Sql Mcq Interview Questions
Advance Your SQL Knowledge: Common Interview Questions and Solutions
Sql Mcq Interview Questions
SQL multiple-choice questions (MCQs) are commonly used in interviews to assess a candidate's knowledge and understanding of SQL concepts and syntax. These questions cover a wide range of topics such as querying databases, data manipulation, joins, functions, and more. Candidates are typically required to select the correct answer from a list of options provided. To excel in SQL MCQ interviews, candidates should have a solid understanding of SQL basics, be familiar with different types of SQL queries, and be able to apply their knowledge to solve various problem scenarios effectively. Practicing with SQL MCQs can help candidates improve their skills and boost their confidence when facing SQL-related interview questions.
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1 - What is SQL and its significance?
SQL stands for Structured Query Language and is a standard programming language designed for managing and manipulating relational databases. Its significance lies in its ability to allow users to access and manipulate data within databases efficiently.
2) What is the difference between SQL and MySQL?
SQL is a standard query language used to interact with relational databases, while MySQL is an open source relational database management system that uses SQL as its language to perform various operations.
3) Explain the difference between WHERE and HAVING clause in SQL.
The WHERE clause filters records before any groupings or aggregations occur, while the HAVING clause filters groups of records after the aggregations have been performed based on specified conditions.
4) What is a primary key in SQL?
A primary key is a column or a set of columns that uniquely identifies each row in a table. It must contain unique values and cannot have NULL values.
5) What is normalization in SQL and why is it important?
Normalization is the process of organizing data in a database efficiently. It reduces redundancy and dependency by organizing fields and table of a database. This ensures that the database is free from any anomalies and supports efficient querying.
6) Explain the difference between DELETE and TRUNCATE commands in SQL.
DELETE is a DML (Data Manipulation Language) command used to remove specific rows from a table, while TRUNCATE is a DDL (Data Definition Language) command that removes all rows from a table, but the table structure and definition remain intact.
7) Can you briefly explain the concept of joins in SQL?
Joins are used to combine rows from two or more tables based on a related column between them. The common types of joins include INNER JOIN (returns rows where there is a match in both tables), LEFT JOIN (returns all rows from the left table and matching rows from the right table), and RIGHT JOIN (returns all rows from the right table and matching rows from the left table).
8) What are the different constraints available in SQL?
Constraints in SQL are used to specify rules for data stored in tables. Some common constraints include NOT NULL (ensures a column cannot have NULL values), UNIQUE (ensures all values in a column are unique), PRIMARY KEY (combines NOT NULL and UNIQUE constraints), FOREIGN KEY (ensures data integrity by enforcing relationships between tables), and CHECK (checks the value being entered meets specified criteria).
9) Describe the difference between clustered and non clustered indexes in SQL.
A clustered index determines the physical order of data in a table, where the rows are stored on disk based on the index key. A table can only have one clustered index. On the other hand, non clustered indexes create a separate structure that contains the index key values and pointers to the actual rows in the table. A table can have multiple non clustered indexes.
10) What is a subquery in SQL and how is it different from a regular query?
A subquery, also known as a nested query, is a query nested within another query. It is used to return data that will be used in the main query. The result of the subquery can be used in conjunction with the main query to perform more complex queries. Regular queries, on the other hand, are standalone queries used to retrieve data from a single table or multiple tables based on specified conditions.
11) What are the different types of SQL commands?
SQL commands can be categorized into Data Definition Language (DDL) commands (CREATE, ALTER, DROP), Data Manipulation Language (DML) commands (SELECT, INSERT, UPDATE, DELETE), Data Query Language (DQL) commands (SELECT), and Data Control Language (DCL) commands (GRANT, REVOKE).
12) How do you handle NULL values in SQL queries?
NULL values in SQL represent missing or unknown data. To handle NULL values in SQL queries, you can use the IS NULL or IS NOT NULL operators to filter rows where a specific column contains a NULL value. Additionally, you can use functions like COALESCE or NVL to replace NULL values with a specified value in query results.
13) What is a view in SQL and why is it used?
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A view in SQL is a virtual table based on the result set of a SELECT statement. It does not store any data itself but provides a way to present data from one or more tables in a predefined format. Views are used to simplify complex queries, restrict access to specific columns, and provide a level of abstraction over the underlying tables.
14) What is a stored procedure in SQL and how is it different from a function?
A stored procedure is a set of SQL statements that are stored in the database and can be executed on demand. It can accept input parameters, perform calculations or operations, and return results. Unlike functions, stored procedures do not have a return type and can contain DML (Data Manipulation Language) and DDL (Data Definition Language) statements. Stored procedures are commonly used for modularity, reusability, and improved performance in database applications.
15) How do you optimize SQL queries for improved performance?
SQL query optimization involves various techniques such as creating indexes on frequently queried columns, minimizing the use of SELECT * to only retrieve necessary fields, avoiding nested queries when possible, using EXPLAIN to analyze query execution plans, and limiting the use of functions in WHERE clauses. Additionally, denormalizing data, caching query results, and ensuring proper indexing can help optimize SQL queries for better performance.
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