Eleo Nona

Eleo Nona

1583309998

Difference Between TRUNCATE, DELETE and DROP commands in SQL Server

The difference between TRUNCATE, DELETE, and DROP is one of the most common interview questions. TRUNCATE, DELETE, and DROP SQL queries are often used in SQL Server to Here are some of the common differences between them.

TRUNCATE

TRUNCATE SQL query removes all rows from a table, without logging the individual row deletions. TRUNCATE is faster than the DELETE query.

The following example removes all data from the Customers table.

TRUNCATE TABLE Customers;   
  1. TRUNCATE is a DDL command
  2. TRUNCATE is executed using a table lock and the whole table is locked to remove all records.
  3. We cannot use the WHERE clause with TRUNCATE.
  4. TRUNCATE removes all rows from a table.
  5. Minimal logging in the transaction log, so it is faster performance-wise.
  6. TRUNCATE TABLE removes the data by deallocating the data pages used to store the table data and records only the page deallocations in the transaction log.
  7. Identify the column is reset to its seed value if the table contains an identity column.
  8. To use Truncate on a table you need at least ALTER permission on the table.
  9. Truncate uses less transaction space than the Delete statement.
  10. Truncate cannot be used with indexed views.
  11. TRUNCATE is faster than DELETE.

DELETE

SQL DELETE query deletes all records from a database table. To execute a DELETE query, delete permissions are required on the target table. If you need to use a WHERE clause in a DELETE, select permissions are required as well.

The following query deletes all rows from the Customers table.

DELETE FROM Customers;  
GO

The following SQL query deletes all rows from the Customers table where OrderID is greater than 1000.

DELETE FROM Customers WHERE OrderId > 1000;  
GO 
  1. DELETE is a DML command.
  2. DELETE is executed using a row lock, each row in the table is locked for deletion.
  3. We can use where clause with DELETE to filter & delete specific records.
  4. The DELETE command is used to remove rows from a table based on WHERE condition.
  5. It maintains the log, so it slower than TRUNCATE.
  6. The DELETE statement removes rows one at a time and records an entry in the transaction log for each deleted row.
  7. Identity of column keep DELETE retains the identity.
  8. To use Delete you need DELETE permission on the table.
  9. Delete uses more transaction space than the Truncate statement.
  10. The delete can be used with indexed views.

DROP

DROP table query removes one or more table definitions and all data, indexes, triggers, constraints, and permission specifications for those tables. DROP command requires to ALTER permission on the schema to which the table belongs, CONTROL permission on the table, or membership in the db_ddladmin fixed database role.

The following SQL query drops the Customers table and its data and indexes from the current database.

DROP TABLE Customers ; 
  1. The DROP command removes a table from the database.
  2. All the tables’ rows, indexes, and privileges will also be removed.
  3. No DML triggers will be fired.
  4. The operation cannot be rolled back.
  5. DROP and TRUNCATE are DDL commands, whereas DELETE is a DML command.
  6. DELETE operations can be rolled back (undone), while DROP and TRUNCATE operations cannot be rolled back

Summary

In this post, we saw the differences between TRUNCATE, DELETE, and DROP SQL commands. We saw key characteristics of these commands.

Thanks for reading!

#sql #sql sever #database #webdev

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Difference Between TRUNCATE, DELETE and DROP commands in SQL Server
Cayla  Erdman

Cayla Erdman

1594369800

Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

#programming books #beginning sql pdf #commands sql #download free sql full book pdf #introduction to sql pdf #introduction to sql ppt #introduction to sql #practical sql pdf #sql commands pdf with examples free download #sql commands #sql free bool download #sql guide #sql language #sql pdf #sql ppt #sql programming language #sql tutorial for beginners #sql tutorial pdf #sql #structured query language pdf #structured query language ppt #structured query language

Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Brain  Crist

Brain Crist

1600347600

SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master

Introduction

This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,

A glimpse of previous articles
Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2
  • We learned to create a database and maintain it using SQL statements.
  • Best practice methods were also mentioned.

