MySQL structure help for joins ( large tables) - mysql

I currently have 2 tables that are used for a select query with a simple join. The first table houses around 6-9 million rows, and this gets used as the join. The primary table is anywhere from 1mil to 300mil rows. However, I notice when I join above 10mil rows on the primary table the select query goes from instant to very slow (3+ seconds and grows).
Here is my table structure and queries.
CREATE TABLE IF NOT EXISTS `links` (
`link_id` int(10) unsigned NOT NULL,
`domain_id` mediumint(7) unsigned NOT NULL,
`parent_id` int(11) unsigned DEFAULT NULL,
`hash` int(10) unsigned NOT NULL,
`url` text NOT NULL,
`type` enum('html','pdf') DEFAULT NULL,
`processed` enum('N','Y') NOT NULL DEFAULT 'N',
UNIQUE KEY `hash` (`hash`),
KEY `idx_processed` (`processed`),
KEY `domain_id` (`domain_id`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 ROW_FORMAT=COMPACT;
CREATE TABLE IF NOT EXISTS `domains` (
`domain_id` mediumint(7) unsigned NOT NULL AUTO_INCREMENT,
`name` varchar(170) NOT NULL,
`blocked` enum('N','Y') NOT NULL DEFAULT 'N',
`count` mediumint(6) NOT NULL DEFAULT '0',
`mcount` mediumint(3) NOT NULL,
PRIMARY KEY (`domain_id`),
KEY `name` (`name`),
KEY `blocked` (`blocked`),
KEY `mcount` (`mcount`),
KEY `count` (`count`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 AUTO_INCREMENT=10834389 ;
Query:
(SELECT link_id, url, hash FROM links, domains WHERE links.domain_id = domains.domain_id and mcount > 1 and processed='N' limit 200)
UNION
(SELECT link_id, url, hash FROM links where processed='N' and type='html' limit 200)
Explain select:
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+--------------+------------+-------+-------------------------+--------------- +---------+---------------------------+---------+-------------+
| 1 | PRIMARY | domains | range | PRIMARY,mcount | mcount | 3 | NULL | 257673 | Using where |
| 1 | PRIMARY | links | ref | idx_processed,domain_id | domain_id | 3 | crawler.domains.domain_id | 1 | Using where |
| 2 | UNION | links | ref | idx_processed | idx_processed | 1 | const | 7090017 | Using where |
| NULL | UNION RESULT | <union1,2> | ALL | NULL | NULL | NULL | NULL | NULL | |
+----+--------------+------------+-------+-------------------------+---------------+---------+---------------------------+---------+-------------+
Right now, I'm trying a partition with 20 partitions on links using domain_id as the key.
Any other options would be greatly appreciated.

A single SELECT statement would replace your entire UNION statement:
SELECT link_id, url, hash
FROM links, domains
WHERE links.domain_id = domains.domain_id
AND mcount > 1
AND processed='N'
AND type='html'
This may not be THE answer you are looking for, but it should help you simplify your question.

When things suddenly slow down you might want to check the size of your indexes (used in the query execution) vs size of various mysql buffers.

