For example I have created 3 index:
click_date - transaction table, daily_metric tableorder_date - transaction tableI want to check does my query use index, I use EXPLAIN function and get this result:
+----+--------------+--------------+-------+---------------+------------+---------+------+--------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+--------------+--------------+-------+---------------+------------+---------+------+--------+----------------------------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 668 | Using temporary; Using filesort |
| 2 | DERIVED | <derived3> | ALL | NULL | NULL | NULL | NULL | 645 | |
| 2 | DERIVED | <derived4> | ALL | NULL | NULL | NULL | NULL | 495 | |
| 4 | DERIVED | transaction | ALL | order_date | NULL | NULL | NULL | 291257 | Using where; Using temporary; Using filesort |
| 3 | DERIVED | daily_metric | range | click_date | click_date | 3 | NULL | 812188 | Using where; Using temporary; Using filesort |
| 5 | UNION | <derived7> | ALL | NULL | NULL | NULL | NULL | 495 | |
| 5 | UNION | <derived6> | ALL | NULL | NULL | NULL | NULL | 645 | Using where; Not exists |
| 7 | DERIVED | transaction | ALL | order_date | NULL | NULL | NULL | 291257 | Using where; Using temporary; Using filesort |
| 6 | DERIVED | daily_metric | range | click_date | click_date | 3 | NULL | 812188 | Using where; Using temporary; Using filesort |
| NULL | UNION RESULT | <union2,5> | ALL | NULL | NULL | NULL | NULL | NULL | |
+----+--------------+--------------+-------+---------------+------------+---------+------+--------+----------------------------------------------+
In EXPLAIN results I see, that index order_date of transaction table is not used, do I correct understand ?
Index click_date of daily_metric table was used correct ?
Please tell my how to understand from EXPLAIN result does my created index is used in query properly ?
My query:
SELECT
partner_id,
the_date,
SUM(clicks) as clicks,
SUM(total_count) as total_count,
SUM(count) as count,
SUM(total_sum) as total_sum,
SUM(received_sum) as received_sum,
SUM(partner_fee) as partner_fee
FROM (
SELECT
clicks.partner_id,
clicks.click_date as the_date,
clicks,
orders.total_count,
orders.count,
orders.total_sum,
orders.received_sum,
orders.partner_fee
FROM
(SELECT
partner_id, click_date, sum(clicks) as clicks
FROM
daily_metric WHERE DATE(click_date) BETWEEN '2013-04-01' AND '2013-04-30'
GROUP BY partner_id , click_date) as clicks
LEFT JOIN
(SELECT
partner_id,
DATE(order_date) as order_dates,
SUM(order_sum) as total_sum,
SUM(customer_paid_sum) as received_sum,
SUM(partner_fee) as partner_fee,
count(*) as total_count,
count(CASE
WHEN status = 1 THEN 1
ELSE NULL
END) as count
FROM
transaction WHERE DATE(order_date) BETWEEN '2013-04-01' AND '2013-04-30'
GROUP BY DATE(order_date) , partner_id) as orders ON orders.partner_id = clicks.partner_id AND clicks.click_date = orders.order_dates
UNION ALL SELECT
orders.partner_id,
orders.order_dates as the_date,
clicks,
orders.total_count,
orders.count,
orders.total_sum,
orders.received_sum,
orders.partner_fee
FROM
(SELECT
partner_id, click_date, sum(clicks) as clicks
FROM
daily_metric WHERE DATE(click_date) BETWEEN '2013-04-01' AND '2013-04-30'
GROUP BY partner_id , click_date) as clicks
RIGHT JOIN
(SELECT
partner_id,
DATE(order_date) as order_dates,
SUM(order_sum) as total_sum,
SUM(customer_paid_sum) as received_sum,
SUM(partner_fee) as partner_fee,
count(*) as total_count,
count(CASE
WHEN status = 1 THEN 1
ELSE NULL
END) as count
FROM
transaction WHERE DATE(order_date) BETWEEN '2013-04-01' AND '2013-04-30'
GROUP BY DATE(order_date) , partner_id) as orders ON orders.partner_id = clicks.partner_id AND clicks.click_date = orders.order_dates
WHERE
clicks.partner_id is NULL
ORDER BY the_date DESC
) as t
GROUP BY the_date ORDER BY the_date DESC LIMIT 50 OFFSET 0
Although I can't explain what the EXPLAIN has dumped, I thought there must be an easier solution to what you have and came up with the following. I would suggest the following indexes to optimize your existing query for the WHERE date range and grouping by partner.
