Selecting a SQL Server Database Version for Your Company

SQL Server database and SQL

Choosing the right version of SQL Server is important for the performance you desire. If you’re installing an older one because your organization’s management prefers an older build or the vendor is unable to support newer versions, it is important to let them know which version your company needs, and why.

For this reason, we will discuss some popular versions of SQL Server from older to newer and mention their advantages in this blog.

Which SQL Server Version Works Best with SQL Performance Tuning?

Knowing the versions that support this task is extremely important because it will give you the ability to improve the SQL Server database and SQL performance.

To that effect, we will discuss the SQL Server 2016, 2017, and 2019 versions here.

SQL Server 2016

This version was chosen by a lot of independent software vendors or ISVs for one reason – 2016’s Service Pack 1 edition came with Enterprise features in Standard mode. These helped create a single application version that worked simultaneously for both Standard as well as Enterprise clients.

Advantages of Choosing this Version:

  • It is easy to find support material online as this version is quite popular and numerous database professionals are well-versed with this version’s tools.
  • Standard Edition users may find this version appealing since it supports 128GB RAM and additional space for internal functions such as query plans.
  • Support for this version ends after 2026 – longer than the older versions (2012/2014).
  • Newer applications that have additional compliance requirements will benefit from features in this version such as Always Encrypted, temporal tables, and Dynamic Data Masking. These will make it somewhat easier to protect and monitor sensitive information.
  • You can have both row store and column store indexes in this version, unlike the earlier ones that only had row store indexes.
  • If you need query plan monitoring to help with SQL performance tuning, you can use the Query Store’s features provided in SQL Server 2016 for this purpose.

SQL Server 2017

Being a newer release, it is one of the most regularly updated versions with patches coming in almost every other month. These patches are important because they resolve significant problems. It also comes with a minimum commit replica configuration to ensure commits are accepted by several replicas.

Advantages of Choosing this Version:

  • The upgrades are easier to get from this version onward due to a Distributed Availability Group that contains multiple SQL Server versions in it. Before this, we had AG version upgrades that were not as convenient, leading most users to construct a new cluster and migrate to it rather than opt for an upgrade.
  • This version contains batch mode execution plans, which gives those who require high-performance column store statements an advantage.
  • If you must run your SQL Server on Linux, you may consider SQL Server 2017 as several bugs have been resolved in the Cumulative Updates.
  • It’s a newer version so support will last longer than that of its predecessor.

SQL Server 2019

Released on November 4, 2019, this version is the latest in the SQL Server series. Naturally, it comes with the longest support lifespan, i.e. it will be supported until 2030. This version also receives regular patch updates to fix many significant issues in the form of Cumulative Updates.

Changes and Features in this Version:

  • Patch contents aren’t documented anymore. Moreover, you are likely to receive updates with undocumented new features – something to consider in case you require it for mission-critical production environments.
  • There is a bit of a learning curve thanks to some cutting-edge features in this version, so be prepared to perform some experimentation as you learn.
  • Some of the best performance features are included in the 2019 compatibility mode. However, you will have to keep a close eye on all SQL Server databases and SQL queries – even the ones running fast at present – as these will alter your current execution plans. In other words, you will have to test both slow and fast queries to make sure the slow ones speed up and the fast ones don’t fall behind in performance.
  • Table variables have gotten better in this version along with user-defined functions.
  • Additional features to watch out for including Big Data Clusters, Java support, and high container availability, so you may want to explore this version if you’re looking for perks like these in the SQL Server you want.

In Conclusion

At this point, SQL Server 2017 might seem like the best version to go with, thanks to a balance of features, stability, and support lifespan. Furthermore, you’ll receive plenty of help with SQL performance tuning – a lifesaver for overworked professionals who may not have the time or resources to upgrade every server every year.

How to Tune SQL Statements with Rewrite and Hints Injection for MySQL?

There are some SQL statements with performance problem have to be tuned by SQL syntax rewrite and Hints injection, it is a little bit difficult for SQL tuning newcomers to master this technique. Developers not only have to understand the relationship between SQL syntax and the final query plan generation but have to understand the usage of optimizer hints and its limitations. Sometimes these two tuning techniques application will affect each other in a complex SQL statement.

