In this piece, we'll go over LSN, the Retrieved function fn_dblog(), and the Recovery Models that go with it in further depth.

Log of SQL Server Transactions
Every SQL Server database has a transaction log that records all transactions as well as the database changes made by each transaction. The transaction log is a crucial component of the database, and if there is a system failure, the transaction log may be necessary to restore consistency to your database.

The SQL Server Transaction Log is useful for recovering deleted or updated data if you run a DELETE or UPDATE operation with the incorrect condition or without filters. This is accomplished by listening to the records included within the SQL Server Transaction Log file. DML operations such as INSERT, UPDATE, and DELETE statements, as well as DDL operations such as CREATE and DROP statements, are among the events that are written to the SQL Server Transaction Log file without any additional configuration from the database administrator.

LSN Function Retrieving from Transaction Log
fn_dblog() is a function.

The fn_dblog() function is one of the SQL Server undocumented functions; it allows you to see transaction log records in the active section of the transaction log file.
fn_dblog() Arguments

The fn_dblog() function takes two arguments.

• The first is the initial log sequence number, abbreviated as LSN. You can alternatively use NULL to return everything from the beginning of the log.
• The second is the LSN at the conclusion. You can alternatively specify NULL, which indicates that you wish to return everything to the log's conclusion.

fn_db_log()
SELECT * FROM fn_dblog (
              NULL, -- Start LSN nvarchar(25)
              NULL  -- End LSN nvarchar(25)
       )

We will not discuss the details of the function but list the possibly useful columns below:

Operation Clumn in fn_dblog()
The ‘Operation’ column indicates the type of operation that has been performed and logged in the transaction log file.

Such as test.

LOP_INSERT_ROWS

LOP_MODIFY_ROW

LOP_DELETE_ROWS

LOP_BEGIN_XACT

Recovery Models
SQL Server backup and restore operations occur within the context of the recovery model of the database. Recovery models are designed to control transaction log maintenance. A recovery model is a database property that controls how transactions are logged, whether the transaction log requires (and allows) backing up, and what kinds of restore operations are available.

Three recovery models exist:
    Simple --- Operations that require transaction log backups are not supported by the simple recovery model.
    Full, and
    Bulk-logged.

Typically, a database uses the full recovery model or simple recovery model. A database can be switched to another recovery model at any time. By default, when a new database is created within Microsoft SQL, the recovery model option is set to full.

Recovery Option
Restoring the db with the RECOVERY option is the default option for users with FULL backup. However, if you have different types of backups (differential, transactional, etc.), you may need to use the NORECOVERY option to combine the backups.

Even Recover database without Restore
RESTORE DATABASE *database_name* WITH RECOVERY

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There are two methods for determining whether a SQL table is temporal: Examine the table definition. There are two system-versioned period entries in temporal tables: sys_start_time and sys_end_time. These columns include the beginning and end dates of the time period for which the row is valid. A table with these two columns is a temporal table.

The OBJECTPROPERTY() function should be used. The OBJECTPROPERTY() function returns information about a database object, such as whether it is a temporal table. To determine whether a table is temporal, use the SQL statement:

SELECT OBJECTPROPERTY(object_id('table_name'), 'IsTemporalTable');

If the query returns a value of 1, the table is temporal. Otherwise, the table is not chronological. For instance, the following SQL statement will determine whether the Products table is temporal:

SELECT OBJECTPROPERTY(object_id('Products'), 'IsTemporalTable');

If the result of the query is 1, then the Products table is temporal. Otherwise, the Products table is not temporal.

Note: Temporal tables are only supported in Microsoft SQL Server 2016 and later versions.

Here are some additional things to keep in mind about temporal tables:

• Temporal tables can be either system-versioned or history-table versioned. System-versioned temporal tables are managed by the database engine, while history-table versioned temporal tables are managed by the user.
• Temporal tables can be used to store both current and historical data. Current data is stored in the table, while historical data is stored in a history table.
• Temporal tables can be used to query both current and historical data. The FOR SYSTEM_TIME clause can be used to specify the time period for which the data should be returned.