Related

mysql group by joined column too slow

I have two tables events and event_params
the first table stores the events with these columns
events | CREATE TABLE `events` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`project` varchar(24) NOT NULL,
`event` varchar(24) NOT NULL,
`date` int(10) unsigned NOT NULL,
PRIMARY KEY (`id`),
KEY `project` (`project`,`event`)
) ENGINE=InnoDB AUTO_INCREMENT=2915335 DEFAULT CHARSET=latin1
and second stores parameters for each event with these columns
event_params | CREATE TABLE `event_params` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`event_id` int(10) unsigned NOT NULL,
`name` varchar(24) NOT NULL,
`value` varchar(524) CHARACTER SET utf8 NOT NULL,
PRIMARY KEY (`id`),
KEY `name` (`name`),
KEY `event_id` (`event_id`),
KEY `value` (`value`),
) ENGINE=InnoDB AUTO_INCREMENT=20789391 DEFAULT CHARSET=latin1
now I want to get count of events those have various values on a specified parameter
I wrote this query for campaign parameter but this is too slow (15 secs to respond)
SELECT
event_params.value as campaign,
count(*) as count
FROM `events`
left join event_params on event_params.event_id = events.id
and event_params.name = 'campaign'
WHERE events.project = 'foo'
GROUP by event_params.value
and here is the EXPLAIN query result:
+----+-------------+--------------+------------+------+---------------------+----------+---------+------------------+------+----------+----------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------------+------------+------+---------------------+----------+---------+------------------+------+----------+----------------------------------------------+
| 1 | SIMPLE | events | NULL | ref | project | project | 26 | const | 1 | 100.00 | Using index; Using temporary; Using filesort |
| 1 | SIMPLE | event_params | NULL | ref | name,event_id,value | event_id | 4 | events.events.id | 4 | 100.00 | Using where |
+----+-------------+--------------+------------+------+---------------------+----------+---------+------------------+------+----------+----------------------------------------------+
can i speed up this query ?
You may try adding the following index on the event_params table, which might speed up the join:
CREATE INDEX idx1 ON event_params (event_id, name, value);
The aggregation step probably can't be optimized much because the COUNT operation involves counting each record.
Move the "campaign value" into the main table, with a suitable length for VARCHAR and then
SELECT
campaign,
count(*) as count
FROM `events`
WHERE project = 'foo'
GROUP by campaign
And have
INDEX(project, campaign)
A bit of advice when tempted to use EAV: Move the 'important' values into the main table; leave only the rarely used or rarely set 'values' in the other table. Also (assuming there are no dups), have
PRIMARY KEY(event_id, name)
More discussion: http://mysql.rjweb.org/doc.php/eav

mysql indexing makes group by slow

Please refer the table strcuture below.
CREATE TABLE `oarc` (
`ID` bigint(20) NOT NULL AUTO_INCREMENT,
`zID` int(11) NOT NULL,
`cID` int(11) NOT NULL,
`bID` int(11) NOT NULL,
`rtype` char(1) COLLATE utf8_unicode_ci NOT NULL,
`created` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
PRIMARY KEY (`ID`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci AUTO_INCREMENT=1821039 ;
Other than the PRIMARY KEY, I have not set any index on this, and when I run the following query
select COUNT(oarc.ID) as total
from `oarc` where`oarc`.`rtype` = 'v'
group
by `oarc`.`zID`
I am getting the result in less than 1 second. But if I add index to zID it is taking more than 5 seconds.
Please see below explain result :
id | select_type | table | type | possible_keys | key | key_len | ref | row | Extra
--------------------------------------------------------------------------------------------------------
1 | SIMPLE | oarc | index | NULL | zone_ID | 4 | NULL | 1909387 | Using where
Currently the table have more than 1821039 records in it and it will increase on a hourly basis. What are the things I need to do in order to reduce the query execution time. I am expecting only something at the table and query level, nothing on my.cnf or server side because I can not do anything there.
Thanks in advance.
Is this better?
CREATE TABLE `oarc` (
`ID` bigint(20) NOT NULL AUTO_INCREMENT,
`zID` int(11) NOT NULL,
`cID` int(11) NOT NULL,
`bID` int(11) NOT NULL,
`rtype` char(1) COLLATE utf8_unicode_ci NOT NULL,
`created` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
PRIMARY KEY (`ID`),
KEY(rtype,zid)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci AUTO_INCREMENT=1821039 ;
explain
select COUNT(oarc.ID) as total
from `oarc` where`oarc`.`rtype` = 'v'
group
by `oarc`.`zID`
+----+-------------+-------+------+---------------+-------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+-------+---------+-------+------+--------------------------+
| 1 | SIMPLE | oarc | ref | rtype | rtype | 3 | const | 1 | Using where; Using index |
+----+-------------+-------+------+---------------+-------+---------+-------+------+--------------------------+

