1.WHERE vs HAVING Clause Example in SQL
Both Having Clause and Where clause is used to filter the data coming from the Select
statement, but still there are some differences between them. These difference are given
below
1) Where clause can be used with Select, Update and Delete Statement Clause but having
clause can be used only with Select statement.
For example, the sql query
Update EmployeeDeptInfo Set departmentid =7 Where employeeid=4
will work fine but the query
Update EmployeeDeptInfo Set departmentid =7 Having employeeid=4
will not work
2) We can't use aggregate functions in the where clause unless it is in a subquery contained
in a HAVING clause whereas we can use aggregate function in Having clause. We can use
column name in Having clause but the column must be contained in the group by clause.
For example, the sql query
select * from EmployeeDeptInfo where count(employeeid)>1
will not work but the query
Select Employeeid, Departmentid from EmployeeDeptInfo Group By Employeeid,
DepartmentId having (count(employeeid) >1)
will work fine
3) Where Clause is used on the individual records whereas Having Clause in conjunction
with Group By Clause work on the record sets ( group of records ).
For Example, in the below sql Query
select employeeid, departmentid from EmployeeDeptInfo where employeeid=5
the where clause will search the table EmployeeDeptInfo for the record whose employeeid
is 5 and then show the output.
but in the below query,
Select Employeeid, Departmentid from EmployeeDeptInfo Group By Employeeid,
DepartmentId having employeeid=5
the result are first grouped by the Group By Clause and then they become again filtered by
the condition defined in the having clause. Sometime , like above both queries, we get the
same result with the help of Where clause and having clause but which way is best is
determined automatically by the optimizer and it select the best way of executing it.
Where Clause:
1.Where Clause can be used other than Select statement also
2.Where applies to each and single row
3.In where clause the data that fetched from memory according
to condition
4.Where is used before GROUP BY clause
Ex:Using Condition for the data in the memory.
Having Clause:
1.Having is used only with the SELECT statement.
2.Having applies to summarized rows (summarized with GROUP BY)
3.In having the completed data firstly fetched and then separated according to condition.
4.HAVING clause is used to impose condition on GROUP Function and is used after GROUP
BY clause in the query
Ex: when using the avg function and then filter the data like ava(Sales)>0
Summary:
Having works like Where clause without Group By Clause
Difference between join and union?
JOIN:
A Join is used for displaying columns with the same or different names from different tables.
The output displayed will have all the columns shown individually. i.e. The columns will be
aligned next to each other.
By using join, you can retrieve data from two or more tables based on logical relationships
between the tables. Joins indicate how sql should use data from one table to select the rows
in another table.
UNION:
The UNION set operator is used for combining data from two tables which have columns
with the same datatype. When a UNION is performed the data from both tables will be
collected in a single column having the same datatype.
Union combines the unique results of two or more queries into a single result set that includes
all the rows that belong to all queries in the union.
Difference between cross product and cartesian product?
There is no difference. Cartesian Products and Cross Joins are the same.
Retrieve data 11th column of the nth column
select 1/2 in sql server.What is Result
zero (0)
difference between inner join and outer join
Inner Join
The join that displays only the rows that have a match in both the joined tables is known as
inner join. This is default join in the query and view Designer.
Outer Joins
A join that return all the rows that satisfy the condition and unmatched rows in the joined
table is an Outer Join.
We are having three types of Outer Joins
Left Outer Join
Right Outer Join
Full Outer Join
Left Outer Join
The left outer join displays all the rows from the first table and matched rows from the
second table.
Right Outer Join
The right outer join displays all the rows from the second table and matched rows from the
first table.
Full Outer Join
Full Outer Join displays all the matching and non matching rows of both the tables.
What is Index?Types of Indexes .How Many Clustered Indexes Can be created on a
table .i created a separate index on each column of a table.what are the advantages and
disadvantages of this approach
An index can be created in a table to increase the performance of application and we can
get the data more quickly and efficiently.