Here is a simple example SQL that retrieves data from EMPLOYEE and DEPARTMENT tables.

select  * from employee,department
where emp_dept=dpt_id
   and emp_dept<‘L’
   and emp_id<1500000
   and emp_salary= dpt_avg_salary
order by dpt_avg_salary

Here the following are the query plans of this SQL, it takes 7.7 seconds to finish. The query shows a “Full Table Scan Department” and nested loop Employee table with a Non-Unique Key Lookup EMPS_SALARY_INX.

You can see that this SQL cannot utilize index scan even though the dpt_dept is an indexed field. It is because the condition emp_dept<‘L’ is not explicitly induced the condition dpt_id < ‘L’ although emp_dept=dpt_id is also listed in the where clause.

To enable the index search of Department table, I explicitly add a condition dpt_id < ‘L’ to the SQL statement as the following:

select   *
from  employee,
     department
where  emp_dept = dpt_id
     and dpt_id < ‘L’
     and emp_dept < ‘L’
     and emp_id < 1500000
     and emp_salary = dpt_avg_salary
order by  dpt_avg_salary

Here is the query plan of the rewritten SQL and the execution time is reduced to 3.4 seconds. The new query plan shows that an Index Range Scan is used for the Department table and nested loop Employee table.

You may find that the nested loop to Employee by EMPS_SALARY_INX lookup may result into a lot of random access to the Employee table. Let me add a BKA hint to ask MySQL to use ‘Batched Key Access’ to join the two tables.

select   /*+ QB_NAME(QB1) BKA(`employee`@QB1) */ *
from  employee,
     department
where  emp_dept = dpt_id
     and dpt_id < ‘L’
     and emp_dept < ‘L’
     and emp_id < 1500000
     and emp_salary = dpt_avg_salary
order by  dpt_avg_salary

The new query plan shows a Batched Key Access is used to join Department and Employee tables, you can BAK information from MySQL manual for details, the new plan takes only 1.99 seconds and it is more than 3 times better than the original SQL syntax.

This kind of rewrite can be achieved by Tosska SQL Tuning Expert for MySQL automatically, it shows that the rewrite is more than 3 times faster than the original SQL.

https://tosska.com/tosska-sql-tuning-expert-tse-for-mysql-2/

How to Tune SQL Statement with CASE Expression for SQL Server I?

Here the following is a simple SQL statement with a CASE expression syntax.

SELECT *
FROM EMPLOYEE
WHERE
CASE
when  emp_id   < 1001000 then ‘Old Employee’
when  emp_dept <‘B’   then ‘Old Department’
ELSE‘Normal’
END = ‘old Employee’

Here the following are the query plans of this SQL, it takes 2.23 seconds in a cold cache situation, which means data will be cached during the SQL is executing. The query shows a Full Table Scan of the EMPLOYEE table due to the CASE expression cannot utilize the emp_id index or emp_dept index.

We can rewrite the CASE expression into the following syntax with multiple OR conditions.

select *
from  EMPLOYEE
where  emp_id < 1005000
     and ‘Old Employee’ = ‘Old Employee’
     or not  ( emp_id < 1005000 )
       and emp_dept < ‘B’
       and‘Old Department’ = ‘Old Employee’
     or not  ( emp_id < 1005000 )
       and not ( emp_dept < ‘B’ )
       and‘Normal’ = ‘Old Employee’

Here is the query plan of the rewritten SQL and the speed is 0.086 seconds. It is 25 times better than the original syntax. The new query plan shows an Index Seek of EMP_ID index.

This SQL rewrite is useful when the CASE expression is equal to a hardcoded literal, but if the literal “  =’Old Employee’ ” replaced by a variable “ = :var ”, this rewrite may not be useful, I will discuss it in my next blog.

This kind of rewrite can be achieved by Tosska SQL Tuning Expert for SQL Server automatically.

