Having some real issues with a few queries, this one inparticular. Info below.
tgmp_games, about 20k rows
CREATE TABLE IF NOT EXISTS `tgmp_games` (
`g_id` int(8) NOT NULL AUTO_INCREMENT,
`site_id` int(6) NOT NULL,
`g_name` varchar(255) NOT NULL,
`g_link` varchar(255) NOT NULL,
`g_url` varchar(255) NOT NULL,
`g_platforms` varchar(128) NOT NULL,
`g_added` datetime NOT NULL,
`g_cover` varchar(255) NOT NULL,
`g_impressions` int(8) NOT NULL,
PRIMARY KEY (`g_id`),
KEY `g_platforms` (`g_platforms`),
KEY `site_id` (`site_id`),
KEY `g_link` (`g_link`),
KEY `g_release` (`g_release`),
KEY `g_genre` (`g_genre`),
KEY `g_name` (`g_name`),
KEY `g_impressions` (`g_impressions`)
) ENGINE=MyISAM DEFAULT CHARSET=latin1;
tgmp_reviews - about 200k rows
CREATE TABLE IF NOT EXISTS `tgmp_reviews` (
`r_id` int(8) NOT NULL AUTO_INCREMENT,
`site_id` int(6) NOT NULL,
`r_source` varchar(128) NOT NULL,
`r_date` date NOT NULL,
`r_score` int(3) NOT NULL,
`r_copy` text NOT NULL,
`r_link` text NOT NULL,
`r_int_link` text NOT NULL,
`r_parent` int(8) NOT NULL,
`r_platform` varchar(12) NOT NULL,
`r_impressions` int(8) NOT NULL,
PRIMARY KEY (`r_id`),
KEY `site_id` (`site_id`),
KEY `r_parent` (`r_parent`),
KEY `r_platform` (`r_platform`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1 ;
Here is the query, takes 3 seconds ish
SELECT * FROM tgmp_games g
RIGHT JOIN tgmp_reviews r ON g_id = r.r_parent
WHERE g.site_id = '34'
GROUP BY g_name
ORDER BY g_impressions DESC LIMIT 15
EXPLAIN
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE r ALL r_parent NULL NULL NULL 201133 Using temporary; Using filesort
1 SIMPLE g eq_ref PRIMARY,site_id PRIMARY 4 engine_comp.r.r_parent 1 Using where
I am just trying to grab the 15 most viewed games, then grab a single review (doesnt really matter which, I guess highest rated would be ideal, r_score) for each game.
Can someone help me figure out why this is so horribly inefficient?
I don't understand what is the purpose of having a GROUP BY g_name in your query, but this makes MySQL performing aggregates on the columns selected, or all columns from both table. So please try to exclude it and check if it helps.
Also, RIGHT JOIN makes database to query tgmp_reviews first, which is not what you want. I suppose LEFT JOIN is a better choice here. Please, try to change the join type.
If none of the first options helps, you need to redesign your query. As you need to obtain 15 most viewed games for the site, the query will be:
SELECT g_id
FROM tgmp_games g
WHERE site_id = 34
ORDER BY g_impressions DESC
LIMIT 15;
This is the very first part that should be executed by the database, as it provides the best selectivity. Then you can get the desired reviews for the games:
SELECT r_parent, max(r_score)
FROM tgmp_reviews r
WHERE r_parent IN (/*1st query*/)
GROUP BY r_parent;
Such construct will force database to execute the first query first (sorry for the tautology) and will give you the maximal score for each of the wanted games. I hope you will be able to use the obtained results for your purpose.
Your MyISAM table is small, you can try converting it to see if that resolves the issue. Do you have a reason for using MyISAM instead of InnoDB for that table?
You can also try running an analyze on each table to update the statistics to see if the optimizer chooses something different.
Related
So basically I created a table:
CREATE TABLE IF NOT EXISTS `student` (
`id` int(4) unsigned NOT NULL AUTO_INCREMENT,
`campus` enum('CAMPUS1', 'CAMPUS2') NOT NULL,
`fullname` char(32) NOT NULL,
`gender` enum('MALE', 'FEMALE') NOT NULL,
`birthday` char(16) NOT NULL,
`phone` char(32) NOT NULL,
`emergency` char(32) NOT NULL,
`address` char(128) NOT NULL,
PRIMARY KEY (`idx`),
KEY `key_student` (`campus`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=1 ;
I have like 20 rows with only 12 in CAMPUS1
But when I use query it: SELECT * FROM student WHERE campus='CAMPUS1'; The EXPLAIN is this:
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE student ALL key_student NULL NULL NULL 20 Using where
I am new to this thing, how does a KEY really works? I read documentation but I cant understand that much.
