New Features in SQL Server 2022 for Developers

SQL Server 2022 brings a comprehensive suite of features designed to enhance the development experience, improve performance, and strengthen security. By leveraging these capabilities, developers can create more efficient, scalable, and secure applications, positioning their organisations to effectively handle modern data challenges and requirements. The focus on intelligent processing, machine learning, data integration, and robust security aligns with the evolving landscape of application development and data management.

Here’s a detailed overview of the new features in SQL Server 2022 tailored for developers.

1. Intelligent Query Processing Enhancements

Overview: SQL Server 2022 continues to build on the Intelligent Query Processing (IQP) capabilities introduced in previous versions. The aim is to enhance query performance automatically without requiring significant code changes. This means that developers can achieve better performance for their applications without extensive rewrites.

Key Feature:

• Parameter Sensitive Plan Optimisation: This feature allows SQL Server to create and maintain multiple execution plans for the same query based on different parameter values. It identifies the most efficient plan based on runtime parameter values rather than relying solely on the static plan generated during compilation.

Example Scenario: Consider a financial application that retrieves transaction records based on different filters, such as dates and account numbers. With parameter-sensitive plan optimization, SQL Server will adaptively select the best execution plan based on the most commonly accessed account numbers or date ranges, leading to reduced execution times and better resource utilisation.

2. Built-in Machine Learning Services

Overview: SQL Server 2022 provides built-in support for machine learning services directly within the database engine. This integration allows developers to run R and Python scripts without the need for external tools.

Key Features:

• Direct Data Access: R and Python scripts can access SQL Server data directly, allowing for real-time analysis without the need to export data to another platform.
• Model Deployment: Developers can train and deploy machine learning models directly within SQL Server, making it easier to use these models in production applications.
• Scalability: Since machine learning is performed on the SQL Server instance, it can take advantage of the existing hardware resources, which may lead to improved performance for large datasets.

Example Scenario: A marketing department might use machine learning to predict customer churn. By training a model directly within SQL Server, they can continuously feed it fresh data from their transactional systems, enabling real-time predictions that can drive immediate business actions, such as targeted retention strategies.

3. SQL Server Ledger

Overview: SQL Server Ledger introduces a new feature that provides blockchain-like functionality, enabling developers to build applications with strong data integrity and immutability. This is particularly useful for industries that require stringent audit trails and data verification.

Key Features:

• Immutable Ledger Tables: These tables track all transactions in a way that prevents any modifications after they are committed, creating an audit trail that can be independently verified.
• Cryptographic Verification: Each transaction is cryptographically hashed, and the hashes are stored in the ledger, ensuring the integrity and authenticity of the data over time.
• Integration with Existing Systems: Developers can integrate ledger functionality with existing applications seamlessly, making it easier to adopt this technology without major architectural changes.

Example Scenario: In a healthcare application, patient treatment records can be stored in a ledger table. Each update to a patient’s treatment plan is recorded in a way that cannot be altered, providing a verifiable history that meets regulatory compliance and can be audited as needed.

4. Enhancements to Query Store

Overview: The Query Store feature is designed to help developers manage query performance by providing historical data on query execution, plan choices, and runtime statistics. The enhancements in SQL Server 2022 provide deeper insights and improved capabilities for tracking query performance over time.

Key Features:

• Query Performance Insights: The enhancements include improved reporting capabilities, allowing developers to visualize query performance trends over time and quickly identify any regressions.
• Automatic Plan Correction: SQL Server can automatically identify when a query's performance has degraded and revert to a previously optimal execution plan, reducing the need for manual intervention.
• Improved Visibility into Query Execution: Developers can see detailed information about query execution times, resource consumption, and plan changes, making it easier to diagnose performance issues.

Example Scenario: A web application might experience slowdowns after a new feature is deployed. Developers can use the Query Store to identify which queries have started to perform poorly, understand the reason behind the changes, and either optimise the queries or revert to a better-performing plan.

5. Azure Synapse Link for SQL Server

Overview: Azure Synapse Link provides a seamless integration between on-premises SQL Server databases and Azure Synapse Analytics, enabling developers to perform analytics on operational data without the need to move data to the cloud.

Key Features:

• Near Real-Time Analytics: Developers can run analytics on data as it is ingested, allowing for timely insights that can influence business decisions.
• Simplified Data Pipelines: This integration allows for the creation of streamlined data pipelines, enabling developers to focus on analysis rather than data movement.
• Enhanced Reporting: Azure Synapse provides powerful analytical capabilities that can be directly applied to operational data, enhancing reporting and decision-making.