Tosska SQL Tuning Expert (TSES™) for SQL Server® – Tosska Technologies Limited

How to Tune SQL Statement with OR conditions in a Subquery for SQL Server?

The following is an example that shows a SQL statement with an EXISTS subquery. The SQL counts the records from the EMPLOYEE table if the OR conditions are satisfied in the subquery of the DEPARTMENT table.

select countn(*) from employee a where
exists (select ‘x’ from department b
    where a.emp_id=b.dpt_manager or a.emp_salary=b.dpt_avg_salary
     )

Here the following is the query plan in the Tosska proprietary tree format, it takes 4 minutes and 29 seconds to finish.

The query plan shows a Nested Loops from EMPLOYEE to full table scan DEPARTMENT, it is the main problem of the entire query plan, the reason is the SQL Server cannot resolve this OR conditions  ”a.emp_id=b.dpt_manager or a.emp_salary=b.dpt_avg_salary” by other join operations.

Let me rewrite the OR conditions in the subquery into a UNION ALL subquery in the following, the first part of the UNION ALL in the subquery represents the “a.emp_id=b.dpt_manager” condition, the second part represents the “a.emp_salary=b.dpt_avg_salary” condition but exclude the data that already satisfied with the first condition.

select  count(*)
from   employee a
where  exists ( select  ‘x’
        from   department b
        where  a.emp_id = b.dpt_manager
        union all
        select  ‘x’
        from   department b
        where  ( not ( a.emp_id = b.dpt_manager )
            or b.dpt_manager is null )
            and a.emp_salary = b.dpt_avg_salary )

Here the following is the query plan of the rewritten SQL, it looks a little bit complex, but the performance is very good now, it takes only 0.447 seconds. There are two Hash Match joins that are used to replace the original Nested Loops from EMPLOYEE to full table scan DEPARTMENT.

Although the steps to the final rewrite is a little bit complicated, this kind of rewrites can be achieved by Tosska SQL Tuning Expert for SQL Server automatically, it shows that the rewrite is more than 600 times fastAlthough the steps to the final rewrite is a little bit complicated, this kind of rewrites can be achieved by Tosska SQL Tuning Expert for SQL Server automatically, it shows that the rewrite is more than 600 times faster than the original SQL.

Tosska SQL Tuning Expert (TSES™) for SQL Server® – Tosska Technologies Limited

How to Tune SQL Statements to Run SLOWER… but Make Users Feel BETTER (Oracle)?

MySQL database and SQL

Your end-users may keep on complaining about some functions of their database application are running slow, but you may found that those SQL statements are already reached their maximum speed in the current Oracle and hardware configuration. There may be no way to improve the SQL unless you are willing to upgrade your hardware. To make your users feel better, sometimes, you don’t have to tune your SQL to run faster but to tune your SQL to run slower for certain application’s SQL statements.

This is an example SQL that is used to display the information from tables Emp_sal_hist and Employee if they are satisfied with certain criteria. This SQL is executed as an online query and users have to wait for at least 5 seconds before any data will be shown on screen after the mouse click.

select * from employee a,emp_sal_hist c
where a.emp_name like ‘A%’
     and a.emp_id=c.sal_emp_id
     and c.sal_salary<1800000
order by c.sal_emp_id

Here the following is the query plan and execution statistics of the SQL, it takes 10.41 seconds to extract all 79374 records and the first records return time ”Response Time” is 5.72 seconds. The query shows a MERGE JOIN of EMPLOYEE and EMP_SAL_HIST table, there are two sorting operations of the corresponding tables before it is being merged into the final result. It is the reason that users have to wait at least 5 seconds before they can see anything shows on the screen.

As the condition “a.emp_id = c.sal_emp_id”, we know that “ORDER BY c.sal_emp_id“ is the same as “ORDER BY a.emp_id“,  as SQL syntax rewrite cannot force a specified operation in the query plan for this SQL, I added an optimizer hint /*+ INDEX(@SEL$1 A EMPLOYEE_PK) */ to reduce the sorting time of order by a.emp_id.

