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MySQL database and sql

Heaps and clustered indexes are two different ways of storing data in SQL Server. Both have their advantages and disadvantages, and we will discuss them in this post.

A Bit about Heaps

Heaps are essentially piles of data that remain unsorted or unorganized, hence the name. Although you can find heaps on tables that don’t have clustered indexes, they may also be present with non-clustered indexes. Heaps provide the benefit of increased input speed which helps while adding data to a table. Data insertion is quicker because the process doesn’t require a logical order to do so.

A Bit about Clustered Indexes

A clustered index is a more organised way of data insertion. In fact, it is the go-to technique for logically sorting information in a table. A clustered index doesn’t need a primary key but you can create one on a predefined key-value. Most DBAs recommend creating them on the most-used columns that come under reference of highly frequent query executions. They also reduce the need for optimization since all the data gets sorted to fit them. The primary benefit of using a clustered index is that it speeds up data reads.

Knowing When to Use a Clustered Index

As noted above, using a clustered index leads to better read rates. Therefore, there are several instances where you may need to identify whether a clustered index will improve performance of SQL query rather than a heap.

To do this, you need to follow these steps:

  • First, it is important to understand where there is a requirement for greater read speed.
  • Check dynamic system views and look for large tables without a clustered index.
  • Once you locate a few such tables, you can analyse the plans and stats of queries in the MSSQL system dynamic management views. Searching through the table name in the variable will show you the usage frequency of the plan. It will also show the text fetched and other necessary validation details that show whether a heap or non-clustered index is in use instead.

You will be able to view object names in the second result set in case the table in question is under use in SQL object. Once you have reviewed the query plans relevant to the use cases, you will have sufficient information to help you decide whether the table requires a clustered index or if a heap is more suitable for it. You will also have to choose all the columns that will have to be in the index in case of the former. Tables with several use cases that mostly share the same columns can provide result sets faster with a clustered index.

When Not to Use Clustered Indexes

This is just as important to know because believe it or not, there are instances where a clustered index can do more harm than good to oracle database performance.

A logging table is one such instance as it normally has far more insert operations than reads or updates. This is because their purpose is to log each occurrence but users may not refer to it as frequently. If you place an index on this kind of table, it can result in hot latches due to lagging data insertions for the last available page. Meanwhile, information keeps getting added onto the same page from other means. The one case where this issue doesn’t occur is when the index’s main column is a GUID, therefore, it isn’t sequential.

Using a clustered index in a table with an excessive number of columns isn’t the best idea, either. The reason behind this is simple: the index is supposed to define the default sort order. Too many columns mean repeated resorting with each new use case, slowing down the database. It will also result in an increase in the size of the non-clustered indexes present in the table.

Another situation where a clustered index can’t help is a column that isn’t usually static as they undergo frequent changes. Changing key values on an index have far greater chances of creating performance-related problems. This is because updating key values typically leads to page splits – these need maintenance, which takes resources and affects performance.

improve MySQL database performance

Oftentimes, database professionals make the mistake of jumping to conclusions when trying to improve MySQL database performance. They assume that the database must be the reason why the application has slowed down. 

In most cases, they may be right- which is why it’s important to start looking for possible bottlenecks and removing them to reduce lag. However, make sure you consider multiple forms of diagnostic data when attempting to uncover the root cause behind poor MySQL database performance. Don’t stick to just monitoring CPU usage or disk IO as relying on a single metric has greater chances of leading you to an incorrect diagnosis.

We need to look at the full picture to understand the complex interdependencies among CPU, memory, and IO. It is important to do so before making reactive changes, such as increasing disk capacity or memory. In this blog, we will take a look at one such reason behind performance bottlenecks- large data volumes.

How Large Data Volumes Affect MySQL Database Performance

Statements that cover a wide scope of data or are unrefined may fetch unreasonably large quantities of information from the database. This doesn’t seem like a problem at first when the database is new and has minimal data.

The true issue emerges as it grows in size, gradually leading to the requirement of Database Server. This is because when a statement fetches data, the data must be scanned into memory. The bigger the size of the data that needs scanning, the greater the load on the CPU, resulting in the need for burst mode due to sudden CPU spikes. This kind of usage increases the chances of your database server crashing.

