I have a query that I use to retrieve table data. The query is very slow when there are more than 3-4 rows returned, and I don't understand why.
This is my query:
select
ig.id,
ig.username,
ig.created,
ig.is_completed,
ig.user_id,
ig.is_error,
ig.last_appeal_process_update,
(unix_timestamp() - ig.created) as time_running,
ig.is_deleted,
ap.id as appealprocessid,
(case
when ap.id is null then 0
when ap.id is not null then ap.status
end
) as current_status,
( select count(*) from appeal_process where ig_account_id = ig.id)
as total_appeals
from instagram_accounts ig
left join appeal_process ap on ig.id = ap.ig_account_id
where
(ig.username like CONCAT('%',?,'%') or ig.id like CONCAT('%',?,'%') or ig.username like CONCAT('%',?,'%')) and
ig.user_id = ? and is_deleted = 0 and
(
ap.id is null or
ap.id = ( -- WE SELECT ONLY THE LATEST APPEAL PROCESS
select max(id) from appeal_process tmp where tmp.ig_account_id = ig.id limit 1
)
)
order by ig.username asc
limit ?,?
EDIT
This is EXPLAIN query (although I have no idea how to read it tbh)
enter image description here
This is SHOW CREATE TABLE for instagram_accounts:
enter image description here
This is SHOW CREATE TABLE for appeal_process:
enter image description here
On instagram_accounts you have critiera specific to user_id, is_deleted but also username. As you are also sorting by username the first fix is to add an index.
CREATE INDEX user_id_deleted_username ON
instagram_accounts(user_id, is_deleted, username);
In appeal_process you are searching by ig_account_id both in the JOIN and tmp subquery:
CREATE INDEX id_account_id ON
appeal_process ( ig_account_id)
On the query, you are pulling the status on the maximum appeal process id for a user. Lets GROUP BY ig.id and that simplifies how to get the results as MAX and others are per group (changes in CAPs for emphasis):
select
ig.id,
ig.username,
ig.created,
ig.is_completed,
ig.user_id,
ig.is_error,
ig.last_appeal_process_update,
(unix_timestamp() - ig.created) as time_running,
ig.is_deleted,
COALESE(MAX(ap.id),0) as appealprocessid,
(SELECT status FROM appeal_process WHERE appeal_process.id = appealprocessid LIMIT 1) as current_status,
COUNT(*) as total_appeals
from instagram_accounts ig
left join appeal_process ap on ig.id = ap.ig_account_id
where
(ig.username like CONCAT('%',?,'%') or ig.id like CONCAT('%',?,'%') or ig.username like CONCAT('%',?,'%')) and
ig.user_id = ? and is_deleted = 0
GROUP BY ig.id
order by ig.username asc
limit ?,?
It is very likely that your problem comes from lack of indexes, it is necessary to index the fields used in the WHERE AND JOIN clauses.
Create an index for each of these fields:
ig_account_id
ig.id
ig.username
is_deleted
ig.user_id
tmp.ig_account_id
Let's assume I have 2 tables. One contains car manufacturer's names and their IDs, the second contains information about car models. I need to select few of them from the first table, but order them by quantity of linked from the second table data.
Currently, my query looks like this:
SELECT DISTINCT `manufacturers`.`name`,
`manufacturers`.`cars_link`,
`manufacturers`.`slug`
FROM `manufacturers`
JOIN `cars`
ON manufacturers.cars_link = cars.manufacturer
WHERE ( NOT ( `manufacturers`.`cars_link` IS NULL ) )
AND ( `cars`.`class` = 'sedan' )
ORDER BY (SELECT Count(*)
FROM `cars`
WHERE `manufacturers`.cars_link = `cars`.manufacturer) DESC
It was working ok for my table of scooters which size is few dozens of mb. But now i need to do the same thing for the cars table, which size is few hundreds megabytes. The problem is that the query takes very long time, sometimes it even causes nginx timeout. Also, i think, that i have all the necesary database indexes. Is there any alternative for the query above?
lets try to use subquery for your count instead.
select * from (
select distinct m.name, m.cars_link, m.slug
from manufacturers m
join cars c on m.cars_link=c.manufacturer
left join
(select count(1) ct, c1.manufacturer from manufacturers m1
inner join cars_link c2 on m1.cars_link=c2.manufacturer
where coalesce(m1.cars_link, '') != '' and c1.class='sedan'
group by c1.manufacturer) as t1
on t1.manufacturer = c.manufacturer
where coalesce(m.cars_link, '') != '' and c.class='sedan') t2
order by t1.ct
my example is on
MYSQL VERSION is
5.6.34-log
Problem summary the below query takes 40 seconds, ORDER_ITEM table
has 758423 records
And PAYMENT table
has 177272 records
And submission_entry table
has 2165698 records
as A Whole Table count.