SELECT  /*+ INDEX(@SEL$1 A EMPLOYEE_PK) */ *
FROM    employee a,
      emp_sal_hist c
WHERE a.emp_name LIKE ‘A%’
    AND a.emp_id=c.sal_emp_id
    AND c.sal_salary<1800000
ORDER BY c.sal_emp_id

Although the overall Elapsed Time is 3 seconds higher in the new query plan, the response time is now reduced from 5.72 seconds to 1.16 seconds, so the users can see the first page of information on the screen more promptly and I believe most users don’t care whether there are 3 more seconds for all 79374 records to be returned. That is why SQL tuning is an art rather than science when you are going to manage your users’ expectations.

This kind of rewrite can be achieved by Tosska SQL Tuning Expert for Oracle automatically.

https://tosska.com/tosska-sql-tuning-expert-pro-tse-pro-for-oracle/

How to Tune SQL Statement with “< ANY (subquery)” Operator for Oracle?

Here the following is a simple SQL statement with a “< ANY (Subquery)” syntax.

SELECT  *
FROM    employee
WHERE  emp_salary< ANY (SELECT emp_salary
              FROM  emp_subsidiary
              where  emp_dept=‘AAA’
              )

Here the following is the query plan of the SQL, it takes 18.49 seconds to finish. The query shows a “TABLE ACCESS FULL” of EMPLOYEE table and “MERGE JOIN SEMI” to a VIEW that is composed of a HASH JOIN of two indexes “INDEX RANGE SCAN” of EMP_SUBSIDIARY.

You can see that it is not an efficient query plan if we know that the emp_salary of EMP_SUBSIDIARY is a not null column, we can rewrite the SQL into the following syntax. The Nvl(Max(emp_salary),-99E124)is going to handle the case that if the subquery returns no record, the -99E124 representing the minimum number that the emp_salary can store to force an unconditional true for the subquery comparison.

SELECT  *
FROM    employee
WHERE  emp_salary < (SELECT  Nvl(Max(emp_salary),-99E124)
            FROM   emp_subsidiary
            WHERE  emp_dept = ‘AAA’)

Here is the query plan of the rewritten SQL and the speed is 0.01 seconds which is 1800 times better than the original syntax. The new query plan shows an “INDEX RANGE SCAN” instead of “TABLE ACCESS FULL” of EMPLOYEE.

This kind of rewrite can be achieved by Tosska SQL Tuning Expert for Oracle automatically, there are other rewrites with similar performance, but it is not suitable to discuss in this short article, maybe I can discuss later in my blog.

https://tosska.com/tosska-sql-tuning-expert-pro-tse-pro-for-oracle/

How to Tune SQL Statements to Run SLOWER… but Make Users Feel BETTER (MySQL)?

Your end-users may keep on complaining about some functions of their database application are running slow, but you may found that those SQL statements are already reached their maximum speed in the current MySQL and hardware configuration. There may be no way to improve the SQL unless you are willing to upgrade your hardware. To make your users feel better, sometimes, you don’t have to tune your SQL to run faster but to tune your SQL to run slower for certain application’s SQL statements.

This is an example SQL that is used to display the information from tables Emp_subsidiary and Employee if they are satisfied with certain criteria. This SQL is executed as an online query and users have to wait for at least 5 seconds before any data will be shown on screen after the mouse click.

select  *
from    employee a,
         emp_subsidiary b
where   a.emp_id = b.emp_id
         and a.emp_grade < 1050
         and b.emp_salary < 5000000
order by a.emp_id

Here the following is the query plan and execution statistics of the SQL, it takes 5.48seconds to extract all 3645 records and the first records return time ”Response Time(Duration)” is 5.39 seconds. The query shows a “Full Table Scan b (emp_subsidiary)” to Nested-Loop “a (employee)” table, an ORDER operation is followed by sorting the returned data by emp_id. You can see there is a Sort Cost=7861.86 at the ORDER step on the query plan. It is the reason that users have to wait at least 5 seconds before they can see anything shows on the screen.