Example Scenario: An e-commerce company can use Azure Synapse Link to analyse customer behaviour in real-time. By connecting their on-premises SQL Server to Azure Synapse, they can quickly generate reports on customer purchasing patterns, allowing for immediate marketing adjustments based on current trends.

6. Enhanced Security Features

Overview: SQL Server 2022 introduces several new security enhancements designed to protect sensitive data and improve overall database security posture.

Key Features:

• Always Encrypted with Secure Enclaves: This enhancement allows certain operations to be performed on encrypted data without exposing it in plaintext, enhancing the security of sensitive information.
• Dynamic Data Masking Enhancements: These improvements offer developers more options for controlling how sensitive data is presented to users, allowing for greater flexibility in displaying data according to user roles.
• Security Monitoring Tools: New tools provide real-time alerts and recommendations for improving database security, helping developers maintain compliance with best practices.

Example Scenario: In a banking application, sensitive information such as customer account details can be protected using Always Encrypted. Developers can configure dynamic data masking to ensure that only authorised personnel can view sensitive data, thus enhancing customer trust and compliance with regulations.

7. SQL Server Management Studio (SSMS) Enhancements

Overview: The latest version of SQL Server Management Studio includes significant enhancements designed to improve the developer experience, making it easier to manage and develop SQL Server databases.

Key Features:

• Improved IntelliSense: Enhanced IntelliSense capabilities help developers write SQL queries more efficiently by providing better auto-completion and suggestions.
• Integrated Monitoring Tools: New monitoring features allow developers to track database performance metrics directly within SSMS, enabling faster troubleshooting and optimisation.
• User-Friendly Interface: A more intuitive user interface makes it easier for developers to navigate complex database structures and management tasks.

Example Scenario: A developer working on a complex SQL query can rely on the improved IntelliSense features to quickly find the right syntax and suggestions, reducing errors and speeding up the query development process.

8. Support for UTF-8 Encoding

Overview: With the introduction of UTF-8 encoding support, SQL Server 2022 allows developers to store and manipulate multilingual data more effectively, which is crucial for global applications.

Key Features:

• Flexible Data Storage: Developers can specify UTF-8 encoding when creating string columns, enabling efficient storage of various character sets.
• Reduced Storage Requirements: By using UTF-8 encoding, developers can save space compared to UTF-16 encoding, particularly for texts primarily in English or other Latin-based languages.

That's all for now.

Implementing dynamic PIVOT in SQL Server

It is well known that PIVOT is one of the new features included in SQL Server 2005 which allows to convert rows into columns. But what happens if we wanted to make it dynamic going beyond limits respect to the number of columns? Today in this post I am going to show you how to do it (applies to SQL Server 2005 through SQL Server 2017). To begin with, we are going to use the following example to analyse some data, which will be pivoted shortly after.

USE AdventureWorks 
GO
SELECT CustomerID,YEAR(DueDate) [Year], TotalDue 
FROM Sales.SalesOrderHeader
ORDER BY CustomerID

According to the result set, there are many sales per customer between the years 2001 and 2004.



In order to pivot the 'TotalDue' per 'Year' we do need to indicate each year in the PIVOT clause. In this case we do also need to know the years which will be taken into account. For instance, this query will pivot 'TotalDue' for the years 2001, 2002, 2003, and 2004.

SELECT CustomerID, [2001] AS '2001', [2002] AS '2002', [2003] AS '2003', [2004]  AS '2004'
FROM (
      SELECT CustomerID,YEAR(DueDate) [Year], TotalDue FROM Sales.SalesOrderHeader
     ) pvt
PIVOT (SUM(TotalDue) FOR [Year] IN ([2001],[2002],[2003],[2004])) AS Child
ORDER BY CustomerID

Having successfully executed the query, we will get the following nice result:


Up to now, everything seems to be perfect. Nevertheless, what's going on if we wanted to pivot for many more years? Obviously, we would have to deal with a big limitation at first glance since we will need to add the years manually inside the query, but it does not make sense for a real business case. As a result, we can say that PIVOT is not scalable, I mean that PIVOT is not 'dynamic' by design. Luckily, the purpose of this post is to show how to implement an algorithm to simulate a dynamic PIVOT in SQL Server by using the native PIVOT clause and sp_executesql.

The algorithm is quite simple and does not deserve major explanation, however, I am going to say that this will only create a query dynamically to pivot 'TotalDue' by adding all years inside, and finally the output code will be executed via sp_executesql.

