SQL Server is a widespread database administration system utilized by organizations of all sizes. In order to effectively manage and maintain a database as a database administrator or developer, it is necessary to have a thorough understanding of SQL. This post will cover some useful SQL Server queries that will assist you in performing a variety of duties.
1. List all databases supported by SQL Server

To view an inventory of all databases on a server, use the query below.

SELECT name FROM sys.databases

This will return a list of all databases on the server, including system databases such as 'master', 'model', and 'tempdb'.

2. Viewing the schema of a SQL table
To see the structure of a table, including column names and data types, you can use the following query:
EXEC sp_help 'table_name'

This will return a list of all columns in the table, along with information such as the data type, length, and whether or not the column is nullable.

3. Checking the size of a SQL Server database
To see the size of a database, including the amount of used and unused space, you can use the following query:

EXEC sp_spaceused

This will return the number of rows in the database, the amount of reserved space, and the amount of used and unused space.

4. Retrieving the current user
To see the current user that is connected to the database, you can use the following query:

SELECT SUSER_NAME()

This can be useful for auditing purposes, or for determining which user is making changes to the database.
5. Viewing the current date and time

To see the current date and time on the server, you can use the following query:
SELECT GETDATE()

This can be useful for storing timestamps in your database, or for checking the current time on the server.

6. Finding the Total Space of the tables in a database
To see the total space of all the tables in a database, you can use the following query:
SELECT t.NAME
       AS
       TableName,
       s.NAME
       AS SchemaName,
       p.rows,
       Sum(a.total_pages) * 8
       AS TotalSpaceKB,
       Cast(Round(( ( Sum(a.total_pages) * 8 ) / 1024.00 ), 2) AS NUMERIC(36, 2)
       ) AS
       TotalSpaceMB,
       Sum(a.used_pages) * 8
       AS UsedSpaceKB,
       Cast(Round(( ( Sum(a.used_pages) * 8 ) / 1024.00 ), 2) AS NUMERIC(36, 2))
       AS
       UsedSpaceMB,
       ( Sum(a.total_pages) - Sum(a.used_pages) ) * 8
       AS UnusedSpaceKB,
       Cast(Round(( ( Sum(a.total_pages) - Sum(a.used_pages) ) * 8 ) / 1024.00,
            2) AS
            NUMERIC(36, 2))
       AS UnusedSpaceMB
FROM   sys.tables t
       INNER JOIN sys.indexes i
               ON t.object_id = i.object_id
       INNER JOIN sys.partitions p
               ON i.object_id = p.object_id
                  AND i.index_id = p.index_id
       INNER JOIN sys.allocation_units a
               ON p.partition_id = a.container_id
       LEFT OUTER JOIN sys.schemas s
                    ON t.schema_id = s.schema_id
WHERE  t.NAME NOT LIKE 'dt%'
       AND t.is_ms_shipped = 0
       AND i.object_id > 255
GROUP  BY t.NAME,
          s.NAME,
          p.rows
ORDER  BY totalspacemb DESC,
          t.NAME

This can be useful for identifying tables that may be consuming a large amount of space, and determining if any optimization is necessary.

7. Connect two Database with Different Servers in SQL Server
To connect two databases on different servers in a SQL Server query, you can use a linked server. A linked server allows you to connect to another instance of an SQL Server and execute queries against it.
exec sp_addlinkedsrvlogin  'Servername', 'false', null, 'userid', 'password';

This can be connected to two databases.

8. Execute the query with the connected server database
To see the query where you use one server database for another server database, you can use the following query:
select  *  from [Servername].[Databasename].[dbo].[tablename]

This can be used from one server database to another database.

9. Disconnect two Database with Different Servers in SQL Server
To disconnect a linked server in SQL Server, you can use the sp_dropserver system stored procedure. Here's the syntax:
drop server exec sp_dropserver    @server='Servername'

This can be disconnected from one server database to another database.

10. Top 20 Costliest Stored Procedures - High CPU
To see the query where you can find the SP which takes a High CPU, you can use the following query:
SELECT TOP (20)
    p.name AS [SP Name],
    qs.total_worker_time AS [TotalWorkerTime],
    qs.total_worker_time/qs.execution_count AS [AvgWorkerTime],
    qs.execution_count,
    ISNULL(qs.execution_count/DATEDIFF(Second, qs.cached_time, GETDATE()), 0) AS [Calls/Second],
    qs.total_elapsed_time,
    qs.total_elapsed_time/qs.execution_count AS [avg_elapsed_time],
    qs.cached_time
FROM    sys.procedures AS p WITH (NOLOCK)
INNER JOIN sys.dm_exec_procedure_stats AS qs WITH (NOLOCK) ON p.[object_id] = qs.[object_id]
WHERE qs.database_id = DB_ID()
ORDER BY qs.total_worker_time DESC OPTION (RECOMPILE);

