Microsoft SQL Server is a Relational Database Management System (RDBMS) developed by Microsoft. It's designed to store, retrieve, and manage data in a relational database format, using Structured Query Language (SQL). Applications and tools interact with SQL Server to access and modify data, using Transact-SQL (T-SQL), which is Microsoft's version of SQL.

A table is a structured container for storing data. It organizes data into rows (records) and columns (fields), much like a spreadsheet. Each row represents a unique piece of information, and each column holds a specific attribute or piece of data about that information. Tables are fundamental to relational databases, allowing you to store and manage data in a well-organized and efficient manner. .

A column (or set of columns) that uniquely identifies each row in a table.

A column that creates a relationship between two tables.

Normalization is the process of organizing data in a database. It includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency.

Denormalization, on the other hand, is the process of combining tables to reduce the complexity of database queries. This can introduce redundancy but may lead to improved performance by reducing the number of joins required..

Clustered indexes sort and store the data rows in the table or view based on their key values. These key values are the columns included in the index definition. There can be only one clustered index per table, because the data rows themselves can be stored in only one order.

A non-clustered index in SQL is an index structure that is separate from the actual data table. It stores a copy of the indexed columns and a pointer to the data row where the actual data is located. This allows for multiple non-clustered indexes on a single table, unlike clustered indexes which can only have one per table.

In SQL, a view is a virtual table based on the result-set of an SQL statement. It's like a table in that it has rows and columns, but it doesn't store any data itself. Instead, it acts like a filter on one or more underlying tables, presenting data as if it were a single table.

Here's a more detailed breakdown:

• Virtual Table: A view doesn't physically store data; it's a stored query.
• Based on a Query: The data in a view is derived from the results of a SELECT statement that defines the view.
• Like a Table: You can query, insert, update, and delete data through a view as if it were a regular table.
• Security and Simplification: Views can be used for security purposes by limiting user access to specific data subsets. They can also simplify complex queries by combining multiple tables into a single, user-friendly view.
• Dynamic Updates: Changes to the underlying tables are reflected in the view's data.

A SQL stored procedure is a pre-compiled group of SQL statements that are stored in a database and can be executed as a single unit. It allows for reusability, modularity, and improved security. Stored procedures can accept input parameters and return multiple output values, making them versatile for various database operations..

In SQL Server, a trigger is a special type of stored procedure that automatically executes when a specific event occurs within the database. These events are typically data manipulation language (DML) operations like INSERT, UPDATE, or DELETE on a table. Triggers help automate tasks, enforce data integrity, and maintain accurate records of database activities.

Elaboration

• Purpose: Triggers are designed to respond to specific events within the database, allowing you to automatically execute code in reaction to those events.
• DML Triggers: These are the most common type of trigger and are associated with tables or views. They fire when a DML operation is performed on that table or view.
• Event-Driven: Triggers are event-driven, meaning they are activated by a specific event occurring in the database.
• Data Integrity and Business Rules: Triggers can be used to enforce business rules and data integrity by automatically executing code that validates or modifies data during an INSERT, UPDATE, or DELETE operation.

Examples

• Automatically updating an audit log table whenever data is modified in another table.
• Preventing invalid data from being inserted into a table by checking constraints within the trigger.
• Triggering a notification when a specific event occurs, such as a large number of orders being placed.

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In SQL Server, DELETE and TRUNCATE are both used to remove data from a table, but they differ in their approach and impact. DELETE removes rows based on specified conditions and logs each deleted row, allowing for rollback within a transaction. TRUNCATE removes all rows from a table faster by deallocating data pages, doesn't log individual deletions, and is typically not rollbackable.

Key Differences

Deletion Method

• DELETE: Removes individual rows based on a WHERE clause condition. Logs each deleted row, allowing for rollbacks within a transaction.
• TRUNCATE: Removes all rows in the table by deallocating the data pages. It does not log individual row deletions and is not typically rollbackable.

Logging

• DELETE: Logs each deleted row, consuming more transaction log space.
• TRUNCATE: Logs only the page deallocation, using less transaction log space.

Speed

• DELETE: Slower due to row-by-row deletion and transaction logging.
• TRUNCATE: Faster as it deallocates the entire table's data pages in one operation.

Rollback

• DELETE: Can be rolled back within a transaction.
• TRUNCATE: Typically not rollbackable.

Triggers

• DELETE: Triggers defined on the table are fired for each deleted row.
• TRUNCATE: Triggers are not fired.

Constraints

• DELETE: Respects constraints (e.g., foreign keys) during deletion.
• TRUNCATE: Bypasses constraints, making it faster.

Use Cases

• DELETE: Used for removing specific rows or subsets of data based on conditions.
• TRUNCATE: Used for resetting a table to an empty state or for quickly removing all data when rollback is not needed.

Summary

DELETE is more flexible for removing specific rows, while TRUNCATE is faster for removing all rows when rollback is not a concern.

In SQL Server, there are several types of joins, each designed to combine data from two or more tables based on a specific relationship. The main types are: Inner Join, Left Outer Join, Right Outer Join, Full Outer Join, and Cross Join. Additionally, Self Join, while not a distinct join type, can be implemented using any of the joins mentioned above.