DECLARE @TableYears AS TABLE([Year] INT NOT NULL)
DECLARE @Year INT, @YearsPVT NVARCHAR(MAX) 
INSERT INTO @TableYears  SELECT DISTINCT YEAR(DueDate) AS [Year] FROM  Sales.SalesOrderHeader 
SET @Year = (SELECT MIN([Year]) FROM @TableYears)
SET @YearsPVT=N''
WHILE @Year IS NOT NULL
BEGIN
  SET @YearsPVT = @YearsPVT + N',['+ CONVERT(NVARCHAR(10),@Year) + N']'
  SET @Year = (SELECT MIN([Year]) FROM @TableYears WHERE [Year]>@Year)
END
SET @YearsPVT = SUBSTRING(@YearsPVT,2,LEN(@YearsPVT))
PRINT @YearsPVT
DECLARE @SQL NVARCHAR(MAX)
 SET @SQL = N'SELECT *
            FROM ( 
                SELECT CustomerID,YEAR(DueDate) [Year], TotalDue FROM Sales.SalesOrderHeader
                ) pvt
            PIVOT (SUM(TotalDue) FOR [Year] IN (' + @YearsPVT + ')) AS Child
            ORDER by CustomerID'
 
EXECUTE sp_executesql @SQL

Now I am going to illustrate another example by using data from Northwind database.

SELECT P.ProductID, C.CategoryName, OD.UnitPrice * OD.Quantity AS TotalAmount  
FROM Products P 
    INNER JOIN dbo.[Order Details] OD
ON P.ProductID=OD.ProductID
   INNER JOIN Categories C
ON C.CategoryID=P.CategoryID

Here the simple result without PIVOT.

Using PIVOT in its old-fashioned way:

SELECT ProductID, [Beverages], [Condiments], [Confections], [Dairy Products], 
       [Grains/Cereals], [Meat/Poultry],[Produce],[Seafood] 
FROM 
(
    SELECT P.ProductID, C.CategoryName, (OD.UnitPrice * OD.Quantity) AS Monto
    FROM Products P 
        INNER JOIN dbo.[Order Details] OD
            ON P.ProductID=OD.ProductID
        INNER JOIN Categories C
            on C.CategoryID=P.CategoryID
) PIV
PIVOT (SUM(Monto) FOR  CategoryName IN ([Beverages], [Condiments], [Confections], [Dairy Products], 
       [Grains/Cereals], [Meat/Poultry],[Produce],[Seafood])) AS Child

Having executed the code above, we will get this result pivoted.



Finally, using dynamic PIVOT the result will be the same.

DECLARE @CatPVT AS NVARCHAR(MAX), @Categorias AS VARCHAR(20)
DECLARE @CatID INT 
SET @CatID=(SELECT MIN(CategoryID) FROM Categories)
SET @Categorias = ( SELECT CategoryName FROM Categories WHERE CategoryID = @CatID)
SET @CatPVT = N''
WHILE @Categorias IS NOT NULL
BEGIN
  SET @CatPVT = @CatPVT + N',['+ @Categorias +N']'
  SET @Categorias = (SELECT TOP(1) CategoryName 
                     FROM Categories WHERE CategoryID > @CatID 
                     ORDER BY CategoryID ASC)
  SET @CatID=(SELECT MIN(CategoryID) FROM Categories WHERE Categoryname=@Categorias)
END
print @CatPVT
SET @CatPVT = SUBSTRING(@CatPVT, 2, LEN(@CatPVT))
 
DECLARE @sql AS NVARCHAR(MAX)
SET @sql = N'SELECT *  
            FROM (SELECT P.ProductID, C.CategoryName, (OD.UnitPrice * OD.Quantity) AS Monto
                  FROM Products P 
                    INNER JOIN dbo.[Order Details] OD
                        ON P.ProductID=OD.ProductID
                    INNER JOIN Categories C
                    ON C.CategoryID=P.CategoryID
            ) PIV
            PIVOT (SUM(Monto) FOR  CategoryName IN ('+ @CatPVT  + ')) AS Child'
 
EXEC sp_executesql @sql

As you have seen, dynamic PIVOT is truly useful for a real business case. Therefore, I hope you make the most out of this algorithm. That is all for now, let me know any remarks you may have. Thanks for reading. Stay tuned.

Getting information about referenced and referencing tables

At times we do need to carry out some tasks related to figure out certain information about references among some database objects. Today's post is going to show an example for tables by using T-SQL. There are two SQL Server system views we will use to query that information, they are 'sys.objects' and 'sys.sysreferences'. The view 'sys.objects' contains information for each database object (DDL and DML triggers) created inside of a particular user schema, and sys.sysreferences has the following important columns which will give us the object id of the referenced and referencing object.

• rkeyid: Contains the ID of the object which is being referenced.
• fkeyid: Contains the ID of the object which is referencing.  

