I have a mysql query to join four tables and I thought that it was just best to join tables but now that mysql data is getting bigger the query seems to cause the application to stop execution.
SELECT
`purchase_order`.`id`,
`purchase_order`.`po_date` AS po_date,
`purchase_order`.`po_number`,
`purchase_order`.`customer_id` AS customer_id ,
`customer`.`name` AS customer_name,
`purchase_order`.`status` AS po_status,
`purchase_order_items`.`product_id`,
`purchase_order_items`.`po_item_name`,
`product`.`weight` as product_weight,
`product`.`pending` as product_pending,
`product`.`company_owner` as company_owner,
`purchase_order_items`.`uom`,
`purchase_order_items`.`po_item_type`,
`purchase_order_items`.`order_sequence`,
`purchase_order_items`.`pending_balance`,
`purchase_order_items`.`quantity`,
`purchase_order_items`.`notes`,
`purchase_order_items`.`status` AS po_item_status,
`purchase_order_items`.`id` AS po_item_id
FROM `purchase_order`
INNER JOIN customer ON `customer`.`id` = `purchase_order`.`customer_id`
INNER JOIN purchase_order_items ON `purchase_order_items`.`po_id` = `purchase_order`.`id`
INNER JOIN product ON `purchase_order_items`.`product_id` = `product`.`id`
GROUP BY id ORDER BY `purchase_order`.`po_date` DESC LIMIT 0, 20
my problem really is the query that takes a lot of time to finish. Is there a way to speed this query or to change this query for faster retrieval of the data?
heres the EXPLAIN EXTENED as requested in the comments.
Thanks in advance, I really hope this is the right channel for me to ask. If not please let me know.
Will this give you the correct list of ids?
SELECT id
FROM purchase_order
ORDER BY`po_date` DESC
LIMIT 0, 20
If so, then start with that before launching into the JOIN. You can also (I think) get rid of the GROUP BY that is causing an "explode-implode" of rows.
SELECT ...
FROM ( SELECT id ... (as above) ...) AS ids
JOIN purchase_order po ON po.id = ids.id
JOIN ... (the other tables)
GROUP BY ... -- (this may be problematic, especially with the LIMIT)
ORDER BY po.po_date DESC -- yes, this needs repeating
-- no LIMIT
Something like this
SELECT
`purchase_order`.`id`,
`purchase_order`.`po_date` AS po_date,
`purchase_order`.`po_number`,
`purchase_order`.`customer_id` AS customer_id ,
`customer`.`name` AS customer_name,
`purchase_order`.`status` AS po_status,
`purchase_order_items`.`product_id`,
`purchase_order_items`.`po_item_name`,
`product`.`weight` as product_weight,
`product`.`pending` as product_pending,
`product`.`company_owner` as company_owner,
`purchase_order_items`.`uom`,
`purchase_order_items`.`po_item_type`,
`purchase_order_items`.`order_sequence`,
`purchase_order_items`.`pending_balance`,
`purchase_order_items`.`quantity`,
`purchase_order_items`.`notes`,
`purchase_order_items`.`status` AS po_item_status,
`purchase_order_items`.`id` AS po_item_id
FROM (SELECT id, po_date, po_number, customer_id, status
FROM purchase_order
ORDER BY `po_date` DESC
LIMIT 0, 5) as purchase_order
INNER JOIN customer ON `customer`.`id` = `purchase_order`.`customer_id`
INNER JOIN purchase_order_items
ON `purchase_order_items`.`po_id` = `purchase_order`.`id`
INNER JOIN product ON `purchase_order_items`.`product_id` = `product`.`id`
GROUP BY purchase_order.id DESC
LIMIT 0, 5
You need to be sure that purchase_order.po_date and all id column are indexed. You can check it with below query.
