How to find previous record [n-per-group max(times

I have a large table containing time series sensor data. Large is anything from a few thousand up to 10M record divided amongst various channels being monitored. For a certain sensor type I need to calculate the time interval between the current and previous reading, i.e. find the largest timestamp prior to the current one.

The obvious approaches come to mind, each measured on Core i5 for a channel of 40k entries:

Correlated subquery

SELECT collect.*, prev.timestamp AS prev_timestamp
FROM data AS collect 
LEFT JOIN data AS prev ON prev.channel_id = collect.channel_id AND prev.timestamp = ( 
    SELECT MAX(timestamp) 
    FROM data 
    WHERE data.channel_id = collect.channel_id AND data.timestamp < collect.timestamp
) 
WHERE collect.channel_id=14 AND collect.timestamp >= 0 
ORDER BY collect.timestamp

Time (exec, fetch) 11sec, 21sec

Plan

+----+--------------------+---------+------+------------------------------+---------+---------+-------------------------+-------+--------------------------+
| id |    select_type     |  table  | type |        possible_keys         |   key   | key_len |           ref           | rows  |          Extra           |
+----+--------------------+---------+------+------------------------------+---------+---------+-------------------------+-------+--------------------------+
|  1 | PRIMARY            | collect | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 | const                   | 45820 | Using where              |
|  1 | PRIMARY            | prev    | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |      13 | const,func              |     1 | Using index              |
|  2 | DEPENDENT SUBQUERY | data    | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 | nils.collect.channel_id |  2495 | Using where; Using index |
+----+--------------------+---------+------+------------------------------+---------+---------+-------------------------+-------+--------------------------+

Anti Join

SELECT d1.*, d2.timestamp AS prev_timestamp
FROM data d1
LEFT JOIN data d2 ON
    d2.channel_id=14 AND
    d2.timestamp < d1.timestamp 
LEFT JOIN data d3 ON
    d3.channel_id=14 AND
    d3.timestamp < d1.timestamp AND
    d3.timestamp > d2.timestamp
WHERE 
    d3.timestamp IS NULL AND
    d1.channel_id=14
ORDER BY timestamp

Time 12sec, 21sec

Plan

+----+-------------+-------+------+------------------------------+---------+---------+-------+-------+--------------------------------------+
| id | select_type | table | type |        possible_keys         |   key   | key_len |  ref  | rows  |                Extra                 |
+----+-------------+-------+------+------------------------------+---------+---------+-------+-------+--------------------------------------+
|  1 | SIMPLE      | d1    | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 | const | 45820 | Using where                          |
|  1 | SIMPLE      | d2    | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 | const | 47194 | Using index                          |
|  1 | SIMPLE      | d3    | ref  | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 | const | 47194 | Using where; Using index; Not exists |
+----+-------------+-------+------+------------------------------+---------+---------+-------+-------+--------------------------------------+

And I've come up with another pattern I'm calling Naive Count

SELECT current.*, prev.timestamp AS prev_timestamp FROM
(
    SELECT data.*, @r1 := @r1+1 AS rownum from data
    CROSS JOIN (SELECT @r1 := 0) AS vars 
    WHERE channel_id=14
    ORDER BY timestamp
) AS current
LEFT JOIN
(
    SELECT data.*, @r2 := @r2+1 AS rownum from data
    CROSS JOIN (SELECT @r2 := 0) AS vars 
    WHERE channel_id=14
    ORDER BY timestamp
) AS prev
ON current.rownum = prev.rownum+1

Time 1.1sec (this one is actually fastest!)

Plan

+----+-------------+------------+--------+------------------------------+---------+---------+-----+-------+----------------+
| id | select_type |   table    |  type  |        possible_keys         |   key   | key_len | ref | rows  |     Extra      |
+----+-------------+------------+--------+------------------------------+---------+---------+-----+-------+----------------+
|  1 | PRIMARY     | <derived2> | ALL    |                              |         |         |     | 24475 |                |
|  1 | PRIMARY     | <derived4> | ALL    |                              |         |         |     | 24475 |                |
|  4 | DERIVED     | <derived5> | system |                              |         |         |     |     1 |                |
|  4 | DERIVED     | data       | ref    | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 |     | 45820 | Using where    |
|  5 | DERIVED     |            |        |                              |         |         |     |       | No tables used |
|  2 | DERIVED     | <derived3> | system |                              |         |         |     |     1 |                |
|  2 | DERIVED     | data       | ref    | ts_uniq,IDX_ADF3F36372F5A1AA | ts_uniq |       5 |     | 45820 | Using where    |
|  3 | DERIVED     |            |        |                              |         |         |     |       | No tables used |
+----+-------------+------------+--------+------------------------------+---------+---------+-----+-------+----------------+

As the query likely runs on small platforms like the RasPi performance is critical- a couple seconds are highest acceptable.

My question: Is the last approach a good one for greatest-n-per-group or are there better ones? Is it expected that correlated subquery is as slow as experienced?

The last approach with variables is reasonable. You might also try:

SELECT collect.*,
       (select max(timestamp)
        from data
        where data.channel_id = collect.channel_id AND data.timestamp < collect.timestamp
       ) AS prev_timestamp
FROM data AS collect 
WHERE collect.channel_id = 14 AND collect.timestamp >= 0 
ORDER BY collect.timestamp;

In addition, create indexes on: collect(channel_id, timestamp).

EDIT:

The following might be the fastest:

  select d.*,
         if(@channel_id = channel_id, @prev_timestamp, NULL) as prev_timestamp,
         @channel_id := channel_id, @prev_timestamp = timestamp
  from data d cross join
       (select @channel_id := 0, @prev_timestamp := 0) vars
  where collect.channel_id = 14 AND collect.timestamp >= 0 
  order by channel_id, timestamp;