For instance, now we are going to figure out which tables are being referenced from the 'Product' table inside the 'AdventureWorks' database:

SELECT S.[name] AS 'Referenced Table'
FROM sys.objects S INNER JOIN sys.sysreferences R 
   ON S.OBJECT_ID = R.rkeyid
WHERE S.[type] = 'U' AND R.fkeyid = OBJECT_ID('[Production].[Product]')

Having done that, we can also figure out which tables are referencing to the 'Product' table. 

SELECT S.[name] AS 'Referencing Table'
FROM sys.objects S INNER JOIN sys.sysreferences R 
   ON S.OBJECT_ID = R.fkeyid
WHERE S.[type] = 'U' AND R.fkeyid = OBJECT_ID('[Production].[Product]')

As I said earlier, not only can we use those views for tables, but also for other objects like functions, stored procedures, views, etc. I hope you can make the most out of this tip. Let me know any remarks you may have. Stay tuned.

Converting Unix Timestamp into SQL Server DateTime

It is well known that developing and integrating applications based on different technologies may end up being a huge challenge, especially when it comes to dealing with data stored in diverse data type formats as it is Timestamp in Unix and DateTime in SQL Server. This post intents to show you a method in SQL Server to convert Unix Timestamp into Datetime. Here it is:

CREATE FUNCTION [dbo].[UNIX_TIMESTAMP_TO_DATETIME] (
@timestamp integer
)
RETURNS datetime
AS
BEGIN
  DECLARE @return datetime
  SET @timestamp = @timestamp - 18000
  SELECT @return = DATEADD(second, @timestamp,{d '1970-01-01'});
   
  RETURN @return
END

The function takes as a parameter a Unix Timestamp value so that it is converted into Datetime, and it will then give you the equivalent value in SQL Server Datetime format.  I know it might not be the be-all and end-all, nevertheless, I am pretty sure it will be use for many people. I hope you make the most out of it. That’s all for now. Let me know any remarks you may have. Thanks for reading. Stay tuned.

SQL2016: DROP IF EXISTS and CREATE OR ALTER statements

Beyond all doubt, using old-fashioned ways of manipulating database objects is not only a wasting of time but also boring. Therefore, it is well-known that there are situations where we face with many errors while altering or dropping certain database objects because they do not exist or  maybe they already are created. The traditional way of completing this task suggests writing a logic to validate first the existence of the object and then make a decision depending on the result, for instance, we usually do it by querying the object from the 'sys.all_objects' system view. Having said that, I am of the idea that this way of working is always a very unproductive task. Luckily, this situation has changed as now with the arrival of SQL Server 2016 we are able to drop/creater/alter database objects without thinking much about whether they are or not existing objects.

Let me expand on what I am saying. New language features of T-SQL have been introduced in SQL Server 2016 such as DROP IF EXISTS and CREATE OR ALTER statements. With DROP IF EXISTS we can drop some sorts of object and validate their existence in only one statement. The objects supported with DROP IF EXISTS are PROCEDURE, TABLE (included COLUMN and CONSTRAINT), TRIGGER, VIEW, FUNCTION, INDEX, ASSEMBLY, ROLE, AGGREGATE, RULE, TYPE, DATABASE, SCHEMA, USER, DEFAULT, SECURITY POLICY, SEQUENCE, and SYNONYM. Thus we do not need to do something like this any longer.

IF EXISTS (SELECT * FROM sys.objects WHERE name = 'MyProcNumberOne')
 DROP PROCEDURE MyProcNumberOne

Here are some examples of DROP IF EXISTS statement.

DROP PROCEDURE IF EXISTS [dbo].[MyProcNumberOne]
GO
DROP TABLE IF EXISTS [dbo].[MyTableDemo]
GO
DROP VIEW IF EXISTS [dbo].[MyViewTest]
GO
DROP VIEW IF EXISTS [dbo].[MyFunctionTwo]
GO
DROP INDEX IF EXISTS [dbo].[IX_MyTableDemo_04]

Now DROP IF EXISTS working on columns and constraints.

ALTER TABLE [dbo].[MyTableDemo] DROP COLUMN IF EXISTS Col2
GO
ALTER TABLE [dbo].[MyTableDemo] DROP CONSTRAINT IF EXISTS FK_MyTableDemo_10
GO

Now talking of the other new statement CREATE OR ALTER, it supports STORED PROCEDURES (including natively compiled), FUNCTIONS (including natively compiled), TRIGGERS, and VIEWS. So we are not going to need the traditional validation any more.

IF NOT EXISTS (SELECT * FROM dbo.sysobjects WHERE id = OBJECT_ID(N'[dbo].[MyProcNumberOne]')
CREATE PROCEDURE dbo.mysproc (@Par1 INT, @Par2 VARCHAR(10), ... )
AS
BEGIN
...
..