SHOW INDEX FROM yourtable;
Since you mentioned that data is getting bigger. I would suggest doing sharding and then you can parallelize multiple queries. Please refer to the following article
Parallel Query for MySQL with Shard-Query
First, I cleaned up readability a bit. You don't need tick marks around every table.column reference. Also, for short-hand, using aliases works well. Ex: "po" instead of "purchase_order", "poi" instead of "purchase_order_items". The only time I would use tick marks is around reserved words that might cause a problem.
Second, you don't have any aggregations (sum, min, max, count, avg, etc.) in your query so you should be able to strip the GROUP BY clause.
As for indexes, I would have to assume you have an index on your reference tables on their respective "id" key columns.
For your Purchase Order table, I would have an index on that based on the "po_date" in the first index field position in case you already had an index using it. Since your Order by is on that, let the engine jump directly to those dated records first and you have your descending order resolved.
SELECT
po.id,
po.po_date,
po.po_number,
po.customer_id,
c.`name` AS customer_name,
po.`status` AS po_status,
poi.product_id,
poi.po_item_name,
p.weight as product_weight,
p.pending as product_pending,
p.company_owner,
poi.uom,
poi.po_item_type,
poi.order_sequence,
poi.pending_balance,
poi.quantity,
poi.notes,
poi.`status` AS po_item_status,
poi.id AS po_item_id
FROM
purchase_order po
INNER JOIN customer c
ON po.customer_id = c.id
INNER JOIN purchase_order_items poi
ON po.id = poi.po_id
INNER JOIN product p
ON poi.product_id = p.id
ORDER BY
po.po_date DESC
LIMIT
0, 20
Related
Please check my query and suggest me indexing value and how can I decide which columns will be in indexes. Query is very slow when where clause exist otherwise query is just fine. Offset value is also slow down query.
SELECT
attachment.attachment_id AS attachmentID,
attachment.data_item_id AS candidateID,
attachment.title AS title,
candidate.first_name AS firstName,
candidate.last_name AS lastName,
candidate.city AS city,
candidate.state AS state
FROM
attachment
LEFT JOIN candidate
ON attachment.data_item_id = candidate.candidate_id
where candidate.is_active = 1
ORDER BY
lastName ASC
LIMIT 92000, 20
Your query is basically:
SELECT . . .
FROM attachment a JOIN
candidate c
ON a.data_item_id = c.candidate_id
WHERE c.is_active = 1
ORDER BY c.last_name ASC
LIMIT 92000, 20;
Note that the WHERE clause turns the LEFT JOIN into an INNER JOIN anyway, so there is no reason to use LEFT JOIN.
I would recommend the following indexes:
candidate(is_active, candidate_id, last_name)
attachment(data_item_id)
You could expand the indexes to include all columns being selected.
Note that offsetting 92,000 rows takes a bit of effort so the query will never be lightning fast.
I have a query that joins four table but I can't understand why its taking about a minute. I know the date between is more than 3 years. I don't really know what to do and how to optimize this query for better performance. Can someone give me suggestion on what to do? Will attached the query and the explain of the query.
SELECT
`purchase_order`.`id`,
`customer`.`name` AS customer_name,
`purchase_order`.`po_date`,
`purchase_order`.`po_number`,
`purchase_order`.`customer_id` AS customer_id ,
`customer`.`name` AS customer_name,
`purchase_order`.`status` AS po_status,
`purchase_order_items`.`product_id`,
`purchase_order_items`.`po_item_name`,
`product`.`weight` as product_weight,
`product`.`pending` as product_pending,
`product`.`company_owner` as company_owner,
`purchase_order_items`.`uom`,
`purchase_order_items`.`po_item_type`,
`purchase_order_items`.`order_sequence`,
`purchase_order_items`.`pending_balance`,
`purchase_order_items`.`quantity`,
`purchase_order_items`.`notes`,
`purchase_order_items`.`status` AS po_item_status,
`purchase_order_items`.`id` AS po_item_id
FROM purchase_order
INNER JOIN customer ON `customer`.`id` = `purchase_order`.`customer_id`
INNER JOIN purchase_order_items ON `purchase_order_items`.`po_id` = `purchase_order`.`id`
INNER JOIN product ON `purchase_order_items`.`product_id` = `product`.`id` WHERE
`purchase_order_items`.`product_id` = '121' AND
`purchase_order`.`po_date`
BETWEEN '2016-01-01' AND '2019-02-28' AND
`purchase_order_items`.`status` IN('Pending','Incomplete')
ORDER BY `purchase_order`.`po_date` DESC LIMIT 0, 20
Im also not sure what to do about the explain and Im still trying to understand why its like this and how can i optimize the query. I hope someone could help me on this.