In SQL we are having two types of indexes are there
1) Clustered Index
2) Non-Clustered Index
Clustered Index
A clustered index is a special type of index that reorders the way records in the table
are physically stored. Therefore table can have only one clustered index. The leaf nodes of a
clustered index contain the data pages.
Non-Clustered Index
A non-clustered index is a special type of index in which the logical order of the index
does not match the physical stored order of the rows on disk. The leaf node of a nonclustered index does not consist of the data pages. Instead, the leaf nodes contain index
rows.
Maximum number of Index per table.
For Sql-2005:
1ClusteredIndex+249NonclusteredIndex=250Index
For Sql-2008:
1ClusteredIndex+999NonclusteredIndex=1000Index
If you create an index on each column of a table, it improves the query (i.e.
SELECT) performance, as the query optimizer can choose from all the existing indexes to
come up with an efficient execution plan. At the same time, data modification operations
(such as INSERT, UPDATE, and DELETE) will become slow, as every time data changes in the
table, all the indexes need to be updated. Another disadvantage is that, indexes need disk
space, the more indexes you have, more disk space is used.
What is a deadlock, Blocking and what is a live lock?
Deadlock: A common issue with SQL Server is deadlocks. A deadlock occurs when two or
more processes are waiting on the same resource and each process is waiting on the other
process to complete before moving forward. When this situation occurs and there is no way
for these processes to resolve the conflict, SQL Server will choose one of processes as the
deadlock victim and rollback that process, so the other process or processes can move
forward.
Blocking
Blocking occurs when one connection (user process or application process) places a lock on
a table or a number of rows and a second connection attempts to read or modify the data
under the lock by first connection. Depending on the type of the lock, this can cause the
second connection to wait until the first connection releases its lock. A blocked connection
waits indefinitely for the blocking connection to release its lock.
The more blocking happens on the server the less concurrency the system achieves. A
certain amount of blocking is unavoidable but too many blocks for longer periods of time
can degrade the performance of SQL Server.
Livelock: A Live lock is one, where a request for exclusive lock is denied continuously
because a series of overlapping shared locks keeps on interfering each other and to adapt
from each other they keep on changing the status which further prevents them to complete
the task. In SQL Server Live Lock occurs when read transactions are applied on table which
prevents write transaction to wait indefinitely. This is different then deadlock as in deadlock
both the processes wait on each other.
Different types of normalization in SQL-SERVER?
NORMALIZATION:
Normalization is the process of organizing data into a related table; it also eliminates
redundancy and increases the integrity which improves performance of the query. To
normalize a database, we divide the database into tables and establish relationships
between the tables.
Database normalization can essentially be defined as the practice of optimizing table
structures. Optimization is accomplished as a result of a thorough investigation of the
various pieces of data that will be stored within the database, in particular concentrating
upon how this data is interrelated.
Normalization Avoids:




Duplication of Data - The same data is listed in multiple lines of the database
Insert Anomaly - A record about an entity cannot be inserted into the table
without first inserting information about another entity - Cannot enter a customer
without a sales order
Delete Anomaly - A record cannot be deleted without deleting a record about a
related entity. Cannot delete a sales order without deleting all of the customer's
information.
Update Anomaly - Cannot update information without changing information in
many places. To update customer information, it must be updated for each sales
order the customer has placed
DE- NORMALIZATION:
Denormalization is the process of adding redundant data to speed up complex queries
involving multiple table JOINS. One might just go to a lower form of Normalization to
achieve Denormalization and better performance. Data is included in one table from
another in order to eliminate the second table which reduces the number of JOINS in a
query and thus achieves performance.
Normalization is a Six stage process - After the first stage, the data is said to be in first
normal form, after the second, it is in second normal form, after the third, it is in third
normal form and so on.
First Normal Form (1st NF)
In 1st NF:




The table cells must be of single value.
Eliminate repeating groups in individual tables.