Output
SP Name: Stored Procedure Name

TotalWorkerTime: Total Worker Time since the last compile time

AvgWorkerTime: Average Worker Time since last compile time

execution_count: Total number of execution since last compile time

Calls/Second: Number of calls/executions per second

total_elapsed_time: total elapsed time

avg_elapsed_time: Average elapsed time

cached_time: Procedure Cached time

10. How to identify DUPLICATE indexes in SQL Server
To see the query where you can find duplicate indexes, you can use the following query:
;WITH myduplicate
     AS (SELECT Sch.[name]                                                 AS
                SchemaName
                ,
                Obj.[name]
                AS TableName,
                Idx.[name]                                                 AS
                IndexName,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 1)  AS
                Col1,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 2)  AS
                Col2,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 3)  AS
                Col3,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 4)  AS
                Col4,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 5)  AS
                Col5,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 6)  AS
                Col6,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 7)  AS
                Col7,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 8)  AS
                Col8,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 9)  AS
                Col9,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 10) AS
                Col10,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 11) AS
                Col11,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 12) AS
                Col12,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 13) AS
                Col13,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 14) AS
                Col14,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 15) AS
                Col15,
                Index_col(Sch.[name] + '.' + Obj.[name], Idx.index_id, 16) AS
                Col16
         FROM   sys.indexes Idx
                INNER JOIN sys.objects Obj
                        ON Idx.[object_id] = Obj.[object_id]
                INNER JOIN sys.schemas Sch
                        ON Sch.[schema_id] = Obj.[schema_id]
         WHERE  index_id > 0)
SELECT MD1.schemaname,
       MD1.tablename,
       MD1.indexname,
       MD2.indexname AS OverLappingIndex,
       MD1.col1,
       MD1.col2,
       MD1.col3,
       MD1.col4,
       MD1.col5,
       MD1.col6,
       MD1.col7,
       MD1.col8,
       MD1.col9,
       MD1.col10,
       MD1.col11,
       MD1.col12,
       MD1.col13,
       MD1.col14,
       MD1.col15,
       MD1.col16
FROM   myduplicate MD1
       INNER JOIN myduplicate MD2
               ON MD1.tablename = MD2.tablename
                  AND MD1.indexname <> MD2.indexname
                  AND MD1.col1 = MD2.col1
                  AND ( MD1.col2 IS NULL
                         OR MD2.col2 IS NULL
                         OR MD1.col2 = MD2.col2 )
                  AND ( MD1.col3 IS NULL
                         OR MD2.col3 IS NULL
                         OR MD1.col3 = MD2.col3 )
                  AND ( MD1.col4 IS NULL
                         OR MD2.col4 IS NULL
                         OR MD1.col4 = MD2.col4 )
                  AND ( MD1.col5 IS NULL
                         OR MD2.col5 IS NULL
                         OR MD1.col5 = MD2.col5 )
                  AND ( MD1.col6 IS NULL
                         OR MD2.col6 IS NULL
                         OR MD1.col6 = MD2.col6 )
                  AND ( MD1.col7 IS NULL
                         OR MD2.col7 IS NULL
                         OR MD1.col7 = MD2.col7 )
                  AND ( MD1.col8 IS NULL
                         OR MD2.col8 IS NULL
                         OR MD1.col8 = MD2.col8 )
                  AND ( MD1.col9 IS NULL
                         OR MD2.col9 IS NULL
                         OR MD1.col9 = MD2.col9 )
                  AND ( MD1.col10 IS NULL
                         OR MD2.col10 IS NULL
                         OR MD1.col10 = MD2.col10 )
                  AND ( MD1.col11 IS NULL
                         OR MD2.col11 IS NULL
                         OR MD1.col11 = MD2.col11 )
                  AND ( MD1.col12 IS NULL
                         OR MD2.col12 IS NULL
                         OR MD1.col12 = MD2.col12 )
                  AND ( MD1.col13 IS NULL
                         OR MD2.col13 IS NULL
                         OR MD1.col13 = MD2.col13 )
                  AND ( MD1.col14 IS NULL
                         OR MD2.col14 IS NULL
                         OR MD1.col14 = MD2.col14 )
                  AND ( MD1.col15 IS NULL
                         OR MD2.col15 IS NULL
                         OR MD1.col15 = MD2.col15 )
                  AND ( MD1.col16 IS NULL
                         OR MD2.col16 IS NULL
                         OR MD1.col16 = MD2.col16 )
ORDER  BY MD1.schemaname,
          MD1.tablename,
          MD1.indexname

This can be Find the Duplicate Indexes, So you can remove the duplicate Indexes.

