I guess this depends on the storage-engine. I can tell for MyISAM, a select without any order will return rows sequentially as they occur in file (even if held in memory).
As you ordered data during write, it will be ordered by id within MyISAM-temptables. So you can safely assume it will always return correct results as long as you don't delete from myISAM-temp.
But the new question is - is temptable created in myIsam-format? I assume the default storage engine will be used. This used to be MyISAM, but was changed to InnoDB after MySQL 5.1.
I don't know how innodb would handle an unsorted select.
-- edit
http://dev.mysql.com/doc/refman/5.1/en/internal-temporary-tables.html
In big (on disk) temporary tables myISAM is used. It is not intentional behavior rows are served sequentially in order as written into, but it is by design (as documented) reliable as long as myISAM table is appended only.
This is most probably not true for any "hashed table" like InnoDB, BDB, and eventually MEMORY. But when memory table is converted to "on disk table", current order is "frozen on the disk", and therefore reliable again.
But I guess we have an other kind of problem here:
The 'real' problem seems to be your "order by" feels too slow, and you would like to get around that. Do you by chance know your table size and sessions max_heap_table_size? This give you a hint if your table has been converted to myisam. You can also play with Index-Hash-method (BTREE, HASH) to look for optimization.
Are you aware that LIMIT N,M will get painfully slow because it has to select N rows, discard them, and then select M rows to return?
I was thinking the NATURAL JOIN
example you just used
SELECT * FROM my_table NATURAL JOIN (
SELECT group_col, MAX(sort_col) sort_col
FROM my_table
GROUP BY group_col
) t
If you shift to another type of JOIN
and impose WHERE
, ordering can come and go without warning in spite of the ill-advised reliance on undocumented behavior of the GROUP BY
.
For this example, I will
- use Windows 7
- use MySQL 5.5.12-log for Windows
- create some sample data
- impose a
LEFT JOIN
without a WHERE
clause
- impose a
LEFT JOIN
with a WHERE clause
For the DB Environment
mysql> select version();
+------------+
| version() |
+------------+
| 5.5.12-log |
+------------+
1 row in set (0.00 sec)
mysql> show variables like '%version_co%';
+-------------------------+------------------------------+
| Variable_name | Value |
+-------------------------+------------------------------+
| version_comment | MySQL Community Server (GPL) |
| version_compile_machine | x86 |
| version_compile_os | Win64 |
+-------------------------+------------------------------+
3 rows in set (0.00 sec)
mysql>
Using this script to generate sample data
DROP DATABASE IF EXISTS eggyal;
CREATE DATABASE eggyal;
USE eggyal
CREATE TABLE groupby
(
id int not null auto_increment,
num int,
primary key (id)
);
INSERT INTO groupby (num) VALUES
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp()));
INSERT INTO groupby (num) SELECT num FROM groupby;
SELECT * FROM groupby;
and these two queries for testing the GROUP BY
subsequent use;
SELECT * FROM groupby A LEFT JOIN
(
SELECT num, MAX(id) id
FROM groupby
GROUP BY num
) B USING (id);
SELECT * FROM groupby A LEFT JOIN
(
SELECT num, MAX(id) id
FROM groupby
GROUP BY num
) B USING (id) WHERE B.num IS NOT NULL;
Let's test the durability of the GROUP BY
's results;
STEP 01 : Create the Sample Data
mysql> DROP DATABASE IF EXISTS eggyal;
Query OK, 1 row affected (0.09 sec)
mysql> CREATE DATABASE eggyal;
Query OK, 1 row affected (0.00 sec)
mysql> USE eggyal
Database changed
mysql> CREATE TABLE groupby
-> (
-> id int not null auto_increment,
-> num int,
-> primary key (id)
-> );
Query OK, 0 rows affected (0.07 sec)
mysql> INSERT INTO groupby (num) VALUES