CREATE OR ALTER statement is also easy to use. If the object exists then it will be altered, otherwise it will be created. I couldn't have been simpler.

CREATE OR ALTER [dbo].[MyProcNumberOne] (@Par1 INT, @Par2 VARCHAR(10), ... )
AS
BEGIN
...
..

To be perfectly honest, I do think that these new language features are the be-all and end-all as they are practical, simple and allow us to work in the sense of improving the quality of deploying new business functionalities and integration of systems. Surely, you will make the most out of these features. That is all for now. Let me know any remarks you may have. Thanks for reading. 

SQL11 (Denali): New object SEQUENCE

SQL Server 2012 CTP1 is coming up with a new object named SEQUENCE which allows to manage sequence numbers between 2^31 – 1 and 2^31 –1. SEQUENCE solves many problems with respect to using the IDENTITY property because it is not tied to the column and can be used for many columns in different tables. In this capacity, this novelty is useful as alternative solution and in replacement of ROW_NUMBER for some cases. SEQUENCE can be used with UNION ALL but not with Functions, DISTINCT, UNION, EXCEPT and INTERSECT. The way of using is very easy, practical, flexible and  offers better performance than IDENTITY. Creating the right indexes on columns which takes values from SEQUENCE object will help tremendously, indeed.

Creating a SEQUENCE object is simple.

CREATE SEQUENCE dbo.MySeq
    AS INT 
    START WITH 1
    INCREMENT BY 1
    MINVALUE 1
    MAXVALUE 100
    CYCLE 
    CACHE 20
;

Now using it:

SELECT NEXT VALUE FOR dbo.MySeq
GO 4

The result would be something like this:

(no column name)

1

2

3

4

If we execute again the previous query, the result will be numbers from 5 to 8, and so on. However, if we want to reinitialise the sequence, it can be done as follows:

ALTER SEQUENCE dbo.MySeq RESTART 

Now using SEQUENCE as an alternative of ROW_NUMBER:

select next value for dbo.MySeq as [nro],  Employees.FirstName   from Employees 

And also in this way:

select next value for dbo.MySeq  over (order by customers.CustomerID ) as [nro], 
       customers.CustomerID,  Customers.ContactName 
 from Customers 

Here are some resources to check out more information about SEQUENCE:

• Creating and Using Sequence Numbers.
  http://msdn.microsoft.com/en-us/library/ff878058(v=SQL.110).aspx
• sp_sequence_get_range (Transact-SQL)
  http://msdn.microsoft.com/en-us/library/ff878352(v=SQL.110).aspx
• SQL Server v.Next (Denali): Using SEQUENCE http://sqlblog.com/blogs/aaron_bertrand/archive/2010/11/11/sql-server-11-denali-using-sequence.aspx

That is all for now, let me know any remark you may have. Thanks for reading.

SQL11 (Denali): OFFSET and FETCH (New options for ORDER BY)

It is known that ORDER BY clause has been improved in 'Denali' (code name of the upcoming version SQL Server 2012) adding more options as a result from looking for new solutions to work on specific business cases such as fetching top N rows per window of results from the result set which we used to do by combining TOP, OVER, and ORDER BY. Nevertheless, the performance of this approach was poor and not even close to being as good as OFFSET and FETCH in 'Denali'.

OFFSET keyword is used for excluding first N rows (default value is zero) whereas FETCH is used for reading/fetching M rows per each window of results starting from position (N+1). Therefore, OFFSET and FETCH allow to get only rows from position (N+1) to (N+M). I do recommend creating one Index (preferably Index Clustered) on ORDER BY columns and using these columns on WHERE clause as much as possible in order to avoid costly operations such as Index Scans or Table Scans. I have performed many tests on 10 millions of rows, and to be to honest, it worked very well. To illustrate, the following query will start fetching from position 4+1=5 (OFFSET position=4 for SQL Server) to the end of the table.

SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address   
FROM dbo.Customers    
ORDER BY CustomerID 
   OFFSET (4) ROWS

Now with DESC the results will be different (excluding last 4 rows)

SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address   
FROM dbo.Customers    
ORDER BY CustomerID  DESC
   OFFSET (4) ROWS

Basically, each execution of the query is done independently, which means that not only are the results sent back to the client side, but also immediately the resources are released. Here is another example how to get only the top 3 rows excluding first 4 rows (OFFSET=4), which means that it only reads the fifth, sixth, and seventh rows.

SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
FROM dbo.Customers    
ORDER BY CustomerID  
   OFFSET (4) ROWS 
   FETCH NEXT 3 ROWS ONLY --  FETCH FIRST 3 ROWS ONLY
GO

Having a need to read the next three rows (eighth, ninth, and tenth rows), we have to increase OFFSET value in three.