MySQL optimization query

i have one MySQL issue. I have to optimize some queries on my website. One of them i have already done, but there are still some which i cannot resolve without your help.
I have a table called "news":
CREATE TABLE IF NOT EXISTS `news` (
`id` int(10) NOT NULL auto_increment,
`edited` smallint(1) NOT NULL default '0',
`site` varchar(30) default NULL,
`foreign_id` varchar(25) default NULL,
`title` varchar(255) NOT NULL,
`text` text NOT NULL,
`image` varchar(255) default NULL,
`horizontal` smallint(1) NOT NULL,
`image_author` varchar(255) default NULL,
`text_author` varchar(255) default NULL,
`lang` varchar(3) NOT NULL,
`link` varchar(255) NOT NULL,
`date` date NOT NULL,
`redirect` smallint(1) NOT NULL,
`parent` int(10) NOT NULL,
`views` int(5) NOT NULL,
`status` smallint(1) NOT NULL,
PRIMARY KEY (`id`),
KEY `lang` (`lang`,`status`),
KEY `date` (`date`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 AUTO_INCREMENT=47122 ;
as you can see i have two indexes: "lang" and "date"
I have tried some combinations of different indexes and this one has produced me the best results ... unfortunately only on my local computer. On the server i still have bad results. I want to say that the database is the same.
query:
SELECT id FROM news WHERE lang = 'en' AND STATUS =1 ORDER BY DATE DESC LIMIT 0, 10
localhost explain:
+----+-------------+-------+-------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+------+---------+------+------+-------------+
| 1 | SIMPLE | news | index | lang | date | 3 | NULL | 23 | Using where |
+----+-------------+-------+-------+---------------+------+---------+------+------+-------------+
server explain:
+----+-------------+-------+------+---------------+--------+---------+-------------+-------+-----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+--------+---------+-------------+-------+-----------------------------+
| 1 | SIMPLE | news | ref | status | status | 13 | const,const | 15840 | Using where; Using filesort |
+----+-------------+-------+------+---------------+--------+---------+-------------+-------+-----------------------------+
I have looked a lot of other similar topics, but unfortunately i cannot find any solution to work on my server. I will be very glad to here from you some solution with some explanation for that so i can optimize my other queries.
Thanks !
This is your query:
SELECT id
FROM news
WHERE lang = 'en' AND STATUS =1
ORDER BY DATE DESC
LIMIT 0, 10
The best index is one that contains all the fields used in the query (four fields in all). The ordering in the index is by equality conditions in the where clause followed by the order by clause followed by other columns in the select clause.
So, try this index: ndws(leng, status, date, id).

