Tips to optimize your SQL server performance
WASHINGTON, July 5, 2017 – In a world where data runs everything, it is necessary for any serious enterprise to have a reliable database. There are multiple database systems to choose from, and your choice depends on your company’s requirements.
From the multiple options of relational database management systems for such entities, SQL Server seems to be one of the most widely used. Its primary function is to store and retrieve data at will, just like many other full-featured databases currently in use. However, there is more to SQL Server than what first meets the eye.
SQL Server is dynamic and comes in a variety of editions to meet the varying needs of different audiences. Today, SQL Server supports multiple entities, from one-machine applications to huge, cloud-based applications. Its flexibility makes it easy for users to define and use multiple composite database types.
Using SQL Server and reaping its benefits, however, are two different things. From the outset, to get the most out of this system you need to ensure optimum performance. That is where the task of SQL Server performance tuning comes in.
Taking full advantage of SQL server requires keen observation and specific, informed steps. But you don’t necessarily need a SQL guru or a DBA consulting service to help you do this. Server performance tuning is not as hard as it seems. In fact, it is a DIY project. Let us walk through the most important steps.
Assessment and Analysis of a Query
One common problem of an SQL server is that of slow database. To unmask the possible causes and come up with viable results, it is necessary to dig through the pile of information hidden in priceless queries. To surge through, you will need to have a deeper understanding of SQL plans, wait types, SQL statements, indexing and resource contention.
In the process of understanding the problem you are dealing with, you must access a basic query. Here’s how:
- Make use of SSMS to go through the query elements, ensuring you are working on a real table and not a view table. The two are different and perform different functions. Query the DMVs in order to verify the row count within your table.
- Use the same query in assessing WHERE and JOIN clauses, taking note of the filtered row count. If a larger percentage of the table is returned minus filters, you have reasons to be worried. This has the potential to slow down a query.
- Determine the number of rows you are working with by considering the returned filters and row count of the tables. This count is generally referred to as a logical or actual set. Where necessary, take advantage of the SQL diagramming tool to go through query selectivity and queries.
- Be careful in your assessment of SELECT function in case the query contains extra columns. If more columns are returned, there will be minimal chances of using the index operations necessary in carrying out an execution plan.
Finding Errors in a Written Query
In SQL Server Performance tuning, the an emphasis on the appropriate use of constraints cannot be overemphasized. You need to carry out a deep analysis of the indexes, constraints and available keys to eliminate the possibilities of overlapping indexes and duplicated efforts. To obtain information on these indexes, you do not need to go to extremes. Simply run the stored procedure, “sp_helpindex”.
To have a good record of performance changes or determine the underlying cause of an under-performing database, you need to compare the estimated and actual plans. It is worth noting that the estimated plans take advantage of estimated statistics to figure out the estimated rows.
On the other hand, actual statistics are necessary for the real execution plans. It is also important to note the difference between actual and estimate plans after making comparisons.
Using the notes you have taken and other findings, proceed to adjust your query. Make changes where necessary, ensuring the expensive operations are considered first.
It is important to only make few changes at a time. If you make numerous changes, you will probably thwart your efforts. Also, be sure to run the query after making changes, recording the difference in observations after every step. You only need to stop when you have achieved a satisfactory outcome.
There may be instances where satisfactory results are not evident even after several re-runs and query adjustments. In such cases, altering code or adjusting indexes become the next available options. You can also make adjustments filtering indexes, covering indexes and existing indexes. After these adjustments, you should be able to get satisfactory results when you run the query, and you should again note down or record the outcomes.
When running queries and making adjustments, you are likely to encounter various hindrances. Be on the lookout for them, lest they slow down the performance. Some of these inhibitors include:
- Scalar functions
- Nested Views
- Code first generators
- Abuse of wildcards
Optimizing SQL Server Performance Tuning
This manual tuning process is undoubtedly effective when carried out the right way. However, it also consumes considerable time and requires significant effort. If you are not happy with something you’ve done, change it.
The same advice applies to the query tuning process. To squeeze the most out of this process, capitalize on the database performance monitoring tool. Along the way, you may discover less obvious but still useful opportunities to improve your database.
For the best outcome, you must be consistent in your use of the database performance-monitoring tool. One obvious advantage is that you will have all the necessary data on SQL Server performance on one secure location. However, the monitoring process must be continuous for the results to be reliable.
To derive optimum benefits from SQL Server, this RDBMS should be operate at its peak level. The good news is, you can do something about it rather than waiting for a miracle to happen. Following the tips and procedures highlighted in this article, you will find it easy to optimize your server’s performance.