SQL consecutive row date difference calculation
Determining the time interval between consecutive records is crucial for data analysis when working with large data sets. In this example, a SQL query is needed to calculate the date difference between consecutive rows with the same account number.
The following is a possible query:
<code class="language-sql">SELECT T1.ID, T1.AccountNumber, T1.Date, MIN(T2.Date) AS NextDate, DATEDIFF(day, T1.Date, MIN(T2.Date)) AS DaysDiff FROM YourTable T1 LEFT JOIN YourTable T2 ON T1.AccountNumber = T2.AccountNumber AND T2.Date > T1.Date GROUP BY T1.ID, T1.AccountNumber, T1.Date;</code>
This query uses LEFT JOIN
to compare each row in table T1
(the original table) to all subsequent rows in table T2
that have the same account number. It then uses the DATEDIFF
function to calculate the date difference and groups the results by ID
, AccountNumber
, and Date
to remove duplicate rows. DATEDIFF(day, ...)
Specifies the number of days to calculate the difference.
Another method is as follows:
<code class="language-sql">SELECT ID, AccountNumber, Date, LEAD(Date, 1, NULL) OVER (PARTITION BY AccountNumber ORDER BY Date) AS NextDate, DATEDIFF(day, Date, LEAD(Date, 1, NULL) OVER (PARTITION BY AccountNumber ORDER BY Date)) AS DaysDiff FROM YourTable;</code>
This query uses window functions LEAD
to get the next row date for each account number. LEAD(Date, 1, NULL) OVER (PARTITION BY AccountNumber ORDER BY Date)
Get the date of the next row of the current row, or NULL if there is no next row. Then calculate the date difference and present the result in the required format. This method is generally more efficient than LEFT JOIN
, especially on large datasets.
Both methods can calculate the date difference of consecutive rows. Which method to choose depends on your database system and performance requirements. The second method (using LEAD
) is usually more concise and efficient.
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