Identify Duplicates Within A Period Of Time Using Redshift SQL

Introduction

In this article, we will explore how to identify duplicates within a period of time using Redshift SQL. We will use a table containing plan details of customers with their customer_id and enroll_date. Our goal is to identify duplicate and valid enrollments from the overall data.

Duplicate Enrollment Definition

A duplicate enrollment is defined as a situation where a customer enrolls multiple times within a specified period. For example, if a customer enrolls on January 1st and then again on January 15th, this would be considered a duplicate enrollment.

Problem Statement

Given a table with the following structure:

We want to identify duplicate enrollments within a specified period, say 30 days.

Solution

To solve this problem, we can use a combination of window functions and conditional logic in Redshift SQL. Here's a step-by-step approach:

Step 1: Define the Window Frame

We need to define a window frame that will allow us to identify duplicate enrollments within a specified period. We can use the ROW_NUMBER() function to assign a unique row number to each enrollment, based on the customer_id and enroll_date.

WITH enrollment_details AS (
  SELECT 
    customer_id,
    enroll_date,
    ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY enroll_date) AS row_num
  FROM 
    your_table
)

Step 2: Identify Duplicate Enrollments

Now that we have a unique row number for each enrollment, we can use a conditional statement to identify duplicate enrollments. We will consider an enrollment as duplicate if it has a row number greater than 1.

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1

Step 3: Filter by Time Period

To filter the duplicate enrollments by a specified time period, we can use a date range condition. For example, to identify duplicate enrollments within the last 30 days, we can use the following query:

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1 AND enroll_date >= CURRENT_DATE - INTERVAL '30 day'

Step 4: Combine the Results

Finally, we can combine the results of the previous steps to get the final list of duplicate enrollments.

WITH enrollment_details AS (
  SELECT 
    customer_id,
    enroll_date,
    ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY enroll_date) AS row_num
  FROM 
    your_table
),
duplicate_enrollments AS (
  SELECT 
    customer_id,
    enroll_date
  FROM 
    enrollment_details
  WHERE 
    row_num > 1 AND enroll_date >= CURRENT_DATE - INTERVAL '30 day'
)
SELECT 
  *
FROM 
  duplicate_enrollments

Example Use Case

Suppose we have a table with the following data:

If we run the above query, we will get the following result:

This shows that customer 1 has a duplicate enrollment on 2022-01-15, and customer 3 has a duplicate enrollment on 2022-03-15.

Conclusion

Q: What is the purpose of using a window function in this query?

A: The window function, specifically ROW_NUMBER(), is used to assign a unique row number to each enrollment, based on the customer_id and enroll_date. This allows us to identify duplicate enrollments within a specified period.

Q: How does the query handle enrollments that occur on the same date?

A: The query uses the ORDER BY clause to sort the enrollments by date. If two enrollments occur on the same date, the query will assign the same row number to both enrollments. However, if the enrollments occur on different dates, the query will assign different row numbers.

Q: Can I modify the query to identify duplicate enrollments within a specific time range?

A: Yes, you can modify the query to identify duplicate enrollments within a specific time range by changing the date range condition in the WHERE clause. For example, to identify duplicate enrollments within the last 60 days, you can use the following query:

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1 AND enroll_date >= CURRENT_DATE - INTERVAL '60 day'

Q: How can I identify duplicate enrollments for a specific customer?

A: To identify duplicate enrollments for a specific customer, you can add a WHERE clause to filter the results by customer_id. For example, to identify duplicate enrollments for customer 1, you can use the following query:

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1 AND customer_id = 1

Q: Can I use this query to identify duplicate enrollments for multiple customers?

A: Yes, you can use this query to identify duplicate enrollments for multiple customers by adding multiple OR conditions to the WHERE clause. For example, to identify duplicate enrollments for customers 1 and 3, you can use the following query:

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1 AND (customer_id = 1 OR customer_id = 3)

Q: How can I modify the query to identify duplicate enrollments based on a different column?

A: To modify the query to identify duplicate enrollments based on a different column, you can change the column name in the PARTITION BY clause and the ORDER BY clause. For example, to identify duplicate enrollments based on the plan_id column, you can use the following query:

WITH enrollment_details AS (
  SELECT 
    plan_id,
    enroll_date,
    ROW_NUMBER() OVER (PARTITION BY plan_id ORDER BY enroll_date) AS row_num
  FROM 
    your_table
),
duplicate_enrollments AS (
  SELECT 
    plan_id,
    enroll_date
  FROM 
    enrollment_details
  WHERE 
    row_num > 1 AND enroll_date >= CURRENT_DATE - INTERVAL '30 day'
)
SELECT 
  *
FROM 
  duplicate_enrollments

Q: Can I use this query to identify duplicate enrollments for a specific date range?

A: Yes, you can use this query to identify duplicate enrollments for a specific date range by changing the date range condition in the WHERE clause. For example, to identify duplicate enrollments for the month of January 2022, you can use the following query:

SELECT 
  customer_id,
  enroll_date
FROM 
  enrollment_details
WHERE 
  row_num > 1 AND enroll_date >= '2022-01-01' AND enroll_date <= '2022-01-31'

Conclusion

In this article, we have answered some frequently asked questions on identifying duplicates within a period of time using Redshift SQL. We have provided examples and code snippets to help you understand how to modify the query to suit your specific use case.