MySQL is trying to be smart (with varying success) when deciding which index to use for a query.
There are cases where it is faster to query the entire table instead of using the index. E.g: if your table has 500 records for CAMPUS1 and 100 records for CAMPUS2 it is faster to do a full (600 records) scan when looking for campus='CAMPUS1'.
When you have only 20 rows you run into the edge cases of the algorithm. Try adding some more rows, and see what happens.
Also, it seems this index will have a very low cardinality (an even split between only 2 values). It will probably not be very useful.
Someone helped me come up with this query but its still too slow; The order by is slowing it down and I dont think its using my index
I'm hoping someone can fix it for me :D Yes I read the manual page but I can't understand it.
Query:
EXPLAIN SELECT u.id, u.url, u.title, u.numsaves
FROM urls u
JOIN tags t ON t.url_id = u.id
AND t.tag = 'osx'
ORDER BY u.numsaves DESC
LIMIT 20
Showing rows 20 - 19 ( 20 total, Query took 1.5395 sec) [numsaves: 6130 - 2107]
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE t ref tag_id tag_id 767 const 49432 Using where; Using index; Using temporary; Using filesort
1 SIMPLE u eq_ref PRIMARY,id_numsaves_IX PRIMARY 4 jcooper_whatrethebest_urls.t.url_id 1
Database:
CREATE TABLE `urls` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`url` text NOT NULL,
`domain` text,
`title` text NOT NULL,
`description` text,
`numsaves` int(11) NOT NULL,
`firstsaved` varchar(256) DEFAULT NULL,
`md5` varchar(255) NOT NULL DEFAULT '',
PRIMARY KEY (`id`),
UNIQUE KEY `md5` (`md5`),
KEY `id_numsaves_IX` (`id`,`numsaves`)
) ENGINE=InnoDB AUTO_INCREMENT=2958560 DEFAULT CHARSET=utf8
CREATE TABLE `tags` (
`url_id` int(11) DEFAULT NULL,
`hash` varchar(255) NOT NULL,
`tag` varchar(255) NOT NULL,
UNIQUE KEY `tag_id` (`tag`,`url_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
I think the main problem with your query is your choice of indexes.
1) tags has a compound UNIQUE KEY on tag and url_id but no PRIMARY KEY.
If nothing else, you should make it primary - this may help a bit with performance. Also, you might want to take a close look if VARCHAR(255) is really necessary for your tags. It makes the index quite big.
2) add a separate index on numsaves since you're ordering by that. The compound index on id and numsaves is not going to help here.
3) EXPLAIN says that you have 49432 rows in tags that match "osx". This is quite redundant. You may want to split your tags table into two, one containing the text while the other contains the N:M link to urls.
I am trying to generate a group query on a large table (more than 8 million rows). However I can reduce the need to group all the data by date. I have a view that captures that dates I require and this limits the query bu it's not much better.
Finally I need to join to another table to pick up a field.
I am showing the query, the create on the main table and the query explain below.
