Please consider the following query
SELECT * FROM PC_SMS_OUTBOUND_MESSAGE AS OM
JOIN MM_TEXTOUT_SERVICE AS TOS ON TOS.TEXTOUT_SERVICE_ID = OM.SERVICE_ID
JOIN PC_SERVICE_NUMBER AS SN ON OM.TO_SERVICE_NUMBER_ID = SN.SERVICE_NUMBER_ID
JOIN PC_SUBSCRIBER AS SUB ON SUB.SERVICE_NUMBER_ID = SN.SERVICE_NUMBER_ID
JOIN MM_CONTACT CON ON CON.SUBSCRIBER_ID = SUB.SUBSCRIBER_ID
--AND CON.MM_CLIENT_ID = 1
AND OM.CLIENT_ID= 1
AND OM.CREATED>='2013-05-08 11:47:53' AND OM.CREATED<='2014-05-08 11:47:53'
ORDER BY OM.SMS_OUTBOUND_MESSAGE_ID DESC LIMIT 50
To get the dataset I require I need to filter on the (commented out) CONTACTS client_id as well as the OUTBOUND_MESSAGES client_id but this is what changes the performance from milliseconds to tens of minutes.
Execution plan without "AND CON.MM_CLIENT_ID = 1":
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE OM index FK4E518EAA19F2EA2B,SERVICEID_IDX,CREATED_IDX,CLIENTID_IDX,CL_CR_ST_IDX,CL_CR_STYPE_ST_IDX,SID_TOSN_CL_CREATED_IDX PRIMARY 8 NULL 6741 3732.00 Using where
1 SIMPLE SUB ref PRIMARY,FKA1845E3459A7AEF FKA1845E3459A7AEF 9 mmlive.OM.TO_SERVICE_NUMBER_ID 1 100.00 Using where
1 SIMPLE SN eq_ref PRIMARY PRIMARY 8 mmlive.OM.TO_SERVICE_NUMBER_ID 1 100.00 Using where
1 SIMPLE CON ref FK2BEC061CA525D30,SUB_CL_IDX FK2BEC061CA525D30 8 mmlive.SUB.SUBSCRIBER_ID 1 100.00
1 SIMPLE TOS eq_ref PRIMARY,FKDB3DF298AB3EF4E2 PRIMARY 8 mmlive.OM.SERVICE_ID 1 100.00
Execution plan with "AND CON.MM_CLIENT_ID = 1":
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE CON ref FK2BEC061CA525D30,FK2BEC06134399E2A,SUB_CL_IDX FK2BEC06134399E2A 8 const 18306 100.00 Using temporary; Using filesort
1 SIMPLE SUB eq_ref PRIMARY,FKA1845E3459A7AEF PRIMARY 8 mmlive.CON.SUBSCRIBER_ID 1 100.00
1 SIMPLE OM ref FK4E518EAA19F2EA2B,SERVICEID_IDX,CREATED_IDX,CLIENTID_IDX,CL_CR_ST_IDX,CL_CR_STYPE_ST_IDX,SID_TOSN_CL_CREATED_IDX FK4E518EAA19F2EA2B 9 mmlive.SUB.SERVICE_NUMBER_ID 3 100.00 Using where
1 SIMPLE SN eq_ref PRIMARY PRIMARY 8 mmlive.SUB.SERVICE_NUMBER_ID 1 100.00 Using where
1 SIMPLE TOS eq_ref PRIMARY,FKDB3DF298AB3EF4E2 PRIMARY 8 mmlive.OM.SERVICE_ID 1 100.00
Any suggestions on how to format the above to make it a little easier on the eye would be good.
ID fields are primary keys.
There are indexes on all joining columns.
You may be able to fix this problem by using a subquery:
JOIN (SELECT C.* FROM CONTACTS C WHERE C.USER_ID = 1) ON C.SUBSCRIBER_ID = SUB.ID
This will materialize the matching rows, which could have downstream effects on the query plan.
