Splitting Column Value Through 2 Columns in MySQL

In this article, we will explore how to split a column value into two separate columns based on the value of another column. This is a common requirement in data analysis and can be achieved using various techniques, including window functions and joins.

Background

The problem statement provides a sample dataset with three columns: timestamp, converationId, and UserId. The goal is to split the timestamp column into two separate columns, ts_question and ts_answer, based on the value of the tpMessage column. The first row of each question-answer pair should be assigned to the ts_question column, while the second row (if it exists) should be assigned to the ts_answer column.

One approach is to use a combination of window functions and joins to achieve this. In this article, we will explore two different approaches: one for when questions and answers always properly interleave in a user’s conversation, and another for when there may be gaps or islands in questions or answers.

Approach 1: When Questions and Answers Always Interleave

When questions and answers always properly interleave in a user’s conversation, we can use window functions to enumerate both series (questions and answers) and then pivot the results. This approach assumes that the first row of each question-answer pair should be assigned to the ts_question column.

The SQL query for this approach is as follows:

SELECT 
    max(case when tpMessage = 'question' then timestamp end) ts_question,
    max(case when tpMessage = 'answer'   then timestamp end) ts_answer,
    conversationId,
    userId, 
    max(case when tpMessage = 'question' then message end) question,
    max(case when tpMessage = 'answer'   then message end) answer
FROM (
    SELECT t.*, 
        row_number() over(partition by userId, conversationId order by timestamp) rn
    FROM mytable t
) t
GROUP BY userId, conversationId, rn;

This query works as follows:

1. The subquery uses the row_number() window function to assign a unique number to each row within each group of rows that have the same userId and conversationId. This allows us to identify the first row of each question-answer pair.
2. The outer query groups the results by userId, conversationId, and rn.
3. For each group, we use a max() window function to select the maximum value from the timestamp column when tpMessage is 'question'. This assigns the first row of each question-answer pair to the ts_question column.
4. We repeat steps 2-3 for the answer column.

This approach works well when questions and answers always properly interleave in a user’s conversation. However, it assumes that the first row of each question-answer pair should be assigned to the ts_question column.

Approach 2: When There May Be Gaps or Islands

When there may be gaps or islands in questions or answers, we need to use an approach that can handle these cases. One way to do this is by using window functions to bring the first answer to each question (if any).

The SQL query for this approach is as follows:

SELECT 
    timestamp ts_question,
    case when lead_tp = 'answer' then lead_timestamp end ts_answer,
    conversationId,
    userId,
    message question,
    case when lead_tp = 'answer' then lead_message end answer
FROM (
    SELECT t.*, 
        lead(tpMessage) over(partition by userId, conversationId order by timestamp) lead_tp,
        lead(timestamp) over(partition by userId, conversationId order by timestamp) lead_timestamp,
        lead(message) over(partition by userId, conversationId order by timestamp) lead_message,
    FROM mytable t
) t
WHERE tpMessage = 'question'

This query works as follows:

1. The subquery uses the lead() window function to bring the next value from the tpMessage, timestamp, and message columns when we have already seen a value.
2. We select the first row of each question-answer pair by using the original values in the tpMessage, timestamp, and message columns.
3. For each group, we use a case expression to assign the next value from the lead() window function to the ts_answer column when lead_tp is 'answer'.

This approach can handle cases where there may be gaps or islands in questions or answers. However, it assumes that the first row of each question-answer pair should be assigned to the ts_question column.

Conclusion

In this article, we have explored two different approaches for splitting a column value into two separate columns based on the value of another column. When questions and answers always properly interleave in a user’s conversation, we can use window functions to enumerate both series (questions and answers) and then pivot the results. However, when there may be gaps or islands in questions or answers, we need to use an approach that can handle these cases.

Ultimately, the choice of approach depends on the specific requirements of your data. By understanding how to split column values into two separate columns, you can perform more advanced data analysis and gain valuable insights from your data.

Last modified on 2023-11-07