SQL Data Deduplication Challenge

This challenge focuses on the common task of identifying and handling duplicate records within a database table. Effective data deduplication is crucial for maintaining data integrity, improving query performance, and ensuring accurate reporting. You will be tasked with developing a strategy to identify and potentially remove or mark duplicate entries based on specific criteria.

Problem Description

You are provided with a database table containing records that may have duplicates. Your goal is to write SQL queries that can identify these duplicate records. Specifically, you need to:

Identify Records: Determine which records are duplicates. A record is considered a duplicate if it has the same values across a defined set of columns as another record.
Preserve One Instance: For each set of duplicate records, you need a way to distinguish one "original" record from the others. This could involve selecting one arbitrarily or based on a specific criterion (e.g., the one with the earliest or latest timestamp, or the one with a unique identifier if available).
Handle Different Deduplication Strategies: Explore different approaches to handle identified duplicates, such as selecting only unique records, or selecting one instance and identifying the others as duplicates.

Key Requirements:

The solution must be implemented using SQL.
The definition of a duplicate record is based on a provided set of key columns.
The solution should clearly identify all instances of duplicate groups.
Consider scenarios where there are multiple duplicates of the same record.

Expected Behavior:

Your SQL queries should return information that allows for the identification of duplicate records. This could manifest as:

A list of records that have at least one duplicate.
A method to select a single, unique instance from each group of duplicates.
A method to flag or identify all but one instance within a duplicate group.

Edge Cases:

Tables with no duplicates.
Tables with records that are duplicates across multiple sets of columns.
Tables where the "original" record needs to be chosen based on a specific ordering (e.g., by an id or created_at column).

Examples

Example 1: Simple Duplicates

Consider a table named customers with the following data:

customer_id	first_name	last_name	email
1	John	Doe	john.doe@email.com
2	Jane	Smith	jane.smith@email.com
3	John	Doe	john.doe@email.com
4	Peter	Jones	peter.j@email.com
5	Jane	Smith	jane.smith@email.com

Deduplication Criteria: first_name, last_name, email

Task: Identify and list all records that have at least one duplicate based on the criteria.

Output (Conceptual):

customer_id	first_name	last_name	email	is_duplicate
1	John	Doe	john.doe@email.com	TRUE
2	Jane	Smith	jane.smith@email.com	TRUE
3	John	Doe	john.doe@email.com	TRUE
4	Peter	Jones	peter.j@email.com	FALSE
5	Jane	Smith	jane.smith@email.com	TRUE

Explanation: Records with customer_id 1 and 3 are duplicates. Records with customer_id 2 and 5 are duplicates. Record with customer_id 4 is unique.

Example 2: Selecting a Single Instance

Using the same customers table and deduplication criteria as Example 1.

Task: Write a query to select only one instance for each set of duplicate records. Prioritize the record with the lower customer_id.

Output (Conceptual):

customer_id	first_name	last_name	email
1	John	Doe	john.doe@email.com
2	Jane	Smith	jane.smith@email.com
4	Peter	Jones	peter.j@email.com

Explanation: For the duplicate group (1, 3), customer_id 1 is selected because it's the lowest. For the duplicate group (2, 5), customer_id 2 is selected. Record 4 is unique and kept.

Example 3: Edge Case - No Duplicates

Consider a table products with the following data:

product_id	product_name	price
101	Laptop	1200
102	Mouse	25
103	Keyboard	75

Deduplication Criteria: product_name, price

Task: Write a query to identify duplicates.

Output (Conceptual):

product_id	product_name	price	is_duplicate
101	Laptop	1200	FALSE
102	Mouse	25	FALSE
103	Keyboard	75	FALSE

Explanation: No records share the same product_name and price, so no duplicates are found.

Constraints

The table can contain a minimum of 0 and a maximum of 1,000,000 rows.
Column values for deduplication criteria will be of standard SQL data types (e.g., VARCHAR, INT, DATE).
The queries should aim for reasonable performance, ideally completing within a few seconds for a table of 1,000,000 rows. Avoid solutions that are O(N^2) or worse if possible.

Notes

This challenge is language-agnostic but assumes standard SQL syntax and functionality.
You might need to use window functions (like ROW_NUMBER(), RANK(), DENSE_RANK(), COUNT() OVER (...)) or GROUP BY clauses with HAVING to achieve the desired results.
Consider how you would handle NULL values when defining duplicates. For this challenge, assume NULL values in the deduplication columns should be treated as distinct unless explicitly stated otherwise by the problem context (which it isn't here).

