💎SQL Reloaded: Extended LTrim/RTrim in SQL Server 2022 (Before and After)

In SQL Server 2022, the behavior of LTrim (left trimming) and RTrim (right trimming) functions was extended with one more string parameter. When provided, the engine checks whether the first parameter starts (for LTrim), respectively ends (for RTrim) with the respective value and removes it, the same as the space character char(32) was removed previously:

-- prior behavior of LTrim/RTrim
DECLARE @text as nvarchar(50) = '  123  '
SELECT '(' + LTrim(@text) + ')' LeftTrimming
, '(' + RTrim(@text) + ')' RightTrimming
, '(' + Ltrim(RTrim(@text)) + ')' Trimming1 -- prior SQL Server 2017
, '(' + Trim(@text) + ')' Trimming2 -- starting with SQL 2017

LeftTrimming	RightTrimming	Trimming1	Trimming2
(123 )	( 123)	(123)	(123)

Here's the new behavior:

-- extended behavior of LTrim/LTrim (SQL Server 2022+)
DECLARE @text as nvarchar(50) = '123abc123abc'
SELECT LTrim(@text , '123') LeftTrimming
, RTrim(@text , 'abc') RightTrimming;

LeftTrimming	RightTrimming
abc123abc	123abc123

 Previosly, to obtain the same result one could write something like:

-- prior solution via Left/Right for the same (SQL Server 2000+)
DECLARE @text as nvarchar(50) = '123abc123abc'
SELECT CASE WHEN Left(@text, 3) = '123' THEN Right(@text,Len(@text)-3) ELSE @text END LeftTrimming
, CASE WHEN Right(@text, 3) = 'abc' THEN Left(@text,Len(@text)-3) ELSE @text END  RightTrimming

-- prior solution via "LIKE" for the same (SQL Server 2000+)
DECLARE @text as nvarchar(50) = '123abc123abc'
SELECT CASE WHEN @text LIKE '123%' THEN Right(@text,Len(@text)-3) ELSE @text END LeftTrimming
, CASE WHEN @text LIKE '%abc' THEN Left(@text,Len(@text)-3) ELSE @text END  RightTrimming

As can be seen, the syntax is considerable simplified. However, there are few the situations when is needed. In the past I had to write code to remove parenthesis, quotes or similar characters:

-- removing parantheses
DECLARE @text as nvarchar(50) = '(testing)'
SELECT LTrim(@text , '(') LeftTrimming
, RTrim(@text , ')') RightTrimming
, RTrim(LTrim(Trim(@text), '('), ')') Trimming 

-- removing double quotes
DECLARE @text as nvarchar(50) = '"testing"'
SELECT LTrim(@text , '"') LeftTrimming
, RTrim(@text , '"') RightTrimming
, RTrim(LTrim(Trim(@text), '"'), '"') Trimming 

The Trim for the 3rd value in both queries was used to remove the eventual spaces before the character to be replaced:

-- removing paranteses with lead/end spaces
SELECT RTrim(LTrim(Trim('   (testing)   '), '('), ')');

Then I thought, maybe I could use the same to remove the tags from an XML element. I tried the following code and unfortunately it doesn't seem to work:

-- attempting to remove the start/end tags from xml elements
DECLARE @text as nvarchar(50) = '<string>testing</string>'
SELECT LTrim(@text , '<string>') LeftTrimming
, RTrim(@text , '</string>') RightTrimming
, RTrim(LTrim(Trim(@text), '<string>'), '</string>') Trimming

LeftTrimming	RightTrimming	Trimming
esting</string>	<string>te	e

That's quite an unpleasant surprise!  In exchange, the value type can be defined as XML and use the following code to obtain the needed result:

-- extracting the value from a tag element
DECLARE @text XML = '<string>testing</string>'
SELECT @text.query('data(/string)') as value

Happy coding!

💎SQL Reloaded: Tricks with Strings via STRING_SPLIT, PATINDEX and TRANSLATE

Searching for a list of words within a column can be easily achieved by using the LIKE operator:

-- searching for several words via LIKE (SQL Server 2000+)
SELECT * 
FROM Production.Product 
WHERE Name LIKE '%chain%'
   OR Name LIKE '%lock%'
   OR Name LIKE '%rim%'
   OR Name LIKE '%spindle%'

The search is quite efficient, if on the column is defined an index, a clustered index scan being more likely chosen.