Create a separate table for each set of related data.
Identify each set of related data with a primary key.
Definition: An entity is in the first normal form if it contains no repeating groups. In
relational terms, a table is in the first normal form if it contains no repeating columns.
Repeating columns make your data less flexible, waste disk space, and make it more difficult
to search for data.
IMP: In 1NF relation the order of tuples (rows) and attributes (columns) does not matter.
Example:
Order Customer
1
Rishabh
2
Preeti
3
Rishabh
4
Rishabh
Contact Person
Manish
Rohan
Manish
Manish
Total
134.23
521.24
1042.42
928.53
The above relation satisfies the properties of a relation and is said to be in first normal form
(or 1NF). Conceptually it is convenient to have all the information in one relation since it is
then likely to be easier to query the database.
Second Normal Form (2nd NF)
In 2nd NF:




Remove Partial Dependencies.
Functional Dependency: The value of one attribute in a table is determined entirely
by the value of another.
Partial Dependency: A type of functional dependency where an attribute is
functionally dependent on only part of the primary key (primary key must be a
composite key).
Create separate table with the functionally dependent data and the part of the key
on which it depends. Tables created at this step will usually contain descriptions of
resources.
Definition: A relation is in 2NF if it is in 1NF and every non-key attribute is fully
dependent on each candidate key of the relation.
Example:
The following relation is not in Second Normal Form:
Order Customer
Contact Person
Total
1
Rishabh
Manish
134.23
2
Preeti
Rohan
521.24
3
Rishabh
Manish
1042.42
4
Rishabh
Manish
928.53
In the table above, the order number serves as the primary key. Notice that the customer
and total amount are dependent upon the order number -- this data is specific to each
order. However, the contact person is dependent upon the customer. An alternative way to
accomplish this would be to create two tables:
Customer
Contact Person
Rishabh
Manish
Preeti
Rohan
Order
1
2
3
4
Customer
Rishabh
Preeti
Rishabh
Rishabh
Total
134.23
521.24
1042.42
928.53
The creation of two separate tables eliminates the dependency problem. In the first table,
contact person is dependent upon the primary key -- customer name. The second table only
includes the information unique to each order. Someone interested in the contact person
for each order could obtain this information by performing a Join Operation.
Third Normal Form (3rd NF)
In 3rd NF:



Remove transitive dependencies.
Transitive Dependency A type of functional dependency where an attribute is
functionally dependent on an attribute other than the primary key. Thus its value is
only indirectly determined by the primary key.
Create a separate table containing the attribute and the fields that are functionally
dependent on it. Tables created at this step will usually contain descriptions of either
resources or agents. Keep a copy of the key attribute in the original file.
A relation is in third normal form, if it is in 2NF and every non-key attribute of the relation is
non-transitively dependent on each candidate key of the relation.
Non-transitive dependency:
Let A, B and C be three attributes of a relation R such that Aïƒ B and Bïƒ C. From these FDs,
we may derive Aïƒ C. This dependence Aïƒ C is transitive.
Example:
Company
ABC Ltd.
XYZ Ltd.
ASD Ltd.
City
Mumbai
Noida
Chennai
State
MH
UP
TN
ZIP
10169
33196
21046
The above table is not in the 3NF.
In this example, the city and state are dependent upon the ZIP code. To place this table in
3NF, two separate tables would be created -- one containing the company name and ZIP
code and the other containing city, state, ZIP code pairings.
Company
ZIP
ABC Ltd.
10169
XYZ Ltd.
33196
ASD Ltd.
21046
City
Mumbai
Noida
Chennai
State
MH
UP
TN
ZIP
10169
33196
21046
This may seem overly complex for daily applications and indeed it may be. Database
designers should always keep in mind the tradeoffs between higher level normal forms and
the resource issues that complexity creates.
Boyce-Codd Normal Form (BCNF)
In BCNF:






When a relation has more than one candidate key, anomalies may result even
though the relation is in 3NF.