Additionally, in case the data does make it from the database server, your app server may not be sufficiently provisioned to handle it. Known as over-fetching, you can overcome this problem by limiting the scope of data selection to relevant records. One way to do that is to opt for the WHERE clause in such queries- after you find them, of course.

The key to locating them is by searching through the database logs and metrics for tell-tale signs of large-scale data fetching. Although you might be able to spot CPU spikes or burst credit utilization from these metrics, it might not be easy to tell which statements are causing this specifically.

Things You Can Do to Improve MySQL Database Performance

Query optimization is one of the best places to begin when you have to improve MySQL database performance. But it differs from case to case and is far from a one-size-fits-all endeavor. That said, there are certain tasks that help in a lot of cases:

  • As mentioned above, you can prevent large result sets and decrease data volume by limiting the search to relevant records using the WHERE clause.
  • Go through the database schema to uncover ways that decrease complexity. For instance, keep an eye out on queries that contain a lot of joins since they take more time than most queries. You can make them run faster by reducing their relationships.
  • A large number of queries also fetch unnecessary fields from tables. You can set them to return only those fields that are important to keep from over-fetching again.
  • Views can help in some, but not all cases. A view is similar to a table that you can create beforehand by executing a statement to predetermine values that may require on-the-spot calculation otherwise.
  • Change the syntax of the SQL to influence database SQL optimizer to generate a better query plan.

Conclusion

If your application is performing poorly, the problem often lies with the database, with inefficient queries. While there isn’t any solution that works for every single query out there, database experts can hone in on the ones that require optimization using diligent analysis and monitoring, along with the right SQL optimizer tool for sql server.

After they successfully find the queries behind slow database performance, all they have to do is take the right steps to resolve this issue. These include optimization techniques, such as adding indexes, editing out unnecessary fields, and inserting the WHERE clause wherever necessary.

Create index oracle

Indexes are among the most useful and underutilized components of SQL. The user can create an Oracle index and store values along with their location in it.

Similar to the index at the end of a book, an index enables the user to go straight to the data they are interested in. Indexes are most useful when a user has to find a few rows. Therefore, they can use an index in statements that return a handful of rows – after creating one, of course!

Simple Techniques to Create an Index in Oracle Database

Creating an index is a simple task in MySQL query optimization as you only need to know two things:

  • The columns that require indexing
  • The name you will give the index

Here’s how to create one:

create index <indexname> on <tablename> ( <col1>, <col2>, <col3>, … <coln> );

Eg. create index cars_colour_metallic on cars (colour);

However, there are a few things to know about indexes before you begin:

  • You can place several columns in a single index, which then becomes a composite or compound index.

For instance, in the above example, you could also add the types of cars in the index like this: create index cars_colour_metallic on cars (colour, type);

  • The order in which you set columns in the index affects its use by the optimizer.

Next, let’s take a look at two of the most important index types users create in Oracle.

Two Major Index Types – and When to Pick Each

There are several kinds of indexes in the Oracle database that can improve your SQL. However, one of the most significant decisions you’ll have to make is likely to involve choosing between B-trees and bitmaps.

Create Index Oracle: B-tree Versus Bitmap Indexes

B-trees:– Indexes are in balanced B-tree format by default, which means all the leaf nodes are located at the same depth. It takes equal effort (O(log n)) to access any value, and one leaf index entry contains one row of data.

Bitmap:- Bitmaps also store indexed values, but in a completely different manner as compared to B-trees. In it, one value entry is associated with a range of row values. A bitmap has a series of 1s (yes) and 0s (no) to indicate whether any of the range rows contains the value or not.

One major difference between these two index types is that a B-tree doesn’t include null indexed values; a bitmap does. A bitmap can, therefore, answer some statements during MySQL query optimization, such as targeted index searches in which the column has a null value.

Although this won’t work for a B-tree, the user can add a constant at the end of an index to turn it into a composite index.

Bitmaps are also helpful because compressing the bits is simpler, which is why a bitmap index is generally smaller as compared to a B-tree index with identical data.

