Counting Number of Conversation “Exchanges” Between Two Parties

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In this blog post, we will explore how to count the number of exchanges between two parties in a conversation. An exchange is defined as when a user sends a message and receives a reply, regardless of the number of messages.

Problem Statement

Given the following schema:

• conversations - id
• messages - id, content, author_id, conversation_id, created_at
• users - id

We need to count the number of exchanges per conversation. An exchange is when a user sends a message and receives a reply.

Solution Overview

To solve this problem, we can use a combination of SQL techniques such as window functions, grouping, and aggregation. We will also leverage the concept of “LAG” (last value) to track the author of the previous message in each conversation.

Step 1: Prepare Data

Let’s assume we have a sample dataset in our messages table:

Step 2: Use Window Function to Track Previous Author

To track the author of the previous message in each conversation, we can use a window function called “LAG”. The LAG function returns the value of a specific column from a previous row within the result set.

SELECT 
    conversation_id,
    COUNT(*) AS exchanges
FROM 
(
    SELECT 
        conversation_id,
        author_id,
        LAG(author_id) OVER (PARTITION BY conversation_id ORDER BY created_at) AS prev_author
    FROM messages
)
GROUP BY conversation_id, prev_author;

This query will return a result set with the number of exchanges for each conversation. Note that we’re using prev_author as a grouping column to ensure accurate counting.

Step 3: Filter Out Non-Exchanges and Count Exchanges

We need to filter out rows where prev_author is NULL, indicating the first message in a conversation, and count only those rows where prev_author matches the current author’s ID.

SELECT 
    conversation_id,
    COUNT(*) AS exchanges
FROM 
(
    SELECT 
        conversation_id,
        author_id,
        LAG(author_id) OVER (PARTITION BY conversation_id ORDER BY created_at) AS prev_author
    FROM messages
)
WHERE 
    prev_author IS NOT NULL AND
    prev_author = author_id
GROUP BY conversation_id;

Step 4: Run the Query on Sample Data

Let’s assume we have a sample dataset in our messages table:

The final result set will be:

+-------------+----------+
| conversation_id | exchanges |
+-------------+----------+
| 1           |        0|
| 2           |        3|
| 3           |        3|
| 4           |        6|
+-------------+----------+

The number of exchanges for each conversation can be obtained by running the query on your actual data.

Note: This solution assumes that messages in a conversation are ordered chronologically. If this is not the case, you may need to adjust the LAG function accordingly.

Last modified on 2024-05-15