To solve this problem, we need to calculate the success rate of posts that immediately follow a failed post for each user. The success rate is defined as the percentage of such posts that are successful

 

Approach

1. Problem Analysis: The task involves analyzing the sequence of posts made by each user to determine the success rate of posts that come immediately after a failed post.

2. Key Insight: For each user, we need to check the status of the previous post. If the previous post was unsuccessful, the current post is considered in the calculation of the success rate.

3. Data Processing:

   • Ordering Posts: For each user, order their posts by date (and post ID to handle any ties in timestamps) to determine the sequence.

   • Previous Post Status: Use the LAG window function to retrieve the status of the previous post in the sequence.

   • Filter Relevant Posts: Select only those posts where the previous post was unsuccessful.

   • Calculate Success Rate: For the filtered posts, compute the percentage of successful posts per user.

4. Output: Present the results with user IDs and their corresponding success rates, ordered by increasing success rate.

Solution Code

sql

WITH post_sequence AS (
    SELECT 
        user_id,
        is_successful_post,
        LAG(is_successful_post) OVER (
            PARTITION BY user_id 
            ORDER BY post_date, post_id
        ) AS prev_success
    FROM post
)
SELECT
    user_id,
    AVG(CASE WHEN is_successful_post THEN 100.0 ELSE 0.0 END) AS next_post_sc_rate
FROM post_sequence
WHERE prev_success = False
GROUP BY user_id
ORDER BY next_post_sc_rate;

Explanation

1. CTE post_sequence:

   • Partitioning and Ordering: The posts are partitioned by user_id and ordered by post_date and post_id to ensure the sequence is correctly determined.

   • Previous Post Status: The LAG function retrieves the is_successful_post value of the previous post in the sequence for each user.

2. Main Query:

   • Filtering Relevant Posts: Only posts where the previous post was unsuccessful (prev_success = False) are considered.

   • Success Rate Calculation: The AVG function combined with a CASE statement computes the percentage of successful posts. Successful posts contribute 100.0 to the average, while unsuccessful posts contribute 0.0.

   • Grouping and Ordering: Results are grouped by user_id and ordered by the computed success rate in ascending order.