If you're looking for SQL Server Interview Questions for Experienced and Freshers, you are at the right place. There are a lot of opportunities from many reputed companies in the world. According to research, the average salary for SQL Server ranges from approximately $69,674 pa.
So, You still have the opportunity to move ahead in your career in SQL. Mindmajix offers Advanced SQL Server Interview Questions & Answers 2021 that helps you in cracking your interview & acquire your dream career as a SQL Server Developer.
|Types of SQL Server Interview Questions|
Top 10 Frequently Asked SQL Server Interview Questions:
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|MySQL Server Vs SQL Server|
|Function||MS SQL Server||MySql|
|Implementation Language||C++||C & C++|
|Supported Programming Lang||It supports C#, PHP, Python, Ruby, R, Visual Basic, Java, etc||It supports c++, C#, Java, PHP, Perl, Python, Ruby, Tcl, Delphi, D, etc|
|Server-Side Scripting.||Net & TransaScripting.||Yes, it supports|
|Concurrency||It supports, yes||It supports, yes|
|Consistency Concept's||It enables immediate consistency||It enables immediate consistency|
|Transaction concepts||It supports ACID||It supports ACID|
It is the way to eliminate redundant data
It is the reverse process of normalization. It increases query performance by reducing the joins. It is used for OLAP applications.
Relationships in SQL server are explained below
Candidate key, Alternate key, Composite key.
Lets you extend the base SQL Server data types by providing a descriptive name and format to the database
E.g. Flight_num appears in many tables and all these tables have varchar(8)
Create a user-defined data-type
A transaction is a logical unit of work in which, all the steps must be performed or none. ACID stands for Atomicity, Consistency, Isolation, and Durability. These are the properties of a transaction.
It plays a very major part. When building a new system, or adding to an existing system, the design must be correct. Ensuring that the correct data is captured and is placed in the appropriate tables, that the right relationships exist between the tables, and that data redundancy is eliminated is an ultimate goal when considering performance. Planning a design should be an iterative process, and constantly reviewed as an application is developed.
It is rare, although it should be the point that everyone tries to achieve, when the initial design and system goals are not altered, no matter how slightly. Therefore, a designer has to be on top of this and ensure that the design of the database remains efficient.
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A developer must investigate volumes of data (capacity planning), what types of information will be stored, and how that data will be accessed. If you are dealing with an upgrade to an existing system, analyzing the present data and where existing data volumes occur, how that data is accessed and where the current response bottlenecks are occurring, can help you search for problem areas in the design.
A new system would require a thorough investigation of what data will be captured, and looking at volumes of data held in other formats also will aid design. Knowing your data is just as important as knowing the constituents of your data. Also, constantly revisit your design. As your system is built, check relationships, volumes of data, and indexes to ensure that the physical design is still at its optimum. Always be ready to check your system by using tools like the SQL Server Profiler.
1.Logical – Planning, Analysis, and Design
2.Physical – Design, Implementation, and Maintenance
Cursors allow row-by-row processing of the result sets.
Types of cursors:
Static – Makes a temporary copy of the data and stores it in tempdb and any modifications on the base table do not reflect in data returned by fetches made by the cursor.
Dynamic – Reflects all changes in the base table.
Forward-only – specifies that the cursor can only fetch sequentially from first to last.
Keyset-driven – Keyset is the set of keys that uniquely identifies a row is built in a tempdb.
Disadvantages of cursors:
Each time you fetch a row from the cursor, it results in a network roundtrip, whereas a normal SELECT query makes only one roundtrip, however large the result set is. Cursors are also costly because they require more resources and temporary storage (which results in more IO operations). Further, there are restrictions on the SELECT statements that can be used with some types of cursors.
Most of the time set-based operations can be used instead of cursors.
Here is an example:
If you have to give a flat hike to your employees using the following criteria:
Salary between 30000 and 40000 — 5000 hike Salary between 40000 and 55000 — 7000 hike Salary between 55000 and 65000 — 9000 hike
In this situation, many developers tend to use a cursor, determine each employee’s salary, and update his salary according to the above formula. But the same can be achieved by multiple update statements or can be combined in a single UPDATE statement as shown below:
UPDATE tbl_emp SET salary = CASE WHEN salary BETWEEN 30000 AND 40000 THEN salary + 5000 WHEN salary BETWEEN 40000 AND 55000 THEN salary + 7000 WHEN salary BETWEEN 55000 AND 65000 THEN salary + 10000 END
another situation in which developers tend to use cursors: You need to call a stored procedure when a column in a particular row meets certain conditions. You don’t have to use cursors for this. This can be achieved using a WHILE loop, as long as there is a unique key to identify each row.