If this doesn't work, then edit your query and add:
The explain plans for both queries.
The indexes available on the table.
EDIT:
Can you try creating a composite index:
PC_SMS_OUTBOUND_MESSAGE(CLIENT_ID, CREATED, SERVICE_ID, TO_ SERVICE_ID, SMS_OUTBOUND_MESSAGE_ID);
This may change both query plans to start on the OM table with the appropriate filtering, hopefully making the results stable and good.
I've solved the riddle! For my case anyway so I'll share.
This all came down to the join order changing once I added that extra clause, which you can clearly see in the execution plan. When the query is fast, the Outbound Messages are at the top of the plan but when slow (after adding the clause), the Contacts table is at the top.
I think this means that the Outbound Messages index can no longer be utilised for the sorting which causes the dreaded;
"Using temporary; Using filesort"
By simply adding STRAIGHT_JOIN keyword directly after the select I could force the execution plan to join in the order denoted directly by the query.
Happy for anyone with a more intimate knowledge of this field to contradict any of the above in terms of what is actually happening but it definitely worked.
Related
Currently I am facing a rather slow query on a website, which also slows down the server on more traffic. How can I rewrite the query or what index can I write to avoid "Using temporary; Using filesort"? Without "order by" everything works fast, but without the wanted result/order.
SELECT cams.name, models.gender, TIMESTAMPDIFF(YEAR, models.birthdate, CURRENT_DATE) AS age, lcs.viewers
FROM cams
LEFT JOIN cam_tags ON cams.id = cam_tags.cam_id
INNER JOIN tags ON cam_tags.tag_id = tags.id
LEFT JOIN model_cams ON cams.id = model_cams.cam_id
LEFT JOIN models ON model_cams.model_id = models.id
LEFT JOIN latest_cam_stats lcs ON cams.id = lcs.cam_id
WHERE tags.name = '?'
ORDER BY lcs.time_stamp_id DESC, lcs.viewers DESC
LIMIT 24 OFFSET 96;
id
select_type
table
partitions
type
possible_keys
key
key_len
ref
rows
filtered
Extra
1
SIMPLE
tags
NULL
const
PRIMARY,tags_name_uindex
tags_name_uindex
766
const
1
100
Using temporary; Using filesort
1
SIMPLE
cam_tags
NULL
ref
PRIMARY,cam_tags_cams_id_fk,cam_tags_tags_id_fk
cam_tags_tags_id_fk
4
const
75565047
100
Using where
1
SIMPLE
cams
NULL
eq_ref
PRIMARY
PRIMARY
4
cam_tags.cam_id
1
100
NULL
1
SIMPLE
model_cams
NULL
eq_ref
model_platforms_platforms_id_fk
model_platforms_platforms_id_fk
4
cam_tags.cam_id
1
100
NULL
1
SIMPLE
models
NULL
eq_ref
PRIMARY
PRIMARY
4
model_cams.model_id
1
100
NULL
1
SIMPLE
lcs
NULL
eq_ref
PRIMARY,latest_cam_stats_cam_id_time_stamp_id_viewers_index
PRIMARY
4
cam_tags.cam_id
1
100
NULL
There are many cases where it is effectively impossible to avoid "using temporary, using filesort".
"Filesort" does not necessarily involve a "file"; it is often done in RAM. Hence performance may not be noticeably hurt.
That said, I will assume your real question is "How can this query be sped up?".
Most of the tables are accessed via PRIMARY or "eq_ref" -- all good. But the second table involves touching an estimated 75M rows! Often that happens as the first table, not second. Hmmmm.
Sounds like cam_tags is a many-to-many mapping table? And it does not have any index starting with name? See this for proper indexes for such a table: http://mysql.rjweb.org/doc.php/index_cookbook_mysql#many_to_many_mapping_table
Since the WHERE and ORDER BY reference more than one table, it is essentially impossible to avoid "using temporary, using filesort".
Worse than that, it needs to find all the ones with "name='?'", sort the list, skip 96 rows, and only finally deliver 24.
