A previous DBA managed a non relational table with 2.4M entries, all with unique ID's. However, there are duplicate records with different data in each record for example:
+---------+---------+--------------+----------------------+-------------+
| id | Name | Address | Phone | Email | LastVisited |
+---------+---------+--------------+---------+------------+-------------+
| 1 | bob | 12 Some Road | 02456 | | |
| 2 | bobby | | 02456 | bob@domain | |
| 3 | bob | 12 Some Rd | 02456 | | 2010-07-13 |
| 4 | sir bob | | 02456 | | |
| 5 | bob | 12SomeRoad | 02456 | | |
| 6 | mr bob | | 02456 | | |
| 7 | robert | | 02456 | | |
+---------+---------+--------------+---------+------------+-------------+
This isnt the exact table - the real table has 32 columns - this is just to illustrate
I know how to identify the duplicates, in this case i'm using the phone number. I've extracted the duplicates into a seperate table - there's 730k entires in total.
What would be the most efficient way of merging these records (and flagging the un-needed records for deletion)?
I've looked at using UPDATE with INNER JOIN's, but there are several WHERE clauses needed, because i want to update the first record with data from subsequent records, where that subsequent record has additional data the former record does not.
I've looked at third party software such as Fuzzy Dups, but i'd like a pure MySQL option if possible
The end goal then is that i'd be left with something like:
+---------+---------+--------------+----------------------+-------------+
| id | Name | Address | Phone | Email | LastVisited |
+---------+---------+--------------+---------+------------+-------------+
| 1 | bob | 12 Some Road | 02456 | bob@domain | 2010-07-13 |
+---------+---------+--------------+---------+------------+-------------+
Should i be looking at looping in a stored procedure / function or is there some real easy thing i've missed?