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This article will teach you about optional parameters and how to use them in stored procedures.

Parameters that are optional
Optional parameters are a sort of parameter in which you can declare a default value, and if that parameter is not passed, the default value is used.
By using several examples, let's establish a "Employees" database and learn how to write a stored method with Optional Parameters.

CREATE TABLE Employees (
EMPID INT PRIMARY KEY,
EMPName VARCHAR (50),
EMPAddress VARCHAR (Max),
ContactNumber VARCHAR (10),
EMPSalary INT
)

--Inserting multiple records in one table.

INSERT INTO Employees (EMPID, EMPName, EMPAddress, ContactNumber, EMPSalary)
VALUES (101, 'Peter', 'London', NULL, 65000),
(102, 'Scott', 'Manchester', 1234567809, 55000),
(103, 'Laura', 'Leeds', NULL, 95000),
(104, 'Samuel', 'Liverpool', 1234506789, 35000)

Now check the table by running a select query.
SELECT * FROM Employees;

Now create stored proc, which inserts records in the table with mandatory parameters.
CREATE OR ALTER PROCEDURE usp_InsertEmployeesRecords
@EMPID INT PRIMARY KEY,
@EMPName VARCHAR (50),
@EMPAddress VARCHAR (Max),
@ContactNumber VARCHAR (10),
@EMPSalary INT
AS
BEGIN
    INSERT INTO Employees VALUES (@EMPID, @EMPName, @EMPAddress, @ContactNumber, @EMPSalary)
    SELECT * FROM Employees                     --Checking if all the records inserted in Employee table or not.
END

The stored procedure “usp_InsertEmployeesRecords” was created
Now let’s execute the same procedure and see the output.

EXECUTE usp_InsertEmployeeRecords 105, 'Maria', 'Leeds', 1203456789, 70000

As you can see above, all records are inserted in the table as values passed for all mandatory parameters.
Now let’s go with another scenario when a user doesn’t have all the information and inserts records in the table for example missing contact number.
Executing the same procedure again.

EXECUTE usp_InsertEmployeesRecords @EMPID = 106, @EMPName = 'Ricky', @EMPAddress = 'London', @EMPSalary = 80000;

After executing the procedure, we got the following error, which means we had created proc with mandatory parameters, and we have not passed the values for all the parameters.

Now to overcome with above error, let's create the proc with an optional parameter.

CREATE OR ALTER PROCEDURE usp_InsertEmployeesRecordsOptParam
@EMPID INT PRIMARY KEY,
@EMPName VARCHAR (50),
@EMPAddress VARCHAR (Max),
@ContactNumber VARCHAR (10) = 'NULL',
@EMPSalary INT
AS
BEGIN
    INSERT INTO Employees VALUES (@EMPID, @EMPName, @EMPAddress, @ContactNumber, @EMPSalary)
    SELECT * FROM Employees                     --Checking if all the records inserted in Employee table or not.
END

The stored procedure “usp_InsertEmployeesRecordsOptParam” was created, as you can see in the above screenshot.

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A temporal table is a sort of database table that is intended to track changes over time without the need for sophisticated custom programming or triggers. It accomplishes this by including system-generated columns in the table that reflect each row's valid time period. System-Versioned Temporal Tables are another name for them.

Temporal Tables with System Verification

The system automatically tracks changes to the data over time in this form of temporal table by creating a new version of each row every time it is modified or removed. The original row is kept with its valid time period, and a new version with its own valid time period is created. This enables you to view the table's history at any moment and query it as if it were a snapshot of the data at that time.

