Artful Common Queries

Find sequence starts and ends

from the Artful Common Queries page

A traditional way to find the first and last values of column value sequences in a table like this ...

drop table if exists t;
create table t(id int);
insert into t values(1),(2),(3),(4),(6),(7),(8);

... uses an exclusion join on the previous sequential value to find the first value of each sequence, and the minimum next value from a left join and an exclusion join on the previous sequential value to find the end of each sequence:

SELECT 
  a.id AS Start, 
  MIN( c.id ) AS End 
FROM tbl AS a
LEFT JOIN tbl AS b ON a.id = b.id + 1
LEFT JOIN tbl AS c ON a.id <= c.id
LEFT JOIN tbl AS d ON c.id = d.id - 1
WHERE b.id IS NULL 
  AND c.id IS NOT NULL
  AND d.id IS NULL
GROUP BY a.id;
+-------+------+
| Start | End  |
+-------+------+
|     1 |    4 |
|     6 |    8 |
+-------+------+

Thanks to Scott Noyes for noticing that a.id<c.id fails to pick up sequences of 1 followed by skips of 1, but a.id<=c.id does. To see how that query works, look at the output of this version of the query with exclusion and aggregation clauses removed:

SELECT a.id AS aid,b.id AS bid, c.id AS c.id, d.di AS did
FROM tbl AS a
LEFT JOIN tbl AS b ON a.id = b.id + 1
LEFT JOIN tbl AS c ON a.id <= c.id
LEFT JOIN tbl AS d ON c.id = d.id - 1
ORDER BY a.id,b.id,c.id,d.id;
+------+------+------+------+
| aid  | bid  | cid  | did  |
+------+------+------+------+
|    1 | NULL |    1 |    2 |
|    1 | NULL |    2 |    3 |
|    1 | NULL |    3 |    4 |
|    1 | NULL |    4 | NULL |  <-- end of sequence starting with 1
|    1 | NULL |    6 |    7 |
|    1 | NULL |    7 |    8 |
|    1 | NULL |    8 | NULL |
|    2 |    1 |    2 |    3 |
|    2 |    1 |    3 |    4 |
|    2 |    1 |    4 | NULL |
|    2 |    1 |    6 |    7 |
|    2 |    1 |    7 |    8 |
|    2 |    1 |    8 | NULL |
|    3 |    2 |    3 |    4 |
|    3 |    2 |    4 | NULL |
|    3 |    2 |    6 |    7 |
|    3 |    2 |    7 |    8 |
|    3 |    2 |    8 | NULL |
|    4 |    3 |    4 | NULL |
|    4 |    3 |    6 |    7 |
|    4 |    3 |    7 |    8 |
|    4 |    3 |    8 | NULL |
|    6 | NULL |    6 |    7 |
|    6 | NULL |    7 |    8 |
|    6 | NULL |    8 | NULL |  <-- end of sequence starting with 6
|    7 |    6 |    7 |    8 |
|    7 |    6 |    8 | NULL |
|    8 |    7 |    8 | NULL |
+------+------+------+------+

But elegant as it looks, the exclusion join method scales badly. In the MySQL Performance forum, Rick James posted a solution that runs much faster and scales linearly:

select starts, ends
from (
  select
    @start as starts,
    if(mx=2, id-1, null) as ends,
    @start := if(mn=1, id, null)
  from ( 
    select @start = -9 
  ) v
  join (
    select 
      max(x) as mx, 
      min(x) as mn, 
      count(*) as ct, 
      id
    from (
      ( select 1 as x, id from tbl )
      union all
      ( select 2, id+1 from tbl )
    ) z 
    group by id
    having ct = 1
  ) w
) u
where starts is not null;

A variant of the problem: when some IDs are used and some are not, find blocks of unused IDs:

DROP TABLE IF EXISTS tbl;
CREATE TABLE tbl(id INT,used BOOL);
INSERT INTO tbl VALUES(1,1),(2,0),(3,0),(4,1),(5,0),(6,0);
SELECT a.id AS Start, MIN( c.id ) AS End
FROM tbl AS a
LEFT JOIN tbl AS b ON a.id=b.id + 1 AND a.used=0 AND b.used=0
LEFT JOIN tbl AS c ON a.id<=c.id AND a.used=0 AND c.used=0
LEFT JOIN tbl AS d ON c.id=d.id-1 AND c.used=0 AND d.used=0
WHERE b.id IS NULL
  AND c.id IS NOT NULL
  AND d.id IS NULL
GROUP BY a.id;
+-------+------+
| Start | End  |
+-------+------+
|     2 |    3 |
|     5 |    6 |
+-------+------+

Here's another variation on the pattern from a MySQL forum. You have a history of prescription dose changes ...