Why You Need to Keep a Check on the Indexes You Create

With all the benefits an index provides, it is important to create as few of them as possible. This is because you may end up creating one for every specific requirement and forget about them over time. The same goes for other users who may come and go on your team. And no one will have a clue why Brad needed to create that six-column function-based nightmare.

Since you don’t know if the index in question is only used for year-end reporting or never used, you cannot drop an index whenever you want. This can result in awkward situations where a table contains more indexes than columns!

So, if you’re unsure between two excellent indexes and one “good enough” index, it is better to choose the latter. And don’t forget to test!

query tuning in sql

Is your SQL Server falling behind in terms of performance? Are poorly-written queries slowing down your applications? Before you set out in search of professional help, make sure you’ve tried everything you could to resolve the issues you’re facing on your database. 

Many problems related to SQL Server can be handled easily with preventative maintenance, patches, and a few activities performed on a regular basis. You can always depend on our SQL performance tuning tools if nothing works for a particular situation. But before that, read the five important things you can do to fix database performance.

5 Things to Do for Effective SQL Performance Tuning

Given below are five simple things you can do to improve database performance:

Check if your SQL Server is up-to-date

An older query engine out of active development is bound to get you in performance-related trouble every now and then. Moreover, the newer versions have much better diagnostic support and will make things faster in multiple ways.

For starters, they come with new versions of the query optimizer. Although Microsoft provides a few tweaks here and there in its service packs, major version releases contain all the best improvements. Other advantages include:

  • Bug fixes
  • New CPU instruction sets
  • Latest software development techniques

Even a 32-bit to 64-bit upgrade can go a long way in improving database performance. This will help regardless of whether you are performing SQL tuning for Oracle or SQL Server.

Increase the Memory

Maxing out its memory will make a difference in its performance. This is because the database utilizes it to cache data instead of making additional trips to disk. Additionally, you gain more memory for cache query plans and can use it for larger sorts and joins. Another advantage is a potential decrease in disk and CPU utilisation, which further helps with SQL performance tuning. Just remember to raise the memory configuration in your SQL Server so it actually makes use of the new RAM.

Open Task Manager

If things remain slow after you’ve increased memory and upgraded your SQL Server,  it’s time to open Task Manager. Sort by CPU, followed by memory, and close any running apps, processes, or software that’s eating up space and you’re unaware of. Configure exceptions for antivirus software, if you have anything installed.

Windows may also be caching data for file system access, stealing RAM from server-side apps such as SQL Server. This can be checked by looking at the Cached number in the “Physical Memory (MB)” tab.

Check the Event Log

This includes both – the Windows Event Log and the SQL Server Log – as they both have potentially useful information. In case Windows or SQL Server are facing any sort of issue, these logs will certainly have more details about it.

You’ll know whether SQL Server is lagging due to hardware-related problems, facing long disk wait times, or dumping core. There may be other services with issues on the server that you can find out about here.

You can also read our post on SQL tuning for Oracle for some useful tips.

See if SQL Server alerts are set up

It is important to ensure these alerts are configured. They will, in turn, help you make sure you’re updated on everything that’s happening in SQL Server. As the person in charge of the database, you need to be aware in case the storage is falling short or other serious errors in SQL Server.

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.

MySQL database and SQL

Effective database management requires one or more tools regardless of the platform your databases run on. The benefit of these tools is, whether they are operating on Windows, macOS, Linux, or the cloud, the tools mentioned below don’t require the same platform as the databases. 

Thanks to plenty of choices when it comes to SQL management tools, it may seem difficult to select the ones that will work best as per your specific needs. In this blog, we’ve picked out the best paid and free SQL tools for Windows along with their essential features.

Free SQL Tools for Windows with a Graphical User Interface (GUI)

Consider the following free SQL tools for Windows to help you with efficient database management:

  1. SQL Server Data Tools (SSDT)

The SSDT is designed for a variety of databases such as Azure SQL, SQL Server relational databases, RS reports(Reporting Services), IS packages(Integration Services), and AS data models (Analysis Services). It is a development tool that allows users to create and implement any SQL Server content form with a convenience identical to that of Visual Studio.

