European Windows 2019 Hosting BLOG

BLOG about Windows 2019 Hosting and SQL 2019 Hosting - Dedicated to European Windows Hosting Customer

European SQL Server 2022 Hosting :: How to Work with LEAD and LAG Window Functions in SQL?

clock May 21, 2024 10:28 by author Peter

Numerous analytical functions in SQL enable us to carry out intricate computations and data analysis jobs. SQL window functions called LEAD and LAG let us access data from other rows that are part of the same resultant row. They are frequently utilized in conjunction with the OVER clause, which specifies how the result set is divided and arranged. The value for the LAG function comes from a row that comes before the current one, whereas the value for the LEAD function comes from a row that comes after the current one.

The offset parameter, which indicates how many rows to advance or retract from the current row, is accepted by both functions. Let's examine the syntax, usage cases, and examples of LEAD and LAG to better understand how they work.

LEAD and LAG Functions Syntax

--LAEAD Function Syntax:
LEAD(column_name, offset, default_value) OVER (
    PARTITION BY partition_expression
    ORDER BY order_expression
)

--LAG Function Syntax:
LAG(column_name, offset, default_value) OVER (
    PARTITION BY partition_expression
    ORDER BY order_expression
)
  • column_name: Name of the column from which you want to retrieve the value.
  • offset: Number of rows to move forward (LEAD Function) or backward (LAG Function) from the current row. The default value is 1 and should be positive.
  • default_value (optional): Default value to return if the lead or lag value is NULL or if there is no subsequent row within the partition.
  • PARTITION BY (optional): Divides the result set into partitions based on the specified expression.
  • ORDER BY: Specifies the ordering of rows within each partition.

Lets take an example for LEAD and LAG functions.create a table named sales with the following structure:

-- Create salas table
CREATE TABLE sales (
    product VARCHAR(50),
    year INT,
    sales_amount DECIMAL(10,2)
);

-- Add some dummy data into the table
INSERT INTO sales (product, year, sales_amount) VALUES
('Apples', 2021, 1500.50),
('Bananas', 2021, 2500.75),
('Carrots', 2021, 3200.00),
('Apples', 2022, 1700.30),
('Bananas', 2022, 2900.20),
('Carrots', 2022, 3400.60),
('Apples', 2023, 1800.00),
('Bananas', 2023, 3100.45),
('Carrots', 2023, 3600.80),
('Oranges', 2021, 1100.25),
('Oranges', 2022, 1300.50),
('Oranges', 2023, 1400.75),
('Tomatoes', 2021, 1200.00),
('Tomatoes', 2022, 1500.35),
('Tomatoes', 2023, 1600.90);

Retrieving the next product's sales amount using LEAD function

SELECT product,year,sales_amount,
    LEAD(sales_amount, 1, 0) OVER (
        ORDER BY year, product
    ) AS next_product_sales
FROM
    sales ;

--Sample O/P
+----------+------+---------------+--------------------+
| product  | year | sales_amount  | next_product_sales |
+----------+------+---------------+--------------------+
| Apples   | 2021 |        1500.5 |             2500.75 |
| Bananas  | 2021 |        2500.75|              3200.0 |
| Carrots  | 2021 |         3200.0|             1100.25 |
| Oranges  | 2021 |        1100.25|              1200.0 |
| Tomatoes | 2021 |         1200.0|              1700.3 |
| Apples   | 2022 |         1700.3|              2900.2 |
| Bananas  | 2022 |         2900.2|              3400.6 |
|.......    .....          .......               ......
+----------+------+---------------+--------------------+

In above Query , we use the LEAD function to retrieve the sales amount of the next product in the same year. If there is no subsequent product, the default_value of 0 is returned.

Retrieving the prev product's sales amount using LAG function

SELECT product, year,sales_amount,
    LAG(sales_amount, 1, 0) OVER (
        ORDER BY year, product
    ) AS prev_product_sales
FROM sales;

--Sample O/P

+----------+------+---------------+--------------------+
| product  | year | sales_amount  | next_product_sales |
+----------+------+---------------+--------------------+
| Apples   | 2021 |        1500.5 |                0.0 |
| Bananas  | 2021 |        2500.75|             1500.5 |
| Carrots  | 2021 |         3200.0|             2500.75|
| Oranges  | 2021 |        1100.25|              3200.0|
| Tomatoes | 2021 |         1200.0|             1100.25|
| Apples   | 2022 |         1700.3|              1200.0|
| .....      ....           .....             ......
+----------+------+---------------+--------------------+

In above Query , we use the LEAD function to retrieve the sales amount of the next product in the same year. If there is no subsequent product, the default_value of 0 is returned.

Use Case

Suppose we want to analyze the sales data for each product, not only by comparing the current year's sales with the previous year but also by looking forward to the next year's sales. We can achieve this by combining the LEAD and LAG functions in a single query.

SELECT product, year, sales_amount,
    sales_amount - LAG(sales_amount, 1) OVER (
        PARTITION BY product
        ORDER BY year
    ) AS year_over_year_diff,
    LEAD(sales_amount, 1, 0) OVER (PARTITION BY product
        ORDER BY year) - sales_amount AS next_year_diff
FROM sales ORDER BY product, year;

-- Sample O/P
+----------+------+---------------+------------------+----------------+
| product  | year | sales_amount  | year_over_year_diff | next_year_diff |
+----------+------+---------------+------------------+----------------+
| Apples   | 2021 |        1500.5 |              NULL |          199.8 |
| Apples   | 2022 |        1700.3 |             199.8 |           99.7 |
| Apples   | 2023 |         1800.0|              99.7 |        -1800.0 |
| Bananas  | 2021 |        2500.75|              NULL |          399.45|
| Bananas  | 2022 |        2900.2 |             399.45|          200.25|
| Bananas  | 2023 |        3100.45|             200.25|        -3100.45|
| Carrots  | 2021 |         3200.0|              NULL |          200.6 |
| .....      ...            ....              .....          ....... ...
+----------+------+---------------+------------------+----------------+

In the LAG Functions we are calculating the year-over-year difference in sales by subtracting the previous year's sales amount from the current year's sales amount. In the LEAD Functions we are calculating the difference between the next year's sales amount and the current year's sales amount. By including both expressions in the same query, we can analyze the sales data for each product by looking at the year-over-year difference as well as the projected difference for the next year.