 

SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
FROM dbo.Customers    
ORDER BY CustomerID  
   OFFSET (7) ROWS ---ó OFFSET (7) ROW 
   FETCH NEXT 3 ROWS ONLY -- ó FETCH FIRST 3 ROWS ONLY
GO

Here the script to read dynamically each result by using variables (and optionally OPTIMIZE FOR hint to optimise this Ad-Hoc query). 

DECLARE @Start INT, @Next INT
SET @Start=0 

SET @Next=3
SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
FROM dbo.Customers    
ORDER BY CustomerID 
     OFFSET (@Start) ROWS    
     FETCH NEXT @Next ROWS ONLY 

 OPTION(OPTIMIZE FOR (@Start=4,@Next=5))
GO

Now the same code inside an stored procedure.

CREATE PROCEDURE dbo.PageFetch(@PageNumber INT, @PageSize INT)
AS
BEGIN
SELECT ROW_NUMBER() OVER (ORDER BY CustomerID) AS 'Nro', 
CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
FROM dbo.Customers    
ORDER BY CustomerID 
     OFFSET (@PageSize * (@PageNumber -1) ) ROWS
     FETCH NEXT @PageSize ROWS ONLY 
END

Querying the results for second, third and fifth windows of results with OFFSET.

EXEC dbo.PageFetch 2,3;
GO
EXEC dbo.PageFetch 3,3;
GO
EXEC dbo.PageFetch 5,3;

Luckily, OFFSET and FETCH are supported by subqueries, functions, derived tables, but not by indexed views and using directly with TOP, OVER, INSERT, UPDATE, MERGE, o DELETE (except inside of independent queries at lower level such as subqueries). Here an illustration.

SELECT  TOP(2) ROW_NUMBER() OVER(ORDER BY CustomerID) AS 'NRO', CompanyName, ContactName, ContactTitle  FROM (
        SELECT  CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
        FROM dbo.Customers    
        ORDER BY CustomerID  
           OFFSET (4) ROWS ---ó OFFSET (4) ROW 
           FETCH NEXT 3 ROWS ONLY -- ó FETCH FIRST 3 ROWS ONLY
) AS T1

Finally, using it with Views.

CREATE VIEW dbo.v1
as
SELECT CustomerID, CompanyName, ContactName, ContactTitle, Address --/..*.../  
FROM dbo.Customers  
ORDER BY CustomerID 
   OFFSET (0) ROWS ---ó OFFSET (4) ROW 
GO
SELECT CustomerID, CompanyName, ContactName FROM dbo.v1
WHERE  CustomerID LIKE 'AN%' 

To sum up, OFFSET and FETCH are excellent improvements which allow to implement solutions to fetch only specific pages/windows of results from the result set with ease. Let me know any remarks you may have. Thanks for reading!

SQL Server 2008: Row Value Constructor

Definitely, we were sometimes in a need of a new technique to insert data massively in SQL Server 2005 and previous versions. We used to do it by using traditional techniques like UNION ALL and individual INSERT statements. This story has ended up with the arrival of a new feature in SQL Server 2008 which allows to insert much data with only one INSERT statement, that is, Row Value Constructor.

To begin with, we are going to illustrate this new feature by creating a new table where four data rows will be inserted.

CREATE TABLE [Production].[Document](
    [DocumentID] [int] IDENTITY(1,1) NOT NULL,
    [Title] [nvarchar](50) COLLATE Latin1_General_CS_AS NOT NULL,
    [FileName] [nvarchar](400) COLLATE Latin1_General_CS_AS NOT NULL,
    [FileExtension] [nvarchar](8) COLLATE Latin1_General_CS_AS NOT NULL,
    [Revision] [nchar](5) COLLATE Latin1_General_CS_AS NOT NULL,
    [ChangeNumber] [int] NOT NULL CONSTRAINT [DF_Document_ChangeNumber]  DEFAULT ((0)),
    [Status] [tinyint] NOT NULL,
    [DocumentSummary] [nvarchar](max) COLLATE Latin1_General_CS_AS NULL,
    
    [ModifiedDate] [datetime] NOT NULL CONSTRAINT [DF_Document_ModifiedDate]  DEFAULT (getdate()),
 CONSTRAINT [PK_Document_DocumentID] PRIMARY KEY CLUSTERED 
(
    [DocumentID] ASC
)
) ON [PRIMARY]

At first, we will do it in SQL Server 2005. This is the traditional and old-fashioned way (one INSERT statement per row): 

INSERT INTO [Production].[Document]([Title],[FileName],[FileExtension],[Revision],[ChangeNumber],[Status],[DocumentSummary])
VALUES ('Installing Replacement Pedals','C:DocumentsInstalling Replacement Pedals.doc','.doc','0',32,2,'Detailed instructions ...')