  1. SQL Server Management Studio (SSMS)

The SQL Server Management Studio tool comes with an interactive Graphical User Interface that helps users control a SQL Server database or an instance. Users can gain access to any part of the SQL Server, Azure Synapse Analytics, or the Azure SQL Database and make changes, regulate, supervise, and develop them. 

You may want to look for this tool when you download free SQL Server as it also offers an all-encompassing utility which brings together a wide range of graphical tools along with several rich script editors. These are useful to DBAs and developers of varying skill levels.

  1. Visual Studio Code

The Visual Studio Code enables users to write T-SQL scripts using a compact editor. We are talking about the mssql extension – the official extension for Visual Studio Code that supports SQL Server linking and offers a productive T-SQL editing experience.

  1. Azure Data Studio

This is also a compact and handy editor capable of running SQL various functions including –

  • Executing SQL statements whenever required
  • Organizing preferred database connections
  • Viewing and storing results in text, JSON, or Excel format
  • Exploring database objects in a familiar environment
  • Editing information

Tosska’s Range of SQL Tuning & Query Optimizer Tools

Tosska Technologies offers several solutions to improve database performance through query optimization in SQL. With the goal of introducing new technologies that will help users overcome SQL-related obstacles, they provide a range of software designed using AI technology capable of solving a broad range of database performance issues.

Here’s what this range includes:

  • Tosska SQL Tuning Expert (TSES™) for SQL Server® – Unlike some of the free SQL tools for Windows, this is a powerful tool that doesn’t require professional expertise to tune your SQL queries. The AI engine does all the work, generating the most useful hints and alternate SQL statements that are semantically equivalent to the query that’s been entered to know whether there are better execution plans. You may pick the best option among the ones provided by the engine.
  • Tosska SQL Tuning Expert (TSEM™) for MySQL® – The TSEM™ comes with the A.I. capabilities of the TSE product range. However, this one-button-solution tool is tailored specifically for the MySQL database, tuning MySQL SQL queries without the users’ intervention. Users don’t have to perform manual rewriting or use the hit-and-trial method for each troublesome query, since it’s all handled by our embedded AI engine.
  • Tosska SQL Tuning Expert for Oracle® (TSE™ and TSE Pro™) version 4 – This tool comes with features exclusive to this family of tools, such as SQL rewrite, index exploration, and injecting Oracle hints to help tune SQL queries and boost their performance. It may or may not access your source code depending on the requirements, and the tool comes with a smart Indexes Advisor that offers cost-efficient indexes as per the workload. Make sure you get it when you download free tool and take advantage of this cutting-edge technology!
  • Tosska In-Memory Maestro (TIM™) for Oracle® – The TIM™ transforms the in-memory SQL optimization process into an automatic one and gives suggestions according to the SQL workload in question through our proprietary A.I. engine. It also offers a user-friendly simulation feature that virtually assesses table objects present in the memory for a SQL workload but doesn’t occupy those table objects.
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.

This is the second blog in our two-part series to explain the best ways to optimize your database, which is best done by enhancing the SQL queries being used. Without much ado, let’s pick up where we left off –

Give Preference to WHERE, instead of HAVING (when defining filters)

A query is efficient when it saves resources by fetching only what’s needed from the database. According to the Order of Operations defined in SQL, WHERE queries are calculated before HAVING statements.

Therefore, it is advisable to give preference to WHERE over HAVING when the goal is to filter a query on the basis of conditions for greater efficiency. 

For instance, let us suppose a hundred sales have been made during the year 2019, and a user wishes to put in a query to determine what the number of sales was for the same time period. They may write something like this:

SELECT Clients.ClientID, Clients.Name, Count(Sales.SalesID)

FROM Clients

   INNER JOIN Sales

   ON Clients.ClientID = Sales.ClientID

GROUP BY Clients.ClientID, Clients.Name

HAVING Sales.LastSaleDate BETWEEN #1/1/2019# AND #12/31/2019#

This statement would return at least a thousand sales records from the Sales table, then filter these thousand records to find the hundred records generated in the year 2019, and lastly, tally the data in the dataset.