HostForLIFEASP.NET SQL Server 2022 Hosting


 

 



European SQL Server 2022 Hosting :: How to Work with LEAD and LAG Window Functions in SQL?

clock May 21, 2024 09:48 by author Peter

Numerous analytical functions in SQL enable us to carry out intricate computations and data analysis jobs. SQL window functions called LEAD and LAG let us access data from other rows that are part of the same resultant row. They are frequently utilized in conjunction with the OVER clause, which specifies how the result set is divided and arranged. The value for the LAG function comes from a row that comes before the current one, whereas the value for the LEAD function comes from a row that comes after the current one.

The offset parameter, which indicates how many rows to advance or retract from the current row, is accepted by both functions. Let's examine the syntax, usage cases, and examples of LEAD and LAG to better understand how they work.

LEAD and LAG Functions Syntax
--LAEAD Function Syntax:
LEAD(column_name, offset, default_value) OVER (
    PARTITION BY partition_expression
    ORDER BY order_expression
)

--LAG Function Syntax:
LAG(column_name, offset, default_value) OVER (
    PARTITION BY partition_expression
    ORDER BY order_expression
)

  • column_name: Name of the column from which you want to retrieve the value.
  • offset: Number of rows to move forward (LEAD Function) or backward (LAG Function) from the current row. The default value is 1 and should be positive.
  • default_value (optional): Default value to return if the lead or lag value is NULL or if there is no subsequent row within the partition.
  • PARTITION BY (optional): Divides the result set into partitions based on the specified expression.
  • ORDER BY: Specifies the ordering of rows within each partition.


Lets take an example for LEAD and LAG functions.create a table named sales with the following structure:
-- Create salas table
CREATE TABLE sales (
    product VARCHAR(50),
    year INT,
    sales_amount DECIMAL(10,2)
);

-- Add some dummy data into the table
INSERT INTO sales (product, year, sales_amount) VALUES
('Apples', 2021, 1500.50),
('Bananas', 2021, 2500.75),
('Carrots', 2021, 3200.00),
('Apples', 2022, 1700.30),
('Bananas', 2022, 2900.20),
('Carrots', 2022, 3400.60),
('Apples', 2023, 1800.00),
('Bananas', 2023, 3100.45),
('Carrots', 2023, 3600.80),
('Oranges', 2021, 1100.25),
('Oranges', 2022, 1300.50),
('Oranges', 2023, 1400.75),
('Tomatoes', 2021, 1200.00),
('Tomatoes', 2022, 1500.35),
('Tomatoes', 2023, 1600.90);

Retrieving the next product's sales amount using LEAD function.

SELECT product,year,sales_amount,
    LEAD(sales_amount, 1, 0) OVER (
        ORDER BY year, product
    ) AS next_product_sales
FROM
    sales ;

--Sample O/P
+----------+------+---------------+--------------------+
| product  | year | sales_amount  | next_product_sales |
+----------+------+---------------+--------------------+
| Apples   | 2021 |        1500.5 |             2500.75 |
| Bananas  | 2021 |        2500.75|              3200.0 |
| Carrots  | 2021 |         3200.0|             1100.25 |
| Oranges  | 2021 |        1100.25|              1200.0 |
| Tomatoes | 2021 |         1200.0|              1700.3 |
| Apples   | 2022 |         1700.3|              2900.2 |
| Bananas  | 2022 |         2900.2|              3400.6 |
|.......    .....          .......               ......
+----------+------+---------------+--------------------+

In above Query , we use the LEAD function to retrieve the sales amount of the next product in the same year. If there is no subsequent product, the default_value of 0 is returned.

Retrieving the prev product's sales amount using LAG function

SELECT product, year,sales_amount,
    LAG(sales_amount, 1, 0) OVER (
        ORDER BY year, product
    ) AS prev_product_sales
FROM sales;

--Sample O/P

+----------+------+---------------+--------------------+
| product  | year | sales_amount  | next_product_sales |
+----------+------+---------------+--------------------+
| Apples   | 2021 |        1500.5 |                0.0 |
| Bananas  | 2021 |        2500.75|             1500.5 |
| Carrots  | 2021 |         3200.0|             2500.75|
| Oranges  | 2021 |        1100.25|              3200.0|
| Tomatoes | 2021 |         1200.0|             1100.25|
| Apples   | 2022 |         1700.3|              1200.0|
| .....      ....           .....             ......
+----------+------+---------------+--------------------+

In above Query , we use the LEAD function to retrieve the sales amount of the next product in the same year. If there is no subsequent product, the default_value of 0 is returned.

Use Case

Suppose we want to analyze the sales data for each product, not only by comparing the current year's sales with the previous year but also by looking forward to the next year's sales. We can achieve this by combining the LEAD and LAG functions in a single query.