If the list of strings to search upon becomes bigger, the query becomes at least more difficult to maintain. Using regular expressions could be a solution. Unfortunately, SQL Server has its limitations in working with patterns. For example, it doesn't have a REGEXP_LIKE function, which is used something like (not tested):

-- Oracle 
SELECT * 
FROM Production.Product 
WHERE REGEXP_LIKE(lower(Name), 'chain|lock|rim|spindle')

However, there's a PATINDEX function which returns the position of a pattern within a string, and which uses the same wildcards that can be used with the LIKE operator:

-- searching for a value via PATINDEX (SQL Server 2000+)
SELECT * 
FROM [Production].[Product] 
WHERE PATINDEX('%rim%', Name)>0

Even if together with the Name can be provided only one of the values, retrieving the values from a table or a table-valued function (TVF) would do the trick. If the values need to be reused in several places, they can be stored in a table or view. If needed only once, a common table expression is more indicated:

-- filtering for several words via PATHINDEX (SQL Server 2008+)
WITH CTE 

AS (

  -- table from list of values (SQL Server 2008+)
  SELECT *
  FROM (VALUES ('chain')
  , ('lock')
  , ('rim')
  , ('spindle')) DAT(words)
) 
SELECT * 
FROM Production.Product PRD
WHERE EXISTS (
	SELECT *
	FROM CTE
	WHERE PATINDEX('%'+ CTE.words +'%', PRD.Name)>0
	)

The query should return the same records as above in the first query!

Besides own's UDFs (see SplitListWithIndex or SplitList), starting with SQL Server 2017 can be used the STRING_SPLIT function to return the same values as a TVF:

-- filtering for several words via PATHINDEX & STRING_SPLIT (SQL Server 2017+)
SELECT * 
FROM Production.Product PRD
WHERE EXISTS (
	SELECT *
	FROM STRING_SPLIT('chain|lock|rim|spindle', '|') SPL
	WHERE PATINDEX('%'+ SPL.value +'%', PRD.Name)>0
	)

A dynamic list of values can be built as well. For example, the list of words can be obtained from a table and the STRING_SPLIT function:

-- listing the words appearing in a column (SQL Server 2017+)
SELECT DISTINCT SPL.value
FROM Production.Product PRD
     CROSS APPLY STRING_SPLIT(Name, ' ') SPL
ORDER BY SPL.value

One can remove the special characters, the numeric values, respectively the 1- and 2-letters words:

-- listing the words appearing in a column (SQL Server 2017+)
SELECT DISTINCT SPL.value
FROM Production.Product PRD
     CROSS APPLY STRING_SPLIT(Replace(Replace(Replace(Replace(Name, '-', ' '), ',', ' '), '/', ' '), '''', ' '), ' ') SPL
WHERE IsNumeric(SPL.value) = 0 -- removing numbers
  AND Len(SPL.value)>2 -- removing single/double letters
ORDER BY SPL.value

The output looks better, though the more complex the text, the more replacements need to be made. An alternative to a UDF (see ReplaceSpecialChars) is the TRANSLATE function, which replaces a list of characters with another. One needs to be careful and have a 1:1 mapping, the REPLICATE function doing the trick:

-- replacing special characters via TRANSLATE (SQL Server 2017+)
SELECT TRANSLATE(Name, '-,/''', Replicate(' ', 4))
FROM Production.Product PRD

Now the query becomes:

-- listing the words appearing in a column using TRANSLATE (SQL Server 2017+)
SELECT DISTINCT SPL.value
FROM Production.Product PRD
     CROSS APPLY STRING_SPLIT(TRANSLATE(Name, '-,/''', Replicate(' ', 4)), ' ') SPL
WHERE IsNumeric(SPL.value) = 0 -- removing numbers
  AND Len(SPL.value)>2 -- removing single/double letters
ORDER BY SPL.value

Happy coding!

💠🛠️SQL Server: Administration (Troubleshooting Login Failed for User)

    Since the installation of an SQL Server 2017 on a virtual machine (VM) in the Microsoft Cloud started to appear in the error log records with the following message:

Login failed for user '<domain>\<computer>$'. Reason: Could not find a login matching the name provided. [CLIENT: <local machine>]
Error: 18456, Severity: 14, State: 5.

   From the text it seemed like a permission problem, thing confirmed by the documentation (see [1]), the Error Number and State correspond to a „User Id is not valid“ situation. In a first step I attempted to give permissions to the local account (dollar sign included). The account wasn’t found in the Active Directory (AD), though by typing the account directly in the “Login name” I managed to give temporarily sysadmin permission to the account. The error continued to appear in the error log. I looked then at the accounts under which the SQL Services run - nothing suspect in there.

   Except the error message, which was appearing with an alarming frequency (a few seconds apart), everything seemed to be working on the server. The volume of  records (a few hundred thousands over a few days) bloating the error log, as well the fact that I didn’t knew what’s going on made me take the time and further investigate the issue.

