Say I need to pull data from several tables like so:
item 1 - from table 1
item 2 - from table 1
item 3 - from table 1 - but select only max value of item 3 from table 1
item 4 - from table 2 - but select only max value of item 4 from table 2
My query is pretty simple:
select
a.item 1,
a.item 2,
b.item 3,
c.item 4
from table 1 a
left join (select b.key_item, max(item 3) from table 1, group by key_item) b on a.key_item = b.key_item
left join (select c.key_item, max(item 4) from table 2, group by key_item) c on c.key_item = a.key_item
I am not sure if my methodology of pulling just a single max item from a table is the most efficient. Assume both tables are over a million rows. my actual sql run forever using this sql setup.
EDIT: I changed the group by clause to reflect comments made. I hope it makes a bit of sense now?
Your best bet is to add an index on table1
and table2
, as follows:
ALTER TABLE table1
ADD INDEX `GoodIndexName1` (`key_item`,`item3`)
ALTER TABLE table2
ADD INDEX `GoodIndexName2` (`key_item`,`item4`)
This will allow you to use queries as described in the MySQL documentation for finding the rows holding the group-wise maximum, which appears to be what you are looking for.
Your original (edited) query should work:
select
a.item1,
a.item2,
b.item3,
c.item4
from table1 a
LEFT OUTER JOIN (
SELECT
b.key_item,
MAX(item3) AS item3
FROM table1
GROUP BY key_item
) b
ON a.key_item = b.key_item
LEFT OUTER JOIN (
SELECT
c.key_item,
MAX(item4)
FROM table2
GROUP BY key_item
) c
ON c.key_item = a.key_item
and if that performs slowly after adding the indexes, try the following too:
SELECT
a.item1,
a.item2,
b.item3,
c.item4
FROM table1 a
LEFT OUTER JOIN table1 b
ON b.key_item = a.key_item
LEFT OUTER JOIN table1 larger_b
ON larger_b.key_item = b.key_item
AND larger_b.item3 > b.item_3
LEFT OUTER JOIN table2 c
ON c.key_item = a.key_item
LEFT OUTER JOIN table2 larger_c
ON larger_c.key_item = c.key_item
AND larger_c.item4 > c.item4
WHERE larger_b.key_item IS NULL
AND larger_c.key_item IS NULL
(I have modified the table and column names only slightly, so that they conform to correct MySQL syntax. )
I work with queries that use the above structure all the time, and they perform very efficiently with indexes like the one I provided.
That said, usually I am using INNER JOINs on the b
and c
tables, but I don't see why your query should have any issues.
If you do experience performance problems still, report the data types of the key_item
columns for each table, as if you try to join on different data types, you will generally get poor performance.