Here’s the basic syntax: (Also checkout SELECT in books online for advanced syntax).
SELECT select_list [HDEV:INTO new_table_] FROM table_source [HDEV:WHERE search_condition] [HDEV:GROUP BY group_by_expression] [HDEV:HAVING search_condition] [ORDER BY order_expression [ASC | HDEV:DESC] ]
Joins are used in queries to explain how different tables are related. Joins also let you select data from a table depending upon data from another table.
Types of joins: INNER JOINs, OUTER JOINs, CROSS JOINs. OUTER JOINs are further classified as LEFT OUTER JOINS, RIGHT OUTER JOINS, and FULL OUTER JOINS.
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Yes, very much. Check out BEGIN TRAN, COMMIT, ROLLBACK, SAVE TRAN, and @@TRANCOUNT
An extended stored procedure is a function within a DLL (written in a programming language like C, C++ using Open Data Services (ODS) API) that can be called from T-SQL, just the way we call normal stored procedures using the EXEC statement.
Yes, you can instantiate a COM (written in languages like VB, VC++) object from T-SQL by using the sp_OACreate stored procedure. Also see books online for sp_OAMethod, sp_OAGetProperty, sp_OASetProperty, sp_OADestroy.
USER_ID(). Also check out other system functions like USER_NAME(), SYSTEM_USER, SESSION_USER, CURRENT_USER, USER, SUSER_SID(), HOST_NAME().
Triggers are special kinds of stored procedures that get executed automatically when an INSERT, UPDATE or DELETE operation takes place on a table. In SQL Server 6.5 you could define only 3 triggers per table, one for INSERT, one for UPDATE, and one for DELETE. From SQL Server 7.0 onwards, this restriction is gone, and you could create multiple triggers per each action. But in 7.0 there’s no way to control the order in which the triggers fire. In SQL Server 2000 you could specify which trigger fires first or fires last using sp_settriggerorder.
Triggers can’t be invoked on demand. They get triggered only when an associated action (INSERT, UPDATE, DELETE) happens on the table on which they are defined. Triggers are generally used to implement business rules, auditing. Triggers can also be used to extend the referential integrity checks, but wherever possible, use constraints for this purpose, instead of triggers, as constraints are much faster.
Till SQL Server 7.0, triggers fire only after the data modification operation happens. So in a way, they are called post triggers. But in SQL Server 2000 you could create pre triggers also – INSTEAD OF triggers.
Virtual tables – Inserted and Deleted from the basis of trigger architecture.
Self-join is just like any other join, except that two instances of the same table will be joined in the query. Here is an example: Employees table which contains rows for normal employees as well as managers. So, to find out the managers of all the employees, you need a self join.
CREATE TABLE emp ( empid int, mgrid int, empname char(10) ) INSERT emp SELECT 1,2,’Vyas’ INSERT emp SELECT 2,3,’Mohan’ INSERT emp SELECT 3,NULL,’Shobha’ INSERT emp SELECT 4,2,’Shridhar’ INSERT emp SELECT 5,2,’Sourabh’ SELECT t1.empname [HDEV:Employee], t2.empname [HDEV:Manager] FROM emp t1, emp t2 WHERE t1.mgrid = t2.empid
Here’s an advanced query using a LEFT OUTER JOIN that even returns the employees without managers (super bosses)
SELECT t1.empname [HDEV:Employee], COALESCE(t2.empname, ‘No manager’) [HDEV:Manager] FROM emp t1 LEFT OUTER JOIN emp t2 ON t1.mgrid = t2.empid
SELECT DATENAME(dw, DATEADD(dd, – DATEPART(dd, GETDATE()) + 1, GETDATE())) AS FirstDay
SELECT TOP 1 salary FROM (SELECT DISTINCT TOP 6 salary FROM employee ORDER BY salary DESC) a ORDER BY salary
You can use index hint (index=index_name) after the table name. SELECT au_lname FROM authors (index=aunmind)
The ORDER BY clause sorts query results by one or more columns up to 8,060 bytes. This will happen by the time when we retrieve data from the database. Clustered indexes will physically sort data while inserting/updating the table.