CREATE TABLE dbo.MyTemporalTable (
Id INT PRIMARY KEY,
Name VARCHAR(50),
EffectiveStartTime DATETIME2 GENERATED ALWAYS AS ROW START,
EffectiveEndTime DATETIME2 GENERATED ALWAYS AS ROW END,
PERIOD FOR SYSTEM_TIME (EffectiveStartTime, EffectiveEndTime)
) WITH (SYSTEM_VERSIONING = ON (HISTORY_TABLE = dbo.MyTemporalTable_History));

How to query the temporal table?
Temporal tables, like database tables, can be queried. To query data across the main and history tables, a new clause FOR SYSTEM_TIME with five temporal-specific sub-clauses has been added. This new SELECT statement syntax is usable on a single table, via multiple joins, and via views on top of several temporal tables.

The five sub-clauses
AS OF <DateTime>
FROM <EffectiveStartTime> TO <EffectiveEndTime>
BETWEEN <EffectiveStartTime> AND <EffectiveEndTime>
CONTAINED IN (EffectiveStartTime, <EffectiveEndTime>)
ALL

-- AS OF (EffectiveStartTime<= date_time AND EffectiveEndTime> date_time)
SELECT * FROM dbo.MyTemporalTable FOR SYSTEM_TIME AS OF '2023-03-10 T10:00:00.0000000'

-- FROM (EffectiveStartTime< date_time AND EffectiveEndTime > date_time)
SELECT * FROM dbo.MyTemporalTable FOR SYSTEM_TIME FROM '2022-01-01' TO '2022-12-31'

--BETWEEN (EffectiveStartTime<= date_time AND EffectiveEndTime > date_time)
SELECT * FROM dbo.MyTemporalTable FOR SYSTEM_TIME BETWEEN '2022-01-01' AND '2022-12-31'

--CONTAINED (EffectiveStartTime>= date_time AND EffectiveEndTime <= date_time)
SELECT * FROM dbo.MyTemporalTable FOR SYSTEM_TIME CONTAINED IN ('2023-01-01', '2023-02-28')

--ALL (All rows)
SELECT * FROM dbo.MyTemporalTable FOR SYSTEM_TIME ALL

How to drop the temporal table?
Dropping a temporal table is similar to dropping any other table in your database. However, we need to consider a few things before dropping a temporal table to avoid data loss and ensure that the cleanup process is handled correctly.

Here are the general steps to drop a temporal table.

Drop the dependent objects: Before dropping the temporal table, you should first drop any dependent objects, such as triggers, indexes, or foreign keys that reference the temporal table.

Disable temporal feature: Disable the temporal feature of the table by running the ALTER TABLE statement to remove the system-versioning or application-time period specification.
ALTER TABLE dbo.MyTemporalTable SET (SYSTEM_VERSIONING = OFF);

Drop the temporal table: After removing all dependent objects and disabling the temporal feature of the table, drop the table using the DROP TABLE statement.
DROP TABLE IF EXISTS dbo.MyTemporalTable;

Limitations of temporal table

• Storage requirements: System-versioned temporal tables require additional storage to maintain historical versions of the data. The size of the history table can grow quickly, especially for tables with many updates or deletes, which can impact performance and increase storage costs.
• Query performance: Querying a temporal table can be more complex than querying a regular table, especially if you need to retrieve data from both the current and historical versions of the data. Depending on the database system, query performance may be slower for temporal tables than for regular tables.
• Configuration complexity: Setting up a temporal table requires some additional configuration steps compared to a regular table. This can make it more complex to create and maintain the table, especially if you are not familiar with the temporal table syntax.
• Compatibility: Not all database systems support temporal tables. While SQL Server, Oracle, and PostgreSQL all support temporal tables, other systems may not. This can limit your ability to use temporal tables if you need to migrate to a different database system in the future.
• Migration complexity: If you have an existing table that you want to make temporal, you may need to perform a data migration to move the existing data to the history table. This can be complex and time-consuming, especially for large tables.