  Looking today at the Windows Logs for Applications I observed that the error is caused by an account used for the Microsoft SQL Server IaaS Agent and IaaS Query Service. Once I gave permissions to the account the error disappeared.

   The search for a best practice on what permissions to give to the IaaS Agent and IaaS Query Service lead me to [2]. To quote, the “Agent Service needs Local System rights to be able to install and configure SQL Server, attach disks and enable storage pool and manage automated security patching of Windows and SQL server”, while the “IaaS Query Service is started with an NT Service account which is a Sys Admin on the SQL Server”. In fact, this was the only resource I found that made a reference to the IaaS Query Service.

   This was just one of the many scenarios in which the above error appears. For more information see for example  [3], [4] or [5].

References:
[1] Microsoft (2017) MSSQLSERVER_18456 [Online] Available from: https://docs.microsoft.com/en-us/sql/relational-databases/errors-events/mssqlserver-18456-database-engine-error?view=sql-server-2017
[2] SQL Database Engine Blog (2018) SQL Server IaaS Extension Query Service for SQL Server on Azure VM, by Mine Tokus Altug [Online] Available from:  https://blogs.msdn.microsoft.com/sqlserverstorageengine/2018/10/25/sql-server-iaas-extension-query-service-for-sql-server-on-azure-vm/
[3] Microsoft Support (2018) "Login failed for user" error message when you log on to SQL Server [Online] Available from: https://support.microsoft.com/en-sg/help/555332/login-failed-for-user-error-message-when-you-log-on-to-sql-server
[4] Microsoft Technet (2018) How to Troubleshoot Connecting to the SQL Server Database [Online] Available from: Engine https://social.technet.microsoft.com/wiki/contents/articles/2102.how-to-troubleshoot-connecting-to-the-sql-server-database-engine.aspx 
[5] Microsoft Blogs (2011)Troubleshoot Connectivity/Login failures (18456 State x) with SQL Server, by Sakthivel Chidambaram [Online] Available from: https://blogs.msdn.microsoft.com/sqlsakthi/2011/02/06/troubleshoot-connectivitylogin-failures-18456-state-x-with-sql-server/

💎SQL Reloaded: Trimming Strings (Before and After)

   One of the annoying things when writing queries is the repetitive lengthy expressions that obfuscate in general the queries making them more difficult to read, understand and troubleshoot, and sometimes such expressions come with a performance penalty as well.    Loading data from Excel, text files and other sources involving poorly formatted data often requires trimming (all) the text values. In the early versions of SQL Server, the equivalent of a Trim function was obtained by using the combined LTrim and RTrim functions. This resumed in writing code like this (based on AdventureWorks 2014 database):

-- trimming via LTrim, RTrim 
SELECT LTrim(RTrim(AddressLine1)) AddressLine1
, LTrim(RTrim(AddressLine2)) AddressLine2
, LTrim(RTrim(City)) City
, LTrim(RTrim(PostalCode)) PostalCode
FROM Person.Address

  This might not look much though imagine you have to deal with 30-50 text attributes, that the code is not written in a readable format (e.g. the way is stored in database), that some attributes require further processing (e.g. removal of special characters, splitting, concatenating).
   Often developers preferred encapsulating the call to the two functions within a user-defined function:

-- Trim user-defiend function
CREATE FUNCTION dbo.Trim(
@string nvarchar(max))
RETURNS nvarchar(max)
BEGIN
    RETURN LTrim(RTrim(@string))
END

   With it the code is somehow simplified, but not by much and includes the costs of calling a user-defined function:

-- trimming via dbo.Trim
SELECT dbo.Trim(AddressLine1) AddressLine1
, dbo.Trim(AddressLine2) AddressLine2
, dbo.Trim(City) City
, dbo.Trim(PostalCode) PostalCode
FROM Person.Address

    In SQL Server 2017 was introduced the Trim function which not only replaces the combined use of LTrim and RTrim functions, but also replaces other specified characters (including CR, LF, Tab) from the start or end of a string.

    By default the function removes the space from both sides of a string:

-- trimming via Trim
SELECT Trim(AddressLine1) AddressLine1
, Trim(AddressLine2) AddressLine2
, Trim(City) City
, Trim(PostalCode) PostalCode
FROM Person.Address

    When a set of characters is provided the function removes the specified characters:

SELECT Trim ('#' FROM '# 843984') Example1
, Trim ('[]' FROM '[843984]') Example2
, Trim ('+' FROM '+49127298000') Example3
, Trim ('+-' FROM '+ 49-12729-8000 ') + ';' Example4
, Trim ('+ ' FROM '+ 49-12729-8000 ') + ';' Example5
, ASCII(Left(Trim (char(13) FROM char(13) + '49127298000'), 1)) Example6

Output:
Example1   Example2     Example3        Example4            Example5            Example6
--------          --------          ------------           -----------------       -----------------        -----------
  843984      843984        49127298000   49-12729-8000 ;  49-12729-8000;    52

  As can be seen when is needed to remove other characters together with the space then is needed to include the space in the list of characters.

