Structured query language (SQL) is a language created to communicate with databases, and it’s used in almost all relational database management systems. However, despite how common SQL is, multiple complexities within the language can mess up even the most experienced relational database users. Avoid the following mistakes to improve your server.
1. SQL Server Blocking
Blocking is a normal component in SQL servers and integral to maintaining princess concurrency and data integrity. However, problematic blocks can occur if the duration of the block goes too long because while the processes are waiting for the block, more blocking will occur behind it and will clog up the system. As a result, your server will slow down.
When blocking persists, it’s typically because a SPID holds locks on a set of resources for a long period, but this resolves itself, or a SPID holds on to a resource and never releases it. For the second example, the programmer has to troubleshoot blocking to resolve the scenario.
2. Data Redundancy
When coding, it’s good practice to have backups, but not for table data. SQL table data should have unique sets of code that don’t repeat anywhere else. While it’s common for other coding languages to use normalization rules, it isn’t necessary for SQL and just clogs up the table.
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3. Missing Primary Keys
In SQL, every table needs a primary key to optimize performance as these automatic clustered indexes help to speed up queries. Without it, the table will bog down your servers because it doesn’t follow SQL requirements. As a rule, all tables need to be unique in the server, so use auto-increment numeric values if other tables don’t fit the coding requirements for SQL.
4. Use JOIN instead of IN or NOT IN
Coders love to take shortcuts when they need to write and initiate large strings of code, but in SQL, you’re often penalized for being sneaky. For example, IN and NOT IN statements are convenient, but they aren’t well optimized because they filter through multiple databases to find one query on the Customer table. For larger servers, it could take several minutes to return a query.
Instead, use the JOIN statement to return the same data, but in less time. When you’re working with a large amount of numbers, it’s better to be efficient and get your query ASAP.
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5. Always Define Columns
Don’t use the asterisk (*) in SELECT statements if you want to maintain customer privacy. If you use an asterisk after the SELECT statement, it will return all customer data, including credit card information and addresses. If your server was hacked, you’d be helping them steal someone’s identity. Avoid all of the trouble and add the customerID, first, and the last name after SELECT.
6. Looping With Too Many Cursors
Cursors are truly the “curse” on SQL servers because they loop through all the servers’ records to run each statement against each other individually. It’s one of the most inefficient ways to locate data in SQL, so it’s best to avoid them. Instead, write the procedure in a way that doesn’t affect the database’s performance to such a degree.
Keep cursors locked away until you plan to stay away from the computer for a few hours, or you won’t be able to get back in without stopping the code.
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7. Messing up the Logic Order
All programming languages have a logical order, which is the way a code needs to be set up in order to initiate. A common mistake is with AND and OR statements. Their commonality can make coders forget how to structure their code, so an error message will pop up. In SQL, you can mix AND OR operations together if you separate them apart, for example:
- WHERE FirstName = ‘Mike’ AND LastName = ‘Write’ OR CustomerId > 0
- WHERE (FirstName = ‘Mike’ OR LastName = ‘Write’) AND CustomerId > 0
In the first coding example, the records returned were for customers greater than zero, but with the following statement, all records with the name Mike and Write are returned.