SQL Data Deduplication Challenge

Problem Description

You are provided with a database table containing records that may have duplicates. Your goal is to write SQL queries that can identify these duplicate records. Specifically, you need to:

Identify Records: Determine which records are duplicates. A record is considered a duplicate if it has the same values across a defined set of columns as another record.
Preserve One Instance: For each set of duplicate records, you need a way to distinguish one "original" record from the others. This could involve selecting one arbitrarily or based on a specific criterion (e.g., the one with the earliest or latest timestamp, or the one with a unique identifier if available).
Handle Different Deduplication Strategies: Explore different approaches to handle identified duplicates, such as selecting only unique records, or selecting one instance and identifying the others as duplicates.

Key Requirements:

The solution must be implemented using SQL.
The definition of a duplicate record is based on a provided set of key columns.
The solution should clearly identify all instances of duplicate groups.
Consider scenarios where there are multiple duplicates of the same record.

Expected Behavior:

Your SQL queries should return information that allows for the identification of duplicate records. This could manifest as:

A list of records that have at least one duplicate.
A method to select a single, unique instance from each group of duplicates.
A method to flag or identify all but one instance within a duplicate group.

Edge Cases:

Tables with no duplicates.
Tables with records that are duplicates across multiple sets of columns.
Tables where the "original" record needs to be chosen based on a specific ordering (e.g., by an id or created_at column).

Examples

Example 1: Simple Duplicates

Consider a table named customers with the following data:

customer_id	first_name	last_name	email
1	John	Doe	john.doe@email.com
2	Jane	Smith	jane.smith@email.com
3	John	Doe	john.doe@email.com
4	Peter	Jones	peter.j@email.com
5	Jane	Smith	jane.smith@email.com

Deduplication Criteria: first_name, last_name, email

Task: Identify and list all records that have at least one duplicate based on the criteria.

Output (Conceptual):

customer_id	first_name	last_name	email	is_duplicate
1	John	Doe	john.doe@email.com	TRUE
2	Jane	Smith	jane.smith@email.com	TRUE
3	John	Doe	john.doe@email.com	TRUE
4	Peter	Jones	peter.j@email.com	FALSE
5	Jane	Smith	jane.smith@email.com	TRUE

Explanation: Records with customer_id 1 and 3 are duplicates. Records with customer_id 2 and 5 are duplicates. Record with customer_id 4 is unique.

Example 2: Selecting a Single Instance

Using the same customers table and deduplication criteria as Example 1.

Task: Write a query to select only one instance for each set of duplicate records. Prioritize the record with the lower customer_id.

Output (Conceptual):

customer_id	first_name	last_name	email
1	John	Doe	john.doe@email.com
2	Jane	Smith	jane.smith@email.com
4	Peter	Jones	peter.j@email.com

Explanation: For the duplicate group (1, 3), customer_id 1 is selected because it's the lowest. For the duplicate group (2, 5), customer_id 2 is selected. Record 4 is unique and kept.

Example 3: Edge Case - No Duplicates

Consider a table products with the following data:

product_id	product_name	price
101	Laptop	1200
102	Mouse	25
103	Keyboard	75

Deduplication Criteria: product_name, price

Task: Write a query to identify duplicates.

Output (Conceptual):

product_id	product_name	price	is_duplicate
101	Laptop	1200	FALSE
102	Mouse	25	FALSE
103	Keyboard	75	FALSE

Explanation: No records share the same product_name and price, so no duplicates are found.

Constraints

The table can contain a minimum of 0 and a maximum of 1,000,000 rows.
Column values for deduplication criteria will be of standard SQL data types (e.g., VARCHAR, INT, DATE).
The queries should aim for reasonable performance, ideally completing within a few seconds for a table of 1,000,000 rows. Avoid solutions that are O(N^2) or worse if possible.

Notes

This challenge is language-agnostic but assumes standard SQL syntax and functionality.
You might need to use window functions (like ROW_NUMBER(), RANK(), DENSE_RANK(), COUNT() OVER (...)) or GROUP BY clauses with HAVING to achieve the desired results.
Consider how you would handle NULL values when defining duplicates. For this challenge, assume NULL values in the deduplication columns should be treated as distinct unless explicitly stated otherwise by the problem context (which it isn't here).