3NF does not deal satisfactorily with the case of a relation with overlapping
candidate keys
i.e. composite candidate keys with at least one attribute in common.
BCNF is based on the concept of a determinant.
A determinant is any attribute (simple or composite) on which some other attribute
is fully functionally dependent.
A relation is in BCNF is, and only if, every determinant is a candidate key.
Definition: A relation is in Boyce-Codd Normal Form (BCNF) if every determinant is a
candidate key. (See the links in the box at right for definitions of determinant and candidate
key.)
The difference between 3NF and BCNF is that for a functional dependency A ïƒ B, 3NF allows
this dependency in a relation if B is a primary-key attribute and A is not a candidate key,
Whereas BCNF insists that for this dependency to remain in a relation, A must be a
candidate key.
Example:
CLIENT INTERVIEW:
ClientNo
InterviewDate
13-may-11
CR76
InterviewTime
10:30
StaffNo
SG5
RoomNo
G101
CR76
13-may-11
12:00
SG5
G101
CR74
13-may-11
12:00
SG37
G102
CR56
02-july-11
10:30
SG5
G102
• FD1 ClientNo, InterviewDate -> InterviewTime, StaffNo, RoomNo (Primary Key)
• FD2 StaffNo, InterviewDate, InterviewTime -> ClientNo (Candidate key)
• FD3 RoomNo, InterviewDate, InterviewTime -> ClientNo, StaffNo (Candidate key)
• FD4 StaffNo, InterviewDate -> RoomNo (not a candidate key)
As a consequece the ClientInterview relation may suffer from update anomalies.
To transform the ClientInterview relation to BCNF, we must remove the violating functional
dependency by creating two new relations called Interview and StaffRoom as shown below,
Interview (ClientNo, InterviewDate, InterviewTime, StaffNo)
StaffRoom (StaffNo, InterviewDate, RoomNo)
INTERVIEW
ClientNo
CR76
InterviewDate
13-may-11
InterviewTime
10:30
StaffNo
SG5
CR76
13-may-11
12:00
SG5
CR74
13-may-11
12:00
SG37
CR56
02-july-11
10:30
SG5
STAFFROOM
StaffNo
SG5
SG37
SG5
InterviewDate
13-may-11
13-may-11
02-july-11
RoomNo
G101
G102
G102
BCNF Interview and StaffRoom relations.
An entity is in Fourth Normal Form (4NF) when it meets the requirement of being in Third
Normal Form (3NF) and additionally:

Has no multiple sets of multi-valued dependencies. In other words, 4NF states that
no entity can have more than a single one-to-many relationship within an entity if
the one-to-many attributes are independent of each other.

Many:many relationships are resolved independently.
Fourth Normal Form (4th NF)
In 4th NF:
An entity is in Fourth Normal Form (4NF) when it meets the requirement of being in Third
Normal Form (3NF) and additionally:


Has no multiple sets of multi-valued dependencies. In other words, 4NF states that
no entity can have more than a single one-to-many relationship within an entity if
the one-to-many attributes are independent of each other.
Fourth Normal Form applies to situations involving many-to-many relationships.
In relational databases, many-to-many relationships are expressed through cross-reference
tables.
Definition: A table is in fourth normal form (4NF) if and only if it is in BCNF and contains no
more than one multi-valued dependency.