DETAILS HERE: BELOW:
I Have This Query, Refer to [1]
I Have added SQL_NO_CACHE for testing repeated tests when re
query.
I Have Optimized indexes Refer to [2], but no significant
improvement.
Find Table Structures here [3]
Find explain plan used [4]
[1]
SELECT SQL_NO_CACHE
`payment`.`id` AS id,
`order_item`.`order_id` AS order_id,
GROUP_CONCAT(DISTINCT (CASE WHEN submission_entry.text = '' OR submission_entry.text IS NULL
THEN ' '
ELSE submission_entry.text END) ORDER BY question.var DESC SEPARATOR 0x1D) AS buyer,
event.name AS event,
COUNT(DISTINCT CASE WHEN (`order_item`.status > 0 OR (
`order_item`.status != -1 AND `order_item`.status >= -2 AND `payment`.payment_type_id != 8 AND
payment.make_order_free = 1))
THEN `order_item`.id
ELSE NULL END) AS qty,
payment.currency AS `currency`,
(SELECT SUM(order_item.sub_total)
FROM order_item
WHERE payment_id =
payment.id) AS sub_total,
CASE WHEN payment.make_order_free = 1
THEN ROUND(payment.total + COALESCE(refunds_total, 0), 2)
ELSE ROUND(payment.total, 2) END AS 'total',
`payment_type`.`name` AS payment_type,
payment_status.name AS status,
`payment_status`.`id` AS status_id,
DATE_FORMAT(CONVERT_TZ(order_item.`created`, '+0:00', '-8:00'),
'%Y-%m-%d %H:%i') AS 'created',
`user`.`name` AS 'agent',
event.id AS event_id,
payment.checked,
DATE_FORMAT(CONVERT_TZ(payment.checked_date, '+0:00', '-8:00'),
'%Y-%m-%d %H:%i') AS checked_date,
DATE_FORMAT(CONVERT_TZ(`payment`.`complete_date`, '+0:00', '-8:00'),
'%Y-%m-%d %H:%i') AS `complete date`,
`payment`.`delivery_status` AS `delivered`
FROM `order_item`
INNER JOIN `payment`
ON payment.id = `order_item`.`payment_id` AND (payment.status > 0.0 OR payment.status = -3.0)
LEFT JOIN (SELECT
sum(`payment_refund`.total) AS `refunds_total`,
payment_refunds.payment_id AS `payment_id`
FROM payment
INNER JOIN `payment_refunds` ON payment_refunds.payment_id = payment.id
INNER JOIN `payment` AS `payment_refund`
ON `payment_refund`.id = `payment_refunds`.payment_id_refund
GROUP BY `payment_refunds`.payment_id) AS `refunds` ON `refunds`.payment_id = payment.id
# INNER JOIN event_date_product ON event_date_product.id = order_item.event_date_product_id
# INNER JOIN event_date ON event_date.id = event_date_product.event_date_id
INNER JOIN event ON event.id = order_item.event_id
INNER JOIN payment_status ON payment_status.id = payment.status
INNER JOIN payment_type ON payment_type.id = payment.payment_type_id
LEFT JOIN user ON user.id = payment.completed_by
LEFT JOIN submission_entry ON submission_entry.form_submission_id = `payment`.`form_submission_id`
LEFT JOIN question ON question.id = submission_entry.question_id AND question.var IN ('name', 'email')
WHERE 1 = '1' AND (order_item.status > 0.0 OR order_item.status = -2.0)
GROUP BY `order_item`.`order_id`
HAVING 1 = '1'
ORDER BY `order_item`.`order_id` DESC
LIMIT 10
[2]
CREATE INDEX order_id
ON order_item (order_id);
CREATE INDEX payment_id
ON order_item (payment_id);
CREATE INDEX status
ON order_item (status);
Second Table
CREATE INDEX payment_type_id
ON payment (payment_type_id);
CREATE INDEX status
ON payment (status);
[3]
CREATE TABLE order_item
(
id INT AUTO_INCREMENT
PRIMARY KEY,
order_id INT NOT NULL,
form_submission_id INT NULL,
status DOUBLE DEFAULT '0' NULL,
payment_id INT DEFAULT '0' NULL
);
SECOND TABLE
CREATE TABLE payment
(
id INT AUTO_INCREMENT,
payment_type_id INT NOT NULL,
status DOUBLE NOT NULL,