Additionally, when you have a query that uses a FUNCTION on a field, it doesn't take advantage of the index. Such as your DATE(order_date) and DATE(click_date). To allow the index to better be used, qualify the full date/time such as 12:00am (morning) up to 11:59pm. I would typically to this via
x >= someDate @12:00 and x < firstDayAfterRange.
in your example would be (notice less than May 1st which gets up to April 30th at 11:59:59pm)
click_date >= '2013-04-01' AND click_date < '2013-05-01'
Table Index
transaction (order_date, partner_id)
daily_metric (click_date, partner_id)
Now, an adjustment. Since your clicks table may have entries the transactions dont, and vice-versa, I would adjust this query to do a pre-query of all possible date/partners, then left-join to respective aggregate queries such as:
SELECT
AllParnters.Partner_ID,
AllParnters.the_Date,
coalesce( clicks.clicks, 0 ) Clicks,
coalesce( orders.total_count, 0 ) TotalCount,
coalesce( orders.count, 0 ) OrderCount,
coalesce( orders.total_sum, 0 ) OrderSum,
coalesce( orders.received_sum, 0 ) ReceivedSum,
coalesce( orders.partner_fee 0 ) PartnerFee
from
( select distinct
dm.partner_id,
DATE( dm.click_date ) as the_Date
FROM
daily_metric dm
WHERE
dm.click_date >= '2013-04-01' AND dm.click_date < '2013-05-01'
UNION
select
t.partner_id,
DATE(t.order_date) as the_Date
FROM
transaction t
WHERE
t.order_date >= '2013-04-01' AND t.order_date < '2013-05-01' ) AllParnters
LEFT JOIN
( SELECT
dm.partner_id,
DATE( dm.click_date ) sumDate,
sum( dm.clicks) as clicks
FROM
daily_metric dm
WHERE
dm.click_date >= '2013-04-01' AND dm.click_date < '2013-05-01'
GROUP BY
dm.partner_id,
DATE( dm.click_date ) ) as clicks
ON AllPartners.partner_id = clicks.partner_id
AND AllPartners.the_date = clicks.sumDate
LEFT JOIN
( SELECT
t.partner_id,
DATE(t.order_date) as sumDate,
SUM(t.order_sum) as total_sum,
SUM(t.customer_paid_sum) as received_sum,
SUM(t.partner_fee) as partner_fee,
count(*) as total_count,
count(CASE WHEN t.status = 1 THEN 1 ELSE NULL END) as COUNT
FROM
transaction t
WHERE
t.order_date >= '2013-04-01' AND t.order_date < '2013-05-01'
GROUP BY
t.partner_id,
DATE(t.order_date) ) as orders
ON AllPartners.partner_id = orders.partner_id
AND AllPartners.the_date = orders.sumDate
order by
AllPartners.the_date DESC
limit 50 offset 0
This way, the first query will be quick on the index to get all possible combinations from EITHER table. Then the left-join will AT MOST join to one row per set. If found, get the number, if not, I am applying COALESCE() so if null, defaults to zero.
CLARIFICATION.
Like you when building your pre-aggregate queries of "clicks" and "orders", the "AllPartners" is the ALIAS result of the select distinct of partners and dates within the date range you were interested in. The resulting columns of that where were "partner_id" and "the_date" respective to your next queries. So this is the basis of joining to the aggregates of "clicks" and "orders". So, since I have these two columns in the alias "AllParnters", I just grabbed those for the field list since they are LEFT-JOINed to the other aliases and may not exist in either/or the respective others.