In this post, we covered some useful queries for working with Microsoft SQL Server. These queries can help you perform tasks such as listing all databases on a server, viewing the schema of a table, checking the size of a database, seeing the current user and date and time, linking to another server database, get Duplicate indexes.

I hope these queries are useful for you!

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In this article, we will learn about SPARSE Column in SQL Server. The SPARSE column is a good feature of SQL Server. It helps us to reduce the space requirements for null values. Using a SPARSE column, we may save up to 20 to 40 percent of space.

SPARSE Column in SQL ServerA SPARSE column is a common column with optimized storage for NULL values. It also reduces the space requirements for null values at the cost of more overhead to retrieve non-null values. In other words, a SPARSE column is better at managing NULL and ZERO values in SQL Server. It does not occupy any space in the database. Using a SPARSE column, we may save up to 20 to 40 percent of the area. We can define a column as a SPARSE column using the CREATE TABLE or ALTER TABLE statements.
CREATE TABLE TableName
(
      .....
      Col1 INT SPARSE,
      Col2 VARCHAR(100) SPARSE,
      Col3 DateTime SPARSE
      .....
)

We may also add/change a column from the graphical view.

Example
In this example, I have created two tables with the same number of columns and the same data type, but one table's columns are created as a SPARSE column. Each table contains 500+ rows.
CREATE TABLE TableName
(
      Col1 INT SPARSE,
      Col2 VARCHAR(100) SPARSE,
      Col3 DateTime SPARSE
)

CREATE TABLE TableName1
(
      Col1 INT ,
      Col2 VARCHAR(100) ,
      Col3 DateTime
)

Using the sp_spaceused stored procedure, we can determine the space occupied by the table data.
sp_spaceused 'TableName'
GO
sp_spaceused 'TableName1'

Advantages of a SPARSE column
    A SPARSE column saves database space when there are zero or null values.
    INSERT, UPDATE, and DELETE statements can reference the SPARSE columns by name.
    We can get more benefits from Filtered indexes on a SPARSE column.
    We can use SPARSE columns with change tracking and change data capture.

Limitations of a SPARSE column
    A SPARSE column must be nullable and cannot have the ROWGUIDCOL or IDENTITY properties.
    A SPARSE column cannot be data types like text, ntext, image, timestamp, user-defined data type, geometry, or geography.
    It cannot have a default value and bounded-to rule.
    A SPARSE column cannot be part of a clustered index or a unique primary key index and partition key of a clustered index or heap.
    Merge replication does not support SPARSE columns.
    The SPARSE property of a column is not preserved when the table is copied.

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Sometimes we have to face a critical situation when SQL Server database going to Suspect Mode. In that moment no work can be done on database. Database may go into suspect mode because the primary file group is damaged and the database cannot be recovered during the startup of the SQL Server
Reason for database to go into suspect mode:

• Data files or log files are corrupt.
• Database server was shut down improperly
• Lack of Disk Space
• SQL cannot complete a rollback or roll forward operation

    
How to recover database from suspect mode:

• Change the status of your database. Suppose database name is “BluechipDB”?

EXEC sp_resetstatus '';
Example:
EXEC sp_resetstatus 'BlueChipDB'

• Set the database in “Emergency” mode

ALTER DATABASE  SET EMERGENCY;
Example:
ALTER DATABASE BlueChipDB SET EMERGENCY

• Check the database for any inconsistency

DBCC CHECKDB('');

Example:
DBCC checkdb('BlueChipDB')

If you get any error after executing DBCC CHECKDB then immediately bring the database in SINGLE USER MODE by running following query. If no error found then you need not execute the following query.

ALTER DATABASE  SET SINGLE_USER WITH ROLLBACK IMMEDIATE

Example:
ALTER DATABASE BlueChipDB SET SINGLE_USER WITH ROLLBACK IMMEDIATE

• For safety, take the backup of the database.
• Run the following query as next step.Remember while using the below query, that uses REPAIR_ALLOW_DATA_LOSS, is a one way operation that is once the database is repaired all the actions performed by these queries can’t be undone.
• There is no way to go back to the previous state of the database.
• So as a precautionary step you should take backup of your database in step 5 mentioned above.

DBCC CHECKDB ('', REPAIR_ALLOW_DATA_LOSS);

Example:
DBCC CheckDB ('BlueChipDB', REPAIR_ALLOW_DATA_LOSS)

• Finally, bring the database in MULTI USER mode

ALTER DATABASE  SET MULTI_USER;
ALTER DATABASE [BlueChipDB]  SET MULTI_USER

• Refresh your database server and verify the connectivity of your database. Now users should be able to connect to the database properly. If any data loss, you can restore database – backup taken in step 5.

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