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp()));
Query OK, 8 rows affected (0.06 sec)
Records: 8 Duplicates: 0 Warnings: 0
mysql> INSERT INTO groupby (num) SELECT num FROM groupby;
Query OK, 8 rows affected (0.05 sec)
Records: 8 Duplicates: 0 Warnings: 0
mysql> SELECT * FROM groupby;
+----+------------+
| id | num |
+----+------------+
| 1 | 269529129 |
| 2 | 387090406 |
| 3 | 1126864683 |
| 4 | 411160755 |
| 5 | 29173595 |
| 6 | 266349579 |
| 7 | 1244227156 |
| 8 | 6231766 |
| 9 | 269529129 |
| 10 | 387090406 |
| 11 | 1126864683 |
| 12 | 411160755 |
| 13 | 29173595 |
| 14 | 266349579 |
| 15 | 1244227156 |
| 16 | 6231766 |
+----+------------+
16 rows in set (0.00 sec)
STEP 02 : Use LEFT JOIN
without a WHERE
clause
mysql> SELECT * FROM groupby A LEFT JOIN
-> (
-> SELECT num, MAX(id) id
-> FROM groupby
-> GROUP BY num
-> ) B USING (id);
+----+------------+------------+
| id | num | num |
+----+------------+------------+
| 1 | 269529129 | NULL |
| 2 | 387090406 | NULL |
| 3 | 1126864683 | NULL |
| 4 | 411160755 | NULL |
| 5 | 29173595 | NULL |
| 6 | 266349579 | NULL |
| 7 | 1244227156 | NULL |
| 8 | 6231766 | NULL |
| 9 | 269529129 | 269529129 |
| 10 | 387090406 | 387090406 |
| 11 | 1126864683 | 1126864683 |
| 12 | 411160755 | 411160755 |
| 13 | 29173595 | 29173595 |
| 14 | 266349579 | 266349579 |
| 15 | 1244227156 | 1244227156 |
| 16 | 6231766 | 6231766 |
+----+------------+------------+
16 rows in set (0.00 sec)
mysql>
STEP 03 : Use LEFT JOIN
with a WHERE
clause
mysql> SELECT * FROM groupby A LEFT JOIN
-> (
-> SELECT num, MAX(id) id
-> FROM groupby
-> GROUP BY num
-> ) B USING (id) WHERE B.num IS NOT NULL;
+----+------------+------------+
| id | num | num |
+----+------------+------------+
| 16 | 6231766 | 6231766 |
| 13 | 29173595 | 29173595 |
| 14 | 266349579 | 266349579 |
| 9 | 269529129 | 269529129 |
| 10 | 387090406 | 387090406 |
| 12 | 411160755 | 411160755 |
| 11 | 1126864683 | 1126864683 |
| 15 | 1244227156 | 1244227156 |
+----+------------+------------+
8 rows in set (0.00 sec)
mysql>
ANALYSIS
Looking at the aforementioned results, here are two questions:
- Why does a
LEFT JOIN
keep an ordering by id
?
- Why in the world did using a
WHERE
impose a reordering ?
- Was it during the JOIN phase ?
- Did the Query Optimizer look ahead at the ordering of the subquery or ignore it ?
No one foresaw any of these effects because the behavior of explicit clauses was relied upon by the implicit behavior of the Query Optimizer.
CONCLUSION
From my perspective, corner cases can only be of an external nature. In light of this, developers must be willing to fully evaluate the results of a GROUP BY
in conjunction with the following twelve(12) aspects:
- aggregate functions
- subquery usage
JOINs
clauses
WHERE
clauses
- sort order of results with no explicit
ORDER BY
clause
- query results using older GA releases of MySQL
- query results using newer beta releases of MySQL
- the current SQL_MODE setting in
my.cnf
- the operating system the code was compiled for
- possibly the size of join_buffer_size with respect to its effect on the Query Optimizer
- possibly the size of sort_buffer_size with respect to its effect on the Query Optimizer
- possibly the storage engine being used (MyISAM vs InnoDB)
Here is the key thing to remember : Any instance of MySQL that works for your query in a specific environment is itself a corner case. Once you change one or more of the twelve(12) evaluation aspects, the corner case is due to break, especially given the first nine(9) aspects.
Best Answer
INNER
,OUTER
, andCROSS
are ignored by MySQL. TheON
andWHERE
control which type ofJOIN
it is.In your examples you have nothing tying the tables together, hence operates like a
CROSS JOIN
.GROUP BY
, etc have no impact.