使用窗口函數(shù)LEAD找出序列中的間隙。首先按值排序，比較當(dāng)前值與下一個(gè)值，若差值大於1，則存在間隙。例如數(shù)據(jù)1,2,5,6,10會(huì)返回兩段間隙：3到4和7到9。對(duì)於日期序列，可用INTERVAL進(jìn)行日期運(yùn)算，方法類似。
To find the start and end of a gap in a sequence using SQL, you can use window functions to identify missing values. This is commonly useful when dealing with auto-incremented IDs, dates, or any ordered numeric sequence where gaps indicate missing entries.
Detect Gaps in a Numeric Sequence
Assume you have a table sequence_table with a column value , and you want to find where numbers are missing.
The idea is to compare each number with the next one. If the difference is greater than 1, a gap exists.
Here's how to do it:
WITH ordered_values AS (
SELECT value, LEAD(value) OVER (ORDER BY value) AS next_value
FROM sequence_table
),
gaps AS (
SELECT
value 1 AS gap_start,
next_value - 1 AS gap_end
FROM ordered_values
WHERE next_value IS NOT NULL
AND next_value - value > 1
)
SELECT gap_start, gap_end FROM gaps;
This query returns all gaps: from gap_start to gap_end .
Example
If your data has values: 1, 2, 5, 6, 10
The output will be:
- gap_start = 3, gap_end = 4
- gap_start = 7, gap_end = 9
Handle Sequential Gaps or Single Missing Values
If you're only interested in single missing numbers (gaps of size 1), filter where gap_start = gap_end .
To find only those:
SELECT gap_start AS missing_value FROM gaps WHERE gap_start = gap_end;
For Date Sequences
If working with dates (eg, daily records), replace arithmetic with DATEADD or interval logic depending on your database.
Example in PostgreSQL:
WITH ordered_dates AS (
SELECT date_col,
LEAD(date_col) OVER (ORDER BY date_col) AS next_date
FROM date_table
),
gaps AS (
SELECT
date_col INTERVAL '1 day' AS gap_start,
next_date - INTERVAL '1 day' AS gap_end
FROM ordered_dates
WHERE next_date IS NOT NULL
AND next_date > date_col INTERVAL '1 day'
)
SELECT gap_start, gap_end FROM gaps;
Basically, the method relies on ordering the sequence and checking the difference between consecutive entries. Adjust based on your data type and SQL dialect.
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