Retrieving Odd Rows from a Table using SQL

Introduction

In the world of data analysis and management, it’s often necessary to extract specific subsets of data from a larger dataset. One common use case is retrieving odd rows from a table, where “odd” refers to rows that have unique or distinctive values compared to their neighboring rows.

In this article, we’ll explore how to achieve this using SQL queries, with a focus on identifying the Cr_id column’s duplicate values and extracting rows based on these duplicates.

Understanding the Problem

The problem statement involves a Base table where every other row has duplicated Cr_id values. The goal is to write an SQL query that retrieves only those c_id = 1 rows where Cr_id is always first, as demonstrated in the provided Output table.

To break this down further, let’s analyze the scenario:

• We have a table called “t” with columns c_id, cr_id, and dt.
• In the Base table, every other row has duplicated Cr_id values.
• Our objective is to retrieve rows where c_id = 1 and the corresponding Cr_id value appears first.

SQL Query

To solve this problem, we’ll use a combination of SQL queries that filter out duplicate values based on Cr_id. Here’s how:

SELECT c_id, cr_id, dt
FROM t
WHERE c_id = 1 AND
      dt = (SELECT MIN(dt) FROM t t1 WHERE t1.cr_id = t.cr_id);

Let’s dissect this query step by step:

• SELECT c_id, cr_id, dt: We’re selecting only the columns we need: c_id, cr_id, and dt.
• FROM t: This specifies our table, “t”.
• WHERE c_id = 1 AND ... : We want to filter rows where c_id is equal to 1. The AND operator ensures that both conditions must be met for a row to be included in the results.
• (SELECT MIN(dt) FROM t t1 WHERE t1.cr_id = t.cr_id) : This subquery retrieves the minimum dt value shared by each Cr_id pair. We use this in our main query as a filter.

How It Works

Here’s an example of how the above query works for the given table:

Suppose we have the following values in the Base table:

We want to retrieve the rows where c_id is equal to 1 and Cr_id is always first.

To do this, we use our subquery:

• First, it finds the minimum dt value shared by each Cr_id pair. In our case, both Cr_id = 56 and Cr_id = 8 share the same minimum date (2020-12-17).
• Then, our main query uses these minimum dates to filter out rows with c_id other than 1.

The resulting output will be:

These are the rows where c_id = 1 and Cr_id is always first.

Why This Works

The reason our query works as expected lies in the way SQL handles duplicate values based on Cr_id.

When we use the subquery (SELECT MIN(dt) FROM t t1 WHERE t1.cr_id = t.cr_id), it returns a single row (the minimum dt value shared by each pair).

Then, in our main query, WHERE c_id = 1 AND dt = ... filters out rows where c_id is not equal to 1.

Because the subquery has already returned all dt values for Cr_id pairs, we don’t need to worry about duplicate values here. We’re only interested in rows with c_id equal to 1 and matching dt values (the minimum shared by each pair).

This approach ensures that our query correctly identifies the desired rows without having to handle duplicate values explicitly.

Conclusion

Retrieving odd rows from a table can be achieved using SQL queries that filter out duplicate values based on specific columns. In this article, we’ve explored how to achieve this using a subquery and filtering conditions to identify rows with unique or distinctive values compared to their neighboring rows.

By understanding the mechanics of SQL and handling duplicate values carefully, developers can write efficient and effective queries to extract specific subsets from larger datasets.

Whether working with relational databases or other data management systems, mastering techniques for extracting specific data points will always be essential in the pursuit of accurate analysis and insight.

Last modified on 2025-03-06