Improving speed of SQL query with MAX, WHERE, and GROUP BY on three different columns

Question

I am attempting to speed up a query that takes around 60 seconds to complete on a table of ~20 million rows.

For this example, the table has three columns (id, dateAdded, name). id is the primary key. The indexes I have added to the table are:

(dateAdded)
(name)
(id, name)
(id, name, dateAdded)

The query I am trying to run is:

SELECT MAX(id) as id, name 
FROM exampletable 
WHERE dateAdded <= '2014-01-20 12:00:00' 
GROUP BY name 
ORDER BY NULL;

The date is variable from query to query.

The objective of this is to get the most recent entry for each name at or before the date added.

When I use explain on the query it tells me that it is using the (id, name, dateAdded) index.

+----+-------------+------------------+-------+------------------+----------------------------------------------+---------+------+----------+-----------------------------------------------------------+
| id | select_type | table            | type  | possible_keys    | key                                          | key_len | ref  | rows     | Extra                                                     |
+----+-------------+------------------+-------+------------------+----------------------------------------------+---------+------+----------+-----------------------------------------------------------+
|  1 | SIMPLE      | exampletable     | index | date_added_index | id_element_name_date_added_index             | 162     | NULL | 22016957 | Using where; Using index; Using temporary; Using filesort |
+----+-------------+------------------+-------+------------------+----------------------------------------------+---------+------+----------+-----------------------------------------------------------+

Edit: Added two new indexes from comments:

(dateAdded, name, id)
(name, id)

+----+-------------+------------------+-------+---------------------------------------------------------------+----------------------------------------------+---------+------+----------+-------------------------------------------+
| id | select_type | table            | type  | possible_keys                                                 | key                                          | key_len | ref  | rows     | Extra                                     |
+----+-------------+------------------+-------+---------------------------------------------------------------+----------------------------------------------+---------+------+----------+-------------------------------------------+
|  1 | SIMPLE      | exampletable     | index | date_added_index,date_added_name_id_index                     | id__name_date_added_index                    | 162     | NULL | 22040469 | Using where; Using index; Using temporary |
+----+-------------+------------------+-------+---------------------------------------------------------------+----------------------------------------------+---------+------+----------+-------------------------------------------+

Edit: Added create table script.

CREATE TABLE `exampletable` (
  `id` int(10) NOT NULL auto_increment,
  `dateAdded` timestamp NULL default CURRENT_TIMESTAMP,
  `name` varchar(50) character set utf8 default '',
  PRIMARY KEY  (`id`),
  KEY `date_added_index` (`dateAdded`),
  KEY `name_index` USING BTREE (`name`),
  KEY `id_name_index` USING BTREE (`id`,`name`),
  KEY `id_name_date_added_index` USING BTREE (`id`,`dateAdded`,`name`),
  KEY `date_added_name_id_index` USING BTREE (`dateAdded`,`name`,`id`),
  KEY `name_id_index` USING BTREE (`name`,`id`)
) ENGINE=MyISAM AUTO_INCREMENT=22046064 DEFAULT CHARSET=latin1

Edit: Here is the Explain from the answer provided by HeavyE.

+----+-------------+--------------+-------+------------------------------------------------------------------------------------------+--------------------------+---------+--------------------------------------------------+------+---------------------------------------+
| id | select_type | table        | type  | possible_k                                                                               | key                      | key_len | ref                                              | rows | Extra                                 |
+----+-------------+--------------+-------+------------------------------------------------------------------------------------------+--------------------------+---------+--------------------------------------------------+------+---------------------------------------+
|  1 | PRIMARY     | <derived2>   | ALL   | NULL                                                                                     | NULL                     | NULL    | NULL                                             | 1732 | Using temporary; Using filesort       |
|  1 | PRIMARY     | example1     | ref   | date_added_index,name_index,date_added_name_id_index,name_id_index,name_date_added_index | date_added_name_id_index | 158     | maxDateByElement.dateAdded,maxDateByElement.name |    1 | Using where; Using index              |
|  2 | DERIVED     | exampletable | range | date_added_index,date_added_name_id_index                                                | name_date_added_index    | 158     | NULL                                             | 1743 | Using where; Using index for group-by |
+----+-------------+--------------+-------+------------------------------------------------------------------------------------------+--------------------------+---------+--------------------------------------------------+------+---------------------------------------+

Answer 1

There is a great Stack Overflow post on optimization of Selecting rows with the max value in a column: https://stackoverflow.com/a/7745635/633063

This seems a little messy but works very well:

SELECT example1.name, MAX(example1.id)
FROM exampletable example1
INNER JOIN (
select name, max(dateAdded) dateAdded
from exampletable
where dateAdded  <= '2014-01-20 12:00:00' 
group by name
) maxDateByElement on example1.name = maxDateByElement.name AND example1.dateAdded = maxDateByElement.dateAdded
GROUP BY name;