Getting the Latest Two Dates for Each Unique ID in a Table

In this article, we will explore how to get the latest two dates for each unique id in a table using SQL. We’ll break down the process step-by-step and provide examples to illustrate each concept.

Understanding the Problem

The problem statement involves a table with three columns: unique_id, date, and an empty column for storing the second-latest date. The goal is to retrieve the latest two dates for each unique id in the table.

Let’s examine the sample data provided in the question:

The desired output for the above data would be:

Using Conditional Aggregation

The proposed solution involves using conditional aggregation and the row_number() function. Let’s break down this approach step-by-step.

Step 1: Creating a Row Number Column

To solve this problem, we need to create a row number column that assigns a unique number to each row within each group (i.e., for each unique id).

select *,
    row_number() over (partition by unique_id order by date desc) as rn
from table_name

In the above query, row_number() is an aggregate function that assigns a unique row number to each row within a partition. The partition by clause groups rows by the unique_id column, and the order by clause specifies the sorting order for dates in descending order (newest first).

Step 2: Creating Conditional Aggregation Columns

Using the row number column created in the previous step, we can now create two new columns that use conditional aggregation to extract the latest date for each unique id.

select unique_id,
       max(case when rn=1 then date end) as latest_date,
       max(case when rn=2 then date end) as _2nd_latest_date
from
(
  select *,
    row_number() over (partition by unique_id order by date desc) as rn
  from table_name
) T
group by unique_id

In the above query, we use max() with a case statement to extract the latest date for each unique id. The rn=1 condition selects the row with the highest row number (i.e., the latest date), and the rn=2 condition selects the second-highest row number (if it exists). If there is only one row for a given unique id, the _2nd_latest_date column will be NULL.

Step 3: Finalizing the Query

Finally, we add an order by clause to ensure that the results are sorted in ascending order by unique_id.

select unique_id,
       max(case when rn=1 then date end) as latest_date,
       max(case when rn=2 then date end) as _2nd_latest_date
from
(
  select *,
    row_number() over (partition by unique_id order by date desc) as rn
  from table_name
) T
group by unique_id
order by unique_id

This final query produces the desired output:

Conclusion

In this article, we demonstrated how to get the latest two dates for each unique id in a table using SQL conditional aggregation and the row_number() function. This technique can be applied to various scenarios where you need to extract multiple values from a single column or perform row-level grouping and aggregations.

We also discussed the importance of understanding the data distribution, identifying opportunities for optimization, and applying effective techniques to improve query performance. By mastering these skills, you’ll become proficient in extracting insights from your data using SQL.

Additional Tips and Variations

• To handle cases where there are multiple dates with the same row number, consider adding additional conditions or using alternative aggregation functions.
• If you need to exclude certain rows from the aggregation (e.g., based on a specific condition), use except clause in your query.
• For larger datasets, consider indexing columns used in aggregations and filtering queries to optimize performance.

Next Steps

Now that we have covered how to get the latest two dates for each unique id, explore other advanced SQL techniques, such as:

• Window functions (e.g., sum() over() or rank() over()).
• Common Table Expressions (CTEs) or derived tables.
• Joins and subqueries.

Stay up-to-date with the latest developments in SQL and data analysis by following industry leaders, attending webinars, or participating in online forums.

Last modified on 2024-01-17