If we compare the above with the same instance using the WHERE clause instead, there is a limit placed on the number of records fetched:

SELECT Clients.ClientID, Clients.Name, Count(Sales.SalesID)

FROM Clients

  INNER JOIN Sales

  ON Clients.ClientID = Sales.CustomerID

WHERE Sales.LastSaleDate BETWEEN #1/1/2019# AND #12/31/2019#

GROUP BY Clients.ClientID, Clients.Name

This statement would return the hundred records from the year 2019, after which it would count the records in the dataset, thereby getting rid of the first step in the HAVING clause.

Keep wildcards strictly at the end of a statement

A wildcard creates the largest search possible when looking for plaintext information like names or designations. However, the wider a search, the less efficient it is, and a leading wildcard worsen the performance – particularly when it’s used with an ending wildcard.

That’s because the database has to find every single record that remotely matches the selected field. Take this query to fetch cities beginning with ‘Ch’, for instance:

SELECT Cities FROM Clients

WHERE Cities LIKE ‘%Ch%’

This statement will not just fetch the expected results of Chicago, Chester, and Chelsea, but will also return unintended results, like Richardson, Canal Winchester, and Cannon Beach.

A more productive statement would be:

SELECT Cities FROM Clients

WHERE Cities LIKE ‘Ch%’

This query will lead only to the expected results of Chicago, Chester, and Chelsea.

Use LIMIT to sample query results

The use of a LIMIT query will make sure the results of new SQL queries are relevant and desirable. As the name suggests, its function is to limit the quantity of records to the number mentioned, saving a lot of resources in the process.

Considering the 2019 sales query from above, let us suppose a limit of 15 records:

SELECT Clients.ClientID, Clients.Name, Count(Sales.SalesID)

FROM Clients

  INNER JOIN Sales

  ON Clients.ClientID = Sales.ClientID

WHERE Sales.LastSaleDate BETWEEN #1/1/2019# AND #12/31/2019#

GROUP BY Clients.ClientID, Clients.Name

LIMIT 15

The results will indicate if the data set is worth using or not.

Adjust Your Timing a Bit

If you’re looking to minimize the impact of your analytical queries on the production database, consult with an Oracle Database Administrator regarding the scheduling of your SQL queries so that they can be run during off-peak hours.

Specific hours when there are fewest concurrent users, generally in the middle of the night, should be chosen to run such resource consuming queries. If your SQL queries are more likely to include the following criteria, consider running it during off-peak timings:

  • Selecting from huge tables (where there are over a million records)
  • Queries with Cartesian or Cross Joins
  • Looping queries
  • SELECT DISTINCT queries
  • Subqueries that are nested
  • Search queries involving wildcards in long text or memo areas
  • Numerous schema statements

Query with Confidence!

Keeping these and other SQL tips into consideration will certainly enable you to construct efficient, smart queries that will operate swiftly and fetch your team the game-changing insights it needs.

SQL statements or queries are designed to retrieve information from the database. A user can achieve the same results through optimization in SQL; using a tuned query is especially useful from an execution perspective. 

Tuning a database is a vital step in organizing and accessing the information in a database. Performance tuning in SQL requires streamlining and homogenizing the environment of a database and the files in it. This simplifies the way users access data in a big way. 

Why Companies Need to Consider Optimization in SQL

Several organizations own databases, but not all of them hire IT staff knowledgeable in the ways of optimization in SQL. Only professionals who have tuning skills and experience along with insider information about the working of databases should do this. 

In case your company has a database but it hasn’t undergone performance tuning, you might encounter inadequate responses to queries and face unnecessary complications when handling data. Don’t let your efficiency get affected because of something avoidable like this! 

Performance Tuning in SQL: What It Involves

Tasks related to performance tuning include optimization in SQL database, creating and managing indexes, and other related tasks to maintain or improve database performance. The goal of MySQL query optimization is to increase the speed and brevity of query responses and to simplify data retrieval. 

Let’s look at three major reasons why companies need to take performance tuning and seriously – 

1. To enhance the rate of data fetching options

If your database lacks optimization, then fetching data can get slower with increasing data loads. Optimizing queries enables users to create indexes and eradicate issues that may be slowing down data retrieval. After all, it can get quite frustrating for your employees to wait for the database to perform its operations, which can pass on to customers forced to wait for the same.