form_submission_id INT NOT NULL,
PRIMARY KEY (id, payment_type_id)
);
[4] Run the snippet to see the table of EXPLAIN in HTML format
<!DOCTYPE html>
<html>
<head>
<title></title>
</head>
<body>
<table border="1" style="border-collapse:collapse">
<tr><th>id</th><th>select_type</th><th>table</th><th>type</th><th>possible_keys</th><th>key</th><th>key_len</th><th>ref</th><th>rows</th><th>Extra</th></tr>
<tr><td>1</td><td>PRIMARY</td><td>payment_status</td><td>range</td><td>PRIMARY</td><td>PRIMARY</td><td>8</td><td>NULL</td><td>4</td><td>Using where; Using temporary; Using filesort</td></tr>
<tr><td>1</td><td>PRIMARY</td><td>payment</td><td>ref</td><td>PRIMARY,payment_type_id,status</td><td>status</td><td>8</td><td>exp_live_18092017.payment_status.id</td><td>17357</td><td></td></tr>
<tr><td>1</td><td>PRIMARY</td><td>payment_type</td><td>eq_ref</td><td>PRIMARY</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.payment.payment_type_id</td><td>1</td><td></td></tr>
<tr><td>1</td><td>PRIMARY</td><td>user</td><td>eq_ref</td><td>PRIMARY</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.payment.completed_by</td><td>1</td><td></td></tr>
<tr><td>1</td><td>PRIMARY</td><td>submission_entry</td><td>ref</td><td>form_submission_id,idx_submission_entry_1</td><td>form_submission_id</td><td>4</td><td>exp_live_18092017.payment.form_submission_id</td><td>2</td><td></td></tr>
<tr><td>1</td><td>PRIMARY</td><td>question</td><td>eq_ref</td><td>PRIMARY,var</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.submission_entry.question_id</td><td>1</td><td>Using where</td></tr>
<tr><td>1</td><td>PRIMARY</td><td>order_item</td><td>ref</td><td>status,payment_id</td><td>payment_id</td><td>5</td><td>exp_live_18092017.payment.id</td><td>3</td><td>Using where</td></tr>
<tr><td>1</td><td>PRIMARY</td><td>event</td><td>eq_ref</td><td>PRIMARY</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.order_item.event_id</td><td>1</td><td></td></tr>
<tr><td>1</td><td>PRIMARY</td><td><derived3></td><td>ref</td><td>key0</td><td>key0</td><td>5</td><td>exp_live_18092017.payment.id</td><td>10</td><td>Using where</td></tr>
<tr><td>3</td><td>DERIVED</td><td>payment_refunds</td><td>index</td><td>payment_id,payment_id_refund</td><td>payment_id</td><td>4</td><td>NULL</td><td>1110</td><td></td></tr>
<tr><td>3</td><td>DERIVED</td><td>payment</td><td>ref</td><td>PRIMARY</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.payment_refunds.payment_id</td><td>1</td><td>Using index</td></tr>
<tr><td>3</td><td>DERIVED</td><td>payment_refund</td><td>ref</td><td>PRIMARY</td><td>PRIMARY</td><td>4</td><td>exp_live_18092017.payment_refunds.payment_id_refund</td><td>1</td><td></td></tr>
<tr><td>2</td><td>DEPENDENT SUBQUERY</td><td>order_item</td><td>ref</td><td>payment_id</td><td>payment_id</td><td>5</td><td>func</td><td>3</td><td></td></tr></table>
</body>
</html>
Expected Restul
It has to be instead of 40 seconds less than 5
IMPORTANT
Updates
1) Reply to comment 1: there is no foreign key at all on those two tables.
UPDATE-1:
On local the original query takes 40 seconds
if i removed only the following it becomes 25 seconds saves 15 seconds
GROUP_CONCAT(DISTINCT (CASE WHEN submission_entry.text = '' OR submission_entry.text IS NULL
THEN ' '
ELSE submission_entry.text END) ORDER BY question.var DESC SEPARATOR 0x1D) AS buyer
if I removed only its the same time around 40 seconds no save!