Advantages of temporal table
The main advantage of a temporal table is that it allows you to maintain a full history of changes to your data over time. This provides several benefits, including:

• Auditing: With a temporal table, you can easily track changes to your data over time. This is useful for auditing purposes, as you can see when and how data was modified, deleted, or added.
• Compliance: Many industries have regulatory requirements that mandate data retention policies. By maintaining a full history of changes to your data, you can ensure compliance with these requirements.
• Recovery: In the event of data loss or corruption, a temporal table can be used to recover lost data. You can restore the table to a previous point in time and recover data that was lost or corrupted.
• Analysis: A temporal table can be used for trend analysis, as you can see how data has changed over time. This can be useful for identifying patterns, trends, and anomalies in your data.
• Data versioning: With a temporal table, you can easily maintain multiple versions of your data. This is useful if you need to maintain different versions of a record for different users or if you need to create a new version of a record without overwriting the previous version.

Overall, the temporal table provides a powerful mechanism for maintaining a full history of changes to your data. This can be useful for a variety of purposes, including auditing, compliance, recovery, analysis, and data versioning. By understanding the limitations of temporal tables, you can make an informed decision about whether they are the right solution for your needs.

Dynamic sorting in SQL Server allows you to dynamically and flexible sort the result set of a query depending on one or more columns. This means that rather than hardcoding the sorting order of the result set in the query, you can determine it at runtime.

There are various approaches to implementing dynamic sorting in SQL Server, but the most frequent is to utilize the ORDER BY clause with a variable containing the column name(s) to sort on.

Here’s an example
DECLARE @SortColumn NVARCHAR(50) = 'LastName'
DECLARE @SortOrder NVARCHAR(4) = 'ASC'

SELECT *
FROM Customers
ORDER BY
  CASE WHEN @SortOrder = 'ASC' THEN
    CASE @SortColumn
      WHEN 'FirstName' THEN FirstName
      WHEN 'LastName' THEN LastName
      WHEN 'City' THEN City
    END
  END ASC,
  CASE WHEN @SortOrder = 'DESC' THEN
    CASE @SortColumn
      WHEN 'FirstName' THEN FirstName
      WHEN 'LastName' THEN LastName
      WHEN 'City' THEN City
    END
  END DESC

In this example, the @SortColumn variable determines which column to sort on, and the @SortOrder variable determines whether to sort in ascending or descending order. The CASE statements in the ORDER BY clause dynamically generate the sort expression based on the values of these variables.

Note that dynamic sorting can be potentially risky, as it can expose your database to SQL injection attacks. It’s important to validate and sanitize any user input that is used to determine the sorting order.

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The migration of data from one database to another is a regular job performed by a Database Administrator. This scenario frequently occurs when businesses need to integrate data from several sources, migrate data to a data warehouse, or do data analytics on a collection of data held in various databases. Ingesting data from one table in a database to another table in a different database is a common scenario, especially when both tables have identical columns. with this article, we'll go over how to do this efficiently with SQL Server Management Studio.

Create the Database Connection
Before you can transfer data between tables in different databases, you must first ensure that you have the required permissions and connectivity to both databases, which frequently entails defining connection settings such as server addresses, authentication credentials, and database names.

Recognize the Tables
It is critical that you have a thorough understanding of both the source and destination tables. The tables in our case share the same columns, which simplifies the operation. You should still double-check that the column names, data types, and constraints are consistent between the two tables. Any inconsistencies can cause data integrity difficulties during the transmission.

Create and run the SQL query
To transfer the data, create a SQL query with the INSERT INTO... function. SELECT the typically used statement for that purpose. The source table, the fields to be transferred, and the destination table should all be specified in the query. After you've written the SQL query, click the Execute button to run it. In our case, we wish to move the data from the SalesData database's DimCustomer table to the data warehouse database's DimCustomer table. The table structure in both tables is the same.

We wrote a simple query in the screenshot below to retrieve all of the records from that table. In the next screenshot below, we switched to the destination database: DataWarehouse, and we selected all the columns in the dimCustomer table without any data ingested thus far. This is necessary to verify the structure of the destination table.

SELECT * FROM DimensionCustomer;

In the following snapshot, we went to the destination database, DataWarehouse, and selected all of the columns in the dimCustomer table with no data ingested thus far. This is required to validate the destination table's structure.