#sql server #benefits of schemas #create schema in sql #database schemas #how to create schema in sql server #schemas #schemas in sql server #sql server schemas #what is schema in sql server

Karlee  Will

Karlee Will

1620516240

Key Differences between SQL Server 2019 for Windows and Linux

Since the release of SQL Server 2017 for Linux, Microsoft has pretty much changed the entire game. It enabled a whole new world of possibilities for their famous relational database, offering what was only available in the Windows space until then.

I know that a purist DBA would tell me right away that the out of the box SQL Server 2019 Linux version has several differences, in terms of features, in regards to its Windows counterpart, such as:

  • No SQL Server Agent
  • No FileStream
  • No System Extended Stored Procedures (e.g. xp_cmdshell)

However, I got curious enough to think “what if they can be compared, at least to some extent, against things that both can do?” So, I pulled the trigger on a couple of VMs, prepared some simple tests, and collected data to present to you. Let’s see how things turn out!

#sql server #sql server 2019 #sql server linux #sql server windows #sql

Cayla  Erdman

Cayla Erdman

1596441660

Welcome Back the T-SQL Debugger with SQL Complete – SQL Debugger

When you develop large chunks of T-SQL code with the help of the SQL Server Management Studio tool, it is essential to test the “Live” behavior of your code by making sure that each small piece of code works fine and being able to allocate any error message that may cause a failure within that code.

The easiest way to perform that would be to use the T-SQL debugger feature, which used to be built-in over the SQL Server Management Studio tool. But since the T-SQL debugger feature was removed completely from SQL Server Management Studio 18 and later editions, we need a replacement for that feature. This is because we cannot keep using the old versions of SSMS just to support the T-SQL Debugger feature without “enjoying” the new features and bug fixes that are released in the new SSMS versions.

If you plan to wait for SSMS to bring back the T-SQL Debugger feature, vote in the Put Debugger back into SSMS 18 to ask Microsoft to reintroduce it.

As for me, I searched for an alternative tool for a T-SQL Debugger SSMS built-in feature and found that Devart company rolled out a new T-SQL Debugger feature to version 6.4 of SQL – Complete tool. SQL Complete is an add-in for Visual Studio and SSMS that offers scripts autocompletion capabilities, which help develop and debug your SQL database project.

The SQL Debugger feature of SQL Complete allows you to check the execution of your scripts, procedures, functions, and triggers step by step by adding breakpoints to the lines where you plan to start, suspend, evaluate, step through, and then to continue the execution of your script.

You can download SQL Complete from the dbForge Download page and install it on your machine using a straight-forward installation wizard. The wizard will ask you to specify the installation path for the SQL Complete tool and the versions of SSMS and Visual Studio that you plan to install the SQL Complete on, as an add-in, from the versions that are installed on your machine, as shown below:

Once SQL Complete is fully installed on your machine, the dbForge SQL Complete installation wizard will notify you of whether the installation was completed successfully or the wizard faced any specific issue that you can troubleshoot and fix easily. If there are no issues, the wizard will provide you with an option to open the SSMS tool and start using the SQL Complete tool, as displayed below:

When you open SSMS, you will see a new “Debug” tools menu, under which you can navigate the SQL Debugger feature options. Besides, you will see a list of icons that will be used to control the debug mode of the T-SQL query at the leftmost side of the SSMS tool. If you cannot see the list, you can go to View -> Toolbars -> Debugger to make these icons visible.

During the debugging session, the SQL Debugger icons will be as follows:

The functionality of these icons within the SQL Debugger can be summarized as:

  • Adding Breakpoints to control the execution pause of the T-SQL script at a specific statement allows you to check the debugging information of the T-SQL statements such as the values for the parameters and the variables.
  • Step Into is “navigate” through the script statements one by one, allowing you to check how each statement behaves.
  • Step Over is “execute” a specific stored procedure if you are sure that it contains no error.
  • Step Out is “return” from the stored procedure, function, or trigger to the main debugging window.
  • Continue executing the script until reaching the next breakpoint.
  • Stop Debugging is “terminate” the debugging session.
  • Restart “stop and start” the current debugging session.

#sql server #sql #sql debugger #sql server #sql server stored procedure #ssms #t-sql queries