INSERT INTO [Production].[Document]([Title],[FileName],[FileExtension],[Revision],[ChangeNumber],[Status],[DocumentSummary])
VALUES ('Introduction 1','C:DocumentsIntroduction 1.doc','.doc','4',28,2,NULL)

INSERT INTO [Production].[Document]([Title],[FileName],[FileExtension],[Revision],[ChangeNumber],[Status],[DocumentSummary])
VALUES ('Lubrication Maintenance','C:DocumentsLubrication Maintenance.doc','.doc','2',11,1,'Guidelines and recommendations...')

INSERT INTO [Production].[Document]([Title],[FileName],[FileExtension],[Revision],[ChangeNumber],[Status],[DocumentSummary])
VALUES ('Seat Assembly','C:DocumentsSeat Assembly.doc','.doc','8',55,2,'Worn or damaged seats...')

This is the cumbersome way by using UNION ALL clause which has sometimes poor performance:

INSERT INTO [Production].[Document]([Title],[FileName],[FileExtension],[Revision],[ChangeNumber],[Status],[DocumentSummary])
SELECT 'Installing Replacement Pedals','C:DocumentsInstalling Replacement Pedals.doc','.doc','0',32,2,'Detailed instructions ...'
UNION ALL
SELECT 'Introduction 1','C:DocumentsIntroduction 1.doc','.doc','4',28,2,NULL
UNION ALL 
SELECT 'Lubrication Maintenance','C:DocumentsLubrication Maintenance.doc','.doc','2',11,1,'Guidelines and recommendations...'
UNION ALL
SELECT 'Seat Assembly','C:DocumentsSeat Assembly.doc','.doc','8',55,2,'Worn or damaged seats...'

Now in SQL Server 2008 we can use Row Value Constructor feature (only one INSERT statement to insert four data rows):

INSERT INTO [Production].[Document](  
      [Title]
      ,[FileName]
      ,[FileExtension]
      ,[Revision]
      ,[ChangeNumber]
      ,[Status]
      ,[DocumentSummary]
)
VALUES ('Installing Replacement Pedals','C:DocumentsInstalling Replacement Pedals.doc','.doc','0',32,2,'Detailed instructions ...'),
('Introduction 1','C:DocumentsIntroduction 1.doc','.doc','4',28,2,NULL),
('Lubrication Maintenance','C:DocumentsLubrication Maintenance.doc','.doc','2',11,1,'Guidelines and recommendations...'),
('Seat Assembly','C:DocumentsSeat Assembly.doc','.doc','8',55,2,'Worn or damaged seats...')

As you have noticed, we do not need to use UNION ALL any longer, it allow to save a lot of time and work. It is truly useful when we need to insert much data and it also offers a remarkable performance. I hope you enjoy this new feature. Thanks for reading again!

Exploring ROW_NUMBER function in SQL Server 2005

Some of the SQL Server 2005 new features are the Ranking functions which are used to analyse data. Among these functions we have, for instance, ROW_NUMBER which helps to enumerate every row of a result set in a simpler way. Before showing the illustration of it, I will share the syntax:

ROW_NUMBER ( ) OVER ( [ partition_by_clause ] order_by_clause )
where:

• partition_by_clause: Divide the result set generated by FROM clause into partitions on which ROW_NUMBER will work.
• order_by_clause: Determine the order for ROW_NUMBER.

Now the illustration: we are going to enumerate the details of the sales based on the price.

SELECT ROW_NUMBER() OVER( ORDER BY UnitPrice DESC ) AS Item, 
SaleOrderID, ProductID, Quantity,UnitPrice 
FROM OrderDetail 

Item    SaleOrderID     ProductID   Quantity    UnitPrice
----    ------------    ---------   --------    -----------
1        00000015       FX8S           1        7621.71
2        00000016       FX8E           1        3601.77
3        00000016       FX5P           1        2207.87
4        00000014       FX5G           1        6507.82
5        00000018       FX21           1        631.62
6        00000019       FX19           1        751.62

Another example of it would be using PARTITION clause for partitions result sets by ProductGroupID and then ROW_NUMBER will be applied based on ProductStock. Therefore, we are writing a query like this:

SELECT ROW_NUMBER() OVER(PARTITION BY ProductGroupID ORDER BY ProductStock ASC) AS Item, 
ProductID, ProductDesc, ProductGroupID, ProductStock 
FROM Products

Item  ProductID    ProductDesc                       ProductGroupID    ProductStock