SELECT product, year, sales_amount,
    sales_amount - LAG(sales_amount, 1) OVER (
        PARTITION BY product
        ORDER BY year
    ) AS year_over_year_diff,
    LEAD(sales_amount, 1, 0) OVER (PARTITION BY product
        ORDER BY year) - sales_amount AS next_year_diff
FROM sales ORDER BY product, year;

-- Sample O/P
+----------+------+---------------+------------------+----------------+
| product  | year | sales_amount  | year_over_year_diff | next_year_diff |
+----------+------+---------------+------------------+----------------+
| Apples   | 2021 |        1500.5 |              NULL |          199.8 |
| Apples   | 2022 |        1700.3 |             199.8 |           99.7 |
| Apples   | 2023 |         1800.0|              99.7 |        -1800.0 |
| Bananas  | 2021 |        2500.75|              NULL |          399.45|
| Bananas  | 2022 |        2900.2 |             399.45|          200.25|
| Bananas  | 2023 |        3100.45|             200.25|        -3100.45|
| Carrots  | 2021 |         3200.0|              NULL |          200.6 |
| .....      ...            ....              .....          ....... ...
+----------+------+---------------+------------------+----------------+

We use the LAG Functions to calculate the sales difference between the current and prior years by deducting the former year's sales figure from the latter. We are computing the difference between the sales amount for the current year and the sales amount for the upcoming year in the LEAD Functions. We may evaluate the sales data for each product by comparing the year-over-year difference and the anticipated difference for the following year by putting both expressions in the same query.

HostForLIFEASP.NET SQL Server 2022 Hosting

 



European SQL Server 2022 Hosting :: How to Convert Rows to CSV & Eliminate Duplicates in SQL Server?

clock May 8, 2024 07:06 by author Peter

Our user belongs to several roles, each of which has a number of privileges associated with it. The responsibilities and privileges that are linked to each user are what users want to see. In order to prevent redundant roles and privileges, the final product should have distinct roles and privileges. Basically, we have to remove duplicates from the string separated by commas.

Let's look at the data—both real and predicted.

Solution
One of two methods can be used to solve this problem in SQL Server utilizing the STRING_AGG() function.

Method 1
We may efficiently eliminate any duplicates by utilizing STRING_AGG() inside a subquery.

SELECT RL.UserName, STRING_AGG(RL.RoleName,', ') AS RoleName, PL.PrivilegeName
FROM (
    SELECT DISTINCT U.UserId, U.Name AS UserName, R.RoleName
    FROM #User U
    INNER JOIN #UserRolePrivilegeMap URPM
    ON U.UserId = URPM.UserId
    INNER JOIN #Role R
    ON URPM.RoleId = R.RoleId) RL
    INNER JOIN (
        SELECT P.UserId, STRING_AGG(P.PrivName,', ') AS PrivilegeName
        FROM (SELECT DISTINCT U.UserId, P.PrivName
              FROM #User U
              INNER JOIN #UserRolePrivilegeMap URPM
                ON U.UserId = URPM.UserId
              INNER JOIN #Privilege P
                ON URPM.PrvId = P.PrvId) P
              GROUP BY P.UserId) PL
        ON RL.UserId = PL.UserId
GROUP BY RL.UserName,PL.PrivilegeName

Expected Result

Method 2
Rows can be converted to Comma-Separated Values (CSV) by utilizing the grouped concatenation method with STRING_AGG(). Then, we can use the XQuery function distinct-values() to retrieve unique values from the XML instance after converting the CSV file to XML.

/*Using XQuery-function distinct-values() get only distinct values*/
SELECT UserName
     ,STUFF((RoleName.query('for $x in distinct-values(/x/text())return <x>{concat(",", $x)}</x>').value('.','varchar(250)')),1,1,'') AS RoleName
     ,STUFF((PrivilegeName.query('for $x in distinct-values(/x/text())return <x>{concat(",", $x)}</x>').value('.','varchar(250)')),1,1,'') AS PrivilegeName
FROM(
SELECT U.Name As UserName
    ,CAST('<x>' + REPLACE(STRING_AGG(R.RoleName,','),',','</x><x>') + '</x>' AS XML) AS   RoleName
    ,CAST('<x>' + REPLACE(STRING_AGG(P.PrivName,','),',','</x><x>') + '</x>' AS XML) AS   PrivilegeName
FROM #User U
INNER JOIN #UserRolePrivilegeMap URPM
ON U.UserId = URPM.UserId
INNER JOIN #Role R
ON URPM.RoleId = R.RoleId
INNER JOIN #Privilege P
ON URPM.PrvId = P.PrvId
GROUP BY U.Name)A

Step 1: Transform the real data into the CSV format indicated below by using the STRING_AGG() function.

Step 2. Next, convert the CSV into XML format.

Step 3. Now, utilize the XQuery function distinct-values() to extract unique values from the XML instance.

Tables and Insert Scripts
/*Create USER Table and Insert Data*/
DROP TABLE IF EXISTS #User
CREATE TABLE #User (UserId INT, Name VARCHAR(50))
INSERT INTO #User (UserId, Name)
VALUES (1, 'John'),
     (2, 'Peter'),
     (3, 'David')

/*Create ROLE Table and Insert Data*/
DROP TABLE IF EXISTS #Role
CREATE TABLE #Role (RoleId INT, RoleName VARCHAR(50))
INSERT INTO #Role (RoleId, RoleName)
VALUES (1, 'IT Admin'), (2, 'Developer'), (3, 'Sr.Developer'), (4, 'Lead'), (5, 'Sr.Lead')

/*Create PRIVILEGE Table and Insert Data*/
DROP TABLE IF EXISTS #Privilege
CREATE TABLE #Privilege (PrvId INT, PrivName VARCHAR(50))
INSERT INTO #Privilege (PrvId, PrivName)
VALUES (1, 'Default'), (2, 'Admin'), (3, 'Creator'), (4, 'Read'), (5, 'Write'), (6, 'Owner')

/*Create USERROLEPRIVILEGEMAP Table and Insert Data*/
DROP TABLE IF EXISTS #UserRolePrivilegeMap
CREATE TABLE #UserRolePrivilegeMap(UserId INT, RoleId INT, PrvId INT)
INSERT INTO #UserRolePrivilegeMap (UserId, RoleId, PrvId)
VALUES (1,1,1), (1,1,2), (1,2,1), (1,2,2), (1,2,4), (1,2,5), (1,4,2),
     (1,4,4), (2,1,1), (2,1,5), (2,1,3), (2,5,1), (2,5,2), (2,5,6),
     (2,5,5), (2,5,3), (3,1,1), (3,1,6), (3,1,5), (3,1,4), (3,3,1),
     (3,3,2), (3,3,4), (3,3,5), (3,3,6)

