MySQL and NoSQL: Help me to choose the right one
There is a big database, 1,000,000,000 rows, called threads (these threads actually exist, I'm not making things harder just because of I enjoy it). Threads has only a few stuff in it, to make things faster: (int id, string hash, int replycount, int dateline (timestamp), int forumid, string title)
Query:
select * from thread where forumid = 100 and replycount > 1 order by dateline desc limit 10000, 100
Since that there are 1G of records it's quite a slow query. So I thought, let's split this 1G of records in as many tables as many forums(category) I have! That is almost perfect. Having many tables I have less record to search around and it's really faster. The query now becomes:
select * from thread_{forum_id} where replycount > 1 order by dateline desc limit 10000, 100
This is really faster with 99% of the forums (category) since that most of those have only a few of topics (100k-1M). However because there are some with about 10M of records, some query are still to slow (0.1/.2 seconds, to much for my app!, I'm already using indexes!).
I don't know how to improve this using MySQL. Is there a way?
For this project I will use 10 Servers (12GB ram, 4x7200rpm hard disk on software raid 10, quad core)
The idea was to simply split the databases among the servers, but with the problem explained above that is still not enought.
If I install cassandra on these 10 servers (by supposing I find the time to make it works as it is supposed to) should I be suppose to have a performance boost?
What should I do? Keep working with MySQL with distributed database on multiple machines or build a cassandra cluster?
Answer
You should read the following and learn a little bit about the advantages of a well designed innodb table and how best to use clustered indexes - only available with innodb !
http://dev.mysql.com/doc/refman/5.0/en/innodb-index-types.html
http://www.xaprb.com/blog/2006/07/04/how-to-exploit-mysql-index-optimizations/
then design your system something along the lines of the following simplified example:
Example schema (simplified)
The important features are that the tables use the innodb engine and the primary key for the threads table is no longer a single auto_incrementing key but a composite clustered key based on a combination of forum_id and thread_id. e.g.
threads - primary key (forum_id, thread_id)
forum_id thread_id
======== =========
1 1
1 2
1 3
1 ...
1 2058300
2 1
2 2
2 3
2 ...
2 2352141
...
Each forum row includes a counter called next_thread_id (unsigned int) which is maintained by a trigger and increments every time a thread is added to a given forum. This also means we can store 4 billion threads per forum rather than 4 billion threads in total if using a single auto_increment primary key for thread_id.
forum_id title next_thread_id
======== ===== ==============
1 forum 1 2058300
2 forum 2 2352141
3 forum 3 2482805
4 forum 4 3740957
...
64 forum 64 3243097
65 forum 65 15000000 -- ooh a big one
66 forum 66 5038900
67 forum 67 4449764
...
247 forum 247 0 -- still loading data for half the forums !
248 forum 248 0
249 forum 249 0
250 forum 250 0
The disadvantage of using a composite key is that you can no longer just select a thread by a single key value as follows:
select * from threads where thread_id = y;
you have to do:
select * from threads where forum_id = x and thread_id = y;
However, your application code should be aware of which forum a user is browsing so it's not exactly difficult to implement - store the currently viewed forum_id in a session variable or hidden form field etc...
Here's the simplified schema:
drop table if exists forums;
create table forums
(
forum_id smallint unsigned not null auto_increment primary key,
title varchar(255) unique not null,
next_thread_id int unsigned not null default 0 -- count of threads in each forum
)engine=innodb;
drop table if exists threads;
create table threads
(
forum_id smallint unsigned not null,
thread_id int unsigned not null default 0,
reply_count int unsigned not null default 0,
hash char(32) not null,
created_date datetime not null,
primary key (forum_id, thread_id, reply_count) -- composite clustered index
)engine=innodb;
delimiter #
create trigger threads_before_ins_trig before insert on threads
for each row
begin
declare v_id int unsigned default 0;
select next_thread_id + 1 into v_id from forums where forum_id = new.forum_id;
set new.thread_id = v_id;
update forums set next_thread_id = v_id where forum_id = new.forum_id;
end#
delimiter ;
You may have noticed I've included reply_count as part of the primary key which is a bit strange as (forum_id, thread_id) composite is unique in itself. This is just an index optimisation which saves some I/O when queries that use reply_count are executed. Please refer to the 2 links above for further info on this.
Example queries
I'm still loading data into my example tables and so far I have a loaded approx. 500 million rows (half as many as your system). When the load process is complete I should expect to have approx:
250 forums * 5 million threads = 1250 000 000 (1.2 billion rows)
I've deliberately made some of the forums contain more than 5 million threads for example, forum 65 has 15 million threads:
forum_id title next_thread_id
======== ===== ==============
65 forum 65 15000000 -- ooh a big one
Query runtimes
select sum(next_thread_id) from forums;
sum(next_thread_id)
===================
539,155,433 (500 million threads so far and still growing...)
under innodb summing the next_thread_ids to give a total thread count is much faster than the usual:
select count(*) from threads;
How many threads does forum 65 have:
select next_thread_id from forums where forum_id = 65
next_thread_id
==============
15,000,000 (15 million)
again this is faster than the usual:
select count(*) from threads where forum_id = 65
Ok now we know we have about 500 million threads so far and forum 65 has 15 million threads - let's see how the schema performs :)
select forum_id, thread_id from threads where forum_id = 65 and reply_count > 64 order by thread_id desc limit 32;
runtime = 0.022 secs
select forum_id, thread_id from threads where forum_id = 65 and reply_count > 1 order by thread_id desc limit 10000, 100;
runtime = 0.027 secs
Looks pretty performant to me - so that's a single table with 500+ million rows (and growing) with a query that covers 15 million rows in 0.02 seconds (while under load !)
Further optimisations
These would include:
partitioning by range
sharding
throwing money and hardware at it
etc...
hope you find this answer helpful :)