A JOIN selects columns from 2 or more tables. A UNION selects rows.
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Referential integrity refers to the consistency that must be maintained between primary and foreign keys, i.e. every foreign key value must have a corresponding primary key value
it updates information about the distribution of key values for one or more statistics groups (collections) in the specified table or indexed view.
It returns the most recently created identity value for the tables in the current execution scope.
First and foremost, a stored procedure is a compiled set of code, where passing T-SQL through languages such as VB, Visual FoxPro, etc., means that the set of code needs to be compiled first. Although T-SQL within VB, etc., can be prepared before running, this is still slower than using a stored procedure. Then, of course, there is the security aspect, where, by building a stored procedure, you can place a great deal of security around it.
When dealing with sensitive data, you can use an encrypted stored procedure to hide sensitive columns, calculations, and so on. Finally, by using a stored procedure, I feel that transactional processing becomes a great deal easier and, in fact, using nested transactions becomes more insular and secure. Having to deal with transactions within code that may have front-end code, will slow up a transaction, and therefore a lock will be held for longer than necessary.
Fast performing stored procedures are like several other areas within T-SQL. Revisiting stored procedures every six months or so, to ensure that they are still running at their optimum performance is essential. However, actual techniques themselves include working with as short a transaction area as possible, as lock contention will certainly impact performance.
Recompiling your stored procedures after index additions if you are unable or not wishing to restart SQL Server, will also ensure that a procedure is using the correct index if that stored procedure is accessing the table which has received the new index. If you have a T-SQL command that joins several tables, and it takes a long time to return a value, first of all, check out the indexes.
But what you may find tends to help, is to break down the code and try to determine which join it is that is causing the performance problem. Then analyze this specific join and see why it is a problem. Always check out a stored procedure’s performance as you build it up by using the SHOWPLAN commands.
Also, try to use EXISTS, rather than a JOIN statement. An EXISTS statement will only join on a table until one record is found, rather than joining all the records. Also, try to look at using subqueries when you are trying to find a handful of values in the subquery statement, and there is no key on the column you are looking upon.
SQL Server cursors are perfect when you want to work one record at a time, rather than taking all the data from a table as a single bulk. However, they should be used with care as they can affect performance, especially when the volume of data increases. From a beginner’s viewpoint, I really do feel that cursors should be avoided every time because if they are badly written, or deal with too much data, they really will impact a system’s performance.
There will be times when it is not possible to avoid cursors, and I doubt if many systems exist without them. If you do find you need to use them, try to reduce the number of records to process by using a temporary table first, and then building the cursor from this. The lower the number of records to process, the faster the cursor will finish. Always try to think “out of the envelope”.
Perhaps one of the performance gains least utilized by developers starting in SQL Server is temporary tables. For example, using one or more temporary tables to break down a problem into several areas could allow blocks of data to be processed in their own individual way, and then at the end of the process, the information within the temporary tables merged and applied to the underlying data.
The main area of your focus should be, is there an alternative way of doing things? Even if I have to break this down into several chunks of work, can I do this work without using cursors, and so result in faster performance. Another area that you can look at is the use of CASE statements within your query.
By using a CASE statement, you can check the value within a column and make decisions and operations based on what you have found. Although you will still be working on a whole set of data, rather than a subset found in a cursor, you can use CASE to leave values, or records as they are, if they do not meet the right criteria. Care should be taken here though, to make sure that by looking at all the data, you will not be creating a large performance impact.
Again, look at using a subset of the data by building a temporary table first, and then merging the results in afterward. However, don’t get caught out with these recommendations and do any of them in every case. Cursors can be faster if you are dealing with small amounts of data. However, what I have found, to be rule number one, is to get a little data into your cursor as is needed.
Perhaps the best performance gain is when you can create a cursor asynchronously rather than needing the whole population operation to be completed before further processing can continue. Then, by checking specific global variables settings, you can tell when there is no further processing to take place. However, even here, care has to be taken. The asynchronous population should only occur on large record sets rather than those that only deal with a small number of rows.
Use the smallest set of data possible. Break out of the cursor loop as soon as you can. If you find that a problem has occurred, or processing has ended before the full cursor has been processed, then exit. If you are using the same cursor more than once in a batch of work, and this could mean within more than one stored procedure, then define the cursor as a global cursor by using the GLOBAL keyword, and not closing or deallocating the cursor until the whole process is finished. A fair amount of time will be saved, as the cursor and the data contained will already be defined, ready for you to use.