/*Join all tables and get the actual data*/
SELECT U.Name AS UserName
    ,R.RoleName
    ,P.PrivName AS PrivilegeName
FROM #User U
INNER JOIN #UserRolePrivilegeMap URPM
ON U.UserId = URPM.UserId
INNER JOIN #Role R
ON URPM.RoleId = R.RoleId
INNER JOIN #Privilege P
ON URPM.PrvId = P.PrvId

Conclusion
Efficiently convert row data into comma-separated values using SQL Server's string aggregate function, ensuring duplicates are removed for streamlined data representation and integrity.

HostForLIFEASP.NET SQL Server 2022 Hosting

 



European SQL Server 2022 Hosting :: Setting Up a Calendar in SQL Server

clock May 3, 2024 08:20 by author Peter

Using SQL Server's built-in capabilities, I've made a basic calendar in the example below.

Temporary SQL Server Tables
The instantaneous result sets that are queried repeatedly can be stored in the temporary tables.

Setting up makeshift tables

SELECT INTO and CREATE TABLE statements are the two methods that SQL Server offers for creating temporary tables.

CREATE OR ALTER PROCEDURE calender(@start_date DATE, @end_date DATE)
AS
BEGIN
    DECLARE @DateDiff INT;
    DECLARE @count INT;
    SET @count = 0; -- DAY ONE COUNT OF START DATE
    SET @DateDiff = DATEDIFF(DAY, @start_date, @end_date); -- DIFF BTW TWO DATE
    DROP TABLE IF EXISTS #temp_cal;
    CREATE TABLE #temp_cal(
        id INT IDENTITY(1,1) PRIMARY KEY,
        d_date DATE,
        end_date DATE
    );
    WHILE @count <= @DateDiff BEGIN
        INSERT INTO #temp_cal(d_date, end_date) VALUES(DATEADD(DAY, @count, @start_date), @end_date);
        SET @count = @count + 1;
    END;
    SELECT DAY(d_date) AS 'DAY',
           MONTH(d_date) AS 'MONTH',
           DATENAME(weekday, d_date) AS 'DAY_NAME',
           DATENAME(month, d_date) AS 'MONTH_NAME',
           DATENAME(year, d_date) AS 'YEAR',
           d_date AS 'DATE',
           DATENAME(week, d_date) AS 'WEEK',
           DATEPART(DY, d_date) AS 'DAY_OF_YEAR',
           DATEPART(ISO_WEEK, d_date) AS 'ISO_WEEK',
           DATEPART(wk, d_date) AS 'US WEEK',
           DATEPART(wk, d_date) AS 'WEEK_OF_YEAR',
           DATEDIFF(DAY,d_date, end_date) AS 'NUMBER_OF_DAYS_IN_MONTH',
           DATEDIFF(WEEK,d_date,end_date) AS 'WEEKS_IN_YEAR',
           DATEDIFF(MONTH,d_date,end_date) AS 'MONTHS_IN_YEAR',
           FORMAT(d_date, 'D', 'en-US' ) AS 'CULTURES_FOR_US'
    FROM #temp_cal;
END;
EXEC calender @start_date = '2023-01-01', @end_date = '2023-12-31';

HostForLIFEASP.NET SQL Server 2022 Hosting

 



European SQL Server 2022 Hosting :: SQL Temporary Tables: Types, Syntax, and Application

clock April 26, 2024 07:30 by author Peter

Temporary tables, often known as temp tables, are widely used by database managers and developers. They function similarly to ordinary tables and are kept in the tempDB database, enabling you to choose, add, and remove data as needed. In the event that they are produced during a stored procedure, they will be removed once the operation is finished.

What does a SQL Server temporary table mean?

In SQL, a temporary table is a database table that is only temporarily present on the database server. For a set amount of time, a temporary table retains some of the data from a regular table.

Temporary tables are useful when you need to regularly work with a small subset of the many records in a table. Sometimes it is not necessary to filter the data several times in order to obtain the subset; instead, you can filter the data only once and save it in a temporary table.

Temporary tables and permanent tables are almost the same. They are created in TempDB and deleted right away after the last connection to the query window that created the table is closed. Temporary Tables can be used to process and store interim findings. Temporary tables are used when it is necessary to store data temporarily.

How to Create a Temporary SQL Table?
CREATE TABLE #tmpEmp
(
  Id INT,
  Name NVARCHAR(50),
  Rank INT
)


Types of Temporary Tables in SQL
There are a couple of temporary tables in SQL.

  • Local Temporary Tables
  • Global Temporary Tables

Local Temporary Tables
TempDB contains local temporary table storage. They are destroyed automatically at the conclusion of the operation or session, and they are only available to the one who created them.

For instance, after a local temporary table called #tmpEmp is created, the user's ability to manipulate the table is limited until the query window's final connection is closed. They can be recognized by the prefix #, such as #table name, and the same temporary table can be created with the same name in many windows.

A local temporary table can be created with the CREATE TABLE command, where the table name is prefixed with a single number sign (#table name).

Syntax
The following is the syntax in SQL Server (Transact-SQL) for making a LOCAL TEMPORARY TABLE.
CREATE TABLE #tablename
(
  column1 datatype [ NULL | NOT NULL ],
    column2 datatype [ NULL | NOT NULL ],
    column3 datatype [ NULL | NOT NULL ],
    ...
    columnn datatype [ NULL | NOT NULL ]
);

Let’s insert some data entry in a temporary table.

