In this article, we are going to touch upon the topic of performance of table variables. In SQL Server, we can create variables that will operate as complete tables. Perhaps, other databases have the same capabilities, however, I used such variables only in MS SQL Server.
I continue a series of articles on the basics of EXPLAIN in PostgreSQL, which is a short review of Understanding EXPLAIN by Guillaume Lelarge.
To better understand the issue, I highly recommend reviewing the original “Understanding EXPLAIN” by Guillaume Lelarge and read my first and second articles.
In my previous article, we started to describe the basics of the EXPLAIN command and analyzed what happens in PostgreSQL when executing a query.
I am going to continue writing about the basics of EXPLAIN in PostgreSQL. The information is a short review of Understanding EXPLAIN by Guillaume Lelarge. I highly recommend reading the original since some information is missed out.
We continue to analyze what is happening on our MS SQL Server. In this article, we are going to explore how to retrieve information about user performance: who makes what, and how much resources are consumed.
I think the second part will be interesting for both database administrators and developers who need to understand what is wrong with the requests on the production server that used to work fine on the test server.
Why does it take so much time to execute a query? Why are there no indexes? Chances are you’ve heard about EXPLAIN in PostgreSQL. However, there are still many people who have no idea how to use it. I hope this article will help users tackle with this great tool.
This article is the author revision of Understanding EXPLAIN by Guillaume Lelarge. Since I have missed out some information, I highly recommend you get acquainted with the original.
Recently, I came across an application that generated DB queries. I understand that there is nothing new about that, but when application began running slow and I had to find out the reason of the slowdown, I was amazed to find these queries. Here is what SQL Server sometimes has to deal with: (more…)
One of the available algorithms to join two tables together in SQL Server is Nested Loops. The nested loops join uses one join input as the outer input table and one as the inner input table. The outer loop iterates the outer input table row by row. The inner loop, executed for each outer row, searches for matching rows in the inner input table.
SQL query describes the expected result, not the way to get the result. The set of specific steps the server must take to return the result is called the query execution plan. The plan is built by the optimizer. Selection of a plan affects execution speed, what makes it one of the most important elements of the query performance problem analysis.
Execution plan comprises operators and their properties that are interrelated with each other in the form of the tree structure. Each operator is responsible for a separate logical or physical operation. All together, they ensure the result described in the query text. Inside the tree, operators are represented by the class objects in the memory of SQL Server. Server users (that is, you and me) see the description generated in XML format with a specific schema, that is displayed graphically by the SQL Server Management Studio (SSMS) environment.
There are many various plan operators and even more properties. Besides, new ones emerge from time to time. This article does not dare to describe all possible variety of operators. Instead, I would like to share the most interesting additions in this subject and to remind some old but useful elements. (more…)
Databases that serve business applications should often support temporal data. For example, suppose a contract with a supplier is valid for a limited time only. It can be valid from a specific point in time onward, or it can be valid for a specific time interval—from a starting time point to an ending time point. In addition, many times you need to audit all changes in one or more tables. You might also need to be able to show the state at a specific point in time or all changes made to a table in a specific period of time. From the data integrity perspective, you might need to implement many additional temporal specific constraints.
There is an information system that I administer. The system consists of the following components:
1. MS SQL Server database
2. Server application
3. Client applications
These information systems are installed on several objects. The information system is used actively 24 hours a day by 2 to 20 users at once on each object. Therefore, you cannot perform routine maintenance all at once. So, I have to «spread» SQL Server index defragmentation throughout the day, rather than defragmenting all the necessary fragmented indexes at one stroke. This applies to other operations as well.