9a2d96073e
* Use a row constructor comparison to avoid a filter
The original query had a WHERE condition that looked like:
(x > a) OR (x = a AND y < b)
This commit changes it to a compound comparison that, given the
lexicographical order it uses, is semantically the same:
(x, y) > (a, b)
This makes the plan in Postgres use an Index Cond instead of a Filter,
having two main performance improvements:
1. The query's time is more or less constant, not increasing every time
this query is executed. This is important because the query is executed
repeatedly until all posts are indexed.
2. The query's time is much shorter: while the original query eventually
takes 30s, hitting the timeout, the new one takes ~30ms.
Notice the difference in the plans below:
- the original query uses a `Filter` step, while the new one uses an
`IndexCond` + `Filter` step.
- the original query has a shared hit count of 40557115 (109GiB), while
the new one has a shared hit count of 13951 (109MiBA). This does not
show exactly how much data is read from disk, given it's a nested loop
node, but it gives us an idea of the amount of data processed in the
server.
Original plan:
agnivaltdb=> EXPLAIN (ANALYZE, BUFFERS) SELECT Posts.*, Channels.TeamId FROM Posts LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE Posts.CreateAt > '1687424888405' OR (Posts.CreateAt = '1687424888405' AND Posts.Id > 'tpomh9yu1tffmdp6dopobwuc9h') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=1.22..2287.94 rows=10000 width=464) (actual time=23921.236..23954.229 rows=10000 loops=1)
Buffers: shared hit=40557115
-> Incremental Sort (cost=1.22..13998881.93 rows=61217938 width=464) (actual time=23921.235..23953.205 rows=10000 loops=1)
Sort Key: posts.createat, posts.id
Presorted Key: posts.createat
Full-sort Groups: 311 Sort Method: quicksort Average Memory: 45kB Peak Memory: 45kB
Buffers: shared hit=40557115
-> Nested Loop Left Join (cost=1.00..11421751.31 rows=61217938 width=464) (actual time=23920.970..23947.067 rows=10001 loops=1)
Buffers: shared hit=40557115
-> Index Scan using idx_posts_create_at on posts (cost=0.57..9889434.54 rows=61217938 width=461) (actual time=23920.930..23931.063 rows=10001 loops=1)
Filter: ((createat > '1687424888405'::bigint) OR ((createat = '1687424888405'::bigint) AND ((id)::text > 'tpomh9yu1tffmdp6dopobwuc9h'::text)))
Rows Removed by Filter: 40920000
Buffers: shared hit=40553119
-> Memoize (cost=0.43..0.70 rows=1 width=30) (actual time=0.001..0.001 rows=1 loops=10001)
Cache Key: posts.channelid
Cache Mode: logical
Hits: 9002 Misses: 999 Evictions: 0 Overflows: 0 Memory Usage: 151kB
Buffers: shared hit=3996
-> Index Scan using channels_pkey on channels (cost=0.42..0.69 rows=1 width=30) (actual time=0.007..0.007 rows=1 loops=999)
Index Cond: ((id)::text = (posts.channelid)::text)
Buffers: shared hit=3996
Planning:
Buffers: shared hit=112
Planning Time: 0.501 ms
Execution Time: 23954.974 ms
(25 rows)
New plan:
agnivaltdb=> EXPLAIN (ANALYZE, BUFFERS) SELECT Posts.*, Channels.TeamId FROM Posts LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE (Posts.CreateAt, Posts.Id) > ('1687424888405', 'tpomh9yu1tffmdp6dopobwuc9h') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=1.15..1666.83 rows=10000 width=464) (actual time=0.366..34.053 rows=10000 loops=1)
Buffers: shared hit=13951
-> Incremental Sort (cost=1.15..10196977.36 rows=61217938 width=464) (actual time=0.365..33.031 rows=10000 loops=1)
Sort Key: posts.createat, posts.id
Presorted Key: posts.createat
Full-sort Groups: 311 Sort Method: quicksort Average Memory: 45kB Peak Memory: 45kB
Buffers: shared hit=13951