Excluding large sets of objects from a query on a table with fast changing order

I have a table of products with a score column, which has a B-Tree Index on it. I have a query which returns products that have not been shown to the user in the current session. I can't simply use simple pagination with LIMIT for it, because the result should be ordered by the score column, which can change between query calls.
My current solution works like this:
SELECT *
FROM products p
LEFT JOIN product_seen ps
ON (ps.session_id = ? AND p.product_id = ps.product_id )
WHERE ps.product_id is null
ORDER BY p.score DESC
LIMIT 30;
This works fine for the first few pages, but the response time grows linear to the number of products already shown in the session and hits the second mark by the time this number reaches ~300. Is there a way to fasten this up in MySQL? Or should I solve this problem in an entirely other way?
Edit:
These are the two tables:
CREATE TABLE `products` (
`product_id` int(15) NOT NULL AUTO_INCREMENT,
`shop` varchar(15) NOT NULL,
`shop_id` varchar(25) NOT NULL,
`shop_category_id` varchar(20) DEFAULT NULL,
`shop_subcategory_id` varchar(20) DEFAULT NULL,
`shop_designer_id` varchar(20) DEFAULT NULL,
`shop_designer_name` varchar(40) NOT NULL,
`created_at` timestamp NULL DEFAULT NULL,
`product_url` varchar(255) NOT NULL,
`name` varchar(255) NOT NULL,
`description` mediumtext NOT NULL,
`price_cents` int(10) NOT NULL,
`list_image_url` varchar(255) NOT NULL,
`list_image_height` int(4) NOT NULL,
`ending` timestamp NULL DEFAULT NULL,
`category_id` int(5) NOT NULL,
`last_update` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
`included_at` timestamp NULL DEFAULT NULL,
`hearts` int(5) NOT NULL,
`score` decimal(10,5) NOT NULL,
`rand_field` decimal(16,15) NOT NULL,
`last_score_update` timestamp NULL DEFAULT NULL,
`active` tinyint(1) NOT NULL DEFAULT '0',
PRIMARY KEY (`product_id`),
UNIQUE KEY `unique_shop_id` (`shop`,`shop_id`),
KEY `score_index` (`active`,`score`),
KEY `included_at_index` (`included_at`),
KEY `active_category_score` (`active`,`category_id`,`score`),
KEY `active_category` (`active`,`category_id`,`product_id`),
KEY `active_products` (`active`,`product_id`),
KEY `active_rand` (`active`,`rand_field`),
KEY `active_category_rand` (`active`,`category_id`,`rand_field`)
) ENGINE=InnoDB AUTO_INCREMENT=55985 DEFAULT CHARSET=utf8
CREATE TABLE `product_seen` (
`seenby_id` int(20) NOT NULL AUTO_INCREMENT,
`session_id` varchar(25) NOT NULL,
`product_id` int(15) NOT NULL,
`last_seen` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
`sorting` varchar(10) NOT NULL,
`in_category` int(3) DEFAULT NULL,
PRIMARY KEY (`seenby_id`),
KEY `last_seen_index` (`last_seen`),
KEY `session_id` (`session_id`,`seenby_id`),
KEY `session_id_2` (`session_id`,`sorting`,`seenby_id`)
) ENGINE=InnoDB AUTO_INCREMENT=17431 DEFAULT CHARSET=utf8
Edit 2:
The query above is a simplification, this is the real query with EXPLAIN:
EXPLAIN SELECT
DISTINCT p.product_id AS id,
p.list_image_url AS image,
p.list_image_height AS list_height,
hearts,
active AS available,
(UNIX_TIMESTAMP( ) - ulp.last_action) AS last_loved
FROM `looksandgoods`.`products` p
LEFT JOIN `looksandgoods`.`user_likes_products` ulp
ON ( p.product_id = ulp.product_id AND ulp.user_id =1 )
LEFT JOIN `looksandgoods`.`product_seen` sb
ON (sb.session_id = 'y7lWunZKKABgMoDgzjwDjZw1'
AND sb.sorting = 'trend'
AND p.product_id = sb.product_id )
WHERE p.active =1
AND sb.product_id IS NULL
ORDER BY p.score DESC
LIMIT 30 ;
Explain output, there is still a temp table and filesort, although the keys for the join exist:
+----+-------------+-------+-------+----------------------------------------------------------------------------------------------------+------------------+---------+----------------------------------+------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+----------------------------------------------------------------------------------------------------+------------------+---------+----------------------------------+------+----------------------------------------------+
| 1 | SIMPLE | p | range | score_index,active_category_score,active_category,active_products,active_rand,active_category_rand | score_index | 1 | NULL | 2299 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | ulp | ref | love_count_index,user_to_product_index,product_id | love_count_index | 9 | looksandgoods.p.product_id,const | 1 | |
| 1 | SIMPLE | sb | ref | session_id,session_id_2 | session_id | 77 | const | 711 | Using where; Not exists; Distinct |
+----+-------------+-------+-------+----------------------------------------------------------------------------------------------------+------------------+---------+----------------------------------+------+----------------------------------------------+
New answer
I think the problem with the real query is the DISTINCT clause. The implication is that either or both of the product_seen and user_likes_products tables can join multiple rows for each product_id which could potentially appear in the result set (given the somewhat disturbing lack of UNIQUE KEYs on the product_seen table), and this is the reason you've included the DISTINCT clause. Unfortunately, it also means MySQL will have to create a temp table to process the query.
Before I go any further, if it's possible to do...
ALTER TABLE product_seen ADD UNIQUE KEY (session_id, product_id, sorting);
...and...
ALTER TABLE user_likes_products ADD UNIQUE KEY (user_id, product_id);
...then the DISTINCT clause is redundant, and removing it should eliminate the problem. N.B. I'm not suggesting you necessarily need to add these keys, but rather just to confirm that these fields are always unique.
If it's not possible, then there may be another solution, but I'd need to know a lot more about the tables involved in the joins.
Old answer
An EXPLAIN for your query yields...
+----+-------------+-------+------+---------------+------------+---------+-------+------+-------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------------+---------+-------+------+-------------------------+
| 1 | SIMPLE | p | ALL | NULL | NULL | NULL | NULL | 10 | Using filesort |
| 1 | SIMPLE | ps | ref | session_id | session_id | 27 | const | 1 | Using where; Not exists |
+----+-------------+-------+------+---------------+------------+---------+-------+------+-------------------------+
...which shows it's not using an index on the products table, so it's having to do a table scan and a filesort, which is why it's slow.
I noticed there's an index on (active, score) which you could use by changing the query to only show active products...
SELECT *
FROM products p
LEFT JOIN product_seen ps
ON (ps.session_id = ? AND p.product_id = ps.product_id )
WHERE p.active=TRUE AND ps.product_id is null
ORDER BY p.score DESC
LIMIT 30;
...which changes the EXPLAIN to...
+----+-------------+-------+-------+-----------------------------+-------------+---------+-------+------+-------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+-----------------------------+-------------+---------+-------+------+-------------------------+
| 1 | SIMPLE | p | range | score_index,active_products | score_index | 1 | NULL | 10 | Using where |
| 1 | SIMPLE | ps | ref | session_id | session_id | 27 | const | 1 | Using where; Not exists |
+----+-------------+-------+-------+-----------------------------+-------------+---------+-------+------+-------------------------+
...which is now doing a range scan and no filesort, which should be much faster.
Or if you want it to also return inactive products, then you'll need to add an index on score only, with...
ALTER TABLE products ADD KEY (score);