INSERT INTO #tmpEmp ([Name], [Rank])
VALUES ('Peter Scott', 196)

Let’s check the results, whether it’s stored or not.
SELECT Id, [Name], [Rank] FROM #tmpEmp

Where do I store the temporary table on the SQL Server?

Another way to create a temporary table in SQL is with the SELECT INTO statement. For the illustration, go through the following things.
SELECT Id, [Name], [Rank]
INTO #tmpEmp1
FROM #tmpEmp

Temporary tables are useful when you need to regularly work with a small subset of the many records in a table. Sometimes it is not necessary to filter the data several times in order to obtain the subset; instead, you can filter the data only once and save it in a temporary table.

Temporary tables and permanent tables are almost the same. They are created in TempDB and deleted right away after the last connection to the query window that created the table is closed. Temporary Tables can be used to process and store interim findings. Temporary tables are used when it is necessary to store data temporarily.

Global Temporary Table in SQL Server
Additionally, they are kept in tempDB. These tables belong to the category of transient tables that are concurrently accessible to all users and sessions. When the final session using the temporary table concludes, they are automatically removed. These tables do not exist in the system catalogs and are not persistent.

A global temporary table is created with the CREATE TABLE command, and the table name is preceded by a double number sign (##table name).

Syntax
The following is the syntax in SQL Server (Transact-SQL) for making a global temporary table.
CREATE TABLE ##tablename
(
  column1 datatype [ NULL | NOT NULL ],
    column2 datatype [ NULL | NOT NULL ],
    column3 datatype [ NULL | NOT NULL ],
    ...
    columnn datatype [ NULL | NOT NULL ]
);


Create a global temporary table.

CREATE TABLE ##tmpEmployee
(
  Id INT NOT NULL IDENTITY (1, 1),
  [Name] NVARCHAR(50),
  [Rank] INT
)

Let’s insert some data entry in a global temporary table.

INSERT INTO ##tmpEmployee ([Name], [Rank])
VALUES ('Peter', 196)
, ('Daniel', 1211)
, ('Maria', 1250)
, ('Laura', 1280)

Let’s check the results, whether it’s stored or not.
SELECT Id, [Name], [Rank] FROM ##tmpEmployee


Where do I store the temporary table on the SQL Server?


Delete Temporary and Global Temporary SQL Table
When possible, we should directly remove temporary tables rather than waiting for them to be deleted automatically when the connection is closed. in order to expeditiously release the temp resources.

Syntax
DROP TABLE TableName

As an illustration,
DROP TABLE #tmpEmp, #tmpEmp1, ##tmpEmployee

Let's check in the Temporary Tables from SQL Server.

HostForLIFEASP.NET SQL Server 2022 Hosting

 



European SQL Server 2022 Hosting :: Recognizing Database Management System Layers

clock April 22, 2024 08:01 by author Peter

This succinct article will help you understand the fundamentals of three-tier architecture in database management systems (DBMS). Discover the layers: data management, application, and display. Each has a specific function in coordinating smooth data exchanges. Discover the benefits, tenets, and real-world applications of this architectural approach, which will enable you to create and implement dependable and expandable database solutions.

Outside Layer
In a database management system's three-tier architecture, the external level, sometimes referred to as the user interface layer, is the highest tier (DBMS). By presenting data in an approachable and comprehensible style, it acts as the entry point for end users to engage with the system. Forms, reports, dashboards, and graphical user interfaces that are customized for particular user roles and preferences are all included in this layer. Users may rapidly access, retrieve, update, and edit data thanks to the external level's streamlined and intuitive interface, which abstracts the intricacies of the underlying database structure.

Conceptual Depth
In the three-tier design of a database management system (DBMS), the conceptual level is the intermediary layer, situated between the external and physical levels. It abstracts the underlying physical storage information from the end users and applications that interact with the system, representing the logical perspective of the database. At this stage, implementation details are not as important as specifying the general structure, organization, and relationships of the data within the database. Entity-relationship diagrams (ERDs) and other conceptual data models, which depict the entities, characteristics, and relationships in the database schema, are commonly used to represent the conceptual level. Because of its capacity to support data independence, this abstraction improves flexibility and maintainability by enabling modifications to the database structure without impacting the external applications.

Physical Level
At the basis of a database management system's (DBMS) three-tier design, the physical level is in charge of overseeing the real data storage and retrieval on the physical storage devices. This tier communicates directly with the disks, RAM, and storage devices that make up the hardware (Data Store). Data is arranged and stored physically using techniques like indexing, segmentation, and storage optimization that are designed for effective access and retrieval. To maintain data integrity, security, and performance, this tier also includes features like disk management techniques, data compression, and encryption. By converting logical data structures into physical storage, the physical level works directly with low-level storage methods, in contrast to the conceptual and external levels, which abstract away from specifics of physical implementation.

These layers communicate with one another in an organized manner, with each layer carrying out particular duties and transferring information or requests to the subsequent layer as needed. Database systems can be designed and managed with modularity, scalability, and maintainability because to this division of responsibilities.

In summary

The conceptual layer establishes logical data structures, the physical layer oversees actual data storage, and the external layer offers user-friendly interfaces in a three-tier architecture. By working together, they produce a coherent framework for effective data processing and administration that improves database systems' scalability, maintainability, and security.

HostForLIFEASP.NET SQL Server 2022 Hosting

 

 


 



European SQL Server 2022 Hosting :: Table-Valued Parameters in SQL Server

clock April 18, 2024 07:32 by author Peter

Table-valued parameters are similar to parameter arrays in that they eliminate the need to build a temporary table or employ numerous parameters by enabling the sending of multiple rows of data to a Transact-SQL statement or routine, such as a stored procedure or function. This article explains how to use a Microsoft SQL Server table-valued argument in a stored procedure.

User-Defined Table Types are tables designed to hold temporary data and are used to declare table-valued parameters. Thus, you can make a Type Table and send it as a parameter for a process that requires, for instance, to receive a list of items. For demonstration purposes, I created a table of products that will be used in the following examples. This is the structure of the Products table.