I have a datehelper table with every YYYY-MM-DD as DATE between the years 2000 and 2100. To this I'm joining a subquery for all unit transactions. unit.end is a DATETIME so my subquery simplifies it to DATE and uses that to join to the datehelper table.
In 5.6 this query takes a couple seconds to run a massive amount of transactions, and it derives a table that is auto keyed based on the DATE(unit.end) in the subquery and uses that to join everything else fairly quickly.
In 5.7, it takes 600+ seconds and I can't get it to derive a table or follow the much better execution plan that 5.6 used. Is there a flag I need to set or some way to prefer the old execution plan?
Here's the query:
EXPLAIN SELECT datehelper.id AS date, MONTH(datehelper.id)-1 AS month, DATE_FORMAT(datehelper.id,'%d')-1 AS day,
IFNULL(SUM(a.total),0) AS total, IFNULL(SUM(a.tax),0) AS tax, IFNULL(SUM(a.notax),0) AS notax
FROM datehelper
LEFT JOIN
(SELECT
DATE(unit.end) AS endDate,
getFinalPrice(unit.id) AS total, tax, getFinalPrice(unit.id)-tax AS notax
FROM unit
INNER JOIN products ON products.id=unit.productID
INNER JOIN prodtypes FORCE INDEX(primary) ON prodtypes.id=products.prodtypeID
WHERE franchiseID='1' AND void=0 AND checkout=1
AND end BETWEEN '2020-01-01' AND DATE_ADD('2020-01-01', INTERVAL 1 YEAR)
AND products.prodtypeID NOT IN (1,10)
) AS a ON a.endDate=datehelper.id
WHERE datehelper.id BETWEEN '2020-01-01' AND '2020-12-31'
GROUP BY datehelper.id ORDER BY datehelper.id;
5.6 result (much faster):
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY datehelper range PRIMARY PRIMARY 3 NULL 365 Using where; Using index
1 PRIMARY <derived2> ref <auto_key0> <auto_key0> 4 datehelper.id 10 NULL
2 DERIVED prodtypes index PRIMARY PRIMARY 4 NULL 10 Using where; Using index
2 DERIVED products ref PRIMARY,prodtypeID prodtypeID 4 prodtypes.id
9 Using index
2 DERIVED unit ref productID,end,void,franchiseID productID 9 products.id 2622 Using where
5.7 result (much slower, no auto key found):
id select_type table partitions type possible_keys key key_len ref rows filtered Extra
1 SIMPLE datehelper NULL range PRIMARY PRIMARY 3 NULL 366 100.00 Using where; Using index
1 SIMPLE unit NULL ref productID,end,void,franchiseID franchiseID 4 const 181727 100.00 Using where
1 SIMPLE products NULL eq_ref PRIMARY,prodtypeID PRIMARY 8 barkops3.unit.productID 1 100.00 Using where
1 SIMPLE prodtypes NULL eq_ref PRIMARY PRIMARY 4 barkops3.products.prodtypeID 1 100.00 Using index
I found the problem. It was the optimizer_switch 'derived_merge' flag which is new to 5.7.
https://dev.mysql.com/doc/refman/5.7/en/derived-table-optimization.html
This flag overrides materialization of derived tables if the optimizer thinks the outer WHERE can be pushed down into a subquery. In this case, that optimization was enormously more costly than joining a materialized table on an auto_key.
I need to optimise my query which is running very slow, but don't know how to do it. It contains a subquery which is making it very slow. If I remove the inline query then it runs very well.
