS maintains its own list of authorized users and their associated privileges; manages memory caches and paging; controls locking for concurrentresource usage; dispatches and schedules user requests; and manages space usage within its table-spacestructures.

I/O, Security, Language Processing, Process Control, Storage Management, Logging and Recovery, Distribution Control, Transaction Control, Memory Management, Lock Management.

Data dictionary is a set of tables and database objects that is stored in a special area of the database and maintained exclusively by the kernel.

The information in the data dictionary validates the existence of the objects, provides access to them, and maps the actual physical storage location.

A database trigger is a PL/SQL block that can defined to automatically execute for insert, update, and delete statements against a table. The trigger can e defined to execute once for the entire statement or once for every row that is inserted, updated, or deleted. For any one table, there are twelve events for which you can define database triggers. A database trigger can call database procedures that are also written in PL/SQL.

It is a program module that provides the interface between the low-level data stored in database, application programs and queries submitted to the system.

It is the program module, which tests for the satisfaction of integrity constraint and checks the authority of user to access data.

Procedures that are not part of a package are known as stand-alone because they independently defined. A good example of a stand-alone procedure is one written in a SQL*Forms application. These types of procedures are not available for reference from other Oracle tools. Another limitation of stand-alone procedures is that they are compiled at run time, which slows execution.

PL/SQL uses cursors for all database information accesses statements. The language supports the use two types 

of cursors 

1.) Implicit 

2.) Explicit