It looks like your query is good. Rewritten using alias names for tables for shorter yet still readable "po" vs "purchase_order", "poi" vs "purchase_order_items"
Your purchase_order table should have an index at a minimum on date THEN id. So your WHERE clause can optimize based on the date, but also have the po.id as a basis to JOIN to your purchase order items table by id.
Next, the purchase order items, would help with an index on ( po_id, product_id, status ) to help optimize that join criteria.
Purchase_Order index (po_date, id )
Purchase_Order_Items index ( po_id, product_id, status )
SELECT
po.id,
c.name AS customer_name,
po.po_date,
po.po_number,
po.customer_id AS customer_id ,
c.name AS customer_name,
po.status AS po_status,
poi.product_id,
poi.po_item_name,
p.weight as product_weight,
p.pending as product_pending,
p.company_owner as company_owner,
poi.uom,
poi.po_item_type,
poi.order_sequence,
poi.pending_balance,
poi.quantity,
poi.notes,
poi.status AS po_item_status,
poi.id AS po_item_id
FROM
purchase_order po
INNER JOIN customer c
ON po.customer_id = c.id
INNER JOIN purchase_order_items poi
ON po.id = poi.po_id
AND poi.product_id = '121'
AND poi.status IN ('Pending','Incomplete')
INNER JOIN product p
ON poi.product_id = p.id
WHERE
po.po_date BETWEEN '2016-01-01' AND '2019-02-28'
ORDER BY
po.po_date DESC
LIMIT
0, 20
If that doesn't help, Your order of tables appears ok but the engine might be trying to think too much for you. You can try adding additional keyword "STRAIGHT_JOIN" (specific to mysql).
select STRAIGHT_JOIN ( ... rest of query )
This tells mySQL to run the query in the table order I gave you.
I have a performance issue with the query below on MYSQL. The below query has 5 tables involved. When I apply the order by and limit, the results are retrieved in 0.3 secs. But without the order by and limit, I was able to get the results in 0.01 secs. I am tired changing the query but that did not work. Could someone please help me with this query so I can get the results in desired time (<0.3 secs).
Below are the details.
m_todos = 286579 (records)
m_pat = 214858 (records)
users = 119 (records)
m_programs = 26 (records)
role = 4 (records)
SELECT *
FROM (
SELECT t.*,
mp.name as A_name,
u.first_name, u.last_name,
p.first, p.last, p.zone, p.language,p.handling,
r.name,
u2.first_name AS created_first_name,
u2.last_name AS created_last_name
FROM m_todos t
INNER JOIN role r ON t.role_id=r.id
INNER JOIN m_pat p ON t.patient_id = p.id
LEFT JOIN users u2 ON t.created_id=u2.id
LEFT JOIN m_programs mp ON t.prog_id=mp.id
LEFT JOIN users u ON t.user_id=u.id
WHERE t.role_id !='9'
AND t.completed = '0000-00-00 00:00:00'
) C
ORDER BY priority DESC, due ASC
LIMIT 0,10
Get rid of the outer SELECT; move the ORDER BY and LIMIT in.
Indexes:
t: (completed)
t: (priority, due)
I assume priority and due are in t?? Please be explicit in the query. It could make a huge difference.