Main Query:
SELECT pgi_raw_data.wsp_channel,
'IOM' AS wsp,
pgi_raw_data.dated,
pgi_accounts.`master`,
pgi_raw_data.event_id,
pgi_raw_data.breed,
Sum(pgi_raw_data.handle),
Sum(pgi_raw_data.payout),
Sum(pgi_raw_data.rebate),
Sum(pgi_raw_data.profit)
FROM pgi_raw_data
INNER JOIN summary_max
ON pgi_raw_data.wsp_channel = summary_max.wsp_channel
AND pgi_raw_data.dated > summary_max.race_date
INNER JOIN pgi_accounts
ON pgi_raw_data.account = pgi_accounts.account
GROUP BY pgi_raw_data.event_id
ORDER BY NULL
The create table:
CREATE TABLE `pgi_raw_data` (
`event_id` char(25) NOT NULL DEFAULT '',
`wsp_channel` varchar(5) NOT NULL,
`dated` date NOT NULL,
`time` time DEFAULT NULL,
`program` varchar(5) NOT NULL,
`track` varchar(25) NOT NULL,
`raceno` tinyint(2) NOT NULL,
`detail` varchar(30) DEFAULT NULL,
`ticket` varchar(20) NOT NULL DEFAULT '',
`breed` varchar(12) NOT NULL,
`pool` varchar(10) NOT NULL,
`gross` decimal(11,2) NOT NULL,
`refunds` decimal(11,2) NOT NULL,
`handle` decimal(11,2) NOT NULL,
`payout` decimal(11,4) NOT NULL,
`rebate` decimal(11,4) NOT NULL,
`profit` decimal(11,4) NOT NULL,
`account` mediumint(10) NOT NULL,
PRIMARY KEY (`event_id`,`ticket`),
KEY `idx_account` (`account`),
KEY `idx_wspchannel` (`wsp_channel`,`dated`) USING BTREE
) ENGINE=InnoDB DEFAULT CHARSET=latin1
This is my view for summary_max:
CREATE ALGORITHM=UNDEFINED DEFINER=`root`#`localhost` SQL SECURITY DEFINER VIEW
`summary_max` AS select `pgi_summary_tbl`.`wsp_channel` AS
`wsp_channel`,max(`pgi_summary_tbl`.`race_date`) AS `race_date`
from `pgi_summary_tbl` group by `pgi_summary_tbl`.`wsp
And also the evaluated query:
1 PRIMARY <derived2> ALL 6 Using temporary
1 PRIMARY pgi_raw_data ref idx_account,idx_wspchannel idx_wspchannel
7 summary_max.wsp_channel 470690 Using where
1 PRIMARY pgi_accounts ref PRIMARY PRIMARY 3 gf3data_momutech.pgi_raw_data.account 29 Using index
2 DERIVED pgi_summary_tbl ALL 42282 Using temporary; Using filesort
Any help on indexing would help.
At a minimum you need indexes on these fields:
pgi_raw_data.wsp_channel,
pgi_raw_data.dated,
pgi_raw_data.account
pgi_raw_data.event_id,
summary_max.wsp_channel,
summary_max.race_date,
pgi_accounts.account
The general (not always) rule is anything you are sorting, grouping, filtering or joining on should have an index.
Also: pgi_summary_tbl.wsp
Also, why the order by null?
The first thing is to be sure that you have indexes on pgi_summary_table(wsp_channel, race_date) and pgi_accounts(account). For this query, you don't need indexes on these columns in the raw data.
MySQL has a tendency to use indexes even when they are not the most efficient path. I would start by looking at the performance of the "full" query, without the joins:
SELECT pgi_raw_data.wsp_channel,
'IOM' AS wsp,
pgi_raw_data.dated,
-- pgi_accounts.`master`,
pgi_raw_data.event_id,
pgi_raw_data.breed,
Sum(pgi_raw_data.handle),
Sum(pgi_raw_data.payout),
Sum(pgi_raw_data.rebate),
Sum(pgi_raw_data.profit)
FROM pgi_raw_data
GROUP BY pgi_raw_data.event_id
If this has better performance, you may have a situation where the indexes are working against you. The specific problem is called "thrashing". It occurs when a table is too bit to fit into memory. Often, the fastest way to deal with such a table is to just read the whole thing. Accessing the table through an index can result in an extra I/O operation for most of the rows.
If this works, then do the joins after the aggregate. Also, consider getting more memory, so the whole table will fit into memory.
Second, if you have to deal with this type of data, then partitioning the table by date may prove to be a very useful option. This will allow you to significantly reduce the overhead of reading the large table. You do have to be sure that the summary table can be read the same way.
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My situation:
the query searches around 90,000 vehicles
the query takes long each time
I already have indexes on all the fields being JOINed.
How can I optimise it?
