How to optimize a query using a range with Mysql - mysql

Question

I try to optimize this query :
select id_store from receipt where receiptDate between '20151109' and '20151116'
I execute this query with the command EXPLAIN. It appears that no key is used. The index of receiptDate is not used. What's wrong ?
Here's the structure of the table receipt :
CREATE TABLE receipt (
id_store tinyint(3) unsigned NOT NULL default '0',
id_receipt int(7) unsigned NOT NULL default '0',
id_product smallint(6) unsigned NOT NULL default '0',
receiptDate char(8) NOT NULL default '',
qty float NOT NULL default '0',
turnover float NOT NULL default '0',
PRIMARY KEY (id_store,id_receipt,id_product,receiptDate),
KEY NDX_1 (receiptDate),
) ENGINE=MEMORY;
Here's the result of the command EXPLAIN :
+----+-------------+---------------------+--------+-----------------------------------------------------------+---------------------------------+---------+--------------------------------------+------+---------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------------------+--------+-----------------------------------------------------------+---------------------------------+---------+--------------------------------------+------+---------------------------------+
| 1 | SIMPLE | receipt | ALL |NDX_1 | | | |24789225| Using where |
+----+-------------+---------------------+--------+-----------------------------------------------------------+---------------------------------+---------+--------------------------------------+------+---------------------------------+
The table receipt contains 24.789.225 lines, with a average of 15.000 lines per day (receiptDate).
I execute the following query and I obtain 120.295 lines :
select count(*) from receipt where receiptDate between '20151109' and '20151116'
Thanks in advance for your help.

Answer 1

Since you indexed receiptDate, the database engine will use this index if the optimizer thinks it will improve performance. The optimizer takes its decisions based on statistics about your table. It creates these statistics in background, this is a mostly transparent process.
Now you are using a MEMORY engine. Because memory tables are supposed to be short lived, these special engines have very limited optimizer capabilities. You might want to force the query to use your index with the FORCE INDEX keyword.
Your date is stored as a CHAR(8), this is slow because the engine has to parse all height CHAR. You will obtain improved performance with an INT (convert the date to YYYYMMDD). Your queries should still work since the engine converts strings inputs to int automatically.
If you were going to use the InnoDB engine, then you should put the date as a primary key if possible, because the primary key is also the Clustered Index with this engine, meaning the data will be physically sorted by date on the storage.

Answer 2

Instead of an 8-byte (or 24-byte if utf8) CHAR(8) for receiptDate, use a 3-byte DATE datatype.
While you are at it, you could save another byte by making id_receipt MEDIUMINT UNSIGNED if it is only 7 digits.
Specify BTREE:
KEY `NDX_1` (`receiptDate`) USING BTREE
since MEMORY may be making it a HASH index. BTREE can handle ranges; HASH has to do a table scan.
I agree that InnoDB is likely to be better overall.