In the next screenshot below, we wrote and executed the query, and from the message displayed, a total of 18,484 records were inserted into the destination table.

INSERT INTO DataWarehouse.dbo.DimCustomer (
    CustomerKey,
    FirstName,
    LastName,
    BirthDate,
    MaritalStatus,
    Gender,
    EmailAddress,
    AnnualIncome,
    NumberofChildren,
    EducationalLevel,
    Address,
    PhoneNumber,
    FirstTransactionDate
)
SELECT
    CustomerKey,
    FirstName,
    LastName,
    BirthDate,
    MaritalStatus,
    Gender,
    EmailAddress,
    AnnualIncome,
    NumberofChildren,
    EducationalLevel,
    Address,
    PhoneNumber,
    FirstTransactionDate
FROM SalesData.dbo.DimensionCustomer;

Verify the Results
After the query execution is complete, it's essential to verify the results. To verify, we executed a simple below mentioned query, and all the records were returned.
SELECT * FROM dimCustomer;

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Today, I'd want to revisit one of the most typical interview questions and replies, which I see frequently referenced in subsequent interviews.

Transaction
A transaction is a collection of SQL statements that operate as a single unit. In layman's terms, a transaction is a unit in which a series of tasks is completed in order to finish the entire activity. To better appreciate this, consider a bank transaction.

SQL Server ACID Properties
SQL Server's ACID properties assure data integrity during a transaction. A transaction is a series of SQL (insert, update, and delete) statements that are handled as a single unit and are executed using the completed or Not principle. To be successful, a transaction must adhere to the ACID Properties. Atomicity, Consistency, Isolation, and Durability are abbreviated as ACID.

Atomicity
Every transaction adheres to atomicity. It indicates that if a transaction is initiated, it must be completed or rolled back. To illustrate, if a person transfers money from account "A" to account "B," the money should be credited to account B after the transaction is completed. If a failure occurs, the modification should be rolled back after debiting the money from account "A." In other words, each transaction will either succeed or fail.

Consistency
Consistency says that after the completion of a transaction, changes made during the transaction should be consistent. Let’s understand this fact by referring to the above example, if account “A” has been debited by 200 RS, then after the completion of the transaction, account “B” should be credited by 200 RS. It means changes should be consistent. In simple words, Consistency means a guarantee that a transaction never leaves your database in a half-finished state.

Isolation
Isolation states that every transaction should be isolated from each other. There should not be any interference between the two transactions. In simple words, Any other operation cannot affect my operation.

Durability
Durability means that once the transaction is completed, all the changes should be permanent. It means that in case of any system failure, changes should not be lost. In simple words, When the Transaction is complete, the changes are saved.Now we can understand this with the help of a Figure. This is very easy for us. This Figure is shown below.

FAQs
Q. What is the difference between the Local and the Distributed SQL Server transactions?
The Local transaction is an SQL Server transaction that processes data from the local database server

The Distributed transaction is an SQL Server transaction that processes data from more than one database server

Q. Some transactions may not complete their execution successfully. Explain these transactions.
These transactions are known as,

Aborted.

Whenever a transaction finishes its final statement, it ultimately enters into this state:

Partially committed.
Q. What is the SQL Server Transaction Log LSN?
Each Transaction log record that is written to the SQL Server transaction log file can be identified by its Log Sequence Number (LSN).

When working with SQL, one of the most significant data types you'll come across is DateTime. DateTime, which represents dates and times, is critical for managing time-sensitive data such as event scheduling, transaction timestamps, and historical records. In this post, we will go deep into DateTime in SQL to help you become a professional SQL developer, looking at its features, functions, real-world examples, and recommended practices.

Understanding DateTime in SQL Server
DateTime is a SQL data type that combines date and time data into a single value. It is required for capturing temporal moments accurately. SQL databases provide a variety of DateTime data types, including DATE, TIME, DATETIME, and TIMESTAMP, each with its own function.

Date and Time Functions
With the help of SQL's DateTime methods, you have numerous options for handling and modifying date and time data. Understanding the syntax and breadth of applications for these functions is critical to realizing their full potential.

