任何使用数据透视或聚合的东西可能会更快，因为它们不需要表是自联接的.基于连接的方法将需要优化器执行几个子查询操作，然后将结果连接在一起.对于较小的数据集，这可能无关紧要，但如果您对较大的数据集进行分析查询，这可能会显着降低性能，

I want to extract results from EAV (entity-attribute-value) tables, or more specifically entity-metadata tables (think like wordpress wp_posts and wp_postmeta) as a "nicely formatted relational table", in order to do some sorting and/or filtering.

I've found some examples of how to format the results within the query (as opposed to writing 2 queries and joining the results in code), but I would like to know the "most efficient" method for doing so, especially for larger result sets.

And when I say "most efficient", I mean for something like the following scenarios:

Get all Entities with last name like XYZ

Return a list of Entities sorted by birthday

---

e.g. turn this:

** ENTITY **
-----------------------
ID  | NAME | whatever
-----------------------
 1  | bob  | etc
 2  | jane | etc
 3  | tom  | etc

** META **
------------------------------------
ID | EntityID | KEY         | VALUE
------------------------------------
 1 |   1      | first name  | Bob
 2 |   1      | last name   | Bobson
 3 |   1      | birthday    | 1983-10-10
 . |   2      | first name  | Jane
 . |   2      | last name   | Janesdotter
 . |   2      | birthday    | 1983-08-10
 . |   3      | first name  | Tom
 . |   3      | last name   | Tomson
 . |   3      | birthday    | 1980-08-10

into this:

** RESULTS **
-----------------------------------------------
EID | NAME | first name | last name    | birthday
-----------------------------------------------
 1  | bob  | Bob        | Bobson       | 1983-10-10
 2  | jane | Jane       | Janesdotter  | 1983-08-10
 3  | tom  | Tom        | Tomson       | 1980-08-10

so I can sort or filter by any of the meta fields.

---

I found some suggestions here, but I can't find any discussion of which performs better.

Options:

1. GROUP_CONCAT:

   SELECT e.*, GROUP_CONCAT( CONCAT_WS('||', m.KEY, m.VALUE) ORDER BY m.KEY SEPARATOR ';;' )
   FROM `ENTITY` e JOIN `META` m ON e.ID = m.EntityID
   

2. Multi-Join:

   SELECT e.*, m1.VALUE as 'first name', m2.VALUE as 'last name', m3.VALUE as 'birthday'
   FROM `ENTITY` e
   LEFT JOIN `META` m1
       ON e.ID = m1.EntityID AND m1.meta_key = 'first name'
   LEFT JOIN `META` m2
       ON e.ID = m2.EntityID AND m2.meta_key = 'last name'
   LEFT JOIN `META` m3
       ON e.ID = m3.EntityID AND m3.meta_key = 'birthday'
   

3. Coalescing:

   SELECT e.*
      , MAX( IF(m.KEY= 'first name', m.VALUE, NULL) ) as 'first name'
      , MAX( IF(m.KEY= 'last name', m.VALUE, NULL) ) as 'last name'
      , MAX( IF(m.KEY= 'birthday', m.VALUE, NULL) ) as 'birthday'
   FROM `ENTITY` e
   JOIN `META` m
       ON e.ID = m.EntityID
   

4. Code:

   SELECT e.* FROM `ENTITY` e WHERE e.ID = {whatever};
   

   in PHP, create a placeholder object from result

   SELECT m.* FROM `META` m WHERE m.EntityID = {whatever};
   

   in PHP, loop through results and attach to entity object like: $e->{$result->key} = $result->VALUE

Which is better in general, and for filtering/sorting?

Related questions:

1. Binding EAV results
2. How to Pivot a MySQL entity

Anything using pivot or aggregates will probably be faster, as they don't require the table to be self-joined. The join based approaches will require the optimiser to perform several sub-query operations and then join the results together. For a small data set this might not matter so much, but this could significantly degrade performance if you're doing an analytic query on a larger data set,