The query is:
EXPLAIN
SELECT t.service_date,
t.service_time,
(SELECT js.modified_date FROM rej_job_status js WHERE js.booking_id=b.booking_id ORDER BY id DESC LIMIT 1) `cancel_datetime`,
b.booking_id,
b.ref_booking_id,
b.phone, b.city,
b.booking_time,
CONCAT(rc.firstname," ",rc.lastname) customer_name,
rc.phone_no,
rs.service_id,
rs.service_name,
rct.city_name
FROM rej_job_details t
JOIN rej_booking b ON t.booking_id = b.booking_id
JOIN rej_customer rc ON rc.customer_id = b.customer
JOIN rej_service rs ON t.service_id = rs.service_id
JOIN rej_city rct ON rct.city_id=b.city
WHERE t.act_status = 0 AND DATE(b.booking_time) >= '2016-06-01'
AND DATE(b.booking_time) <= '2016-06-14'
ORDER BY b.booking_time DESC
LIMIT 0 , 50
The explain plan shows this:
id select_type table type possible_keys key key_len ref rows Extra
1 PRIMARY b ALL PRIMARY NULL NULL NULL 32357 Using where; Using filesort
1 PRIMARY rct eq_ref PRIMARY PRIMARY 4 crmdb.b.city 1 NULL
1 PRIMARY t ref booking_id booking_id 4 crmdb.b.booking_id 1 Using where
1 PRIMARY rs eq_ref PRIMARY,service_id PRIMARY 4 crmdb.t.service_id 1 NULL
1 PRIMARY rc eq_ref PRIMARY PRIMARY 4 crmdb.b.customer 1 Using where
2 DEPENDENT SUBQUERY js index NULL PRIMARY 4 NULL 1 Using where
a) How to read this explain plan and know what it means?
b) How can I optimize this query?
booking_time is hiding inside a function, so INDEX(booking_time) cannot be used. That leads to a costly table scan.
AND DATE(b.booking_time) >= '2016-06-01'
AND DATE(b.booking_time) <= '2016-06-14'
-->
AND b.booking_time >= '2016-06-01'
AND b.booking_time < '2016-06-15' -- note 3 differences in this line
Or, this might be simpler (by avoiding second date calculation):
AND b.booking_time >= '2016-06-01'
AND b.booking_time < '2016-06-01' + INTREVAL 2 WEEK
In the EXPLAIN, I expect the 'ALL' to become 'range', and 'Filesort' to vanish.
To understand the full explain-plan, you should read the documentation, but the most important information it includes is the indexes mysql uses, or, usually more revealing, which it doesn't use.
For your DEPENDENT SUBQUERY (that is your "inline query"), it doesn't use a good index, which makes your query slow, so you need to add the index rej_job_status(booking_id) on your table rej_job_status.
Create it, test it and check your explain plan again, it should then list that new index under key for your DEPENDENT SUBQUERY.
Another optimization might be to add an index rej_booking(booking_time) for your table rej_booking. It depends on your data if it improves the query, but you should try it, since right now, mysql doesn't use an index for that selection.
I've always thought that Joins were faster than Subqueries. However for a very simple query in a small dataset the Join is returning in 1.0s whereas the Correlated-Subquery returns in 0.001s. Seems like something is wrong. I note that both queries are using the correct (appallingly named) indexes. Over 1 sec seems excessive for the Join. Any ideas?