CREATE TABLE Products (
    Id INT NOT NULL,
    Name NVARCHAR(100) NULL,
    Description NVARCHAR(200) NULL,
    CreatedDate DATETIME2 NOT NULL CONSTRAINT [DF_Products_CreatedDate] DEFAULT GETUTCDATE(),
    CreatedBy NVARCHAR(150) NOT NULL,
    CONSTRAINT PK_Product PRIMARY KEY(Id)
 );

Adding Just One Product

Imagine a situation in which a user opens your app and needs to register just one item. And to do that, a process for adding this product to the database must exist. You must first develop a procedure to add a single product to the products database in order to accomplish that. The ID, Name, Description, and the user who created the product should be sent as parameters to this procedure.

CREATE PROCEDURE InsertProduct (
        @Id INT,
        @Name NVARCHAR(100),
        @Description NVARCHAR(200),
        @User NVARCHAR(150)
    )
AS
BEGIN
    INSERT INTO Products (
        Id,
        Name,
        Description,
        CreatedBy
    )
    VALUES (
          @Id,
          @Name,
          @Description,
          @User
    );
END

For testing this procedure, we can run some scripts adding aBEGIN TRANSACTIONwith aROLLBACKin the end (this is useful when testing to avoid needing to delete/change/revert the data on each test that is made), and inside of that, we can execute the statements to insert the products.

BEGIN TRANSACTION
SELECT * FROM Products;
EXEC InsertProduct 1, 'Galaxy S22', 'Smartphone Samsung Galaxy S22', 'Henrique';
EXEC InsertProduct 2, 'iPhone 14 Pro', 'Smartphone Apple iPhone 14 Pro', 'Henrique';
EXEC InsertProduct 3, 'iPhone 13 Pro', 'Smartphone Apple iPhone 13 Pro', 'Henrique';
SELECT * FROM Products;
ROLLBACK

On line 1, there is the BEGIN transaction statement, and this is to allow us to revert the changes at the end of the execution.
On line 3, we run aSELECTquery to check the data in the products table.
On lines 5 up to 7, we run the InsertProductprocedure to insert the products. Note that in order to insert three products, we needed to execute the procedure three times, once for each product.
On line 9, we run a new select query to check the data in the products table.
On line 11, there is the rollback statement, to revert the changes that were made.

This is the result.

Adding a Large Number of Products
Now imagine a situation where you receive a list of products to add to the product table, rather than just one product. In this instance, a Table Type parameter—which functions as a sort of array of products—should be included in the code. The properties that are listed in the products table should also be included in the type table's columns. For instance, the type table will include the columns Name and Description.

CREATE TYPE ProductType AS TABLE (
  Id INT NOT NULL,
  Name NVARCHAR(100) NULL,
  Description NVARCHAR(200) NULL,
  PRIMARY KEY(Id)
);

Once the Type Table is created, it’s possible to see it here.

The type table and the user entering the records will be the two arguments for the new method we'll be creating, InsertProducts (plural). The Insert Products process is as follows.

CREATE PROCEDURE InsertProducts (
    @Products ProductType READONLY,
    @User NVARCHAR(150)
  )
AS
BEGIN
  INSERT INTO Products (
    Id,
    Name,
    Description,
    CreatedBy
  )
  SELECT
    prd.Id,
    prd.Name,
    prd.Description,
    @User
  FROM @Products prd
END

  • On line 2, there is the parameter@Productsof typeProductType, and it must have theREADONLYkeyword.
  • On line 3, there is the parameter@CreatedByof typeNVARCHAR, which is for saving the name of the user who runs the procedure to insert products. Note: this second parameter is here only to demonstrate that even when a procedure has a type table as a parameter, is still possible to use more parameters of different types — in case you need to get the user who executed the SQL script, you can use theSYSTEM_USERin the SQL Script, instead of receiving the user as a parameter.
  • On line 7, the INSERT statement begins.
  • On line 13, there is the select query, which will read the data from the table type that was received as a parameter (@Products), and it will use the data to insert it into the product table.

Let’s test the procedure now. For that, let’s use the TRANSACTION with aROLLBACKin the end, as we did before, and for testing, we will add some data into the type table and execute the procedure by sending this type table as a parameter.

BEGIN TRANSACTION
  SELECT * FROM Products;
  DECLARE @Products ProductType;
  INSERT INTO @Products
  SELECT 1, 'Galaxy S22+', 'Smartphone Samsung Galaxy S22+'
  UNION ALL
  SELECT 2, 'iPhone 14 Pro', 'Smartphone Apple iPhone 14 Pro'
  UNION ALL
  SELECT 3, 'iPhone 13 Pro', 'Smartphone Apple iPhone 13 Pro';
  EXEC InsertProducts @Products, 'Henrique';
  SELECT * FROM Products;
ROLLBACK

  • On line 1, a new transaction is started.
  • On line 3, we first run select to check the data we have in the product table before running the procedure.
  • On line 5, the variable of typeProductTypeis declared.
  • On lines 7 up to 12, three records are inserted into the@Productsvariable.
  • On line 14, the procedure to insert products is executed and receives as parameters the Type table variable (@Products) and a user ('Henrique').
  • On line 16, a new selection, the Productstable is executed, and the three records are expected to be inserted into the table.
  • On line 18, a rollback is executed to revert the changes.

This is the result.

Since this is a new table, it is to be expected that the initial select query returned no results. The three products were added to the product table using the second select query, which was run subsequent to the insert function. For the scenarios in which the product table contains records, let's run another test. Let's add additional data to the table to support that.