COUNT(DISTINCT CASE WHEN (`order_item`.status > 0 OR (
`order_item`.status != -1 AND `order_item`.status >= -2 AND `payment`.payment_type_id != 8 AND
payment.make_order_free = 1))
THEN `order_item`.id
ELSE NULL END) AS qty,
if I removed only it takes around 36 seconds saves 4 seconds
(SELECT SUM(order_item.sub_total)
FROM order_item
WHERE payment_id =
payment.id) AS sub_total,
CASE WHEN payment.make_order_free = 1
THEN ROUND(payment.total + COALESCE(refunds_total, 0), 2)
ELSE ROUND(payment.total, 2) END AS 'total',
Remove HAVING 1=1; the Optimizer may not be smart enough to ignore it. Please provide EXPLAIN SELECT (not in html) to see what the Optimizer is doing.
It seems wrong to have a composite PK in this case: PRIMARY KEY (id, payment_type_id). Please justify it.
Please explain the meaning of status or the need for DOUBLE: status DOUBLE
It will take some effort to figure out why the query is so slow. Let's start by tossing the normalization parts, such as dates and event name and currency. That is whittle down the query to enough to find the desired rows, but not the details on each row. If it is still slow, let's debug that. If it is 'fast', then add back on the other stuff, one by one, to find out what is causing a performance issue.
Is just id the PRIMARY KEY of each table? Or are there more exceptions (like payment)?
It seems 'wrong' to specify a value for question.var, but then use LEFT to imply that it is optional. Please change all LEFT JOINs to INNER JOINs unless I am mistaken on this issue.
Are any of the tables (perhaps submission_entry and event_date_product) "many-to-many" mapping tables? If so, then follow the tips here to get some performance gains.
When you come back please provide SHOW CREATE TABLE for each table.
Guided by the strategies below,
pre-evaluating agregations onto temporary tables
placing payment at the top - since this seems to be the most deterministic
grouping joins - enforcing to the query optimizer the tables relationship
i present a revised version of your query:
-- -----------------------------------------------------------------------------
-- Summarization of order_item
-- -----------------------------------------------------------------------------
drop temporary table if exists _ord_itm_sub_tot;
create temporary table _ord_itm_sub_tot(
primary key (payment_id)
)
SELECT
payment_id,
--
COUNT(
DISTINCT
CASE
WHEN(
`order_item`.status > 0 OR
(
`order_item`.status != -1 AND
`order_item`.status >= -2 AND
`payment`.payment_type_id != 8 AND
payment.make_order_free = 1
)
) THEN `order_item`.id
ELSE NULL
END
) AS qty,
--
SUM(order_item.sub_total) sub_total
FROM
order_item
inner join payment
on payment.id = order_item.payment_id
where order_item.status > 0.0 OR order_item.status = -2.0
group by payment_id;
-- -----------------------------------------------------------------------------
-- Summarization of payment_refunds
-- -----------------------------------------------------------------------------
drop temporary table if exists _pay_ref_tot;
create temporary table _pay_ref_tot(
primary key(payment_id)
)
SELECT
payment_refunds.payment_id AS `payment_id`,
sum(`payment_refund`.total) AS `refunds_total`
FROM
`payment_refunds`
INNER JOIN `payment` AS `payment_refund`
ON `payment_refund`.id = `payment_refunds`.payment_id_refund
GROUP BY `payment_refunds`.payment_id;
-- -----------------------------------------------------------------------------
-- Summarization of submission_entry
-- -----------------------------------------------------------------------------
drop temporary table if exists _sub_ent;
create temporary table _sub_ent(
primary key(form_submission_id)
)
select
submission_entry.form_submission_id,
GROUP_CONCAT(
DISTINCT (
CASE WHEN coalesce(submission_entry.text, '') THEN ' '
ELSE submission_entry.text
END
)
ORDER BY question.var
DESC SEPARATOR 0x1D
) AS buyer
from
submission_entry
LEFT JOIN question
ON(
question.id = submission_entry.question_id
AND question.var IN ('name', 'email')
)
group by submission_entry.form_submission_id;
-- -----------------------------------------------------------------------------
-- The result
-- -----------------------------------------------------------------------------
SELECT SQL_NO_CACHE