1. GETDATE() / CURRENT_TIMESTAMP
Retrieves the current date and time.

Syntax
GETDATE() | CURRENT_TIMESTAMP

Examples
SELECT GETDATE() AS CurrentDateTime;

Output

SELECT CURRENT_TIMESTAMP AS CurrentTimestamp;

Output

2. DATEADD()
Adds or subtracts a specified time interval to/from a DateTime value.

Syntax
DATEADD(interval, number, date)

interval: Specifies the unit of time (e.g., year, month, day) to add or subtract.
number: Represents the quantity of intervals to add (positive) or subtract (negative).
date: The starting date or time to which the operation is applied.

Example
SELECT DATEADD(year, 2, '2023-09-13') AS NewDate;In this example, we add 2 years to the given date, resulting in '2025-09-13'.

Example
SELECT DATEADD(day, -10, '2023-09-13') AS NewDate;

Output

Here, we subtract 10 days from the given date, resulting in '2023-09-03'.

Example
SELECT DATEADD(hour, 3, '2023-09-13 10:00:00') AS NewTime;

Output

This adds 3 hours to the given time, resulting in '2023-09-13 13:00:00'. As per the above example of DateAdd, we can modify the datetime value in different ways.

3. DATEDIFF()
Calculates the difference between two DateTime values in a specified unit (e.g., years, months, days).

Syntax
DATEDIFF(interval, start_date, end_date)

interval: Specifies the unit of time (e.g., year, month, day) to calculate the difference in.
start_date: The beginning date or time.
end_date: The ending date or time.

Example
SELECT DATEDIFF(day, '2023-09-10', '2023-09-13') AS DaysDifference;

Output

In this example, we calculate the difference in days between '2023-09-10' and '2023-09-13', resulting in '3'.

Example
SELECT DATEDIFF(month, '2023-01-15', '2023-09-20') AS MonthsDifference;

Output

Here, we calculate the difference in months between '2023-01-15' and '2023-09-20', resulting in '8'.

Example
SELECT DATEDIFF(year, '1995-08-19', GETDATE()) AS AgeInYears;

Output

In this example, we determine the age of a person born on '1995-08-19' by calculating the difference in years between their birthdate and the current date using GETDATE(). The result is the person's age in years.

4. CONVERT()
Converts DateTime values between different formats.

Syntax
CONVERT(data_type, expression, style)

data_type: Specifies the target data type to which you want to convert the expression.
expression: The value or column to be converted.
style: Defines the format for the conversion (optional).

Example
SELECT CONVERT(DATE, GETDATE()) AS DateOnly;

Output

In this example, we convert the current date and time obtained using GETDATE() into a Date data type. This results in extracting only the date portion, like '2023-09-13'.

Example
SELECT CONVERT(DATETIME, '2023-09-13 15:16:00', 120) AS ConvertedDateTime;

Output

Here, we convert the string '2023-09-13 15:16:00' into a DateTime data type using style '120'. This results in a DateTime value like '2023-09-13 15:16:00.000'.

5. FORMAT()
Formats DateTime values into user-friendly strings.

Syntax
FORMAT(expression, format)
expression: The value or column you want to format, often a DateTime value.
format: Specifies the desired format for the expression.

Example
SELECT FORMAT(GETDATE(), 'd') AS ShortDate;

Output

In this example, we format the current date and time obtained using GETDATE() into a short date format (MM/DD/YY or equivalent based on localization). The result could be something like '09/13/23'.

Example
SELECT FORMAT(GETDATE(), 'MMMM dd, yyyy HH:mm:ss') AS CustomFormattedDateTime;

output

Here, we take the current date and time and format it into a custom string that includes the full month name, day, year, and time in the 'MMMM dd, yyyy HH:mm:ss' format. The result might look like 'September 13, 2023 15:23:52'.