If the following works, it should speed things up a lot: Start by finding the t.id without all the JOINs:
SELECT id
FROM m_todos
WHERE role_id !='9'
AND completed = '0000-00-00 00:00:00'
ORDER BY priority DESC, due DESC
LIMIT 10
That will benefit from this covering composite index:
INDEX(completed, role_id, priority, due, id)
Debug that. Then use it in the rest:
SELECT t.*, the-other-stuff
FROM ( that-query ) AS t1
JOIN m_todos AS t USING(id)
then-the-rest-of-the-JOINs
ORDER BY priority DESC, due ASC -- yes, again
If you don't need all of t.*, it may be beneficial to spell out the actual columns needed.
The reason for this to run much faster is that the 10 rows are found efficiently by looking only at the one table. The original code was shoveling around a lot more rows than 10 and they included all the columns of t, plus columns from the other tables.
My version does only 10 lookups for all the extra stuff.
I have a mysql query and it works fine when i use where clause, but when i donot use
where clause it gone and never gives the output and finally timeout.
Actually i have used Explain command to check the performance of the query and in both cases the Explain gives the same number of rows used in joining.
I have attached the image of output got with Explain command.
Below is the query.
I couldn't figure whats the problem here.
Any help is highly appreciated.
Thanks.
SELECT
MCI.CLIENT_ID AS CLIENT_ID, MCI.NAME AS CLIENT_NAME, MCI.PRIMARY_CONTACT AS CLIENT_PRIMARY_CONTACT,
MCI.ADDED_BY AS SP_ID, CONCAT(MUD_SP.FIRST_NAME, ' ', MUD_SP.LAST_NAME) AS SP_NAME,
MCI.FK_PROSPECT_ID AS PROSPECT_ID, MCI.DATE_ADDED AS ADDED_ON,
(SELECT GROUP_CONCAT(LT.TAG_TEXT SEPARATOR ', ')
FROM LK_TAG LT
INNER JOIN M_OBJECT_TAG_MAPPING MOTM
ON LT.PK_ID = MOTM.FK_TAG_ID
WHERE MOTM.FK_OBJECT_ID = MCI.FK_PROSPECT_ID
AND MOTM.OBJECT_TYPE = 1
AND MOTM.IS_ACTIVE = 1
) AS TAGS,
IFNULL(SUM(GET_DIGITS(MMR.RCP_AMOUNT)), 0) AS REVENUE_SO_FAR,
IFNULL(SUM(GET_DIGITS(MMR.RCP_RUPEES)), 0) AS REVENUE_INR,
COUNT(DISTINCT PMI_MONTHLY.PROJECT_ID) AS MONTHLY,
COUNT(DISTINCT PMI_FIXED.PROJECT_ID) AS FIXED,
COUNT(DISTINCT PMI_HOURLY.PROJECT_ID) AS HOURLY,
COUNT(DISTINCT PMI_ANNUAL.PROJECT_ID) AS ANNUAL,
COUNT(DISTINCT PMI_CURRENTLY_RUNNING.PROJECT_ID) AS CURRENTLY_RUNNING_PROJECTS,
COUNT(DISTINCT PMI_YET_TO_START.PROJECT_ID) AS YET_TO_START_PROJECTS,
COUNT(DISTINCT PMI_TECH_SALES_CLOSED.PROJECT_ID) AS TECH_SALES_CLOSED_PROJECTS
FROM
M_CLIENT_INFO MCI
INNER JOIN M_USER_DETAILS MUD_SP
ON MCI.ADDED_BY = MUD_SP.PK_ID
LEFT OUTER JOIN M_MONTH_RECEIPT MMR
ON MMR.CLIENT_ID = MCI.CLIENT_ID
LEFT OUTER JOIN M_PROJECT_INFO PMI_FIXED
ON PMI_FIXED.CLIENT_ID = MCI.CLIENT_ID AND PMI_FIXED.PROJECT_TYPE = 1
LEFT OUTER JOIN M_PROJECT_INFO PMI_MONTHLY
ON PMI_MONTHLY.CLIENT_ID = MCI.CLIENT_ID AND PMI_MONTHLY.PROJECT_TYPE = 2
LEFT OUTER JOIN M_PROJECT_INFO PMI_HOURLY
ON PMI_HOURLY.CLIENT_ID = MCI.CLIENT_ID AND PMI_HOURLY.PROJECT_TYPE = 3
LEFT OUTER JOIN M_PROJECT_INFO PMI_ANNUAL
ON PMI_ANNUAL.CLIENT_ID = MCI.CLIENT_ID AND PMI_ANNUAL.PROJECT_TYPE = 4
LEFT OUTER JOIN M_PROJECT_INFO PMI_CURRENTLY_RUNNING
