In SQL, it’s not unusual to see subqueries in SELECT statements, where they can help narrow down the results based on a complex condition.
But the SELECT statement isn’t the only place we can put a subquery.
We can use subqueries in an UPDATE statement, and we can update multiple rows too, if required.
In this article, we look at how to update multiple columns by using a SQL subquery in the UPDATE statement.
When looking at ways to fix slow running SQL queries, one of the first things we might do is look at what indexes are available to support the query. If none are available, then we might look at creating one. And if there is an index, perhaps it doesn’t cater for the query as well as it could.
Indexes are often created on a single column, but this isn’t the only way to create an index. We can also create indexes on multiple columns. These are typically known as composite indexes.
When writing SQL queries, we sometimes find ourselves including a subquery in the query in order to get the results we want. Sometimes the subquery we include could be taken out of that query and run by itself to return its own independent result set. But not the correlated subquery.
A correlated subquery relies on the outer query for its data. We can’t simply move it outside of the outer query and expect it to work.
Let’s take a look the correlated subquery in SQL and observe it in action with a few examples.
SQL joins are fundamental operations in relational databases, allowing us to combine data from multiple tables. Two of the most commonly used join types are INNER JOIN and LEFT JOIN. Understanding the difference between these joins is crucial if you intend to use joins in your queries.
In this article, we’ll look at the difference between the INNER JOIN and LEFT JOIN using a simple example.
The WHERE clause is a fundamental part of SQL queries that allows us to filter data based on specific conditions. Understanding how to use various operators within the WHERE clause can significantly enhance our ability to retrieve precisely the data we need.
This article explores some of the operators that are most commonly used with the WHERE clause.
When used in the FROM clause, a SQL subquery creates a temporary table that can be queried like any other table. These queries are sometimes called derived tables or table expressions because the outer query uses the results of the subquery as a data source.
In this article we look at three different examples of SQL subqueries that are placed into the FROM clause.
In SQL, indexing can be a great way to improve query performance across our database. We can create indexes to support the most commonly used queries, and these indexes can help our queries run much faster.
But it’s not always a matter of just “adding an index” and leaving it at that. If we really want the best bang for our buck, we usually need to look at how best to implement the index. There are many decisions that go into designing the best index for the job. And one such decision might be, should this be a filtered index?
But what exactly is a filtered index, and how can it improve our database efficiency?
Let’s find out.
Ever wanted to populate a table with data from another table? That’s where the INSERT statement with a subquery comes in handy. Using this method, we can insert the full contents of another table, or we can insert just a select number of rows or columns based on certain criteria.
Below are four examples of using the INSERT statement with a subquery, with each one slightly more complex than the previous.
A UNIQUE constraint is a rule we apply to one or more columns in a database table to ensure that the values in those columns are unique across all rows. This means that no two rows in the table can have the same value(s) in the column(s) where we’ve applied the UNIQUE constraint. It’s an essential tool for maintaining data integrity and preventing duplicate entries in our database.