How can I optimize a Mysql query that searches for rows in a certain date range

Here is the query:
select timespans.id as timespan_id, count(*) as num
from reports, timespans
where timespans.after_date >= '2011-04-13 22:08:38' and
timespans.after_date <= reports.authored_at and
reports.authored_at < timespans.before_date
group by timespans.id;
Here are the table defs:
CREATE TABLE `reports` (
`id` int(11) NOT NULL auto_increment,
`source_id` int(11) default NULL,
`url` varchar(255) default NULL,
`lat` decimal(20,15) default NULL,
`lng` decimal(20,15) default NULL,
`content` text,
`notes` text,
`authored_at` datetime default NULL,
`created_at` datetime default NULL,
`updated_at` datetime default NULL,
`data` text,
`title` varchar(255) default NULL,
`author_id` int(11) default NULL,
`orig_id` varchar(255) default NULL,
PRIMARY KEY (`id`),
KEY `index_reports_on_title` (`title`),
KEY `index_content_on_reports` (`content`(128))
CREATE TABLE `timespans` (
`id` int(11) NOT NULL auto_increment,
`after_date` datetime default NULL,
`before_date` datetime default NULL,
`after_offset` int(11) default NULL,
`before_offset` int(11) default NULL,
`is_common` tinyint(1) default NULL,
`created_at` datetime default NULL,
`updated_at` datetime default NULL,
`is_search_chunk` tinyint(1) default NULL,
`is_day` tinyint(1) default NULL,
PRIMARY KEY (`id`),
KEY `index_timespans_on_after_date` (`after_date`),
KEY `index_timespans_on_before_date` (`before_date`)
And here is the explain:
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+----------------------------------------------+
| 1 | SIMPLE | timespans | range | index_timespans_on_after_date,index_timespans_on_before_date | index_timespans_on_after_date | 9 | NULL | 84 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | reports | ALL | NULL | NULL | NULL | NULL | 183297 | Using where |
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+----------------------------------------------+
And here is the explain after I create an index on authored_at. As you can see, the index is not actually getting used (I think...)
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+------------------------------------------------+
| 1 | SIMPLE | timespans | range | index_timespans_on_after_date,index_timespans_on_before_date | index_timespans_on_after_date | 9 | NULL | 86 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | reports | ALL | index_reports_on_authored_at | NULL | NULL | NULL | 183317 | Range checked for each record (index map: 0x8) |
+----+-------------+-----------+-------+--------------------------------------------------------------+-------------------------------+---------+------+--------+------------------------------------------------+
There are about 142k rows in the reports table, and far fewer in the timespans table.
The query is taking about 3 seconds now.
The strange thing is that if I add an index on reports.authored_at, it actually makes the query far slower, about 20 seconds. I would have thought it would do the opposite, since it would make it easy to find the reports at either end of the range, and throw the rest away, rather than having to examine all of them.
Can someone clarify? I'm stumped.
Instead of two separate indexes for the timespan table, try merging them into a single multi-column index with before_date and after_date in a single index. Then add that index to authored_at as well.
i rewrite you query like this:
select t.id, count(*) as num from timespans t
join reports r where t.after_date >= '2011-04-13 22:08:38'
and r.authored_at >= '2011-04-13 22:08:38'
and r.authored_at < t.before_date
group by t.id order by null;
and change indexes of tables
alter table reports add index authored_at_idx(authored_at);
You can used partition feature of database on column after_date. It will help u a lot.