SELECT COUNT(*) expensive query mysql? I have following query:

    SELECT COUNT(*) AS `numrows`
    FROM (`phppos_items`)
    WHERE `deleted` =  0


explain:

mysql&gt; explain SELECT COUNT(*) AS `numrows`
    -&gt; FROM (`phppos_items`)
    -&gt; WHERE `deleted` =  0;
+----+-------------+--------------+------+---------------+---------+---------+-------+------+-------------+
| id | select_type | table        | type | possible_keys | key     | key_len | ref   | rows | Extra       |
+----+-------------+--------------+------+---------------+---------+---------+-------+------+-------------+
|  1 | SIMPLE      | phppos_items | ref  | deleted       | deleted | 4       | const |    1 | Using index |
+----+-------------+--------------+------+---------------+---------+---------+-------+------+-------------+


Will this query always be indexed AND fast as the rows in the table grow?
"Will this query always be indexed AND fast as the rows in the table grow?"

Definitely not necessarily. If there are many records and/or the value of deleted is skewed in some way (i.e. it's (nearly) always one particular value, or split 50-50), then the optimiser may decide to ignore a given index. Googling "why does mysql not use an index" gives 3.5M results 

[EDIT]

You said:

"Thank you for your answer. Is there a different type of query I can use to count the number of rows with a WHERE clause?"

No -  that's what COUNT() is for. See here. Basically, you can't get round problems like the one you outline - indexes are frequently helpful, but there's no "magic bullet" that will cope well with all data volumes and profiles. 

To see how difficult this problem is, check here - that's > 600 pages on the fundamentals of how an RDBMS decides on the best plan for a query. It is far from a trivial problem!