-> Nested Loop Left Join (cost=1.00..7619846.74 rows=61217938 width=464) (actual time=0.059..26.840 rows=10001 loops=1)
Buffers: shared hit=13951
-> Index Scan using idx_posts_create_at on posts (cost=0.57..6087529.97 rows=61217938 width=461) (actual time=0.040..10.548 rows=10001 loops=1)
Index Cond: (createat >= '1687424888405'::bigint)
Filter: (ROW(createat, (id)::text) > ROW('1687424888405'::bigint, 'tpomh9yu1tffmdp6dopobwuc9h'::text))
Rows Removed by Filter: 2
Buffers: shared hit=9955
-> Memoize (cost=0.43..0.70 rows=1 width=30) (actual time=0.001..0.001 rows=1 loops=10001)
Cache Key: posts.channelid
Cache Mode: logical
Hits: 9002 Misses: 999 Evictions: 0 Overflows: 0 Memory Usage: 151kB
Buffers: shared hit=3996
-> Index Scan using channels_pkey on channels (cost=0.42..0.69 rows=1 width=30) (actual time=0.007..0.007 rows=1 loops=999)
Index Cond: ((id)::text = (posts.channelid)::text)
Buffers: shared hit=3996
Planning:
Buffers: shared hit=112
Planning Time: 0.471 ms
Execution Time: 34.716 ms
(26 rows)
* Go back to the old query for MySQL
As one could expect, the two databases have completely opposite
behaviours, and for MySQL, the old query is significantly faster than
the new one, exactly for the same reason than in Postgres, but the other
way around: the old query uses an Index range scan while the new one
would use a Filter.
Old query (0.18s):
mysql> EXPLAIN ANALYZE SELECT Posts.*, Channels.TeamId FROM Posts USE INDEX(idx_posts_create_at_id) LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE Posts.CreateAt > 1557752415221 OR (Posts.CreateAt = 1557752415221 AND Posts.Id > 'ad59ire57tfwmjr5r8xqxc75qw') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000;
--------------
EXPLAIN ANALYZE SELECT Posts.*, Channels.TeamId FROM Posts USE INDEX(idx_posts_create_at_id) LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE Posts.CreateAt > 1557752415221 OR (Posts.CreateAt = 1557752415221 AND Posts.Id > 'ad59ire57tfwmjr5r8xqxc75qw') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000
--------------
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| -> Limit: 10000 row(s) (cost=7472068.91 rows=10000) (actual time=0.063..164.174 rows=10000 loops=1)
-> Nested loop left join (cost=7472068.91 rows=5559093) (actual time=0.062..163.450 rows=10000 loops=1)
-> Index range scan on Posts using idx_posts_create_at_id over (CreateAt = 1557752415221 AND 'ad59ire57tfwmjr5r8xqxc75qw' < Id) OR (1557752415221 < CreateAt), with index condition: ((Posts.CreateAt > 1557752415221) or ((Posts.CreateAt = 1557752415221) and (Posts.Id > 'ad59ire57tfwmjr5r8xqxc75qw'))) (cost=1357066.29 rows=5559093) (actual time=0.043..97.358 rows=10000 loops=1)
-> Single-row index lookup on Channels using PRIMARY (Id=Posts.ChannelId) (cost=1.00 rows=1) (actual time=0.006..0.006 rows=1 loops=10000)
|
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.18 sec)
New query (5s):
mysql> EXPLAIN ANALYZE SELECT Posts.*, Channels.TeamId FROM Posts USE INDEX(idx_posts_create_at_id) LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE (Posts.CreateAt, Posts.Id) > (1557752415221, 'ad
59ire57tfwmjr5r8xqxc75qw') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000;
--------------
EXPLAIN ANALYZE SELECT Posts.*, Channels.TeamId FROM Posts USE INDEX(idx_posts_create_at_id) LEFT JOIN Channels ON Posts.ChannelId = Channels.Id WHERE (Posts.CreateAt, Posts.Id) > (1557752415221, 'ad59ire57tfwmjr5r8xqxc75qw') ORDER BY Posts.CreateAt ASC, Posts.Id ASC LIMIT 10000
--------------
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN |
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| -> Limit: 10000 row(s) (cost=11119405.48 rows=10000) (actual time=5295.106..5455.285 rows=10000 loops=1)