Example
SELECT FORMAT(GETDATE(), 'HH:mm:ss') AS TimeOnly;

Output

In this example, we format the current date and time into a time-only format (HH:mm:ss), showing only the hours, minutes, and seconds. The result could be something like '15:25:43'.

Upcoming Events
Retrieve events that are scheduled for the future.

CREATE TABLE Events (
    EventID INT PRIMARY KEY,
    EventName VARCHAR(100),
    EventDateTime DATETIME
);


INSERT INTO Events (EventID, EventName, EventDateTime)
VALUES
    (1, 'Tech Conference', '2023-09-20 14:30:00'),
    (2, 'Product Launch', '2023-10-05 09:00:00'),
    (3, 'Workshop of SQL', '2023-09-25 10:00:00'),
    (4, 'Seminar', '2023-11-15 15:45:00'),
    (5, 'Annual Conference', '2022-08-01 18:00:00'),
    (6, 'Annual MVP Seminar', '2022-10-14 11:30:00');


Select * From Events

SELECT EventName, EventDateTime
FROM Events WHERE EventDateTime > GETDATE() Order By EventDateTime;

Output

Best Practices

When working with DateTime functions in SQL, consider these best practices:

• Data Validation: Ensure that your DateTime values are valid to avoid unexpected results.
• Avoid Mixing Data Types: Be cautious when mixing different DateTime data types in calculations.
• Optimize Queries: Index DateTime columns for improved query performance, especially in large datasets.
• Handle Time Zones: Address time zone issues when dealing with international data.

Summary
DateTime type in SQL, enabling you to handle date and time-related data effectively. By understanding its properties, functions, and best practices, you can ensure data accuracy and precision in your SQL databases.

If you find this article valuable, please consider liking it and sharing your thoughts in the comments.

Thank you, and happy coding.

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In SQL Server, you can use the MERGE statement to perform conditional INSERT, UPDATE, or DELETE operations in a single query. The MERGE statement is often used for synchronizing data between two tables or performing upserts (INSERT or UPDATE, depending on whether a matching row exists). Here's an example of how you can use the MERGE statement with multiple examples for each operation (INSERT, UPDATE, DELETE):

Assume you have two tables: TargetTable and SourceTable. We'll use these tables for our examples.
INSERT

Suppose you want to insert rows from SourceTable into TargetTable if they don't already exist in the target table.

MERGE INTO TargetTable AS Target
USING SourceTable AS Source
ON Target.ID = Source.ID
WHEN NOT MATCHED BY TARGET THEN
    INSERT (ID, Name)
    VALUES (Source.ID, Source.Name);

This SQL code will insert rows from SourceTable into TargetTable where the ID doesn't match.
UPDATE

Suppose you want to update existing rows in TargetTable with data from SourceTable. When there's a match.
MERGE INTO TargetTable AS Target
USING SourceTable AS Source
ON Target.ID = Source.ID
WHEN MATCHED THEN
    UPDATE SET Target.Name = Source.Name;

This code updates the Name column in TargetTable If there's a matching ID in SourceTable.
DELETE

Suppose you want to delete rows from TargetTable If they don't exist in SourceTable.
MERGE INTO TargetTable AS Target
USING SourceTable AS Source
ON Target.ID = Source.ID
WHEN NOT MATCHED BY SOURCE THEN
    DELETE;

This code will delete rows from TargetTable where the ID doesn't match any in SourceTable.

Now, let's see how you can execute these MERGE statements with multiple examples.
-- Example 1: Insert
INSERT INTO SourceTable (ID, Name)
VALUES (1, 'John'), (3, 'Alice');

-- Example 2: Update
UPDATE SourceTable
SET Name = 'Bob'
WHERE ID = 2;

-- Example 3: Delete
DELETE FROM SourceTable
WHERE ID = 4;

-- Execute MERGE for all operations
MERGE INTO TargetTable AS Target
USING SourceTable AS Source
ON Target.ID = Source.ID
WHEN NOT MATCHED BY TARGET THEN
    INSERT (ID, Name)
    VALUES (Source.ID, Source.Name)
WHEN MATCHED THEN
    UPDATE SET Target.Name = Source.Name
WHEN NOT MATCHED BY SOURCE THEN
    DELETE;

In this example, we first perform individual INSERT, UPDATE, and DELETE operations on the SourceTable. Then, we execute the MERGE statement to synchronize the TargetTable with the SourceTable using a single query. The MERGE statement handles all three operations based on the specified conditions.

