MySQL Group Concat Function
By Will Mayall
19-December-2014
Contents
Overview ................................................................................................................................................... 1
Understanding Your Data ............................................................................................................... 1
Making Sense of Your Data ........................................................................................................... 3
Summary ...................................................................................................................................................... 4
Overview
This document is intended to explain how and when to
use the distinct and group concat functions in MySQL.
Understanding Your Data
There are cases when your data has “one to many”
relationships, but you only want to see distinct values
of “one to many.” Getting “one to many” values
returned can be accomplished using the distinct and
group concat functions.
Below is the table definition:
mysql> desc ec3;
+------------------+----------------------+------+-----+---------------------+-------+
| Field
| Type
| Null | Key | Default
| Extra |
+------------------+----------------------+------+-----+---------------------+-------+
| pers_id
| int(10) unsigned
| NO
| PRI | 0
|
|
| co_id
| int(10) unsigned
| NO
| MUL | NULL
|
|
| email
| varchar(100)
| NO
| MUL | NULL
|
|
1
| domain
| varchar(100)
| YES
| MUL | NULL
|
|
| checked
| datetime
| YES
| MUL | NULL
|
|
| ok_syntax
| tinyint(1)
| YES
|
| NULL
|
|
| ok_domain
| tinyint(1)
| YES
|
| NULL
|
|
| code
| varchar(45)
| YES
| MUL | NULL
|
|
| message
| varchar(100)
| YES
| MUL | NULL
|
|
| seconds
| smallint(3) unsigned | YES
|
|
|
| working
| datetime
| YES
| MUL | 0000-00-00 00:00:00 |
|
| reason_code
| varchar(45)
| YES
| MUL | NULL
|
|
| reason_message
| varchar(100)
| YES
| MUL | NULL
|
|
| certified
| datetime
| YES
|
| NULL
|
|
| hygiene
| varchar(100)
| YES
|
| NULL
|
|
| netprotect
| tinyint(1)
| YES
|
| 0
|
|
| netprotectby
| varchar(100)
| YES
|
| NULL
|
|
| domainknowledge
| text
| YES
|
| NULL
|
|
| addressknowledge | text
| YES
|
| NULL
|
|
| version
| varchar(25)
| NO
|
| EmailVerify5
|
|
| tag
| varchar(64)
| NO
|
|
|
|
| primary
| tinyint(1)
| YES
|
| 1
|
|
| retry
| int(11)
| YES
| MUL | 0
|
|
| NULL
+------------------+----------------------+------+-----+---------------------+-------+
23 rows in set (0.00 sec)
mysql>
To get an idea of the problem, executing the below
query will turn one co_id and many messages with the
same value.
mysql> select co_id,message from ec3 where co_id = 5;
+-------+------------------+
| co_id | message
|
+-------+------------------+
|
5 | Domain Confirmed |
2
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
|
5 | Domain Confirmed |
+-------+------------------+
11 rows in set (0.00 sec)
mysql>
Making Sense of Your Data
The query in the last example makes no sense, and
furthermore, what if there are more than one message?
In comes the functions distinct and group concat!
mysql> select co_id,group_concat(distinct ec3.message) from ec3 where message is not NULL group
by co_id having count(distinct message) > 1 order by co_id limit 10;
+-------+----------------------------------------------------------------------+
| co_id | group_concat(distinct ec3.message)
|
+-------+----------------------------------------------------------------------+
|
2 | Domain Confirmed,Email Valid
|
|
13 | Email Valid,Domain Confirmed
|
|
15 | Domain Confirmed,Internal Error
|
|
18 | Domain Confirmed,Domain Confirmed. Potentially Dangerous
|
|
19 | Domain Confirmed,Domain Confirmed. Potentially Dangerous,Email Valid |
|
20 | Email Valid,Domain Confirmed,Email Valid Potentially Dangerous
|
|
21 | Domain Confirmed,Domain Confirmed. Potentially Dangerous
|
|
27 | Email Valid,Email Not Valid
|
3
|
28 | Domain Confirmed. Potentially Dangerous,Domain Confirmed
|
|
35 | Domain Confirmed,Not Verified, Dangerous Domain
|
+-------+----------------------------------------------------------------------+
10 rows in set (0.68 sec)
mysql>
Summary
Sometimes the data in your database makes no sense.
Using functions to filter the data helps you understand
trends and can make valuable use of the data.
4