Here is the query:
SELECT vehicles.make_id,
vehicles.fuel_id,
vehicles.body_id,
vehicles.transmission_id,
vehicles.colour_id,
vehicles.mileage,
vehicles.vehicle_year,
vehicles.engine_size,
vehicles.trade_or_private,
vehicles.doors,
vehicles.model_id,
Round(3959 * Acos(Cos(Radians(51.465436)) *
Cos(Radians(vehicles.gps_lat)) *
Cos(
Radians(vehicles.gps_lon) - Radians(
-0.296482)) +
Sin(
Radians(51.465436)) * Sin(
Radians(vehicles.gps_lat)))) AS distance
FROM vehicles
INNER JOIN vehicles_makes
ON vehicles.make_id = vehicles_makes.id
LEFT JOIN vehicles_models
ON vehicles.model_id = vehicles_models.id
LEFT JOIN vehicles_fuel
ON vehicles.fuel_id = vehicles_fuel.id
LEFT JOIN vehicles_transmissions
ON vehicles.transmission_id = vehicles_transmissions.id
LEFT JOIN vehicles_axles
ON vehicles.axle_id = vehicles_axles.id
LEFT JOIN vehicles_sub_years
ON vehicles.sub_year_id = vehicles_sub_years.id
INNER JOIN members
ON vehicles.member_id = members.id
LEFT JOIN vehicles_categories
ON vehicles.category_id = vehicles_categories.id
WHERE vehicles.status = 1
AND vehicles.date_from < 1330349235
AND vehicles.date_to > 1330349235
AND vehicles.type_id = 1
AND ( vehicles.price >= 0
AND vehicles.price <= 1000000 )
Here is the vehicle table schema:
CREATE TABLE IF NOT EXISTS `vehicles` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`number_plate` varchar(100) NOT NULL,
`type_id` int(11) NOT NULL,
`make_id` int(11) NOT NULL,
`model_id` int(11) NOT NULL,
`model_sub_type` varchar(250) NOT NULL,
`engine_size` decimal(12,1) NOT NULL,
`vehicle_year` int(11) NOT NULL,
`sub_year_id` int(11) NOT NULL,
`mileage` int(11) NOT NULL,
`fuel_id` int(11) NOT NULL,
`transmission_id` int(11) NOT NULL,
`price` decimal(12,2) NOT NULL,
`trade_or_private` tinyint(4) NOT NULL,
`postcode` varchar(25) NOT NULL,
`gps_lat` varchar(50) NOT NULL,
`gps_lon` varchar(50) NOT NULL,
`img1` varchar(100) NOT NULL,
`img2` varchar(100) NOT NULL,
`img3` varchar(100) NOT NULL,
`img4` varchar(100) NOT NULL,
`img5` varchar(100) NOT NULL,
`img6` varchar(100) NOT NULL,
`img7` varchar(100) NOT NULL,
`img8` varchar(100) NOT NULL,
`img9` varchar(100) NOT NULL,
`img10` varchar(100) NOT NULL,
`is_featured` tinyint(4) NOT NULL,
`body_id` int(11) NOT NULL,
`colour_id` int(11) NOT NULL,
`doors` tinyint(4) NOT NULL,
`axle_id` int(11) NOT NULL,
`category_id` int(11) NOT NULL,
`contents` text NOT NULL,
`date_created` int(11) NOT NULL,
`date_edited` int(11) NOT NULL,
`date_from` int(11) NOT NULL,
`date_to` int(11) NOT NULL,
`member_id` int(11) NOT NULL,
`inactive_id` int(11) NOT NULL,
`status` tinyint(4) NOT NULL,
PRIMARY KEY (`id`),
KEY `type_id` (`type_id`),
KEY `make_id` (`make_id`),
KEY `model_id` (`model_id`),
KEY `fuel_id` (`fuel_id`),
KEY `transmission_id` (`transmission_id`),
KEY `body_id` (`body_id`),
KEY `colour_id` (`colour_id`),
KEY `axle_id` (`axle_id`),
KEY `category_id` (`category_id`),
KEY `vehicle_year` (`vehicle_year`),
KEY `mileage` (`mileage`),
KEY `status` (`status`),
KEY `date_from` (`date_from`),
KEY `date_to` (`date_to`),
KEY `trade_or_private` (`trade_or_private`),
KEY `doors` (`doors`),
KEY `price` (`price`),
KEY `engine_size` (`engine_size`),
KEY `sub_year_id` (`sub_year_id`),
KEY `member_id` (`member_id`),
KEY `date_created` (`date_created`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 AUTO_INCREMENT=136237 ;
The EXPLAIN:
1 SIMPLE vehicles ref type_id,make_id,status,date_from,date_to,price,mem... type_id 4 const 85695 Using where
1 SIMPLE members index PRIMARY PRIMARY 4 NULL 3 Using where; Using index; Using join buffer
1 SIMPLE vehicles_makes eq_ref PRIMARY PRIMARY 4 tvs.vehicles.make_id 1 Using index
1 SIMPLE vehicles_models eq_ref PRIMARY PRIMARY 4 tvs.vehicles.model_id 1 Using index
1 SIMPLE vehicles_fuel eq_ref PRIMARY PRIMARY 4 tvs.vehicles.fuel_id 1 Using index
1 SIMPLE vehicles_transmissions eq_ref PRIMARY PRIMARY 4 tvs.vehicles.transmission_id 1 Using index
1 SIMPLE vehicles_axles eq_ref PRIMARY PRIMARY 4 tvs.vehicles.axle_id 1 Using index
1 SIMPLE vehicles_sub_years eq_ref PRIMARY PRIMARY 4 tvs.vehicles.sub_year_id 1 Using index
1 SIMPLE vehicles_categories eq_ref PRIMARY PRIMARY 4 tvs.vehicles.category_id 1 Using index
Improving the WHERE clause
Your EXPLAIN shows that MySQL is only utilizing one index (type_id) for selecting the rows that match the WHERE clause, even though you have multiple criteria in the clause.