DATABASE PERFORMANCE OPTIMIZATION / TUNING
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This is a very open-ended question and there could be a lot of reasons behind the poor performance of a query. But some general issues that you could talk about would be:
An ER diagram or Entity-Relationship diagram is a special picture used to represent the requirements and assumptions in a system from a top-down perspective. It shows the relations between entities (tables) in a database.
A prime attribute is an attribute that is part of a candidate key.
The ACID properties. Atomicity, Consistency, Isolation, and Durability.
A non-prime attribute is an attribute that is not a part of a candidate key.
This means the transaction finish completely, or it will not occur at all.
Consistency means that the transaction will repeat predictably each time it is performed.
The data the transactions are independent of each other. The success of one transaction doesn’t depend on the success of another.
Guarantees that the database will keep track of pending changes so that the server will be able to recover if an error occurs.
A DBMS is a set of software programs used to manage and interact with databases.
It is a set of software programs used to interact with and manage relational databases. Relational databases are databases that contain tables.
Refers to computer-based techniques used in identifying, extracting, and analyzing business data, such as sales revenue by-products and/or departments, or by associated costs and incomes.
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Database normalization is the process of organizing the fields and tables of a relational database to minimize redundancy and dependency.
The way in which two or more concepts/entities are connected, or the state of being connected.
One to one, one to many, many to many, many to fixed cardinality.
An OLTP is the process of gathering the data from the users, and a database is initial information.
Identifying and non-identifying.
Something that exists by itself, although it need not be of material existence.
A table that is composed of foreign keys that points to other tables.
An attribute that would not exist if it were not for the existence of a relation.
An associative entity is a conceptual concept. An associative entity can be thought of as both an entity and a relationship since it encapsulates properties from both. It is a relationship since it is serving to join two or more entities together, but it is also an entity since it may have its own properties.
A derived attribute is an attribute that is obtained from the values of other existing columns and does not exist on its own. A derived persistent attribute is a derived attribute that is stored. A computed attribute is an attribute that is computed from internal system values.
Simple, composite (split into columns), multi-valued (becomes a separate table), derived, computed, derived persistent.
Yes, this is the requirement.
It is a key that is composed of one attribute.
Give/ recite the types of UDF functions.
Scalar, In-line, Multi
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Primary keys – Unique clustered index by default, doesn’t accept null values, only one primary key per table.
Foreign Key – References a primary key column. It can have null values. Enforces referential integrity.
Unique key – can have more than one per table. It can have null values. It cannot have repeating values. Maximum of 999 clustered indexes per table.
CTEs also is known as common table expressions are used to create a temporary table that will only exist for the duration of a query. They are used to create a temporary table whose content you can reference to simplify a query structure.
It is a column that is optimized for holding null values.
It wouldn’t allow the user Peter to operate CREATE TABLE regardless of his role.
It will allow the SELECT operation on the table ‘project’ by Peter.
It will revoke the permission granted on that table to Peter.
Database encryption, CDCs tables – For on the fly auditing of tables, Merge operation, INSERT INTO – To bulk inserts into a table from another table, Hierarchy attributes, Filter indexes, C like operations for numbers, resource management, Intellisense – For making programming easier in SSMS, Execution Plan Freezing – To freeze in place how a query is executed.
A table variable is faster in most cases since it is held in memory while a temporary table is stored on a disk. However, when the table variable’s size exceeds memory size the two table types tend to perform similarly.
1 byte, 2 bytes, 4 bytes, and 8 bytes.
It will give you the number of active transactions for the current user.
It is query bound.
It keeps a record of all activities that occur during a transaction and is used to roll back changes.
Before images refer to the changes that are rolled back on if a transaction is rolled back. After images are used to roll forward and enforce a transaction. Using the before images are called the undo activity. Using after images are called the redo activity.
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A shared lock locks a row so that it can only be read. An exclusive lock locks a row so that only one operation can be performed on it at a time. An update lock basically has the ability to convert a shared lock into an exclusive lock.
If you use TOP 3 WITH TIES *, it will return the rows, that have a similarity in each of their columns with any of the column values from the returned result set.
By concurrently running the same resources that access the same information in a transaction.