To reduce the sorting time of a.emp_id, since a.emp_id=b.emp_id, so I can rewrite the order by clause from “order by a.emp_id” to “order by b.emp_id”, MySQL now can eliminate the sorting time by using the EMPLOYEE_PK after the nested loop operation.

select  *
from    employee a,
         emp_subsidiary b
where   a.emp_id = b.emp_id
         and a.emp_grade < 1050
         and b.emp_salary < 5000000
order by b.emp_id

Although the overall Elapsed Time is higher in the new query plan, you can see that the response time is reduced from 5.397 seconds to 0.068, so the users can see the first page of information on the screen instantly and they don’t care whether there are 2 more seconds for all 3,645 records to be returned. That is why SQL tuning is an art rather than science when you are going to manage your users’ expectations.

This kind of rewrite can be achieved by Tosska SQL Tuning Expert for MySQL automatically.

https://tosska.com/tosska-sql-tuning-expert-tse-for-mysql-2/

5 Chief Oracle SQL Performance Tuning Methodologies

optimization of SQL queries

Nearly every organization in the present era stores its information in separate databases depending on their specifications. Soft copies are given greater preference due to advancements in storage technology, making databases – and their performance – important in the day-to-day operations of an organization.

Therefore, DBAs conduct regular checks and Oracle SQL performance tuning to make sure the database is running the way it should. Performance tuning is done with the help of different methods and tools to maintain maximum efficiency.

5 Major Tools and Methods to Conduct SQL Performance Tuning

Consider these techniques and tools to streamline SQL tuning for your database:

  1. Implement Regular Server Health Check-ups

Optimal server health is essential for good database performance and performance tuning tasks also depend on it, which is why DBAs must perform server health screenings from time to time. You can detect whether server health is ideal or if there are slowdowns using Dynamic Management Views or DMVs.

  1. Assess Statement-related Statistics Simultaneously

Since Oracle SQL query tuning impacts real-time tasks, it is recommended to track the same in real-time to determine the source of slowdowns more quickly.

Live Query Statistics can help you in this regard: it shows statistics of all the statements that are running at that instant to enable the analysis of every step. Such a tool proves useful in troubleshooting SQL performance tuning related problems.

  1. Examine Execution Plans

DBAs use the Execution Plan tool to find out all the data retrieval techniques selected by the SQL Server query optimizer. All they have to do is choose the “Include Actual Execution Plan” before they execute the SQL statement they wish to optimize.

Once the Execution Plan tab shows up, you can determine whether there are any missing indexes by right-clicking and selecting the “Missing Index Details” option. Doing it will create the missing index and improve database performance.

  1. Determine Performance Impact of Transact-SQL Queries

Certain tools such as Database Engine Tuning Advisor can provide multiple benefits during Oracle database and SQL tuning. These include the analysis of the impact on performance and suggesting changes to be made on the basis of such observations.

  1. Observe Resource Consumption

DBAs can enhance database performance dramatically by keeping an eye on resource consumption and ensuring maximum productivity. There are certain parameters you can monitor such as buffer manager page requests with the help of System Monitor.

As its name suggests, it informs about the resources being utilized (Monitor Resource Usage) through predefined objects, counters that gather the counts and rates instead of event-related information. This tool also provides alert notifications when you want to set thresholds of the counts mentioned above.

To Conclude

Database Administrators can conveniently work on improving SQL database performance to a large extent using Oracle SQL performance tuning. This will help them lower the response time by taking the steps necessary to enhance throughput upon identification of all the areas that have been impacted.

The tips explained above mention some of the best SQL performance tuning tools to take care of some of the major tasks related to tuning. These are especially useful for large databases as they play an important role in boosting overall productivity.

How to Tune Bad Performance SET ROWCOUNT SQL Statements for SQL Server?

Some SQL statements will be running very slow after SET ROWCOUNT or TOP is used.  SET ROWCOUNT and TOP are used to tell SQL Server to select a specific number of rows from the SQL statements instead of extracting all records. Not many people know that SQL Server will try to re-optimize your SQL statements after you adding SET ROWCOUNT or TOP, the result is normally good after re-optimization of your SQL statements that can generate query plans for retrieving the first few records as fast as possible.