Notes:
The dbo.Trim function can be created in SQL Server 2017 environments as well.
The collation of the database will affect the behavior of Trim function, therefore the results might look different when a case sensitive collection is used.

Happy coding!

💠🛠️SQL Server: Administration (Database Recovery on SQL Server 2017)

I installed today SQL Server 2017 CTP 2.1 on my Lab PC without any apparent problems. It was time to recreate some of the databases I used for testing. As previously I had an evaluation version of SQL Server 2016, it expired without having a backup for one of the databases. I could recreate the database from scripts and reload the data from various text files. This would have been a relatively laborious task (estimated time > 1 hour), though the chances were pretty high that everything would go smoothly. As the database is relatively small (about 2 GB) and possible data loss was neglectable, I thought it would be possible to recover the data from the database with minimal loss in less than half of hour. I knew this was possible, as I was forced a few times in the past to recover data from damaged databases in SQL Server 2005, 2008 and 2012 environments, though being in a new environment I wasn’t sure how smooth will go and how long it would take.  

Plan A - Create the database with  ATTACH_REBUILD_LOG option:

As it seems the option is available in SQL Server 2017, so I attempted to create the database via the following script:
 

CREATE DATABASE  ON 
(FILENAME='I:\Data\.mdf') 
FOR ATTACH_REBUILD_LOG 

And as expected I run into the first error:
Msg 5120, Level 16, State 101, Line 1 Unable to open the physical file "I:\Data\.mdf". Operating system error 5: "5(Access is denied.)".
Msg 1802, Level 16, State 7, Line 1 CREATE DATABASE failed. Some file names listed could not be created. Check related errors.

It looked like a permissions problem, though I wasn’t entirely sure which account is causing the problem. In the past I had problems with the Administrator account, so it was the first thing to try. Once I removed the permissions for Administrator account to the folder containing the database and gave it full control permissions again, I tried to create the database anew using the above script, running into the next error:

File activation failure. The physical file name "D:\Logs\_log.ldf" may be incorrect. The log cannot be rebuilt because there were open transactions/users when the database was shutdown, no checkpoint occurred to the database, or the database was read-only. This error could occur if the transaction log file was manually deleted or lost due to a hardware or environment failure.
Msg 1813, Level 16, State 2, Line 1 Could not open new database ''. CREATE DATABASE is aborted.

This approach seemed to lead nowhere, so it was time for Plan B.

Plan B - Recover the database into an empty database with the same name:

Step 1: Create a new database with the same name, stop the SQL Server, then copy the old file over the new file, and delete the new log file manually. Then restarted the server. After the restart the database will appear in Management Studio with the SUSPECT state.

Step 2: Set the database in EMERGENCY mode:

ALTER DATABASE  SET EMERGENCY, SINGLE_USER

Step 3: Rebuild the log file:

ALTER DATABASE <database_name> 

REBUILD LOG ON (Name=’_Log', 

FileName='D:\Logs\.ldf')

The rebuild worked without problems.

Step 4: Set the database in MULTI_USER mode:

ALTER DATABASE  SET MULTI_USER 

Step 5: Perform a consistency check:

DBCC CHECKDB () WITH ALL_ERRORMSGS, NO_INFOMSG 

After 15 minutes of work the database was back online.

Warnings:
Always attempt to recover the data for production databases from the backup files! Use the above steps only if there is no other alternative!
The consistency check might return errors. In this case one might need to run CHECKDB with REPAIR_ALLOW_DATA_LOSS several times [2], until the database was repaired.
After recovery there can be problems with the user access. It might be needed to delete the users from the recovered database and reassign their permissions!  

Resources:
[1] In Recovery (2008) Creating, detaching, re-attaching, and fixing a SUSPECT database, by Paul S Randal [Online] Available from: https://www.sqlskills.com/blogs/paul/creating-detaching-re-attaching-and-fixing-a-suspect-database/ 
[2] In Recovery (2009) Misconceptions around database repair, by Paul S Randal [Online] Available from: https://www.sqlskills.com/blogs/paul/misconceptions-around-database-repair/
[3] Microsoft Blogs (2013) Recovering from Log File Corruption, by Glen Small [Online] Available from: https://blogs.msdn.microsoft.com/glsmall/2013/11/14/recovering-from-log-file-corruption/