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Dos and Don’ts for Faster and Better Performing SQL Database Queries

All the database administrators and developers want database queries to perform faster and easier, and the DBMS and SQL developers are trying many ways to achieve this goal. However, none of the methods they have in hand is fully optimal or foolproof. However, even though there is no such single turn-key answer to convert each query perfectly, some specific dos and don’ts will help you out with this to a big extent. While some of these are relational database management system specific, most other such tricks are applied to all types of database management models.

Let us explain some of the dos and don’ts for better performance of SQL database queries. Do use these expert measures in order to improve the SQL performance based on your use cases. Database administrators may already be knowing about these because they may not only be suffering from speed-related issues, but there can be issues related to various database-related operations too.

Do’s and Don’ts for Better Performance of SQL Database Queries:

MY SQL Database

Do Not Use Cursors:

SQL database errors may also be caused as some operations are blocking other operations for longer than actually needed. This will significantly decrease the concurrency in the database systems. However, you cannot completely avoid using cursors, and when such a need arises, you may be able to stay away from the cursor-related performance issues by doing cursor operations against the temp table.

For example, you consider the cursor, which goes through a table and updates some columns based on the comparison process. Instead of making a comparison against the live table, you should be able to put the data into a temp table and make an instant comparison out there. Sniping the data modifications may greatly increase the currency of your data.

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Don’t Use Nest Views:

It may be convenient to use views; however, you need to be very careful about using this. Views will help us to secure large queries from the users and standardize the data access process. You can also easily find yourself in a situation where you have many views. This is known as nesting views, which can cause some performance-related issues. One problem here is that you will be having much more data in return than you actually need. Another major problem with nest views is the query optimizer may ultimately give up and return a bad query plan.

Use Table Valued Function:

This is another expert trick and one of the hidden secrets which not much has explored. On using a scalar function in the SELECT list of the queries, the function gets called for every single row in the result set. It can further reduce the performance of big queries by a considerable amount. However, you can also greatly improve the performance by converting the scalar function to a table view function and use a cross apply in the query. This is an expert trick that can yield better results. In order to assess these features in light of your specific use cases, you may approach the expert providers like

Use Partitioning by Avoiding Any Larger Data Moves:

SQL server

Everyone may not be able to take advantage of this move as it largely relies on the partitioning in SQL Server Enterprise. However, those you can take advantage of this, it will be a great improvement. Most people do not realize that all the tables on the SQL server are partitioned. You can further separate a table into multiple partitions as you like, but each table is partitioned from the very beginning itself.

If you run an SQL server Enterprise edition, then you already have the advantage of partitioning all the tables as you wish. With this, you can use the partition features like SWITCH in order to archive large amounts of data from the load.

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Usage of Stored Procedures:

This is a very regular technique used. It is suggested that you do not use object-relational mappers or RMC, which may produce some of the worst queries. These error codes are responsible for many performance-related issues. ORM code generator may not possibly write SQL queries as good a human expert who knows what they are doing. If you use ORM, you should separately write your stored procedures and keep it as a stored procedure instead of ORM writing it on queries. There may be many arguments against this, but once you talk to the developers and admin, you will understand the high risk involved and let the RMC write the SQL queries.

There are many advantages of using stored procedures. For beginners, you may be pushing only fewer data across the entire network with stored procedures. If you have a longer query, it may take many round trips across the network to get the entire query to reach the database server. This may not include the time taken for the server to put the query back together and run it for considering the query, which may run many hundred times in a second.

Using a stored procedure will greatly cut the traffic as a standard store procedure is much shorter to run. Stored procedures may also be much easier to trace in the profiler or any other search tool. Stored procedures in the actual scenario are a real object in the database, which means it is easy to get the performance statistics on the stored procedures than on the ad-hoc queries.

Adding to it, store procedures also parameterize much consistently. With this, you will be more likely to re-use the execution plans and deal with caching issues in a better way to stop stored procedures. This also makes it much easier for the admins to deal with the edge cases and also auditing or change-locking behavior. Stored procedures can also handle the edge cases and even have ad hoc queries.

You need not have to count everything which we discussed in this list. However, you may try to explore your specific use cases and adopt the most appropriate modalities to ensure a faster and better performance of the SQL database queries.

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