`payment`.`id` AS id,
`order_item`.`order_id` AS order_id,
--
_sub_ent.buyer,
--
event.name AS event,
--
_ord_itm_sub_tot.qty,
--
payment.currency AS `currency`,
--
_ord_itm_sub_tot.sub_total,
--
CASE
WHEN payment.make_order_free = 1 THEN ROUND(payment.total + COALESCE(refunds_total, 0), 2)
ELSE ROUND(payment.total, 2)
END AS 'total',
--
`payment_type`.`name` AS payment_type,
`payment_status`.`name` AS status,
`payment_status`.`id` AS status_id,
--
DATE_FORMAT(
CONVERT_TZ(order_item.`created`, '+0:00', '-8:00'),
'%Y-%m-%d %H:%i'
) AS 'created',
--
`user`.`name` AS 'agent',
event.id AS event_id,
payment.checked,
--
DATE_FORMAT(CONVERT_TZ(payment.checked_date, '+0:00', '-8:00'), '%Y-%m-%d %H:%i') AS checked_date,
DATE_FORMAT(CONVERT_TZ(payment.complete_date, '+0:00', '-8:00'), '%Y-%m-%d %H:%i') AS `complete date`,
--
`payment`.`delivery_status` AS `delivered`
FROM
`payment`
INNER JOIN(
`order_item`
INNER JOIN event
ON event.id = order_item.event_id
)
ON `order_item`.`payment_id` = payment.id
--
inner join _ord_itm_sub_tot
on _ord_itm_sub_tot.payment_id = payment.id
--
LEFT JOIN _pay_ref_tot
on _pay_ref_tot.payment_id = `payment`.id
--
INNER JOIN payment_status ON payment_status.id = payment.status
INNER JOIN payment_type ON payment_type.id = payment.payment_type_id
LEFT JOIN user ON user.id = payment.completed_by
--
LEFT JOIN _sub_ent
on _sub_ent.form_submission_id = `payment`.`form_submission_id`
WHERE
1 = 1
AND (payment.status > 0.0 OR payment.status = -3.0)
AND (order_item.status > 0.0 OR order_item.status = -2.0)
ORDER BY `order_item`.`order_id` DESC
LIMIT 10
The query from your question present aggregated functions without explicit groupings... this is pretty awkward and in my solution I try to devise aggregations that 'make sense'.
Please, run this version and tell us your findings.
Be, please, very careful not just on the running statistics, but also on the summarization results.
(The tables and query are too complex for me to do the transformation for you. But here are the steps.)
Reformulate the query without any mention of refunds. That is, remove the derived table and the mention of it in the complex CASE.
Debug and time the resulting query. Keep the GROUP BY order_item ORDER BY order_item DESC LIMIT 10 and do any other optimizations already suggested. In particular, get rid of HAVING 1=1 since it is in the way of a likely optimization.
Make the query from step #2 be a 'derived table'...
Something like:
SELECT lots of stuff
FROM ( query from step 2 ) AS step2
LEFT JOIN ( ... ) AS refunds ON step2... = refunds...
ORDER BY step2.order_item DESC
The ORDER BY is repeated, but neither the GROUP BY, nor the LIMIT need be repeated.
Why? The principle here is...
Currently, it is going into the refunds correlated subquery thousands of times, only to toss it all but 10 times. The reformulation cuts that back to only 10 times.
(Caveat: I may have missed a subtlety preventing this reformulation from working as I presented it. If it does not work, see if you can make the 'principle' help you anyway.)
Here is the minimum you should do each time you see a query with a lot of joins and pagination: you should select those 10 (LIMIT 10) ids that you group by from the first table (order_item) with as minimum joins as possible and then join the ids back to the first table and make all other joins. That way you will not move around in temporary tables all those thousands of columns and rows that you do not need to display.
You look at the inner joins and WHERE conditions, GROUP BYs and ORDER BYs to see whether you need any other tables to filter out rows, group or order ids from the first table. In your case, it doesn't seem you need any joins, except for payment.
Now you write the query to select those ids:
SELECT o.order_id, o.payment_id
FROM order_item o
JOIN payment p
ON p.id = o.payment_id AND (p.status > 0.0 OR p.status = -3.0)
WHERE order_item.status > 0.0 OR order_item.status = -2.0
ORDER BY order_id DESC
LIMIT 10
If there might be several payments for a single order, you should use GROUP BY order_id DESC instead of ORDER BY. To make the query work quicker you need a BTREE index on status column for order_item table, or even a composite index on (status, payment_id).