DROP TABLE IF EXISTS dose_change;
CREATE TABLE dose_change (
  oid INTEGER UNSIGNED PRIMARY KEY AUTO_INCREMENT,
  dose_date DATETIME NOT NULL,
  dose INTEGER UNSIGNED,
);
INSERT INTO dose_change (dose_date, dose) values
('2025-01-01', 10),('2025-01-02', 10),('2025-01-03', 20),('2025-01-04', 20),
('2025-01-05', 10),('2025-01-06', 10),('2025-01-07', 10),('2025-01-08', NULL),
('2025-01-09', NULL),('2025-01-10', 30),('2025-01-11', 30),('2025-01-12', 30),
('2025-01-13', 10),('2025-01-14', 20),('2025-01-15', 10),('2025-01-16', NULL),
('2025-01-17', 10);
SELECT * FROM dose_change;
+-----+---------------------+------+
| oid | dose_date           | dose |
+-----+---------------------+------+
|   1 | 2025-01-01 00:00:00 |   10 |
|   2 | 2025-01-02 00:00:00 |   10 |
|   3 | 2025-01-03 00:00:00 |   20 |
|   4 | 2025-01-04 00:00:00 |   20 |
|   5 | 2025-01-05 00:00:00 |   10 |
|   6 | 2025-01-06 00:00:00 |   10 |
|   7 | 2025-01-07 00:00:00 |   10 |
|   8 | 2025-01-08 00:00:00 | NULL |
|   9 | 2025-01-09 00:00:00 | NULL |
|  10 | 2025-01-10 00:00:00 |   30 |
|  11 | 2025-01-11 00:00:00 |   30 |
|  12 | 2025-01-12 00:00:00 |   30 |
|  13 | 2025-01-13 00:00:00 |   10 |
|  14 | 2025-01-14 00:00:00 |   20 |
|  15 | 2025-01-15 00:00:00 |   10 |
|  16 | 2025-01-16 00:00:00 | NULL |
|  17 | 2025-01-17 00:00:00 |   10 |
+-----+---------------------+------+

... and you want the dosage history:

2025-01-01 - 2000-01-03, 10
2025-01-03 - 2000-01-05, 20
2025-01-05 - 2000-01-08, 10
2025-01-10 - 2000-01-13, 30
2025-01-13 - 2000-01-14, 10
2025-01-14 - 2000-01-15, 20
2025-01-15 - 2000-01-16, 10
2025-01-17 - null      , 10

Forum contributor "laptop alias" posted this solution:

SELECT a.dose_date AS start
     , MIN(DATE(c.dose_date)) + INTERVAL 1 DAY AS end
     , a.dose
  FROM 
     ( SELECT x.dose_date, x.dose, COUNT(*) id 
         FROM dose_change x
         JOIN dose_change y
           ON y.dose_date <= x.dose_date
        GROUP BY x.oid
     ) AS a
  LEFT JOIN 
     ( SELECT x.dose_date, x.dose, COUNT(*) id 
         FROM dose_change x
         JOIN dose_change y
           ON y.dose_date <= x.dose_date
        GROUP BY x.oid
     ) AS b ON a.id = b.id + 1 AND b.dose = a.dose
  LEFT JOIN  
     ( SELECT x.dose_date, x.dose, COUNT(*) id 
         FROM dose_change x
         JOIN dose_change y
           ON y.dose_date <= x.dose_date
        GROUP BY x.oid
     ) AS c ON a.id <= c.id AND c.dose = a.dose
  LEFT JOIN 
     ( SELECT x.dose_date, x.dose, COUNT(*) id 
         FROM dose_change x
         JOIN dose_change y
           ON y.dose_date <= x.dose_date
        GROUP BY x.oid
     ) AS d ON c.id = d.id - 1 AND d.dose = c.dose
WHERE b.id IS NULL AND c.id IS NOT NULL AND d.id IS NULL
GROUP BY start;
+---------------------+------------+------+
| start               | end        | dose |
+---------------------+------------+------+
| 2025-01-01 00:00:00 | 2025-01-03 |   10 |
| 2025-01-03 00:00:00 | 2025-01-05 |   20 |
| 2025-01-05 00:00:00 | 2025-01-08 |   10 |
| 2025-01-10 00:00:00 | 2025-01-13 |   30 |
| 2025-01-13 00:00:00 | 2025-01-14 |   10 |
| 2025-01-14 00:00:00 | 2025-01-15 |   20 |
| 2025-01-15 00:00:00 | 2025-01-16 |   10 |
| 2025-01-17 00:00:00 | 2025-01-18 |   10 |
+---------------------+------------+------+

Tom Melly found this simpler but slower solution:

SELECT 
  a.dose_date AS StartDate, 
  a.dose AS Dose,
  ( SELECT b.dose_date 
    FROM dose_change AS b 
    WHERE b.dose_date > a.dose_date AND (b.dose <> a.dose OR b.dose IS NULL) 
    ORDER BY b.dose_date ASC LIMIT 1
  ) AS StopDate
FROM dose_change AS a
WHERE Coalesce(
               (SELECT c.dose 
                FROM dose_change AS c 
                WHERE c.dose_date <= a.dose_date 
                ORDER BY c.dose_date DESC LIMIT 1,1 
               ), -99999 
              ) <> a.dose
  AND a.dose IS NOT NULL
ORDER BY a.dose_date ASC;

Last updated 14 Dec 2024