Example:
Take an example of Employee Table
info(Employee, Skills, Hobbies)
Employee
Skills
Hobbies
1
Programming
Golf
1
Programming
Bowling
1
Analysis
Golf
1
Analysis
Bowling
2
Analysis
Golf
2
Analysis
Gardening
2
Management
Golf
2
Management
Gardening
This table is difficult to maintain since adding a new hobby requires multiple new rows
corresponding to each skill. This problem is created by the pair of multi-valued
dependencies EMPLOYEE -> SKILLS and EMPLOYEE -> HOBBIES. A much better alternative
would be to decompose INFO into two relations:
Employee
Skills
1
Programming
1
Analysis
2
Analysis
2
Management
Hobbies(Employee, Hobby)
Employee
Hobbies
1
Golf
1
Bowling
2
Golf
2
Gardening
Fifth Normal Form (5th NF)
In 5th NF:


A relation that has a join dependency cannot be decomposed by a projection into
other relations without spurious results
A relation is in 5NF when its information content cannot be reconstructed from
several smaller relations i.e. from relations having fewer attributes than the original
relation
Definition: A table is in fifth normal form (5NF) or Project-Join Normal Form (PJNF) if it is in
4NF and it cannot have a lossless decomposition into any number of smaller tables.
Fifth normal form, also known as join-projection normal form (JPNF), states that no nontrivial join dependencies exist. 5NF states that any fact should be able to be reconstructed
without any anomalous results in any case, regardless of the number of tables being joined.
A 5NF table should have only candidate keys and it's primary key should consist of only a
single column.
Example:
Take an example of a buying table. This is used to track buyers, what they buy, and from
whom they buy. Take the following sample data:
Buyer
Vendor
Item
Shalley
Kashmir House Jeans
Mary
Kashmir House Jeans
Shalley
Radhika Sarees Saree
Mary
Radhika Sarees Saree
Shalley
Radhika Sarees Suit
The problem with the above table structure is that if Claiborne starts to sell Jeans then how
many records must you create to record this fact? The problem is there are pair wise cyclical
dependencies in the primary key. That is, in order to determine the item you must know the
buyer and vendor, and to determine the vendor you must know the buyer and the item, and
finally to know the buyer you must know the vendor and the item.
And the solution is to break this one table into three tables; Buyer-Vendor, Buyer-Item, and
Vendor-Item. So following tables are in the 5NF.
BUYER-VENDOR
Buyer
Vendor
Shalley
Kashmir House
Mary
Kashmir House
Shalley
Radhika Sarees
Mary
Radhika Sarees
BUYER-ITEM
Buyer
Item
Shalley
Jeans
Mary
Jeans
Shalley
Saree
Mary
Saree
Shalley
Suit
VENDOR- ITEM
Vendor
Kashmir House
Radhika Sarees
Item
Jeans
Saree
Radhika Sarees
Suit
Difference between correlated subquery and nested subquery :Subquery:-If a sql statement contains another sql statement then the sql statement which is
inside another sql statement is called Subquery. It is also known as nested query. The Sql
Statement which contains the other sql statement is called Parent Statement.
Nested Subquery:-If a Subquery contains another subquery, then the subquery inside
another subquery is called nested subquery.
Correlated Subquery
A query is called correlated subquery when both the inner query and the outer query are
interdependent. For every row processed by the inner query, the outer query is processed
as well. The inner query depends on the outer query before it can be processed.
Difference between CTE and Temp Table and Table Variable
Temp Table or Table variable or CTE are commonly used for storing data temporarily in SQL
Server. In this article, you will learn the differences among these three.
CTE
CTE stands for Common Table expressions. It was introduced with SQL Server 2005. It is a
temporary result set and typically it may be a result of complex sub-query. Unlike temporary
table its life is limited to the current query. It is defined by using WITH statement. CTE
improves readability and ease in maintenance of complex queries and sub-queries. Always
begin CTE with semicolon.
A sub query without CTE is given below :
1.
2.
3.
4.
5.
SELECT * FROM (
SELECT Addr.Address, Emp.Name, Emp.Age From Address Addr
Inner join Employee Emp on Emp.EID = Addr.EID) Temp
WHERE Temp.Age > 50
ORDER BY Temp.NAME
By using CTE above query can be re-written as follows :
1.
2.
3.
4.
5.
6.
7.
8.
9.