ON PMI_CURRENTLY_RUNNING.CLIENT_ID = MCI.CLIENT_ID AND PMI_CURRENTLY_RUNNING.STATUS = 4
LEFT OUTER JOIN M_PROJECT_INFO PMI_YET_TO_START
ON PMI_YET_TO_START.CLIENT_ID = MCI.CLIENT_ID AND PMI_YET_TO_START.STATUS < 4
LEFT OUTER JOIN M_PROJECT_INFO PMI_TECH_SALES_CLOSED
ON PMI_TECH_SALES_CLOSED.CLIENT_ID = MCI.CLIENT_ID AND PMI_TECH_SALES_CLOSED.STATUS > 4
WHERE YEAR(MCI.DATE_ADDED) = '2012'
GROUP BY MCI.CLIENT_ID ORDER BY CLIENT_NAME ASC
Yes, as many people have said, the key is that when you have the where clause, mysql engine filters the table M_CLIENT_INFO --probably drammatically--.
A similar result as removing the where clause is to to add this where clause:
where 1 = 1
You will see that the performance is degraded also because mysql will try to get all the data.
Remove the where clause and all columns from select and add a count to see how many records you get. If it is reasonable, say up to 10k, then do the following,
put back the select columns related to M_CLIENT_INFO
do not include the nested one "TAGS"
remove all your joins
run your query without where clause and gradually include the joins
this way you'll find out when the timeout is caused.
I would try the following. First, MySQL has a keyword "STRAIGHT_JOIN" which tells the optimizer to do the query in the table order you've specified. Since all you left-joins are child-related (like a lookup table), you don't want MySQL to try and interpret one of those as a primary basis of the query.
SELECT STRAIGHT_JOIN ... rest of query.
Next, your M_PROJECT_INFO table, I dont know how many columns of data are out there, but you appear to be concentrating on just a few columns on your DISTINCT aggregates. I would make sure you have a covering index on these elements to help the query via an index on
( Client_ID, Project_Type, Status, Project_ID )
This way the engine can apply the criteria and get the distinct all out of the index instead of having to go back to the raw data pages for the query.
Third, your M_CLIENT_INFO table. Ensure that has an index on both your criteria, group by AND your Order By, and change your order by from the aliased "CLIENT_NAME" to the actual column of the SQL table so it matches the index
( Date_Added, Client_ID, Name )
I have "name" in ticks as it is also a reserved word and helps clarify the column, not the keyword.
Next, the WHERE clause. Whenever you apply a function to an indexed column name, it doesn't work the greatest, especially on date/time fields... You might want to change your where clause to
WHERE MCI.Date_Added between '2012-01-01' and '2012-12-31 23:59:59'
so the BETWEEN range is showing the entire year and the index can better be utilized.
Finally, if the above do not help, I would consider splitting your query some. The GROUP_CONCACT inline select for the TAGS might be a bit of a killer for you. You might want to have all the distinct elements first for the grouping per client, THEN get those details.... Something like
select
PQ.*,
group_concat(...) tags
from
( the entire primary part of the query ) as PQ
Left join yourGroupConcatTableBasis on key columns
im trying to generate a report using CodeIgniter and Datatables.net .
