How to Select Every Row Where Column Value is NOT Distinct

sql

subqueries

sql-performance

best-practices

byAnton Shumikhin·Dec 20, 2024

To identify and return rows with duplicated values in your_column, take advantage of the GROUP BY and HAVING clauses to filter duplicates, then join them back to the original table to fetch the entire row detail:

SELECT a.*
FROM your_table a
INNER JOIN (
    SELECT your_column
    FROM your_table
    GROUP BY your_column
    HAVING COUNT(*) > 1 -- Only party crashers allowed
) b 
ON a.your_column = b.your_column; -- Party is at b's place

Above SQL isolates duplicated entries using GROUP BY and filters them by COUNT(*) greater than one. It then rebirths these duplicates in the context of their original rows via an INNER JOIN.

Exploring the Query's Depths

Timid by a sea of rows? Let's coax out the non-distinct values lurking beneath. Though our JOIN based approach surfaces these rogues swiftly, alternative methods may better suit your unique voyage.

Sailing with subqueries and the IN operator

Here's another route, embedding a subquery within a WHERE...IN clause:

SELECT *
FROM your_table
WHERE your_column IN (
    SELECT your_column
    FROM your_table
    GROUP BY your_column
    HAVING COUNT(your_column) > 1 -- sea monsters only
);

A more personal voyage with EXISTS

The EXISTS keyword can power a correlated subquery, reflecting true whenever our condition is met:

SELECT *
FROM your_table a
WHERE EXISTS (
    SELECT 1
    FROM your_table b
    WHERE a.your_column = b.your_column AND a.id <> b.id -- I am not my twin
);

Navigating with CTEs

A Common Table Expression (CTE) can render a map to chart your complex queries:

WITH DuplicateFinder AS (
    SELECT your_column, COUNT(*) OVER (PARTITION BY your_column) as Cnt -- Counting the clones
)
SELECT *
FROM your_table
WHERE your_column IN 
    (SELECT your_column FROM DuplicateFinder WHERE Cnt > 1); -- Reunion time!

Opportunities for customization

While JOIN works wonders on large seas of data, SUBQUERY may prove a more reliable compass in smaller oceans. Understanding and testing your data landscape is key to optimizing performance.

Pitfalls and perils

While hunting non-distinct rows is indeed fun, it's crucial to stay wary of known dangers and inconveniences.

Heavy performance tolls

Sifting colossal datasets can put a strain on your resources. Do ensure appropriate indexing is in place for speedier retrievals.

NULL handling anomalies

NULL in SQL is treated as a distinct value; hence, duplicates of NULL aren't counted in COUNT(). A custom workaround may be required for your quests.

Data type disparities

Ensure column data types are consistent, as implicit conversions can lead to wrong results or reduced performance.

Polishing your SQL skills

Here are some pro tips to enhance your SQL journey, delivering clarity, performance, and precision:

Consider indexing your_column for a speed boost.
When duplicates are sparse, an EXISTS clause can terminate early, saving processing time.
Use COUNT(1) for potential performance benefits compared to COUNT(*), as it avoids fetching all fields.
Always use aliases (a, b) to improve readability and clarify query context.