Now, when you are sure that the ids are those that you expected, you make all other joins:
SELECT order_item.order_id,
`payment`.`id`,
GROUP_CONCAT ... -- and so on from the original query
FROM (
SELECT o.order_id, o.payment_id
FROM order_item o
JOIN payment p
ON p.id = o.payment_id AND (p.status > 0.0 OR p.status = -3.0)
WHERE order_item.status > 0.0 OR order_item.status = -2.0
ORDER BY order_id DESC
LIMIT 10
) as ids
JOIN order_item ON ids.order_id = order_item.order_id
JOIN payment ON ids.payment_id = payment.id
LEFT JOIN ( ... -- and so on
The idea is that you significantly lower the temporary tables you need to process. Now every row selected by the joins will be used in the result set.
UPD1: Another thing is that you should simplify the aggregation in LEFT JOIN:
SELECT
sum(payment.total) AS `refunds_total`,
refs.payment_id AS `payment_id`
FROM payment_refunds refs
JOIN payment ON payment.id = refs.payment_id_refund
GROUP BY refs.payment_id
or even replace the LEFT JOIN with a correlated subquery, since the correlation will be executed only for those 10 rows (make sure, you use this whole query with three columns as the subquery, otherwise, the correlation will be computed for each row in the resulting join before the GROUP BY):
SELECT
ids.order_id,
ids.payment_id,
(SELECT SUM(p.total)
FROM payment_refunds refs
JOIN payment p
ON refs.payment_id_refund = p.id
WHERE refs.payment_id = ids.payment_id
) as refunds_total
FROM (
SELECT o.order_id, o.payment_id
FROM order_item o
JOIN payment p
ON p.id = o.payment_id AND (p.status > 0.0 OR p.status = -3.0)
WHERE order_item.status > 0.0 OR order_item.status = -2.0
ORDER BY order_id DESC
LIMIT 10
) as ids
You will also need to an index (payment_id, payment_id_refund) on payment_refunds and you can even try a covering index (payment_id, total) on payment as well.
I'm hoping someone fluent in MySQL will be able to assist me with this. I'm trying to do a select on a select on a select, but the query doesn't seem to want to complete. Any help would be greatly appreciated.
SELECT
product as pid,
leg_name as name,
dimensions as dims
FROM
pmaint
WHERE
product in (
SELECT product
FROM qb_export_items_attributes
WHERE attribute_name = 'Z'
AND product in (
SELECT product
FROM pmainT
WHERE type_ID = (
SELECT ID
FROM type
WHERE SOFTCARTCATEGORY = 'End Table Legs'
)
)
AND attribute_value <= 3.5
)
Try to use INNER JOINs instead of IN subqueries
UPD: I've edited this query according you comment. the first JOIN subquery output all product where both attributes exists and true.
SELECT
pmaint.product as pid,
pmaint.leg_name as name,
pmaint.dimensions as dims
FROM
pmaint
JOIN (select product from qb_export_items_attributes
where ((attribute_name = 'Z') and (attribute_value <= 3.5))
OR
((attribute_name = 'top_square') and (attribute_value >= 4))
GROUP BY product HAVING COUNT(*)=2
)
t1 on (pmaint.product=t1.product )
JOIN type on (pmaint.type_ID=type.ID)
WHERE
type.SOFTCARTCATEGORY = 'End Table Legs'
I have two tables users and work_orders.
Now I need to get work_orders results by filtering from users table field.
My following query did not return result.
SELECT `work_orders`.`id` as id, `work_orders`.`type` as type
, `work_orders`.`title` as title, `work_orders`.`status` as status
, `work_orders`.`publish_date` as publish_date
, `work_orders`.`priority` as priority, `work_orders`.`assigned_to` as assigned_to
, `work_orders`.`client_id` as client_id, `work_orders`.`due_date` as due_date
FROM (`work_orders`)
LEFT JOIN `users`
ON `users`.`id` = `work_orders`.`assigned_to`
WHERE `work_orders`.`status` != 'closed'
AND users.manager_id = '143'
ORDER BY `work_orders`.`id` DESC
LIMIT 30
Is your WHERE clause filtering out all results?
Also, if you want to display work_orders that only pertain to certain users, change your LEFT JOIN to an INNER JOIN, or use EXISTS.
Try this...
SELECT field1, field2, ...
FROM work_orders
WHERE EXISTS (
SELECT 1
FROM users
WHERE users.id = work_orders.assigned_to
AND manager_id='143'
)