2. To refrain from coding loops

Making your database go through a coding loop is akin to hammering it repeatedly. That’s because the same query is executed several times when it is placed in a loop. However, once you remove the query from the loop, you will experience a definite surge in performance because the query is run only once rather than going through multiple iterations. 

3. To increase the performance of your SQL statements 

Query tuning in SQL includes changing previous query patterns and habits that were affecting the speed of data storage and retrieval. For example, the use of SELECT is reduced by opting for separate column declaration and eliminating correlated subqueries. Queries are also simplified by obviating temporary tables at times, aside from many other techniques of optimization in SQL

Your database will be able to manage much more data after the application of all these improvements as these will increase its efficiency, making it scalable as well. Once your database has scalability, it also overcomes lower performance and ensures user satisfaction in terms of experience. 
If you require professional tools to manage MySQL query optimization and tuning, then Tosska can help you. Tosska provides highly intuitive tools that can simplify query tuning beyond your imagination, and it does this with the help of innovative AI technologies. Contact us today to learn more about our range of query optimization products and services.

SQL performance tuning can be an extremely complicated task, especially where data in huge quantities is concerned. When implementing queries to insert data in large quantities, even the tiniest of changes can have a major impact on performance – for better or for worse. 

If you are new to databases, you may be wondering what SQL performance tuning is and how you can use it with sound knowledge of the fundamentals and a few tricks up your sleeve. In this blog, you will find some fundamental techniques for SQL tuning to improve performance of SQL query being entered in the database. 

Techniques to Improve the Performance of SQL Queries

Consider these five tips and techniques to enhance database performance – 

Indexing

Indexes are quite effective in SQL tuning but are often overlooked at the time of development. Basically, an index is a data structure that can boost data retrieval speeds in tables by supplying quick random lookups and prompt access to requested records. This implies that once you have made an index, selecting, SQL performance monitoring, and sorting operations are faster. 

They are also useful in defining a primary key that will prevent other columns from having the same values. Naturally, database indexing is a vast topic that deserves its own set of blogs, but for now, it is important to understand that the aim is to index the larger columns intended for searching and ordering.

  • Keep in mind, however, that indexes must be modified after INSERT, UPDATE, and DELETE operations, which means they could actually worsen the performance of the database if your tables are receiving a large number of these commands. 
  • Furthermore, Database Administrators usually discard their indexes before executing gigantic batch inserts involving millions of rows, to hasten the insertion process. Once the task is complete, they then create the indexes all over again. It is important to remember, in such cases, that when the indexes are dropped in this manner, it affects all the queries being executed in that table. Hence, to improve performance of SQL query, this approach is typically taken in certain situations that require a single sizable insertion.

Execution Plan Tool in SQL Server

This tool helps create indexes and it shows all the data retrieval techniques selected by the query optimizer. There are walkthroughs available that will help newcomers learn more about this tool.

  • If you are using the SQL Server Management Studio, you can fetch the execution plan by pressing on Ctrl+M to select the “Include Actual Execution Plan” option before executing your query. This leads to a third tab named “Execution Plan” that will show any missing indexes that it has detected.

Steer Clear of Coding Loops

Suppose you need to insert a thousand queries in your database in one go. In that case, you may be tempted to do it using a loop but you must, in fact, refrain from doing so. 

  • Instead, consider changing the snippets containing the loop in unique INSERT or UPDATE statements that have additional rows and values. 
  • Make sure that your WHERE clause avoids updating the stored value if it matches the existing value. Such a trivial optimization can dramatically improve performance of SQL query by updating only hundreds of rows instead of thousands.

Checking Whether a Record Exists 

This is a handy SQL optimization approach that concerns the use of EXISTS(). 

  • In case you want to know if a certain record is present in the database, make a preference for EXISTS() instead of COUNT(). That’s because EXISTS() can give you much better performance with more coherent code as it leaves the table the moment it gets the data it needs. On the other hand, COUNT() scans the whole table every single time, counting up each and every entry that matches your condition.


 

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