It is used for determining the amount of time that the system will wait for a lock to be released.
SELECT * FROM emp_table WHERE enter_date > ANY (SELECT enter_date FROM works_on)
SELECT * FROM emp_table WHERE enter_date > ALL (SELECT enter_date FROM works_on)
while, if, case, for each, etc.
It is used to determine whether a query returns one or more rows. If it does, the EXIST function returns TRUE, otherwise, it will return FALSE.
Inner Join: It is used to retrieve matching records from both the tables
SELECT employee.employee_name, employee.address, employee.salary, employee.age, FROM Department D INNER JOIN Employees E ON department.D_no=employee.D_no WHERE department.D_name= ‘ECE’
SELECT * FROM employee;
SELECT employee.employee_no, employee.employee_name, employee.address, employee.salary, employee.age, department.department_name FROM department D INNER JOIN employee E ON department.D_no=employee.D_no
SELECT employee.employee_no, employee.employee_name, employee.address, employee.salary, employee.age FROM department D INNER JOIN employee E ON dept.D_no=emp.D_no WHERE dept.D_name=’ECE’ and E.salary>20000
SELECT emp.e_no, emp.e_name, emp.address, emp.salary, emp.age, dept.dname FROM department D INNER JOIN employee E ON dept.D_no=emp.D_no WHERE dept.D_name=’ECE’ and emp.E_name like ‘a%’
SELECT emp.e_no, emp.e_name, emp.address, emp.salary, emp.age, dept.d_name FROM department D INNER JOIN employee E ON dept.D_no=emp.D_no WHERE E.age between 20 and 24
SELECT emp.e_no, emp.e_name, emp.address, emp.salary, emp.age, dept.d_name FROM department D INNER JOIN employee E ON dept.D_no=emp.D_no WHERE E.address=’hyd’
SELECT emp.e_no, emp.e_name, emp.address, emp.salary, emp.age, dept.d_name FROM department D INNER JOIN employee E ON dept.D_no=emp.D_no WHERE E.age>20 and E.salary>20000 and dept.D_name=’ECE’
|State ID||State Name|
|City ID||City Name||State ID|
Blood Group Details
|Blood Group ID||Blood Group|
|Donor ID||Donor Name||Phone Number||City ID||Blood Group ID|
SELECT C.City_Name FROM State S INNER JOIN City C ON S.State_ID WHERE S.State_Name ‘AP’
SELECT D.Donor_ID, D_Name, D_Phone No, C.City_Name FROM Donor D INNER JOIN City C ON D.City_ID=C.City_ID
SELECT D.Donor_ID, D_Name, D_Phone No, B.Blood_Group FROM Donor D INNER JOIN Blood B ON D.Blood_ID=B.Blood_ID;
SELECT D.Donor_ID, D_Name, D_Phone No, C.City_Name FROM Donor D INNER JOIN City C ON C.City_ID=D.City_ID WHERE C.City_Name=’hyderabad’
SELECT D.Donor_ID, D_Name, D_Phone No FROM Donor D INNER JOIN Blood B ON D.Donor_ID=B.Blood_ID WHERE B.Blood_Group=’A+ve’
SELECT D.Donor_ID, D_Name, D_Phone No, C.City_Name B.Blood_Group FROM Blood B INNER JOIN Donor D ON D.Blood_ID=B.Donor_Name INNER JOIN City C ON D.City_ID=C.City_ID
SELECT D.Donor_Name, D. Phone_Number, B.Blood_Group FROM Donor D INNER JOIN Blood B ON D.Blood_ID=B.Blood_ID INNER JOIN City C ON D.City_ID=C.City_ID WHERE C.City_Name=’hyderabad’ and B.Blood_Group=’A+ve’
Outer Join A join that includes rows even if they do not have related rows in the joined table is an Outer Join. You can create three different outer joins to specify the unmatched rows to be included:
Employee Details Table
Department Details Table
SELECT e.* FROM Employee E LEFT OUTER JOIN Department D ON E.D_no WHERE D.D_No IS NULL