Join Types Breakdown

Inner Join

Returns only the rows where the join condition is met in both tables.

Left Outer Join (or Left Join)

Returns all rows from the left table and the matching rows from the right table. If a match isn't found, NULL values are returned for the right table columns.

Right Outer Join (or Right Join)

Returns all rows from the right table and the matching rows from the left table. If a match isn't found, NULL values are returned for the left table columns.

Full Outer Join (or Full Join)

Returns all rows from both tables. If a match is found, the matching values are returned; otherwise, NULL values are used for the missing columns.

Cross Join

Returns the Cartesian product of the two tables, meaning all possible combinations of rows from both tables.

Self Join

Joins a table to itself. This is useful for comparing rows within the same table. A Self Join can be implemented using Inner Join, Outer Join, or Cross Join depending on the specific requirements.

In SQL Server, WHERE and HAVING are both used for filtering data, but they apply to different stages of the query process. WHERE filters rows before any grouping or aggregation, while HAVING filters grouped data after aggregation. In essence, WHERE works on individual rows, and HAVING works on groups of rows.

Detailed Breakdown

WHERE Clause

• Filters rows based on conditions that apply to individual rows in the table.
• Applies before the GROUP BY clause.
• Used with standard operators and comparisons.
• Examples:
  • WHERE salary > 50000
  • WHERE department = 'IT'

HAVING Clause

• Filters groups of rows based on conditions that apply to aggregated values (e.g., SUM(), AVG(), COUNT()).
• Applies after the GROUP BY clause.
• Must be used with aggregate functions.
• Examples:
  • HAVING AVG(salary) > 60000
  • HAVING COUNT(*) > 5

In Simpler Terms

• Think of WHERE as filtering the data before you group it.
• Think of HAVING as filtering the groups after they are created.
• If you want to filter rows based on individual column values, use WHERE.
• If you want to filter groups based on aggregate values of those groups, use HAVING.

In SQL Server, indexing refers to creating special lookup tables that speed up data retrieval operations. These indexes act like a table of contents, allowing the database server to quickly locate data within a table without scanning every row. By using indexes, you can significantly improve query performance, especially for tables with large amounts of data.

Key Concepts

Purpose

Indexes help the database engine quickly find the specific rows that match a query's criteria.

Speed

Without indexes, the database would have to scan every row in a table to find the data you're looking for, which can be slow for large tables.

Structure

Indexes are typically implemented as B-tree structures, which are efficient data structures for searching.

Columns

Indexes are usually created on columns that are frequently used in WHERE clauses or JOIN conditions in queries.

Types

SQL Server supports various index types, including:

• Clustered Indexes
• Nonclustered Indexes

How It Works

1. Data Organization: An index stores a sorted representation of the indexed columns, along with pointers to the actual data rows in the table.
2. Efficient Search: When a query uses a column that is indexed, the database engine can use the index to quickly find the rows that match the query’s criteria.
3. Reduced Full Table Scans: Indexes help avoid scanning the entire table, saving time and system resources.

Benefits of Using Indexes

• Faster Query Performance: Significantly reduces the time it takes to retrieve data.
• Improved Application Responsiveness: Faster queries lead to a better user experience.
• Reduced Disk I/O: Less data needs to be read from disk when using indexes.

Considerations

Over-Indexing

Adding too many indexes can slow down INSERT, UPDATE, and DELETE operations and consume extra storage.

Maintenance

Indexes need to be maintained. They can become fragmented or outdated if the underlying data changes frequently, which may require regular rebuilding or reorganizing.

A temporary result set used within a query.

A temporary table used to store data temporarily.

#TempTable supports indexes and transactions. TableVariable is stored in memory, faster for small data.

UNION removes duplicates. UNION ALL keeps duplicates.

A sequence of operations performed as a single logical unit.

Atomicity, Consistency, Isolation, Durability

A tool to monitor SQL Server events.

ROW_NUMBER(): Unique values
RANK(): Gaps in ranking
DENSE_RANK(): No gaps

A container that holds database objects like tables and views.

NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT

A visual representation of how SQL Server executes a query.

Use indexes, avoid SELECT *, use joins appropriately, review execution plans.

Dividing large tables into smaller, manageable pieces.

Access objects in the same order, keep transactions short, use appropriate isolation levels.

Read Uncommitted, Read Committed, Repeatable Read, Serializable, Snapshot

A subquery that depends on the outer query.

master, model, msdb, tempdb, resource

Use TRY...CATCH blocks.

CHAR: Fixed length, VARCHAR: Variable length

Database Console Commands used for maintenance and validation.

A disaster recovery method by shipping logs to a secondary server.

Copying and distributing data across servers.

Synchronous: Waits for commit. Asynchronous: Doesn’t wait.

A high availability feature for database failover.

Reads data without locking, allowing dirty reads.

Use indexing, check execution plans, optimize joins and subqueries.

Backup/Restore, Detach/Attach, or use SSMS export tools.

A tool to schedule jobs and automate tasks.

Allow queries to be run on external databases.

Use SQL Server Agent jobs and define steps/triggers.

Stores temporary tables, variables, and intermediate query results.

Use sp_who2, sys.dm_exec_requests, and review lock chains.