Please compare these two queries with their Explain plans:
a) Using a Join
select user.id, user.username,
count(distinct bet_placed.id) as bets_placed,
count(distinct bet_won.id) as bets_won,
count(distinct bets_involved.id) as bets_involved
from user
left join bet as bet_placed on bet_placed.user_placed = user.id
left join bet as bet_won on bet_won.user_won = user.id
left join bet_accepters as bets_involved on bets_involved.user = user.id
group by user.id
Explain plan:
id select_type table type possible_keys key key_len ref rows filtered Extra
1 SIMPLE user index PRIMARY PRIMARY 4 NULL 86 100.00 NULL
1 SIMPLE bet_placed ref fk_bet_user1_idx fk_bet_user1_idx 4 xxx.user.id 6 100.00 "Using index"
1 SIMPLE bet_won ref user_won_idx user_won_idx 5 xxx.user.id 8 100.00 "Using index"
1 SIMPLE bets_involved ref FK_user_idx FK_user_idx 4 xxx.user.id 8 100.00 "Using index"
Average response time: 1.0 secs
b) Using a Correlated-Subquery
select user.id, user.username,
(select COALESCE(count(bet.id), 0) from bet where bet.user_placed = user.id) as bets_placed,
(select COALESCE(count(bet.id), 0) from bet where bet.user_won = user.id) as bets_won,
(select COALESCE(count(bet_accepters.id), 0) from bet_accepters where bet_accepters.user = user.id) as bets_involved
from user;
Explain plan:
id select_type table type possible_keys key key_len ref rows filtered Extra
1 PRIMARY user ALL NULL NULL NULL NULL 86 100.00 NULL
4 "DEPENDENT SUBQUERY" bet_accepters ref FK_user_idx FK_user_idx 4 xxx.user.id 8 100.00 "Using index"
3 "DEPENDENT SUBQUERY" bet ref user_won_idx user_won_idx 5 xxx.user.id 8 100.00 "Using index"
2 "DEPENDENT SUBQUERY" bet ref fk_bet_user1_idx fk_bet_user1_idx 4 xxx.user.id 6 100.00 "Using index"
Average response time: 0.001 secs
Please see
which shows a comparison in speed/rows for different types of query.
It may be that there is little/no difference (either way) on 'smaller' datasets (but may ary on way the db has been set up, as well as the DBMS used), but as you can see,
However, in relation to other 'query types', these are much faster than other operations (shown below):
Subquery vs. Join
Both the subquery and join solutions perform reasonably well when very
small partitions are involved (up to several hundred rows per
partition). As partition size grows, the performance of these
solutions degrades in a quadratic (N2) manner, becoming quite poor.
But as long as the partitions are small, performance degradation
caused by an increase in number of partitions is linear. One factor
that might affect your choice between using a subquery-based or
join-based solution is the number of aggregates requested. As I
discussed, the subquery-based approach requires a separate scan of the
data for each aggregate, whereas the join-based approach doesn’t—so
you’ll most likely want to use the join approach when you need to
calculate multiple aggregates.
~SOURCE
Below query taking one sec to execute. I need to optimize following. I have 10 query in my page, so its takes more than 15 sec. loading the page. I need help to optimize the query.
SELECT p.mhSlug, p.cgSlug, p.CatDescription, p.cSlug, COUNT(DISTINCT(p.RootModelNumber)) AS prodCount
FROM tbl_products AS p
STRAIGHT_JOIN ModelPrice AS mp ON (mp.product_id = p.id AND mp.Available = 1) STRAIGHT_JOIN Brand_Data AS bd ON bd.pkID = p.pkBrand
STRAIGHT_JOIN tbl_store_brands AS sb ON sb.categoryID = p.pkCategory AND sb.brandID = p.pkBrand
LEFT JOIN tbl_filters AS f ON (f.SKU = p.SKU)
WHERE mhSlug = 'plumbing' AND p.cgSlug = 'bathroom-fixtures' AND mp.Available = 1
GROUP BY p.cSlug
ORDER BY p.cSlug
Here EXPLAIN:
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE p ref PRIMARY,pkBrand,cgslug,mhslug,pkCategory,CategoryrBrand,mhcgc,mhcg cgslug 228 const 41164 Using where; Using filesort
1 SIMPLE mp ref product_id,product_idAvail product_id 9 ekidtv_uakc.p.id 1 Using where
1 SIMPLE bd eq_ref PRIMARY,id PRIMARY 4 ekidtv_uakc.p.pkBrand 1 Using index
1 SIMPLE sb ref brandID,categoryID,brandCat,CatBrand brandCat 10 ekidtv_uakc.bd.pkID,ekidtv_uakc.p.pkCategory 1 Using where; Using index
1 SIMPLE f ref SKU,SKUSortField SKU 303 ekidtv_uakc.p.SKU 2 Using index
Please help any body. I have struggle last two days.
Any body able to help me. I did not any improvement.
You need to create or review the indexes on your tables. See indexes documentation for mysql.
I dont see anything wrong on your query.