In this table, I have a price change history. The prices are checked regularly and as you can see, sometimes the price does not change. How can I take a specific sku and delete all cases where a duplicate price is consecutively measured. As you can see, on 08-08, the price changed to 79.47. Then, it stayed that way until 08-11 when it changed to 79.41. I don't need all the repeated 79.47 since I can just assume that the price didn't change. So, I just need each point in time that the price changed, and that will allow me to save a lot of space.
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║ id ║ sku ║ amount ║ date ║
╠══════════╬════════╬════════╬═════════════════════╣
║ 225200 ║ 388744 ║ 60 ║ 2014-08-02 22:08:18 ║
║ 1571656 ║ 388744 ║ 79.47 ║ 2014-08-06 20:53:36 ║
║ 1572002 ║ 388744 ║ 79.47 ║ 2014-08-06 20:53:42 ║
║ 2092567 ║ 388744 ║ 79.45 ║ 2014-08-07 01:22:13 ║
║ 2608362 ║ 388744 ║ 79.44 ║ 2014-08-07 05:50:45 ║
║ 4403138 ║ 388744 ║ 79.44 ║ 2014-08-07 18:59:02 ║
║ 4935625 ║ 388744 ║ 79.44 ║ 2014-08-07 23:18:56 ║
║ 5356014 ║ 388744 ║ 79.47 ║ 2014-08-08 03:41:30 ║
║ 5703764 ║ 388744 ║ 79.47 ║ 2014-08-08 08:00:47 ║
║ 8559295 ║ 388744 ║ 79.47 ║ 2014-08-09 22:40:42 ║
║ 8878123 ║ 388744 ║ 79.47 ║ 2014-08-10 02:54:05 ║
║ 9204053 ║ 388744 ║ 79.47 ║ 2014-08-10 07:13:06 ║
║ 9538507 ║ 388744 ║ 79.47 ║ 2014-08-10 11:27:51 ║
║ 9863478 ║ 388744 ║ 79.47 ║ 2014-08-10 15:44:34 ║
║ 10184051 ║ 388744 ║ 79.47 ║ 2014-08-10 20:02:29 ║
║ 10503334 ║ 388744 ║ 79.41 ║ 2014-08-11 00:18:44 ║
║ 10821782 ║ 388744 ║ 79.33 ║ 2014-08-11 04:34:22 ║
║ 11135386 ║ 388744 ║ 79.33 ║ 2014-08-11 08:52:31 ║
║ 11446160 ║ 388744 ║ 79.33 ║ 2014-08-11 13:07:56 ║
║ 11760103 ║ 388744 ║ 79.33 ║ 2014-08-11 17:26:09 ║
║ 12074366 ║ 388744 ║ 79.33 ║ 2014-08-11 21:42:37 ║
║ 12399508 ║ 388744 ║ 79.47 ║ 2014-08-12 02:13:05 ║
║ 12726720 ║ 388744 ║ 79.47 ║ 2014-08-12 06:45:28 ║
║ 12726970 ║ 388744 ║ 79.47 ║ 2014-08-12 06:45:37 ║
║ 13059695 ║ 388744 ║ 79.47 ║ 2014-08-12 11:16:35 ║
║ 13406731 ║ 388744 ║ 79.47 ║ 2014-08-12 15:53:01 ║
║ 13750598 ║ 388744 ║ 79.48 ║ 2014-08-12 20:24:4 ║
╚══════════╩════════╩════════╩═════════════════════╝
So, after the query, it would hopefully look like this:
╔══════════╦════════╦════════╦═════════════════════╗
║ id ║ sku ║ amount ║ date ║
╠══════════╬════════╬════════╬═════════════════════╣
║ 225200 ║ 388744 ║ 60 ║ 2014-08-02 22:08:18 ║
║ 1571656 ║ 388744 ║ 79.47 ║ 2014-08-06 20:53:36 ║
║ 2092567 ║ 388744 ║ 79.45 ║ 2014-08-07 01:22:13 ║
║ 2608362 ║ 388744 ║ 79.44 ║ 2014-08-07 05:50:45 ║
║ 5356014 ║ 388744 ║ 79.47 ║ 2014-08-08 03:41:30 ║
║ 10503334 ║ 388744 ║ 79.41 ║ 2014-08-11 00:18:44 ║
║ 10821782 ║ 388744 ║ 79.33 ║ 2014-08-11 04:34:22 ║
║ 12399508 ║ 388744 ║ 79.47 ║ 2014-08-12 02:13:05 ║
║ 13750598 ║ 388744 ║ 79.48 ║ 2014-08-12 20:24:4 ║
╚══════════╩════════╩════════╩═════════════════════╝
Best Answer
This should do the job :
Here is the fiddle.