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In SQL, a default value is a value that is assigned to a column when no other value is given. Default values can be used to ensure that every row in a table has a value for a specific column, even if the value is unknown when the row is produced.

Assume we have a table of employees and we want to ensure that each employee has a gender. We could add a Gender column and set the default value to male. This means that if no other value is supplied, any new employee will be assigned the gender male by default.

Now we'll look at the significance of default values in SQL, their benefits, and potential drawbacks.

SQL Default Values' Importance
Default values serve several essential purposes in SQL databases.

• Data Integrity: They ensure that essential fields are never left empty. For instance, in a user table, a default value for the 'registration_date' column can ensure that every new user has a registration date.
• Simplifying Data Entry: Defaults can simplify data entry by providing initial values for fields, reducing the workload on users and preventing errors.
• Compatibility: Default values can make your database more compatible with external systems or APIs that expect specific data formats.

How to Create a SQL Default Value
In SQL, you can use the DEFAULT term to specify a default value. The examples below demonstrate how to set dafault values in SQL.

Example 1
The following is an example of how to set a default value of 0 for a numeric column.     

-- Creating a table with default values
CREATE TABLE Products (
  ID INT NOT NULL,
  ProductName VARCHAR(20) NOT NULL,
  Price INT DEFAULT 0
);

-- Inserting a new user with defaults
INSERT INTO Products (ID , ProductName) VALUES (1, 'Laptop');
INSERT INTO Products (ID , ProductName) VALUES (2, 'Keyboard');

-- Querying the table
SELECT * FROM Products;

Output

The Price column in this example has a default value of 0. This means that if no other value is supplied, any new entry entered into the Products table will have a value of 0 for the Price column.

Example No. 2
The example below shows how to define a default value for a date and string column.

-- Creating a table with default values
CREATE TABLE Users(
    Id INT PRIMARY KEY,
    UserName VARCHAR(50) NOT NULL,
    Registration_Date DATE DEFAULT GETDATE(),
    Gender VARCHAR(6) DEFAULT 'Male'
);

-- Inserting a new user with defaults
INSERT INTO Users (Id, UserName) VALUES (1, 'Peter');
INSERT INTO Users (Id, UserName) VALUES (2, 'Scott');
INSERT INTO Users (Id, UserName) VALUES (3, 'Laura');

-- Querying the table
SELECT * FROM Users;

In this example, the Registration_Date column has a default value of GETDATE(), which means the current date of the server, and the gender column has a default value of Male.

Advantages of Using Default Values
Now, let's delve into the advantages of utilizing default values in SQL.

• Consistency: Default values promote consistency across your database. When multiple records are inserted without specifying a particular column's value, they all get the same default value.
• Time-Saving: They save time during data insertion, especially for columns that often have the same value. This efficiency can boost developer productivity.
• Error Prevention: Defaults can help prevent human errors by ensuring that important fields are never left blank. This is especially critical for fields containing critical data.

Disadvantages of Using Default Values
While default values offer numerous benefits, they can also have some drawbacks:

• Hidden Data: Default values may hide missing or incorrect data. If users rely too heavily on defaults, it can lead to data quality issues.
• Complexity: In some cases, handling default values can add complexity to SQL queries, especially when you need to override or update them.
• Overuse: Overusing default values can make your database less flexible. It's essential to strike a balance between defaults and explicit data entry.

Summary
Default values can be a useful tool for ensuring data integrity, simplifying data entry, and improving performance. However, it is important to be aware of the potential disadvantages of using default values before using them. If you find this article valuable, please consider liking it and sharing your thoughts in the comments.
Thank you, and happy coding.

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