----  ---------    ------------------------------    --------------    -----------
1     DS02         MAINBOARD 845 PEMYL               G003               -1
2     DS06         MAINBOARD 850 EV2                 G003               10
1     DS07         TECLADO 104 MULTIMEDIA32          G004               20
1     DS12         SWITCH 5 PORT 10/100, 220V        G006               26
1     DS45         MUEBLE DE OFICINA                 G007               34
1     DS76         DISCO DURO                        G008               20
1     DS07         IMPRESORA LASER                   G009               10
1     DS45         MEMORIA STICK                     G010               2
2     DS29         MEMORIA VIDEO                     G010               5
1     DS08         TINTA CANON BCI24 NEGRO           G011               12
1     DS41         WEB CAM ALTIOR MODELO B02         G012               0
1     DS74         MONITOR DE 15                     G016               6
1     DS83         IMPRESORA MATRICIAL DFX5001       G018               12
2     DS84         IMPRESORA MATRICIAL DFX8502       G018               17
3     DS21         IMPRESORA MATRICIAL FX21944       G018               48

(15 row(s) affected)

As I mentioned before, this functionality is helpful, simple and easy to use it, so it does not worth a major explanation. That is all for now. Thanks for reading. Stay tuned.

The power of PIVOT in SQL Server 2005

With the arrival of SQL Server 2005, we have many new features available to make the most out of it. Today's post is going to be about one of the greatest new functionalities, that is, the powerful PIVOT sentence which can be used for converting rows into columns (and vice versa) in order to have a vision much more structured and meaningful of the data result sets.

So, moving on the example, we are going to use some tables of the 'Northwind' database like 'Orders', 'Orders Details', 'Employees', and 'Products'. The objective is to show the total value sold by each employee for the following products: 'Alice Mutton', 'Filo Mix', 'Flotemysost', 'Geitost', 'Konbu', 'Maxilaku', 'Pavlova', 'Tofu', and  'Vegie-spread'. Well, in SQL Server 2000, it can be done by using INNER JOINs and 3 Subqueries (if you had more tables to query, it would become a complex work to do). As a result of this, not only does the query become complex, but also it is not the most optimum choice.

SELECT Ventas1.*

FROM (SELECT Empleado, 

        (SELECT Products.ProductName FROM Products    

          WHERE Products.Productid=Ventas.ProductID) Producto, 

                SUM (ventas.ValorVendido)Total

      FROM (SELECT (C.lastname + ‘ ‘ + c.firstname)Empleado,ProductId,

                 (OD.Unitprice*OD.Quantity) [ValorVendido]

            FROM [Order Details] OD

             INNER JOIN ( [Orders] O        

              INNER JOIN Employees C

            ON O.Employeeid=C.Employeeid)

             ON OD.Orderid=O.OrderID) Ventas

GROUP BY Empleado, Productid) Ventas1

WHERE Producto IN(‘Alice Mutton’,‘Filo Mix’,‘Flotemysost’,‘Geitost’,

‘Konbu’,‘Maxilaku’,‘Pavlova’,‘Tofu’,‘Vegie-spread’)

Here we can see the partial result:



Having seen how difficult some queries can become by using old-fashioned and traditional techniques, now we are going rewrite the query to use PIVOT. Here is the code:

SELECT Empleado, [Alice Mutton],[Filo Mix],[Flotemysost],

      [Geitost],[Konbu], [Maxilaku],[Pavlova],[Tofu],[Vegie-spread]

FROM (SELECT Empleado, 

             (SELECT PRoducts.Productname FROM Products

             WHERE Products.Productid=Ventas.Productid) Producto,

                 SUM (ventas.ValorVendido) Total

      FROM (SELECT (C.lastname+ ‘ ‘ + C.firstname) Empleado, ProductID, 

               (OD.Unitprice*OD.Quantity) [ValorVendido]

            FROM [Order Details]OD

                INNER JOIN ([Orders] O

                INNER JOIN Employees C

             ON O.EmployeeID=C.EmployeeID

        )

ON OD.OrderID=O.OrderID) Ventas

GROUP BY Empleado,Productid) ventas1

PIVOT(SUM(total) FOR [Producto] IN ([Alice Mutton],[Filo Mix],[Flotemysost],

[Geitost],[Konbu],[Maxilaku],[Pavlova],[Tofu],[Vegie-spread])) AS pvt

Only after successfully familiarising with PIVOT will we realise how easy and practical is use it so as to save not only time but also costs. More details about it can be found by checking the following resource http://msdn2.microsoft.com/es-es/library/ms177410.aspx.

That is all for now until next post. Let me know any remarks and experience you have may using PIVOT. Thanks for reading. Stay tuned.