;With CTE1(Address, Name, Age)--Column names for CTE, which are optional
AS
(
SELECT Addr.Address, Emp.Name, Emp.Age from Address Addr
INNER JOIN EMP Emp ON Emp.EID = Addr.EID
)
SELECT * FROM CTE1 --Using CTE
WHERE CTE1.Age > 50
ORDER BY CTE1.NAME
When to use CTE
1. This is used to store result of a complex sub query for further use.
2. This is also used to create a recursive query.
Temporary Tables
In SQL Server, temporary tables are created at run-time and you can do all the operations
which you can do on a normal table. These tables are created inside Tempdb database.
Based on the scope and behaviour temporary tables are of two types as given below1. Local Temp Table
Local temp tables are only available to the SQL Server session or connection (means
single user) that created the tables. These are automatically deleted when the
session that created the tables has been closed. Local temporary table name is
stared with single hash ("#") sign.
1. CREATE TABLE #LocalTemp
2. (
3. UserID int,
4. Name varchar(50),
5. Address varchar(150)
6. )
7. GO
8. insert into #LocalTemp values ( 1, 'Shailendra','Noida');
9. GO
10. Select * from #LocalTemp
The scope of Local temp table exist to the current session of current user means to
the current query window. If you will close the current query window or open a new
query window and will try to find above created temp table, it will give you the error.
2. Global Temp Table
Global temp tables are available to all SQL Server sessions or connections (means all
the user). These can be created by any SQL Server connection user and these are
automatically deleted when all the SQL Server connections have been closed. Global
temporary table name is stared with double hash ("##") sign.
1. CREATE TABLE ##GlobalTemp
2. (
3. UserID int,
4. Name varchar(50),
5. Address varchar(150)
6. )
7. GO
8. insert into ##GlobalTemp values ( 1, 'Shailendra','Noida');
9. GO
10. Select * from ##GlobalTemp
11.
Global temporary tables are visible to all SQL Server connections while Local
temporary tables are visible to only current SQL Server connection.
Table Variable
This acts like a variable and exists for a particular batch of query execution. It gets dropped
once it comes out of batch. This is also created in the Tempdb database but not the
memory. This also allows you to create primary key, identity at the time of Table variable
declaration but not non-clustered index.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
GO
DECLARE @TProduct TABLE
(
SNo INT IDENTITY(1,1),
ProductID INT,
Qty INT
)
--Insert data to Table variable @Product
INSERT INTO @TProduct(ProductID,Qty)
SELECT DISTINCT ProductID, Qty FROM ProductsSales ORDER BY ProductID ASC
--Select data
Select * from @TProduct
--Next batch
GO
Select * from @TProduct --gives error in next batch
Note
1. Temp Tables are physically created in the Tempdb database. These tables act as the
normal table and also can have constraints, index like normal tables.
2. CTE is a named temporary result set which is used to manipulate the complex subqueries data. This exists for the scope of statement. This is created in memory rather
than Tempdb database. You cannot create any index on CTE.
3. Table Variable acts like a variable and exists for a particular batch of query execution.
It gets dropped once it comes out of batch. This is also created in the Tempdb
database but not the memory.
In subqueries, which is efficient ,the IN clause or EXISTS clause? Does they produce the same
result?????
EXISTS is efficient bcose,
1.Exists is faster than IN clause.
2.IN check returns values to main query where as EXISTS returns Boolean (T or F).
In terms of optimization both are different,Exists is used where both the queries(main and
subqueries) returns the same structure results like select name,id from emp where exists
(select depname,depid from dep)but if the returning structure is different then we use In
clause for exp select name,id from emp where id in(select depid from dep
)
what is database transaction? properties of transaction?
A transaction is a unit of work that is performed against a database. Transactions are units
or sequences of work accomplished in a logical order, whether in a manual fashion by a user
or automatically by some sort of a database program.
A transaction is the propagation of one or more changes to the database. For example, if
you are creating a record or updating a record or deleting a record from the table, then you
are performing transaction on the table. It is important to control transactions to ensure
data integrity and to handle database errors.