To be able to utilize an index for all of the criteria in the WHERE clause, and to reduce the size of the result set as quickly as possible, add a multi-column index on the following columns on the vehicles table:
(status, date_from, date_to, type_id, price)
The columns should be in order of highest cardinality to least.
For example, vehicles.date_from is likely to have more distinct values than status, so put the date_from column before status, like this:
(date_from, date_to, price, type_id, status)
This should reduce the rows returned in the first part of the query execution, and should be demonstrated with a lower row count on the first line of the EXPLAIN result.
You will also notice that MySQL will use the multi-column index for the WHERE in the EXPLAIN result. If, by chance, it doesn't, you should hint or force the multi-column index.
Removing the unnecessary JOINs
It doesn't appear that you are using any fields in any of the joined tables, so remove the joins. This will remove all of the additional work of the query, and get you down to one, simple execution plan (one line in the EXPLAIN result).
Each JOINed table causes an additional lookup per row of the result set. So, if the WHERE clause selects 5,000 rows from vehicles, since you have 8 joins to vehicles, you will have 5,000 * 8 = 40,000 lookups. That's a lot to ask from your database server.
Instead of expensive calculation of precise distance for all of the rows use a bounding box and calculate the exact distance only for rows inside the box.
The simplest possible example is to calculate min/max longitude and latitude that interests you and add it to WHERE clause. This way the distance will be calculated only for a subset of rows.
WHERE
vehicles.gps_lat > min_lat ANDd vehicles.gps_lat < max_lat AND
vehicles.gps_lon > min_lon AND vehicles.gps_lon < max_lon
For more complex solutions see:
MySQL spatial extensions
How to use MySQL spatial extensions
https://stackoverflow.com/a/5237509/342473
Is you SQL faster without this?
Round(3959 * Acos(Cos(Radians(51.465436)) *
Cos(Radians(vehicles.gps_lat)) *
Cos(Radians(vehicles.gps_lon) -
Radians(-0.296482)) +
Sin(Radians(51.465436)) *
Sin(Radians(vehicles.gps_lat)))) AS distance
performing math equation is very expensive
Maybe you should consider a materialized view that pre-calculate you distance, and you can select from that view. Depending on how dynamic you data is, you may not have to refresh you data too often.
To be a little more specific than #Randy of indexes, I believe his intention was to have a COMPOUND index to take advantage of your querying critieria... One index that is built on a MINIMUM of ...
( status, type_id, date_from )
but could be extended to include the date_to and price too, but don't know how much the index at that granular level might actually help
( status, type_id, date_from, date_to, price )
EDIT per Comments
You shouldn't need all those individual indexes... Yes, the Primary Key by itself. However, for the others, you should have compound indexes based on what your common querying criteria might be and remove the others... the engine might get confused on which might be best suited for the query. If you know you are always looking for a certain status, type and date (assuming vehicle searches), make that as one index. If the query is looking for such information, but also prices within that criteria it will already be very close on the few indexed records that qualify and fly through the price as just an extra criteria.
If you offer querying like Only Automatic vs Manual transmission regardless of year/make, then yes, that could be an index of its own. However, if you would TYPICALLY have some other "common" criteria, tack that on as a secondary that MAY be utilized in the query. Ex: if you look for Manual Transmissions that are 2-door vs 4-door, have your index on (transmission_id, category_id).