Good Example for Query Re-optimization for SET ROWCOUNT

Here the following is an example that shows the SQL takes 6.78 seconds to retrieve 217500 rows from the database, the query plan shows a good plan with a Hash Match for two Table Scan of [DEPARTMENT] and [EMPLOYEE].

The following screen shows the new query plan is generated after the SET ROWCOUNT 1 is used, the query plan is changed from Hash Match to Nested Loops. Nested Loops operation normally provides faster first few records retrieval time but may not be good for overall records extraction in certain situations. It is good to see that SQL Server uses only 0.013 seconds to extract the first row for this SQL.

Bad Example for Query Re-optimization for SET ROWCOUNT

Let’s see a bad example that shows how SQL Server degrades a good query plan to a bad query plan after the SET ROWCOUNT 1 is used. Here the following is an example that shows the SQL takes 0.118 seconds to retrieve 1613 rows from the database, the query plan is a little bit complex but it is a good query plan to retrieve all 1613 rows.

The following screen shows the new query plan is generated after the SET ROWCOUNT 1 is used, the query plan is now changed to Nested Loops with two Table Scans. The new query plan takes 1.312 seconds to extract only the first record, it is even slower than the 0.118 seconds that is used to extract all 1613 rows from the database.

How to Solve This Problem?

We can use Hints injection or SQL syntax rewrite to influence SQL Server to get back the original plan or generate an even better query plan for the SET ROWCOUNT or TOP operation. The following Hints injection generated a good query plan that is almost 90 times better than the original SQL with SET ROWCOUNT 1.

Tosska SQL Tuning Expert (TSES™) for SQL Server® – Tosska Technologies Limited

How to Tune Cold Cache SQL Statements for SQL Server?

For SQL statements that are not executed frequently, so that the relevant data is no longer exists in the buffer cache, a cold cache will significantly affect the performance of a SQL statement. A good performance SQL for hot cache may not be performing well in a cold cache environment. Experience developers will tune their SQL running well for both environments.

Here the following is an example SQL:

select * from
EMPLOYEE A
 where  A.EMP_ID IN (SELECT B.EMP_ID from EMP_SUBSIDIARY B
                      where B.EMP_DEPT < ‘D’)

Here the following is the query plan in the Tosska proprietary tree format, it takes 8.024 seconds for the first execution with cache delay and it takes 3.7 seconds for the second execution without caching time.

According to the query plan, you may find that the most significant IO consumption is the Table Scan of [EMPLOYEE] table. To simulate the cold cache environment, we can use the DBCC DROPCLEANBUFFERS command to clear the data cache before each execution of rewritten or optimized SQL statement.

Let me add an optimizer hint OPTION(LOOP JOIN) to the SQL and try to change the query plan from a Hash Match to a Nested Loop join. So, the EMP_ID(EMPLOYEE_PK) and a RID Lookup to [EMPLOYEE] will be used instead of using Table Scan. I hope that the RID Lookup can select fewer data from hard disk with matched EMP_ID in both [EMPLOYEE] and [EMP_SUBSIDIARY].

select *
from  EMPLOYEE A
where A.EMP_ID in (select B.EMP_ID
          from   EMP_SUBSIDIARY B
          where   B.EMP_DEPT < ‘D’) OPTION(LOOP JOIN)

Here the following is the query plan, the time is reduced from 8.024 seconds to 1.565 seconds with data cache overhead, and the physical reads are also dropped from 190,621 to 39,044. It shows a wrong IO estimation If you just rely on the SQL Server’s EstimateIO x EstimiateExecutions in the query plan.

There are other even better tuning solutions for this SQL with the A.I. SQL tuning tool in the following:

Tosska SQL Tuning Expert (TSES™) for SQL Server® – Tosska Technologies Limited

The following SQL with an optimizer hint generate a more complicated query plan with the best execution time of 0.7 seconds. The SQL is tuned by cold cache simulation that data will be flushed before each execution of SQL alternatives.