Скачать или смотреть How to Select Rows with Non-Matching Nulls in SQL: A Guide to Avoiding Unwanted Data

Struggling with SQL queries? Learn how to effectively select all rows with non-matching NULL entries using methods like `NOT EXISTS` and window functions. Perfect for PostgreSQL users.
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How to Select Rows with Non-Matching Nulls in SQL

When working with databases, you may encounter scenarios where you need to filter out data based on specific conditions, including the presence of NULL values associated with foreign keys. One common question that arises is: How can I select all rows that do not correspond to a row with a NULL value for a specific foreign key?

In this post, we’ll explore how to achieve this in SQL, particularly using PostgreSQL, and provide examples to clarify the techniques.

The Problem Explained

Consider the following sample table that consists of foreign keys and timestamps:

[[See Video to Reveal this Text or Code Snippet]]

In this table, we see that foreign key 1 has multiple entries, including one with a NULL value. If we wish to select rows that have foreign keys 2 and 3, we need a way to exclude all rows associated with foreign key 1 since one of its related rows has a NULL value.

Now, let's explore how to structure a SQL query that will allow us to achieve this.

Solution 1: Using NOT EXISTS

A straightforward approach to filtering out rows with non-matching NULL rows is to use the NOT EXISTS clause. Here’s how this can be implemented:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Query

The main query selects all the records from mytable, aliased as t.

The NOT EXISTS subquery checks if there are any rows in mytable, aliased as t1, where:

The foreign_key matches that of the main query (i.e., t.foreign_key).

The created_at field is NULL.

If no such row exists, the main query retains the record. This effectively filters out all entries linked to foreign keys with NULL values.

Solution 2: Using Window Functions

Another method to handle this scenario is by utilizing window functions. One approach is to implement boolean windowing to determine the presence of NULL values for each foreign key. Here’s how you can do this:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Query

The inner query selects all records and uses BOOL_OR to check for the presence of NULL values across the foreign_key groups.

The PARTITION BY clause allows us to group rows by foreign_key, calculating whether any row in that group has created_at as NULL.

The outer query then filters the results by only selecting the records where has_null is false.

Conclusion

When working with SQL data selection, ensuring you're accurately excluding rows related to foreign keys that have NULL entries is essential. The two solutions we've discussed—the NOT EXISTS clause and the window function method—are powerful tools in your querying toolbox.

By mastering these techniques, you can keep your datasets clean and relevant for effective analysis. Whether you choose the traditional subquery method or the modern window function approach, make sure to experiment with both to see which fits your needs best!

If you have any questions or need further examples, feel free to ask in the comments below!