Practically, you will club many SQL queries into a group and you will execute all of them
together as a part of a transaction.
Properties of Transactions:
Transactions have the following four standard properties, usually referred to by the
acronym ACID:




Atomicity: ensures that all operations within the work unit are completed
successfully; otherwise, the transaction is aborted at the point of failure, and
previous operations are rolled back to their former state.
Consistency: ensures that the database properly changes states upon a successfully
committed transaction.
Isolation: enables transactions to operate independently of and transparent to each
other.
Durability: ensures that the result or effect of a committed transaction persists in
case of a system failure.
what is computed column in sql server:Computed columns are derived columns based on the other existing columns. Computed
columns are a data type that can be created based on the situation.
We can create a computed column at either of the following two levels:
1. Whenever we create the table.
2. By using an alter statement.
What is denormalization and when would you go for it?
De-normalization is the process of attempting to optimize the performance of a database by
adding redundant data. It’s used To introduce redundancy into a table in order to
incorporate data from a related table. The related table can then be eliminated. Denormalization can improve efficiency and performance by reducing complexity in a data
warehouse schema.
The Reason for Denormalization
Only one valid reason exists for denormalizing a relational design - to enhance performance.
However, there are several indicators which will help to identify systems and tables which
are potential denormalization candidates. These are:
• Many critical queries and reports exist which rely upon data from more than one table.
Often times these requests need to be processed in an on-line environment.
• Repeating groups exist which need to be processed in a group instead of individually.
• Many calculations need to be applied to one or many columns before queries can be
successfully answered.
• Tables need to be accessed in different ways by different users during the same
timeframe.
• Many large primary keys exist which are clumsy to query and consume a large amount of
disk space when carried as foreign key columns in related tables.
• Certain columns are queried a large percentage of the time causing very complex or
inefficient SQL to be used.
What is view ?Advantages and Disadvantages of views in Sql Server
What is view ?
View is the simply subset of table which are stored logically in a database means a view is a
virtual table in the database whose contents are defined by a query.
To the database user, the view appears just like a real table, with a set of named columns
and rows of data. SQL creates the illusion of the view by giving the view a name like a table
name and storing the definition of the view in the database.
Views are used for security purpose in databases,views restricts the user from viewing
certain column and rows means by using view we can apply the restriction on accessing the
particular rows and columns for specific user. Views display only those data which are
mentioned in the query, so it shows only data which is returned by the query that is defined
at the time of creation of the View.
Advantages of views
Security
Each user can be given permission to access the database only through a small set of views
that contain the specific data the user is authorized to see, thus restricting the user's access
to stored data
Query Simplicity
A view can draw data from several different tables and present it as a single table, turning
multi-table queries into single-table queries against the view.
Structural simplicity
Views can give a user a "personalized" view of the database structure, presenting the
database as a set of virtual tables that make sense for that user.
Consistency
A view can present a consistent, unchanged image of the structure of the database, even if
the underlying source tables are split, restructured, or renamed.
Data Integrity
If data is accessed and entered through a view, the DBMS can automatically check the data
to ensure that it meets the specified integrity constraints.
Logical data independence.
View can make the application and database tables to a certain extent independent. If
there is no view, the application must be based on a table. With the view, the program can
be established in view of above, to view the program with a database table to be separated.
Disadvantages of views
Performance
Views create the appearance of a table, but the DBMS must still translate queries against
the view into queries against the underlying source tables. If the view is defined by a
complex, multi-table query then simple queries on the views may take considerable time.
Update restrictions
When a user tries to update rows of a view, the DBMS must translate the request into an
update on rows of the underlying source tables. This is possible for simple views, but more
complex views are often restricted to read-only.
What is Linked Servers or Database Links?How to setup Linked Servers?
Don't be confused by the two terms; both are the same. In SQL Server it is called a Linked
Server whereas in Oracle it's DBLinks (Database Links).