Again, you want whatever will help narrow down the field of criteria based on some "minimum" condition. If you tack on an extra column to the index that might "commonly" be applied, that should only help the performance.
To clarify this as an answer: if you do not already have these indexes, you should consider adding them
do you also have indexes on these:
vehicles.status
vehicles.date_from
vehicles.date_to
vehicles.type_id
vehicles.price
This query:
explain
SELECT `Lineitem`.`id`, `Donation`.`id`, `Donation`.`order_line_id`
FROM `order_line` AS `Lineitem`
LEFT JOIN `donations` AS `Donation`
ON (`Donation`.`order_line_id` = `Lineitem`.`id`)
WHERE `Lineitem`.`session_id` = '1'
correctly uses the Donation.order_line_id and Lineitem.id indexes, shown in this EXPLAIN output:
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE Lineitem ref session_id session_id 97 const 1 Using where; Using index
1 SIMPLE Donation ref order_line_id order_line_id 4 Lineitem.id 2 Using index
However, this query, which simply includes another field:
explain
SELECT `Lineitem`.`id`, `Donation`.`id`, `Donation`.`npo_id`,
`Donation`.`order_line_id`
FROM `order_line` AS `Lineitem`
LEFT JOIN `donations` AS `Donation`
ON (`Donation`.`order_line_id` = `Lineitem`.`id`)
WHERE `Lineitem`.`session_id` = '1'
Shows that the Donation table does not use an index:
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE Lineitem ref session_id session_id 97 const 1 Using where; Using index
1 SIMPLE Donation ALL order_line_id NULL NULL NULL 3
All of the _id fields in the tables are indexed, but I can't figure out how adding this field into the list of selected fields causes the index to be dropped.
As requested by James C, here are the table definitions:
CREATE TABLE `donations` (
`id` int(10) unsigned NOT NULL auto_increment,
`npo_id` int(10) unsigned NOT NULL,
`order_line_detail_id` int(10) unsigned NOT NULL default '0',
`order_line_id` int(10) unsigned NOT NULL default '0',
`created` datetime default NULL,
`modified` datetime default NULL,
PRIMARY KEY (`id`),
KEY `npo_id` (`npo_id`),
KEY `order_line_id` (`order_line_id`),
KEY `order_line_detail_id` (`order_line_detail_id`)
) ENGINE=InnoDB AUTO_INCREMENT=7 DEFAULT CHARSET=utf8
CREATE TABLE `order_line` (
`id` bigint(20) unsigned NOT NULL auto_increment,
`order_id` bigint(20) NOT NULL,
`npo_id` bigint(20) NOT NULL default '0',
`session_id` varchar(32) collate utf8_unicode_ci default NULL,
`created` datetime default NULL,
PRIMARY KEY (`id`),
KEY `order_id` (`order_id`),
KEY `npo_id` (`npo_id`),
KEY `session_id` (`session_id`)
) ENGINE=InnoDB AUTO_INCREMENT=23 DEFAULT CHARSET=utf8
I also did some reading about cardinality, and it looks like both the Donations.npo_id and Donations.order_line_id have a cardinality of 2. Hopefully this suggests something useful?
I'm thinking that a USE INDEX might solve the problem, but I'm using an ORM that makes this a bit tricky, and I don't understand why it wouldn't grab the correct index when the JOIN specifically names indexed fields?!?
Thanks for your brainpower!
The first explain has "uses index" at the end. This means that it was able to find the rows and return the result for the query by just looking at the index and not having to fetch/analyse any row data.
In the second query you add a row that's likely not indexed. This means that MySQL has to look at the data of the table. I'm not sure why the optimiser chose to do a table scan but I think it's likely that if the table is fairly small it's easier for it to just read everything than trying to pick out details for individual rows.
edit: I think adding the following indexes will improve things even more and let all of the join use indexes only:
ALTER TABLE order_line ADD INDEX(session_id, id);
ALTER TABLE donations ADD INDEX(order_line_id, npo_id, id)
This will allow order_line to to find the rows using session_id and then return id and also allow donations to join onto order_line_id and then return the other two columns.
Looking at the auto_increment values can I assume that there's not much data in there. It's worth noting that the amount of data in the tables will have an effect on the query plan and it's good practice to put some sample data in there to test things out. For more detail have a look in this blog post I made some time back: http://webmonkeyuk.wordpress.com/2010/09/27/what-makes-a-good-mysql-index-part-2-cardinality/