SQL Server deadlock trace flags
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Introduction
In this article, I’m going to explain how you can find the cause of an SQL Server deadlock using trace flags and the SQL error log.
As a rule of thumb, the more locks are acquired, the higher the probability of a deadlock. And, since SQL Server uses 2PL by default, it’s not uncommon to have to track deadlock issues that affect application performance.
Optimistic vs. Pessimistic Locking
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Introduction
In this article, I’m going to explain what is the difference between optimistic and pessimistic locking, as well as when you should employ one or the other concurrency control strategies.
Merge Join Algorithm
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Introduction
In this article, we are going to see how the Merge Join Algorithm, also known as Sort-Merge Join, works and when it’s suitable for a relational database system to employ it in order to execute an SQL JOIN query.
MySQL Query Profiling Using Performance Schema
If you are trading Stocks and Crypto using Revolut, then you are going to love RevoGain!
Introduction
In this article, I’m going to explain how to do query profiling using the MySQL Performance Schema.
The Performance Schema has been available since MySQL 5.5.3 and allows MySQL to instrument SQL queries and store their trace information in various tables that you can later inspect in order to determine why a given SQL statement is slow.
On older versions of MySQL, you might have used the SHOW PROFILE command, but since this feature has been deprecated, you should now use the Performance Schema for SQL query profiling.
SQL Server OPENJSON – Map JSON to a relational table
If you are trading Stocks and Crypto using Revolut, then you are going to love RevoGain!
Introduction
In this article, I’m going to explain how the SQL Server OPENJSON function works and how it can help you transform a JSON object into a relational database table.
When using a relational database system, it’s a very good idea to design the database schema according to the relational model. However, there are specific situations when the relational model is way too strict, and that’s when a JSON column type might be very handy.
For instance, as I explained in this article, when designing an audit log table, it’s much more convenient to store the before and after row snapshots in JSON columns, as this strategy will accommodate future target table modifications while also avoiding duplicating every target table column in the audit log table. Thanks to the JSON column approach, we can even use a single audit log table for all target tables that we are auditing.