Now i'm trying to the amount of closed jobs (its a human resources system). I used to query all jobs and in PHP do a foreach and then doing the calcs.
Because im want to use all the features of Datatables (sorting specifically) im trying to do all the calcs in mySQL.
The problem is: the second subquery is very very very slow.
SELECT
jobs.jobs_id, clients.nome_fantasia, concat_ws(' ', user_profiles.first_name, user_profiles.last_name) as fullname,
jobs.titulo_vaga, jobs.qtd_vagas, company.name as nome_company, jobs_status.name as status_name, DATEDIFF(NOW(), jobs.data_abertura) as date_idade,
(select count(job_cv.jobs_id) from job_cv where job_cv.jobs_id = jobs.jobs_id) as qtd_int,
(select count(distinct job_cv.user_id) from job_cv_history join job_cv on job_cv.job_cv_id = job_cv_history.job_cv_id where job_cv_history.status = '11' and job_cv.jobs_id = jobs.jobs_id ) as fechadas
FROM (jobs)
JOIN clients ON lients.clients_id=jobs.clients_idJOIN user_profiles ON jobs.consultor_id=user_profiles.user_id
JOIN jobs_status ON jobs.status=jobs_status.jobs_status_id
JOIN company ON jobs.company_id=company.company_id
LIMIT 50
Some one can help me? I can provide more information if its needed.
UPDATE
The idea to use JOIN instead SELECT work with the first subquery but with the second one not, there a way to pass a 'variable' to use inside the subquery? Like the current jobs_id?
UPDATE AGAIN
This line works fine by itself. But inside the subquery take about a minute with worng values
SELECT job_cv.jobs_id,count(distinct job_cv.user_id) AS fechadas
FROM job_cv_history
JOIN job_cv
ON job_cv.job_cv_id = job_cv_history.job_cv_id
WHERE job_cv_history.status = '11'
GROUP BY job_cv.jobs_id
It is not subquery that is slow. It's the fact, that you're executing these subqueries for each row returned from outer query. Move these to joins instead, and you should observe increase in performance.
SELECT
jobs.jobs_id, clients.nome_fantasia, concat_ws(' ', user_profiles.first_name, user_profiles.last_name) as fullname,
jobs.titulo_vaga, jobs.qtd_vagas, company.name as nome_company, jobs_status.name as status_name, DATEDIFF(NOW(), jobs.data_abertura) as date_idade,
qtd.qtd_int,
fechadas.fechadas
FROM (jobs)
JOIN clients ON lients.clients_id=jobs.clients_idJOIN user_profiles ON jobs.consultor_id=user_profiles.user_id
JOIN jobs_status ON jobs.status=jobs_status.jobs_status_id
JOIN company ON jobs.company_id=company.company_id
JOIN (
SELECT jobs_id, count(jobs_id) AS qtd_int FROM job_cv GROUP BY jobs_id
) AS qtd ON qtd.jobs_id = jobs.jobs_id
JOIN (
SELECT job_cv.user_id, count(distinct job_cv.user_id) AS fechadas
FROM job_cv_history
JOIN job_cv
ON job_cv.job_cv_id = job_cv_history.job_cv_id
WHERE job_cv_history.status = '11'
GROUP BY job_cv.user_id
) AS fechadas ON job_cv.jobs_id = jobs.jobs_id
LIMIT 50
You may try to create these indexes:
ALTER TABLE `job_cv` ADD INDEX `job_cv_cindex` (`job_cv_id` ASC, `jobs_id` ASC, `user_id` ASC);
ALTER TABLE `job_cv_history` ADD INDEX `job_cv_history_cindex` (`job_cv_id` ASC, `status` ASC);
use Joins instead of sub queries. It significantly improves the performance in MySql.
try to use Left join on your case and see if performance improves or not