Database administrators can never afford to ignore SQL database issues because the smallest ones can bring the biggest losses to the organization.
At the same time, even a minor scope for change can prove to be a great opportunity for database query optimization.
Although one may need a considerable amount of experience to discover such areas, let alone apply the right solution to gain optimal performance – there are plenty of tools to help those who may lack sufficient skills, experience, or expertise.
Optimizing an Oracle SQL Query with the Help of Tools
Known as specially designed SQL Server optimizers, these tools have the ability to carry out an in-depth assessment of query execution plans to find out where and why bottlenecks are taking place if any.
Among these tools, an incredibly popular one is the SQL Query profiler that was designed and created specifically for Oracle SQL query tuning for SQL Server in dbForge Studio.
In this post, we will observe how this tool works for a typical yet frequently performed task – getting rid of redundant data in a particular table.
Problem: Let us suppose that our database contains a table with the times of all the employees of every department at which each member of staff begins their shift. Since we are already aware of the presence of multiple departments in the organization, let us focus on a single department in particular.
It is important to note here that the names of the same employees are present in different departments as well. However, we want to know what time the sales staff begin working.
There are at least three ways of handling this situation, one of which is explained below:
Solution 1: The first, most common method is to collect a list of the staff from the department you want to approach – sales, in this case. Once you have fetched the names using the appropriate oracle query optimizer tool, assuming they also have department IDs, you can simply delete the same data that exists in the lists of other departments.
For this, you will have to gain access to the table twice. Before you remove data, SQL Server uses the table spool operation so you can prevent multiple scanning of the same data from the first table. It proves extremely resource-consuming, however.
That’s because the operator goes through the entire input table and replicates every row inside an invisible spool table that is saved in the tempdb database. This hidden spool table lasts only as long as the query does, while the operator enables the subsequent elements to gather information from the buffer rather than the actual table.
We can save our CPU resources by skipping table spool reading. How? By optimization in sql, or in other words, changing the way we write our query. Simply use ROW_NUMBER to reduce the complexity of the execution plan, thereby speeding up query execution.
In Conclusion
At this point, however, sorting the data to classify it according to shift hours becomes the most resource-consuming task. Since the chances of one employee clocking in for more than one department at the same time is extremely low, we can switch to a column with a composite primary key instead.
Database experts will step in here to remind you about cluster indexes which can arrange table rows with the help of primary key columns. You may also get rid of unnecessary columns to simplify the original table. In short, not only will a primary key addition enable the user to discard the sorting operator – saving significant resources in the process – it will quicken up the query. Users only need a few things to make substantial performance improvements. These include a bit of knowledge regarding various operators and database performance optimization, a decent profiler to optimize query plans, and the right combination of techniques.
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