INSERT INTO Products (Id, Name, Description, CreatedBy)
  VALUES (1, 'Galaxy S21+', 'Smartphone Samsung Galaxy S21+', 'Henrique'),
          (2, 'Galaxy S22', 'Smartphone Samsung Galaxy S22', 'Henrique'),
    (3, 'Galaxy S22+', 'Smartphone Samsung Galaxy S22+', 'Henrique');


Now, let’s do another test, adding new records using the InsertProductsprocedure.

BEGIN TRANSACTION
  SELECT * FROM Products;
  DECLARE @Products ProductType;
  INSERT INTO @Products
  SELECT 4, 'iPhone 13 Pro', 'Smartphone Apple iPhone 13 Pro'
  UNION ALL
  SELECT 5, 'iPhone 14 Pro', 'Smartphone Apple iPhone 14 Pro';
  EXEC InsertProducts @Products, 'Henrique';
  SELECT * FROM Products;
ROLLBACK

  • On line 3, the first SELECT will return the records that were previously added to the products table.
  • On line 5, the variable of typeProductTypeis declared.
  • On lines 7 up to 10, two products are added to theProductTypetable, which will be used as a parameter to the procedure.
  • On line 12, the procedureInsertProductsis executed.
  • On line 14, a second selects executed, to return the products.

This is the result.


The new records with Ids 4 and 5 were added to the product table as anticipated.

In summary

It is feasible to build a stored method or function that requires a list of data as a parameter by declaring User-Defined Table Types and employing Tabled-Valued Parameters. This makes it feasible to deliver a large amount of data with a single request rather than having to run the function numerous times (one for each data).

HostForLIFEASP.NET SQL Server 2022 Hosting

 


 



European SQL Server 2022 Hosting :: SQL Server Temporary Tables and Table Variables

clock April 5, 2024 08:27 by author Peter

Data manipulation skills are critical for developers and database administrators in the realm of SQL Server databases. While there are many tools in SQL Server, temporary tables and table variables are particularly helpful for arranging and modifying data while the user is logged in. Temporary tables and table variables are examined in detail in this guide, along with examples that demonstrate how to utilize them and explain their differences.

SQL Temporary Tables
The TempDB system database is where temporary tables are created, and only the current session has access to them. Until they are specifically removed, they remain in place for the remainder of the session.

Table Properties within SQL Server

Conversely, table variables are only present for the length of the script or batch in which they are declared and are declared using the DECLARE statement. They are a lightweight choice for smaller datasets because they are kept in memory instead of TempDB.

Examples and Use Cases
Temporary Tables: To ensure data integrity and speed up processing when you need to store intermediate results during intricate data transformations or calculations within a session. Temporary tables are very useful for decomposing complicated searches into more manageable steps, which improves the readability and maintainability of the code.

As an illustration

CREATE TABLE #TempEmployees (
ID INT,
Name VARCHAR(50),
Department VARCHAR(50)
);

INSERT INTO #TempEmployees (ID, Name, Department)
SELECT ID, Name, Department
FROM Employees
WHERE Department = 'HumanResource';


Table Variables: When you need to hold a small set of data within a batch or script, providing a lightweight and temporary storage solution without the overhead of creating a physical table. They are particularly useful for passing small datasets as parameters to functions or stored procedures, enhancing performance, and simplifying code implementation.

Example
DECLARE @EmployeeTable TABLE (
ID INT,
Name VARCHAR(50),
Department VARCHAR(50)
);

INSERT INTO @EmployeeTable (ID, Name, Department)
SELECT ID, Name, Department
FROM Employees
WHERE Department = 'HumanResource';


Comparative Analysis
While both temporary tables and table variables serve similar purposes, they differ in several key aspects, including:

  • Scope: Temporary tables are scoped to the session, while table variables are scoped to the batch or script.
  • Storage: Temporary tables reside in the TempDB database, whereas table variables are stored in memory.
  • Indexing: Temporary tables support indexing and statistics, whereas table variables do not.
  • Transactions: Temporary tables support transactions, allowing for rollback operations, whereas table variables do not participate in transactions.

Best Practices
To make the most of temporary tables and table variables, consider the following best practices:

  • Evaluate the size of your dataset: Table variables are more suitable for smaller datasets, while temporary tables are better suited for larger datasets.
  • Properly index your temporary tables for improved performance, especially if dealing with large datasets and complex queries.
  • Drop temporary objects when no longer needed to avoid cluttering TempDB and consuming unnecessary resources.
  • Use table variables for lightweight operations such as small data manipulations or as parameters for functions and stored procedures.

Conclusion
An essential part of any SQL Server developer's toolbox, temporary tables and table variables provide versatile options for handling data while a session is open. Developers and database managers can fully utilize these constructs to maximize efficiency and speed data manipulation operations by knowing their distinctions, best practices, and useful applications. SQL Server experts can handle complicated data difficulties with confidence and speed when they use temporary tables and table variables, whether it's for storing intermediate findings, managing transactions, or performing iterative processing.



SQL Server Hosting - HostForLIFE :: Understanding FORMATMESSAGE() Function in SQL Server

clock March 27, 2024 10:01 by author Peter

SQL Server includes a variety of functions for manipulating data effectively. FORMATMESSAGE() is a powerful function. This function is essential for dynamically formatting messages, allowing for clearer communication inside the database system. In this post, we will look at the subtleties of FORMATMESSAGE(), including its usage, benefits, and practical applications.

The FORMATMESSAGE() function
FORMATMESSAGE() is a built-in SQL Server function that formats messages dynamically by replacing placeholders with provided values. It's very beneficial when you need to create messages dynamically based on various inputs. The function makes use of a message string that contains placeholders (represented by tokens) that are substituted by actual values when executed.

Syntax
FORMATMESSAGE ( message_string, arg1, arg2, ... )

Here, message_string represents the message template containing placeholders, and arg1, arg2, etc., are the arguments used to replace these placeholders.

Usage and Examples
Let's see the usage of FORMATMESSAGE() with a few examples.