SELECT * FROM Employee E WHERE E_No=101
SELECT * FROM Employee E WHERE E_No IS NULL
SELECT D.* FROM Employee E RIGHT OUTER JOIN Department D ON E.D.No=D.D_No WHERE E.D_No IS NULL
SELECT E.*, D.* FROM Employee E FULL JOIN Department D ON E.D_No=D.D_No WHERE E.D_No IS NULL or D.D_No IS NULL
Department Details Table
Course Details Table
Student Details Table
Enroll Details Table
Employee Details Table
Semester Details Table
Course Department Details
Instructor Details Table
Course Instructor Table
SELECT S.Student_No, S.Student_Name, S.Enroll_Date, D.Dept_Name FROM Student S INNER JOIN Enroll E ON S.Student_No=E.Student_No INNER JOIN Department D ON D.Dept_No=E.Dept_No
SELECT E.Emp_No, E.Emp_Name, A.Address, D.Dept_Name FROM Employee E INNER JOIN Address A ON E.Emp_No=A.Emp_No INNER JOIN Instructor I ON A.Emp_No=I.Emp_No INNER JOIN Department D ON I.Dept_No=D.Dept_No
SELECT C.Course_Name FROM Department D INNER JOIN Course Department CD ON D.Dept_NO=CD.Dept_NO INNER JOIN Course C ON CD.CourseDept_ID=C.Course_ID WHERE D.Dept_Name=’ECE’
SELECT S.Student_No, S.Student_Name, S.Enroll_Date, D.Dpet_Name, Sem.Student_Name FROM Enroll E INNER JOIN Student S ON S.Student_No=E.Student_No INNER JOIN Deprtment D ON E.Dept_No=D.Dept_No INNER JOIN Semester SE ON E.Student_ID=Sem.Student_ID
SELECT C.Course_Name FROM Department D INNER JOIN Syllabus Sy ON D.Dept_No=Sy.Dept_No INNER JOIN Course C ON Sy.Course_ID=C.Course_ID INNER JOIN Semester Se ON Syllabus_Sy_ID=Se_Sy_ID WHERE D.Dept_Name=’ECE’ and Se.Semester=’1’
SELECT E.Emp_Name FROM Employee E INNER JOIN Course Instructor Ci ON E.Emp_No=Ci.Emp_No INNER JOIN Semester Se ON Se.Student_ID=Ci.Student_ID INNER JOIN Dept D ON Ci.Dept_No=D.Dept_No WHERE D.Dept_Name=’ECE’ and Se.Student_Name=’1’
SELECT S.Student_NO, S.Student_Name, S.Enroll_Date FROM Student S INNER JOIN Enroll E ON S.Student_No=E.Student_No INNER JOIN Department D ON E.Dept_No=D.Dept_No WHERE D.Dept_Name=’ECE’
SELECT S.Student_No, S.Student_Name, S.Enroll_Date, D.Dept_Name FROM Student S INNER JOIN Enrollment E ON S.Student_No=E.Student_No INNER JOIN Department D ON D.Dept_No=E.Dept_No INNER JOIN Semester Se ON E.Student_ID=Se.Student_ID WHERE D.Dept_Name=’ECE’ and Se.Student_Name=’1’
SELECT E.Emp_Name FROM Employee E INNER JOIN Course Instructor Ci ON E.Emp_No=Ci.Emp_No INNER JOIN Course C ON Ci.Course_ID=C.Course_ID WHERE C.Course_Name=’EDC’
SELECT E.Emp_No, Emp_Name, D.Dept_Name FROM Employee E INNER JOIN Address A ON E.Emp_No=A.Emp_No INNER JOIN Instructor I ON A.Emp_No=I.Emp_No INNER JOIN Department D ON I.Dept_No=D.Dept_No WHERE A.Address=’hyderabad’
Using Range Operator:: BETWEEN, NOT BETWEEN
SELECT * FROM Employee WHERE Salary>20000 AND Age>23;
SELECT * FROM Employee WHERE Salary>20000 AND Dept_Name=’ECE’
SELECT * FROM Employee Details WHERE Age BETWEEN 18 AND 22;
SELECT * FROM Employee WHERE Salary BETWEEN 20000 AND 23000;
SELECT * FROM Employee WHERE Age NOT BETWEEN 18 AND 22;
Using String Operators:: LIKE, NOT LIKE
SELECT * FROM Employee WHERE Emp_Name LIKE ‘a%’
a% ----> starts with a %a ----> ends with a
SELECT * FROM Employee WHERE Salary>20000 AND Age>20 AND Emp_Name LIKE ‘a%’
SELECT * FROM employee WHERE Emp_Name NOT LIKE ‘a%’
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