Linked Servers allows you to connect to other database instances on the same server or on
another machine or remote servers.
It allows SQL Server to execute SQL scripts against OLE DB data sources on remote servers
using OLE DB providers.
The remote servers can be SQL Server, Oracle etc. which means those databases tht support
OLE DB can be used for linking servers.
How to setup Linked Servers?
Referer:http://www.c-sharpcorner.com/uploadfile/suthish_nair/linked-servers-in-sqlserver-2008/
This can be done in two ways.
1.Using Transact-SQL
2.SQL Server Management Studio
Using the following syntax we can create a Linked Server.
Example:
Handling error in sql server?
The two most common mechanisms for error handling in SQL Server 2005 are:


@@ERROR
TRY-CATCH Block
How we find third, Fourth and Fifth highest salary through SQl queries?
 2nd Highest Salary
select max(salary) from Employeedetails
where salary not in (select Distinct top 1 salary from Employeedetails order by salary
desc )
 3nd Highest Salary
select max(salary) from Employeedetails
where salary not in (select Distinct top 2 salary from Employeedetails order by salary
desc )
 4nd Highest Salary
select max(salary) from Employeedetails
where salary not in (select Distinct top 3 salary from Employeedetails order by salary
desc )


Company: Accenture- Pune
Sr.No. User Defined Function
1
2
3
4
5
6
7
8
9
10
11
12
13
Date:02-09-2014
Differences between Stored Procedure and User Defined Function in SQL Server
Stored Procedure
Function must return a value. Stored Procedure may or not return values.
Will allow only Select
Can have select statements as well as DML statements
statements, it will not allow us
such as insert, update, delete and so on
to use DML statements.
It will allow only input
parameters, doesn't support It can have both input and output parameters.
output parameters.
User Defined Function can have
Stored Procedure can have upto 2100 input parameters.
upto 1023 input parameters.
It will not allow us to use tryFor exception handling we can use try catch blocks.
catch blocks.
Transactions are not allowed
Can use transactions within Stored Procedures.
within functions.
We can use only table
Can use both table variables as well as temporary table in
variables, it will not allow using
it.
temporary tables.
Stored Procedures can't be
Stored Procedures can call functions.
called from a function.
Procedures can't be called from Select/Where/Having and
Functions can be called from a
so on statements. Execute/Exec statement can be used to
select statement.
call/execute Stored Procedure.
A UDF can be used in join
Procedures can't be used in Join clause
clause as a result set.
User Defined Function can't
Procedures can returns XML Data Type.
returns XML Data Type.
User Defined Function doesn't
Procedures are support Exception handling
support Exception handling
User Defined Function doesn't
support set options like set
Procedures support set options like set ROWCOUNT
ROWCOUNT
Difference between Temp Table and Table Variable:
Temp Table or Table variable or CTE are commonly used for storing data temporarily in SQL Server
1.
2.
3.
4
5
6
7.
TEMPTABLE
TABLE-VARIABLE
Temp Tables are physically created
in the Tempdb database
can create constraints, index like
normal tables.
These tables act as the normal
table
You can create default values on
table variable columns
Temporary Table structure can be
changed after it’s creation.
Temp Table support DDL
statements like ALTER, CREATE,
DROP etc
Temp Table can’t be used in User
Defined Functions.
This is also created in the Tempdb database but not the
memory
You can not create constraints in table variables
It gets dropped once it comes out of batch
You can not create default values on table variable
columns
Temporary Table structure can’t be changed after it’s
creation.
Table Variables doesn’t support DDL statements like
ALTER, CREATE, DROP etc
Table Variables can be used in User Defined Functions.
Difference between cross join and Full outer join
CROSS-JOIN
1
No join conditions are specified
2
Results in pairs of rows.
3
Results in Cartesian product of two tables.
FULL-OUTER JOIN
A combination of both left and
right outer joins
Results in every row from both
of the tables , at least once.
Assigns NULL for unmatched
fields