Basic Usage

Suppose we want to generate a message dynamically to display the name and age of a person. We can achieve this using FORMATMESSAGE() as follows.
DECLARE @Name NVARCHAR(50) = 'peter'
DECLARE @Age INT = 30
DECLARE @Msg NVARCHAR(100)

SET @message = FORMATMESSAGE('Name: %s, Age: %d', @Name, @Age)
PRINT @Msg

In this example, %s and %d are placeholders for string and integer values, respectively. FORMATMESSAGE() replaces these placeholders with the values of @Name and @Age, generating the final message.

Error Messages
FORMATMESSAGE() is commonly used to generate error messages dynamically, incorporating relevant details.
DECLARE @ErrorCode INT = 5001
DECLARE @ErrorMessage NVARCHAR(200)

SET @ErrorMessage = FORMATMESSAGE('An error occurred with code: %d', @ErrorCode)
RAISERROR(@ErrorMessage, 16, 1)

Here, the error code is dynamically incorporated into the error message using FORMATMESSAGE().

Advantages of FORMATMESSAGE() Function

Dynamic Message Generation: FORMATMESSAGE() allows for the dynamic generation of messages based on variable inputs, enhancing flexibility in SQL Server scripting.
Localization Support: It facilitates localization by enabling the creation of messages tailored to different languages or regions.
Consistency: By using placeholders, FORMATMESSAGE() ensures consistency in message formatting across various contexts, enhancing readability and maintainability.

Where Can FORMATMESSAGE() be Used?

  • Error Handling: It's widely used to generate informative error messages dynamically, aiding in effective error handling and troubleshooting.
  • Logging: FORMATMESSAGE() can be utilized to format log messages dynamically, incorporating relevant details such as timestamps, event IDs, and descriptions.
  • Reporting: It enables the generation of customized report messages based on dynamic data, enhancing the clarity and relevance of reports

Conclusion

  • FORMATMESSAGE() emerges as a versatile function in SQL Server, offering the capability to format messages dynamically with ease and precision. Its ability to incorporate variable inputs into message templates makes it indispensable in scenarios requiring dynamic message generation, error handling, logging, and reporting. By leveraging FORMATMESSAGE(), database developers can streamline communication within the database environment, fostering clarity, consistency, and efficiency in SQL scripting.

HostForLIFEASP.NET SQL Server 2022 Hosting



European SQL Server 2022 Hosting :: Advantages of Temporary Tables vs Table Variables in SQL Server

clock March 21, 2024 09:30 by author Peter

In the world of SQL Server database management, developers frequently come across instances in which they need to store temporary data for the duration of a session or query. Two popular methods for accomplishing this are temporary tables and table variables. While they fulfill comparable functions, they have distinct differences that make one more appropriate than the other in particular contexts. In this post, we'll look at the benefits of using temporary tables over table variables in SQL Server.

Understanding Temporary Tables and Table Variables
Before diving into the comparison, let's briefly define each concept:

  • Temporary Tables: Temporary tables are created within the tempdb system database. They are visible only to the session that creates them and are automatically dropped when the session ends or when the user explicitly drops them. Temporary tables are created using the CREATE TABLE syntax preceded by a single hash (#) sign for local temporary tables or a double hash (##) sign for global temporary tables.
  • Table Variables: Table variables are variables that hold a result set for later processing. They are declared using the DECLARE keyword and are scoped to the batch, stored procedure, or function in which they are declared. Unlike temporary tables, table variables are not stored in tempdb and are always destroyed when the scope that declares them exits.

Advantages of Temporary Tables

  • Performance Optimization: Temporary tables often offer better performance compared to table variables, especially for large datasets. SQL Server's query optimizer can create more accurate execution plans for temporary tables, resulting in faster query processing. Temporary tables benefit from statistics, indexes, and parallel execution plans, which can significantly enhance query performance.
  • Scalability: Temporary tables can handle larger datasets more efficiently than table variables. Since temporary tables are stored in tempdb, which can utilize multiple disk arrays and processors, they can better scale to handle increased data volumes and concurrent user requests.
  • Complex Data Manipulation: Temporary tables allow for more complex data manipulation operations. They support features such as altering table structure, adding indexes, and joining with other tables. These capabilities make temporary tables suitable for scenarios where extensive data transformation or aggregation is required.
  • Reduced Recompilations: Table variables can lead to increased query recompilations due to their inherent nature of being treated as a single-row table with unknown statistics. This can negatively impact performance, especially in complex queries or stored procedures. In contrast, temporary tables maintain statistics, reducing the likelihood of recompilations and improving query plan stability.

When to Use Table Variables?
While temporary tables offer several advantages, table variables have their place in certain scenarios:

  • Small Result Sets: Table variables are suitable for storing small result sets, especially when performance overhead is not a concern.
  • Minimal Data Manipulation: If the data manipulation requirements are minimal and the dataset is small, table variables can be a simpler and more lightweight option.

Conclusion
While both temporary tables and table variables serve the purpose of storing temporary data in SQL Server, temporary tables offer superior performance, scalability, and flexibility for handling larger datasets and complex data manipulation tasks. By leveraging temporary tables effectively, developers can optimize query performance and improve the overall efficiency of database operations. However, it's essential to assess the specific requirements of each scenario and choose the appropriate option based on factors such as data volume, query complexity, and performance considerations.

HostForLIFEASP.NET SQL Server 2022 Hosting



About HostForLIFE

HostForLIFE is European Windows Hosting Provider which focuses on Windows Platform only. We deliver on-demand hosting solutions including Shared hosting, Reseller Hosting, Cloud Hosting, Dedicated Servers, and IT as a Service for companies of all sizes.

We have offered the latest Windows 2019 Hosting, ASP.NET 5 Hosting, ASP.NET MVC 6 Hosting and SQL 2019 Hosting.


Month List

Tag cloud

Sign in