-> Nested loop left join (cost=11119405.48 rows=10000) (actual time=5295.105..5454.572 rows=10000 loops=1)
-> Filter: ((Posts.CreateAt,Posts.Id) > (1557752415221,'ad59ire57tfwmjr5r8xqxc75qw')) (cost=221.48 rows=10000) (actual time=5295.078..5388.668 rows=10000 loops=1)
-> Index scan on Posts using idx_posts_create_at_id (cost=221.48 rows=10000) (actual time=0.055..5314.753 rows=600000 loops=1)
-> Single-row index lookup on Channels using PRIMARY (Id=Posts.ChannelId) (cost=1.00 rows=1) (actual time=0.006..0.006 rows=1 loops=10000)
|
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (5.46 sec)
```
* Add comment explaining the difference between DBs
---------
Co-authored-by: Mattermost Build <build@mattermost.com>
Mattermost is an open source platform for secure collaboration across the entire software development lifecycle. This repo is the primary source for core development on the Mattermost platform; it's written in Go and React and runs as a single Linux binary with MySQL or PostgreSQL. A new compiled version is released under an MIT license every month on the 16th.
Deploy Mattermost on-premises, or try it for free in the cloud.
Learn more about the following use cases with Mattermost:
Other useful resources:
- Download and Install Mattermost - Install, setup, and configure your own Mattermost instance.
- Product documentation - Learn how to run a Mattermost instance and take advantage of all the features.
- Developer documentation - Contribute code to Mattermost or build an integration via APIs, Webhooks, slash commands, Apps, and plugins.
Table of contents
- Install Mattermost
- Native mobile and desktop apps
- Get security bulletins
- Get involved
- Learn more
- License
- Get the latest news
- Contributing
Install Mattermost
- Download and Install Mattermost Self-Hosted - Deploy a Mattermost Self-hosted instance in minutes via Docker, Ubuntu, or tar.
- Get started in the cloud to try Mattermost today.
- Developer machine setup - Follow this guide if you want to write code for Mattermost.
Other install guides:
- Deploy Mattermost on Docker
- Mattermost Omnibus
- Install Mattermost from Tar
- Ubuntu 20.04 LTS
- Kubernetes
- Helm
- Debian Buster
- RHEL 8
- More server install guides
Native mobile and desktop apps
In addition to the web interface, you can also download Mattermost clients for Android, iOS, Windows PC, macOS, and Linux.
Get security bulletins
Receive notifications of critical security updates. The sophistication of online attackers is perpetually increasing. If you're deploying Mattermost it's highly recommended you subscribe to the Mattermost Security Bulletin mailing list for updates on critical security releases.
Get involved
- Contribute to Mattermost
- Find "Help Wanted" projects
- Join Developer Discussion on a Mattermost server for contributors
- Get Help With Mattermost
Learn more
- API options - webhooks, slash commands, drivers, and web service
- See who's using Mattermost
- Browse over 700 Mattermost integrations
License
See the LICENSE file for license rights and limitations.
Get the latest news
- X - Follow Mattermost on X, formerly Twitter.
- Blog - Get the latest updates from the Mattermost blog.
- Facebook - Follow Mattermost on Facebook.
- LinkedIn - Follow Mattermost on LinkedIn.
- Email - Subscribe to our newsletter (1 or 2 per month).
- Mattermost - Join the ~contributors channel on the Mattermost Community Server.
- IRC - Join the #matterbridge channel on Freenode (thanks to matterircd).
- YouTube - Subscribe to Mattermost.
Contributing
Please see CONTRIBUTING.md. Join the Mattermost Contributors server to join community discussions about contributions, development, and more.